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• PLoS Comput Biol
• v.16(5); 2020 May

Ad hoc efforts for advancing data science education

Orianna demasi.

1 Department of Computer Science, University of California, Davis, California, United States of America

Alexandra Paxton

2 Department of Psychological Sciences, University of Connecticut, Storrs, Connecticut, United States of America

3 Center for the Ecological Study of Perception and Action, University of Connecticut, Storrs, Connecticut, United States of America

4 IDEO, San Francisco, California, United States of America

Associated Data

All data that we are able to share, while in compliance with our IRB approval and participant consent, can be found within the manuscript and appendices. For access to additional de-identified data, please contact the Office for Protection of Human Subjects University of California, Berkeley at 510/642-7461 or ude.yelekreb@shpo .

With increasing demand for training in data science, extracurricular or “ad hoc” education efforts have emerged to help individuals acquire relevant skills and expertise. Although extracurricular efforts already exist for many computationally intensive disciplines, their support of data science education has significantly helped in coping with the speed of innovation in data science practice and formal curricula. While the proliferation of ad hoc efforts is an indication of their popularity, less has been documented about the needs that they are designed to meet, the limitations that they face, and practical suggestions for holding successful efforts. To holistically understand the role of different ad hoc formats for data science, we surveyed organizers of ad hoc data science education efforts to understand how organizers perceived the events to have gone—including areas of strength and areas requiring growth. We also gathered recommendations from these past events for future organizers. Our results suggest that the perceived benefits of ad hoc efforts go beyond developing technical skills and may provide continued benefit in conjunction with formal curricula, which warrants further investigation. As increasing numbers of researchers from computational fields with a history of complex data become involved with ad hoc efforts to share their skills, the lessons learned that we extract from the surveys will provide concrete suggestions for the practitioner-leaders interested in creating, improving, and sustaining future efforts.

Author summary

Large datasets are becoming integral to society broadly and to biological sciences in particular. As a result, demand for sophisticated data skills and experience has skyrocketed and left some individuals scrambling to cross-train and acquire more computational skills. While universities are racing to develop formal curricula to meet this demand, diverse informal efforts have emerged to fill the immediate demand for skills and experience. These “ad hoc” efforts have been playing a vital role in data science education, especially for domain scientists. While some studies have shown specific ad hoc formats to have considerable impact, few studies have focused on these efforts holistically. Here, we survey effort organizers from leading data science institutes and collect lessons learned. We find that efforts are commonly reported to successfully provide opportunities in difficult areas where curricula could improve, such as providing approachable introductions to new skills, increasing diversity of backgrounds, and fostering heterogeneous communities. However, efforts also report challenges fulfilling diverse needs and offer suggestions. In total, the lessons that we collect from these efforts are useful to improve future ad hoc efforts and to inform formal programs, which may be looking for inspiration to design innovative educational formats.

Introduction

Interest in data science and related fields has surged over the last several years [ 1 ]. Typically seen as applying programming ability and statistical knowledge to answer questions derived from domain-specific expertise, data scientists have come into high demand as datasets have grown in size and complexity [ 2 ]. While many university curricula are acknowledging the need for data science training and other computationally minded educational opportunities [ 3 – 12 ], formal program structures and course offerings that embrace these new data and techniques can be slow to change.

To bridge the immediate gap between current curricula and the new demands of data science, a tapestry of extracurricular educational opportunities (i.e., opportunities that do not offer any course credit and are not required to complete a degree program) has emerged to provide students with essential data science skills. These ad hoc education efforts can take a variety of formats—including hours-long workshops, week-long boot camps, and semester-long research projects—and are intended to complement existing formal educational structures [ 13 – 15 ] by embracing new tools and pedagogy as they emerge [ 16 , 17 ]. These efforts are spearheaded by practitioner-leaders—data scientists across career stages and paths who may or may not have formal teaching expertise but want to share their knowledge with others. Researchers from fields with a strong tradition of complex data and computational skills—like computational biology—have been some of the fastest to jump into these educational opportunities, eager to share their skills with burgeoning data scientists and established researchers integrating data science into fields in the “long tail” of big data and computational work.

Previous studies have considered the benefit of specific ad hoc formats like hack weeks [ 13 ], summer programs [ 14 ], and workshops [ 8 , 15 , 18 – 20 ]. Some of this work has indicated that—along with filling educational gaps temporarily created by data science’s rapid growth—ad hoc efforts may also help address more systemic weaknesses through innovative paradigms developed across rapid iterations [ 13 ]. Other work has addressed the institutional change of data science education [ 11 ] and how to design formal efforts or courses related to computational skills [ 10 , 21 ]. Prior work has also considered lessons learned from individual event formats, such as short courses or workshops [ 8 , 19 , 20 , 22 – 24 ], mentor–mentee relationships [ 25 ], and summer programs [ 26 ]. However, to our knowledge, no study has yet looked holistically at the benefits that different extracurricular formats can provide and has extracted lessons learned for future efforts and novel formats.

To formally understand the breadth, impacts, and opportunities for growth for ad hoc efforts broadly, we surveyed organizers from a variety of efforts. These efforts were all organized at the Moore-Sloan Data Science Environments (MSDSEs), an early initiative to promote interdisciplinary data science research, education, and communities at New York University (NYU), the University of Washington (UW), and the University of California, Berkeley (UC Berkeley). This survey asked organizers to be constructively self-critical to share lessons learned for future efforts through a balanced view of the efforts with which they had been involved. (For survey details, see “ Materials and methods ” section.) In addition to describing their efforts, we asked them to outline the goals of their events, to explicitly describe the ways in which they were successful and unsuccessful in relation to those goals, to list ways in which they (or others) would change their effort (or similar efforts), and to provide their lessons and thoughts about the future of ad hoc education in data science.

Using these data, we then turned to the major contribution for the current paper: providing concrete guidance to improve future ad hoc education efforts in data science across effort formats. To achieve this, we asked past organizers to reflect on their experiences and provide suggestions for future organizers in a series of structured closed-form and open-form questions. From the open-ended responses, we used qualitative research methods [ 27 , 28 ] to extract a codebook for capturing recurring themes. (For more on how the codebook was developed, see “ Materials and methods ”.) This codebook—a secondary contribution of the current work—is intended to be both a guide to the specific responses for our survey and a tool for future qualitative and quantitative explorations. These lessons learned additionally provide us an opportunity to explore implications for the future of ad hoc data science education—especially within evolving and increasingly rich formal education structures.

Our survey received 24 total responses, but 2 were excluded because the respondent did not consent to participate in the research. The 22 included responses represented the perspectives of 18 unique organizers on 19 unique efforts ( Table 1 ). The original 24 survey responses represented—to the best of our knowledge—a comprehensive list of ad hoc data science education efforts within the MSDSEs at the time. (There were and are additional ad hoc efforts at each host university, but we restrict our focus to ad hoc education efforts in data science sponsored by an MSDSE.) Therefore, the 22 responses included in these analyses represent a nearly comprehensive list.

Abbreviation: MSDSE, Moore-Sloan Data Science Environment

Many of these efforts represented multiple (e.g., annual) iterations of an event or multiple events in a series, so considerably more events are represented. The data were originally collected as a means to understand how ad hoc efforts in the MSDSE could be improved. Pursuant to UC Berkeley Institutional Review Board (IRB) protocol ID 2017-11-10487, we subsequently obtained consent from the respondents so that the lessons learned could be shared more broadly.

Taken together, the organizers in our survey reported approximately 1,194 participants for the events considered. However, since some organizers noted that the events occurred regularly (e.g., weekly, quarterly), these ad hoc efforts may have included up to 3,554 participants, using the reported frequency and assuming relatively stable rates of participation. While there may have been overlap in participants between events, these ad hoc efforts touched a large number of individuals seeking data science training and experience.

Types of efforts held at the MSDSEs

The efforts reported in our survey included a variety of formats (see Table 2 for examples). Each of the efforts reported in our survey could generally be characterized along 2 orthogonal axes: high or low investment and long-term or short-term cohesion. Investment captures the amount of resources (e.g., space, funding) and/or efforts required to create the event. Cohesion focuses on the persistence of the effort over time. This does not necessarily mean that the specific individuals involved in the effort will remain the same over time; instead, this captures the persistence of the effort itself.

Count indicates the number of survey responses that represented efforts that could be classified as a given type.

Abbreviations: HILT, high investment, long-term cohesion; HIST, high investment, short-term cohesion; LILT, low investment, long-term cohesion; LIST, low investment, short-term cohesion

High investment, short-term cohesion

The majority of the MSDSE efforts in our survey were high investment, short-term cohesion (HIST; Table 2 ), as they required coordination among multiple leaders to create a unified program spanning several days or a week. HIST efforts could include well-known types of ad hoc efforts discussed in other works—for example, hack weeks (i.e., multiday events that mix tutorials and lectures with dedicated time to intensively work on a project [ 13 ]) and multiple-day workshops (e.g., Software Carpentry [ 15 ]) at all 3 campuses. The majority of the HIST efforts included in our survey were not driven by faculty members, highlighting the openness of ad hoc education effort leadership.

Low investment, short-term cohesion

Ad hoc education efforts described as low investment, short-term cohesion (LIST) are often single-day events with much more distributed investment requirements. Examples of LISTs would include other popular formats, such as single-day “un-conferences” [ 29 ] focusing on cross-disciplinary analyses of a single type of data or “lightning talks” (i.e., 3- to 10-minute talks) aimed at practically tackling single questions or topics in data science. By their nature, these efforts afford the opportunity for much more targeted events that take advantage of existing strengths within the local community and target specific needs or narrow topics.

High investment, long-term cohesion

High investment, long-term cohesion (HILT) efforts require multiple investments (e.g., time, resources, cost) to persist over months or years. To do so, some efforts required hierarchies of training for researcher or software development mentors (e.g., “train the trainer” models). Prototypical HILT efforts reported in our survey included a focus on hands-on research projects or software development through close mentoring relationships for an extended period of time (e.g., semester, summer). While these efforts are rewarding, the required resources present a substantial challenge.

Low investment, long-term cohesion

Efforts classified as low investment, long-term cohesion (LILT) exist on longer scales but require relatively little centralized investment. Such efforts are often championed by a single organizer who can set up the structure over a semester or year. For example, LILT efforts could include short consulting sessions, ongoing peer-learning tutorials, and lecture series. The loosely connected structure allows organizers to take advantage of existing community expertise while deepening community ties and broadening community knowledge. These events may build on one another, but their relatively informal structure may impose lower barriers to entry for participants.

Diverse intended audiences for ad hoc efforts

To understand which audiences ad hoc efforts have tried to engage and whether they successfully engaged underserved audiences, we asked organizers to name their target populations using a multiple-answer question on our survey. As seen in Fig 1 , each audience listed was targeted by multiple efforts. We tried to be as broad as possible in identifying different kinds of diversity: In addition to using the word “diverse” in reference both to demographics and disciplines, we included a range of other kinds of diversity (including career stage, programming backgrounds, and career goals).

Efforts typically reported more than one target audience, and each audience listed was targeted by multiple efforts. The audiences included in the figure were multiple-choice options for the survey question, except for “Faculty,” which was written into the “Other” option often, as indicated here.

Every respondent indicated targeting more than one of the identified populations, and some indicated additional audiences that were not specified by the survey question. By having various effort structures, as discussed earlier, some ad hoc efforts (especially those with short-term cohesion) can create a lower barrier to entry than formal curricula and thus provide initial contact with data science to diverse audiences. These efforts can also be tuned to meet needs of specific audiences, as they are extracurricular and often relatively brief. By incorporating more diverse audiences, ad hoc efforts can enrich learning outcomes and make data science more accessible.

Common goals of ad hoc efforts

Using multiple-answer responses, every respondent indicated that their effort had in mind at least one of 4 listed goals that are not always well met by formal curricula ( Fig 2 ). Many efforts also indicated additional, unlisted goals—with one of the most significant themes being building community and research collaborations. This theme manifested in a variety of ways, but the diverse communities formed at ad hoc events and persisting beyond events were often described as a long-term benefit to research and educational outcomes. By targeting the areas listed, ad hoc education attempts to supplement curricula with novel structures to address traditional challenges or shortcomings of curricula.

Community building was not included as a possible multiple-answer response, but it was cited in open-ended responses for approximately a third of all efforts.

Lessons learned: Things that worked

While many open-ended responses to our question about effort successes were specific to the event or the type of ad hoc effort held, we found 5 general characteristics that commonly emerged as successes of ad hoc education. Most of these characteristics explicitly emerged from a grounded approach (further discussed in the “Materials and methods” section) as codes and can be used to design or plan and evaluate future efforts. Note that the frequency with which these characteristics were reported is likely underestimated due to the current research methods: The open-ended survey questions did not explicitly ask about individual characteristics but instead allowed respondents to volunteer information about whatever stood out to them as successes.

Increasing diversity across backgrounds, experiences, perspectives, and skills

By providing approachable introductions on limited time scales, many efforts also reported targeting diversity (e.g., career stages, demographics, disciplines; Fig 1 ), and 50% of survey responses mentioned successfully engaging a diverse audience. Data science often requires individuals to reach across disciplines. While this diversity sparks exciting research and important discoveries, it can also create barriers both to entry and to progress. By offering small modules with directed foci, ad hoc efforts provide a less daunting environment to data science education that can empower learners and accelerate individuals’ access to new information and skills.

Fostering technical skills and research

One of the most common successes across ad hoc efforts seemed to be creating formats that could make a new topic, skill set, and/or technical method approachable. Ad hoc effort organizers frequently mentioned (68.2% of responses) having given participants the opportunity for hands-on experience building and practicing technical skills and research, not just theoretical concepts.

Many of these efforts were specifically designed as introductions to material. University curricula often leave students choosing between taking a formal course or learning the skill on their own. Ad hoc education efforts smoothed the spectrum between these options, helping learners to quickly access new material with expert support. The approachability of tutorial, “hacker” session, and workshop formats is important not only for individuals new to data science broadly but also for those transitioning into new or interdisciplinary areas and awareness of new methods.

Technical skills require significant practice to refine, and ad hoc efforts supported this through structured practice (e.g., direct instruction, project-directed learning) and feedback. As examples, some ad hoc efforts provided supported introductions to new programming libraries with a tutorial format, while others offered opportunities for more practice through a semester-long, hands-on, and mentored research project. However, this success requires further investigation from participants’ perspectives and objective outcomes, as recent work has found null learning effects [ 30 ] and thus contradicts work that found positive effort outcomes [ 13 , 19 , 20 , 31 ].

Fostering nontechnical skills

Similarly, many efforts mentioned providing experience in nontechnical skills (40.9% of responses), such as leading a teaching session at a workshop or mentoring a group of undergraduates through a research project. While nontechnical skills like presenting, mentoring, management, and communication are vital to successful careers in data science, university settings do not always provide supportive environments to build, practice, and refine these skills. Ad hoc education efforts gave opportunities to build novel skill sets commonly seen as outside the scope of standard university curricula.

Building enduring communities that improve research

A large proportion of responses indicated that efforts had significant participation (40.9% of responses). Many of these described this participation as building communities around common problems, tools, or experiences and reported that these communities persisted across multiple versions of the effort or beyond the effort. Because efforts can attract diverse audiences, many efforts reported that the newly formed communities included members who otherwise would probably not have connected. In addition to the broad benefits that emerge from being part of a community, organizers also reported specific productive collaborations that stemmed from certain efforts.

Lessons learned: Things that didn't work

While many organizers who took our survey felt that their effort had been somewhat successful, all but 3 efforts elaborated on room for improvement. The majority of efforts (86.4%) mentioned specific ways that they could refine logistics for their effort or similar kinds of efforts (e.g., scheduling time, organizing materials). However, the organizers’ responses also mentioned more general opportunities for improvement. We grouped the general responses into 4 themes.

As with successes, we note that each of these challenges are likely underreported, due to the open nature of our survey question about effort shortcomings and the lack of participant reports.

Unclear expectations of participants and organizers

A notable shortcoming was a lack of sufficiently articulating and communicating mutual expectations a priori. In the survey, 18.2% of responses mentioned some form of struggling to manage participants’ expectations, but this is likely a low estimate, given that other efforts implied similar issues through the envisioned changes they described for their efforts.

“Participant expectations” included information about what prior knowledge or skills participants should have, guidelines about what participants and practitioner-leaders would provide, and goals for what everyone should gain from participating or leading. Unclear or insufficient discussions of necessary background, participant roles, and scope of efforts were reported as leading to frustration and disappointment. For example, organizers reported that participants without sufficient background information found sessions unapproachable or intimidating. Similarly, when ad hoc efforts tried to foster mentor–mentee relationships, frustration and disappointment often arose on both sides of the relationship when expectations of both parties were not clearly discussed at the start of the relationship.

Challenges bridging diverse skill sets and levels

Diversity of attendants was consistently reported as a goal and positive outcome when achieved. However, with such a breadth of skills, the most commonly mentioned shortcoming (40.9%) was difficulty in getting everyone on the same page. Different skill sets and levels made it challenging to present new material at an optimal pace for everyone. Diverse participants also brought diverse expectations for individual events, which could be hard to satisfy, as has previously been noted by Software Carpentries [ 31 ].

Difficulty cultivating sustained leadership

Despite feeling rewarded by contributing to educational advancement of participants, 22.7% of responses mentioned that organizers reported burnout as a serious consideration. Ad hoc efforts are exciting and meaningful contributions to the data science and institutional communities, but they often go unrewarded or even unacknowledged within traditional academic structures. As a result, organizers struggled to find additional help or people to continue their efforts, which often drove the future of an effort into uncertainty.

Difficulty maintaining sustained engagement

Sustaining engagement among participants was another challenge mentioned in nearly a quarter of responses (22.7%). Eliciting initial excitement for data science projects and events was easy, but converting that excitement into regular event attendance, volunteering for presentations, or research output was much more difficult. Due to the extracurricular nature of ad hoc education efforts, there was often insufficient incentive to motivate continued engagement for both practitioner-leaders and participants.

Here, we have considered both multiple-choice and open-ended responses from a survey of organizers of ad hoc education efforts in data science across the MSDSEs. From these, we have generated a taxonomy of ad hoc efforts, have created a codebook for extracting themes from open-ended responses, and have provided a series of lessons learned that emerged from explicit comments from individual organizers and a broader consideration of the responses as a whole. Again, the extent to which these lessons have been experienced by efforts is—if anything—underreported because of the open nature of the survey; the pervasiveness of these (and potentially other) areas of strength and areas for improvement merits further investigation. In this discussion, we build on these reflections of past work to provide concrete suggestions for future ad hoc efforts. We then turn to consider a number of open questions facing ad hoc efforts in data science education that arise naturally from our data and articulate some of the limitations of our work.

Suggestions for ad hoc education efforts

Despite the successes of past ad hoc education efforts, there remain areas for improvement that can help guide plans for future events. In particular, there is a need for better communication and more conscious planning. Importantly, although the suggestions listed here are informed by the survey of MSDSE effort organizers, these suggestions equally apply to all practitioner-leaders, not just those affiliated with the MSDSE initiative, and some have also been cited as lessons or suggestions in previous work that has looked at individual educational effort formats. These suggestions may be most valuable to practitioner-leaders from institutions with lower levels of institutional support and/or smaller existing data science communities, as these suggestions can help make the most of the available opportunities, time, and resources. Adopting these suggestions can help improve both the quality of individual ad hoc efforts and the quality of ad hoc education—and data science practice—more broadly.

Survey participants before and after events

Nearly a third of respondents (31.8%) reported surveying participants either before or after events and noted the utility of that information in shaping their current and future efforts. (Several other respondents noted that they would like to adopt pre- or postevent surveys in the future, and 13.6% noted regretting that they did not have success metrics from surveys.)

Surveys prior to events provided leaders and organizers with essential insights for effectively planning an event. It can help practitioner-leaders set an appropriate pace for tutorials and projects, help organizers manage prospective expectations, and help organizers decide how time should be allocated in longer events (e.g., how to partition time between tutorials and hacking sessions during a hack week) [ 20 ]. Participant surveys conducted after an effort are valuable for gathering feedback for improvement and for gathering metrics of success that could then be used to evaluate efforts and bolster support for future instances of the effort [ 8 , 13 , 20 , 24 , 30 – 32 ].

Communicate goals to manage expectations

Organizers should carefully articulate the goals of the event to practitioner-leaders before the event to identify the minimum knowledge or skills that will be required to participate fully in the event. Articulating and communicating goals and expectations was noted as a challenge in the responses to our survey, consistent with a number of lessons or suggestions for individual formats identified by previous work [ 20 , 24 – 26 , 29 , 32 ]. These goals and requirements should then be shared with participants to improve understanding—and manage expectations—as also noted in related work [ 32 ]. If possible, this information should be prominently shared when soliciting participation so that participants can take that information into account when deciding whether to join the event, especially for multiday events like workshops and hackathons.

Communicate necessary prior knowledge

Articulating the effort’s goals and target audiences will help organizers to decide how to manage the tradeoff between required participant preparation and the speed and depth of the ad hoc education effort. Additionally, organizers could identify ways that the participants could prepare for the effort, as suggested by 27.3% of respondents in our survey. Organizers should include any essential requirements in the recruitment materials so that participants have a clear understanding of what prior experience (if any) is needed to benefit from the event and so that participants can arrive prepared for the effort. It is important to set expected knowledge at an appropriate level, as setting a high bar of required skills may discourage potential participants with little data science background and thus decrease diversity.

Engage representatives to foster diversity

Articulation and communication of event goals are particularly important for efforts that seek to engage diverse audiences. Ad hoc education efforts present a fantastic opportunity to creatively reach audiences that are cross-disciplinary and underrepresented within data science. However, organizers should actively work to reach these audiences as leaders and participants, and effective efforts are unlikely to organically materialize without explicit articulation and dedicated planning. This is reflected by the challenges faced by some respondents in successfully engaging diverse audiences (18.2%) and by the near-majority of efforts reporting that they would make changes to address issues of diversity (45.5%), including one respondent explicitly advocating for diversifying the effort leadership.

Efforts seeking to reach diverse disciplines or demographics should identify clear steps to successfully achieve that goal, as related efforts have also reflected [ 20 ]. If an effort intends to target participation by diverse research fields, organizers should reach out to representatives from those areas early in the planning process, either to include the representatives in the organizing process or to request feedback on organizational structure. This is especially important when practitioner-leaders come from more computationally minded fields (e.g., computational biology) and are reaching out to audiences from less traditionally computational fields (e.g., social sciences). Partnering with representatives can provide invaluable insights into engaging and servicing the target audience, including suggestions on material that should be covered, use-case examples to effectively translate and demonstrate skills, or even help advertising within that community.

Support development of soft skills

Organizers should also consider how practitioner-leaders will benefit from engaging in the ad hoc effort to help sustain broad engagement of practitioner-leaders. Many soft skills—such as management, public speaking, presenting, communicating, and teaching—are invaluable for any field or career track. Ad hoc education efforts provide wonderful opportunities for practitioner-leaders to practice these skills, but additional support for development would benefit the leaders and potentially improve the incentives for participation. Financial incentives are a possible option, but alternative models of support may be considered, such as providing constructive presentation feedback from the audience, suggestions for developing mentor–mentee relationships [ 25 ], or organizers to presenters and building camaraderie among mentors. Organizers could even open a dialogue with potential practitioner-leaders directly to see what might be the most useful benefits to provide.

Avoid duplication

Conducting duplicate or significantly overlapping efforts at the same institution is not always the best use of resources. These can generate unnecessary time constraints on organizers and individuals who try to participate in too many overlapping efforts. This may have been of particular concern in our survey, as it targeted the coordinated MSDSEs, but ad hoc efforts can be cross-institutional, a situation in which this concern could be exacerbated. It is also relevant to any large institution where, e.g., multiple departments may rely on ad hoc efforts to teach coding skills. Individuals’ oversubscription to overlapping efforts can exacerbate problems with follow-through and burnout. The coordination of efforts within institutions or cross-institution communities and disciplines remains a difficult but important concern. It is most acutely felt at institutions with relatively lower levels of institutional support or with relatively smaller data science communities.

Work towards continuity, reproducibility, and scalability

One possible way to help coordinate education efforts may be by using the tools of scientific reproducibility that have already become a staple for data science (e.g., open code repositories like GitHub and the Open Science Framework). By openly sharing these materials, organizers of new efforts can see what topics have been covered by other efforts and prevent the unnecessary duplication of efforts by reusing existing materials as appropriate [ 18 , 22 , 33 ]. Efforts that have generated a stable repository of education materials reported this to be a major achievement and benefit for future sessions. Some efforts are actively working to address these questions [ 13 ], and future work may seek to document the impact and uptake of shared learning materials.

In addition to providing lasting resources for ad hoc effort participants, adopting open science principles may facilitate incorporating particularly relevant and successful ad hoc efforts into formal curricula components. Using such tools may be most impactful by serving as vehicles to replicate and spread expertise to smaller and less well-funded institutions.

Open questions

The shape of ad hoc efforts will undoubtedly change at the MSDSEs and beyond as data science matures. As such, many questions remain facing ad hoc education efforts for data science. Through survey responses and conversations with other data science educators and researchers, we have identified a few open questions that will likely influence the future of ad hoc efforts at the MSDSEs and beyond by contributing to conversations at the intersection of ad hoc efforts and formal data science curricula. The open questions that follow are meant to engage education-focused members of the entire data science community as they work together to identify a range of solutions that can address a variety of institutional, domain, and individual needs.

To what extent will formal educational opportunities that emerge for data science diminish the need for ad hoc education efforts?

Changes in formal curricula are unlikely to entirely eliminate the need for any ad hoc efforts. This is evident from the existence of ad hoc efforts (e.g., informal research projects, summer schools, lecture series) in mature disciplines (e.g., biology, physics) and because some strengths of ad hoc efforts have been much more difficult for formal curricula to achieve (e.g., improving diversity, providing approachable introductions). However, the nature and content of ad hoc efforts will undoubtedly change as formal education efforts in data science grow and as novel formats for curricula are considered across departments [ 34 ]. For example, basic programming skills and model interpretation are being increasingly taught in many departments [ 5 , 6 , 8 – 10 ], degree programs in data science are proliferating [ 12 ], and some universities are beginning to require introductions to computer science. Incorporating some of the skills taught in ad hoc efforts into formal curricula will likely change the balance of ad hoc efforts and curricula, potentially lessening the need for some ad hoc efforts.

How can we identify the often overlooked institutional infrastructure that already supports ad hoc efforts?

Although many of the respondents did not explicitly address it, the institutional infrastructure within and across the MSDSEs has been an essential element in the successes of ad hoc efforts. As a result, it is important to recognize the invisible infrastructure that makes this possible at institutions: dedicated co-working spaces that are perfect for these events, administrative staff that support logistics and communications, a wealth of knowledge shared freely throughout sibling programs, and funding for scholars across career stages to work collaboratively. These have been key for the success of the ad hoc efforts run across the MSDSEs and are, arguably, the most difficult to reproduce given the financial investment. In order to expand access to ad hoc data science education, we must identify these invisible contributors to success at high-resource institutions and then attempt to identify solutions that can accommodate a range of resource availabilities at other institutions.

To what extent should ad hoc efforts facilitate replication at resource-poor institutions?

While ad hoc efforts at individual institutions have provided data science support for some individuals, it is unclear how to scale efforts not only within institutions but also between institutions. Generating material and support for implementing efforts outside of the MSDSEs—especially at institutions with varying resources—is a particularly important area for consideration. Like the previous open question, addressing these disparities in resources and outcomes will take a concerted effort across a range of institutions. Ultimately, creating a variety of different ad hoc data science education effort models may allow lower-resource institutions greater flexibility in identifying models that can work for them. However, answering this question will take additional work and must incorporate more diverse voices: The institutions that we have considered share similar profiles as large research institutions and therefore may not have lessons that generalize to institutions with different profiles.

Limitations and future directions

This work is a first step in examining the ad hoc data science education landscape, so it has various limitations that provide avenues for future work.

First, our survey targeted only efforts held at the MSDSEs, which are coordinated efforts at institutions of somewhat similar profiles (i.e., large research universities in the United States). Thus, lessons learned might need adaption for efforts at institutions of different profiles with different focuses, resources, and communities. Further work is needed to fully generalize to data science education beyond the MSDSEs. For example, the high level of targeted investment in data science through the mission of the MSDSEs—along with the general level of resources available at the host institutions—present a certain set of ad hoc effort opportunities, and there may be unique pressures, concerns, and opportunities at institutions with different profiles that cannot be readily seen in our survey. Future work should target a broader range of institutions to compare and contrast their needs and experiences.

Second, our work is grounded in a largely open-ended survey of organizers of these events and is limited to their subjective perceptions, which may be biased. We were concerned about potential positive bias in reporting retrospectives, so we designed the survey to try to produce a holistic and balanced view of each event: Out of the 6 open-ended questions asked, only 1 question explicitly asked organizers to describe their successes, while 3 questions were designed to get organizers to think about limitations of their effort. However, organizers may still have unintentionally responded more positively due to their personal involvement in the efforts, as has been established by behavioral research on response bias (e.g., [ 35 ]).

Third—and related to the previous limitation—we did not collect data on participants’ subjective experiences or on objective learning outcomes. Some previous work has looked to empirically examine participants’ perceptions and learning outcomes (e.g., [ 13 , 19 , 20 , 30 , 31 ]), and the present work is intended to complement that work. Future work should attempt to bridge these 2 perspectives quantitatively and qualitatively. Special attention should be paid to whether the organizers’ goals and perceived benefits match participants’ expectations and experiences. These follow-ups are especially important given recent mixed findings on whether short-format trainings—such as boot camps—are [ 13 , 19 , 20 , 31 ] or are not [ 30 ] effective.

Finally, shortcomings (and successes) are likely underreported because codes were derived from responses to open-ended questions. A more accurate count might come from creating a survey that asks for explicit ratings of closed-form questions. Future work should identify converging ways of evaluating ad hoc efforts by bridging qualitative and quantitative methodologies. One starting point may be to leverage the codebook developed here to inform closed-form surveys or to continue to code open-ended responses.

While ad hoc efforts (like volunteer research experience and seminar series) have broadly been a staple of academic institutions, ad hoc efforts have played a particularly important role within data science education. The role of ad hoc efforts will likely continue to rapidly evolve with the evolution of data science itself—especially as the field grows to encompass formal courses, degrees, divisions, and departments.

We explored a variety of ways that ad hoc education efforts have attempted to complement formal curricula, along with important considerations that can increase the likelihood that these efforts meet their desired impacts. Additional qualitative and quantitative work is needed, but our discussion of the lessons learned across the MSDSEs will allow future efforts to improve upon past efforts and to benefit a wider audience.

Here, we developed a new codebook that may be used to ground future evaluations of ad hoc efforts. We then used that codebook to extract insights, suggestions, and recommendations that will allow active and future practitioner-leaders from a variety of fields—in computational biology and beyond—to improve their educational outreach. By presenting this synthesis of ad hoc education efforts in data science to practitioner-leaders, we seek to inform conversations about refining these efforts, understanding their place in data science education, and shaping the future of data science education.

Materials and methods

We sought to compile an understanding of what types of ad hoc efforts have been developed and to extract a series of lessons learned from these responses.

Efforts surveyed

To find a diverse yet tractable group of ad hoc efforts to survey, we considered the efforts undertaken across the MSDSEs. We sought to include every educational effort held at an MSDSE that did not necessarily provide any course credit and was not required to complete a degree program. In some cases, students could apply for independent study to receive credit for extended (e.g., semester-long) ad hoc efforts, but this was not universally the case.

The MSDSEs were the Center for Data Science at NYU ( https://cds.nyu.edu ), the Berkeley Institute for Data Science at UC Berkeley ( https://bids.berkeley.edu ), and the eScience Institute at UW ( https://escience.washington.edu ). These sibling initiatives were charged with advancing the intersection of domain sciences and data science, making them a prime test case for understanding the state of ad hoc education efforts today.

Data collected

To learn from the MSDSEs’ ad hoc education efforts, we contacted the organizational leads of the MSDSE environments to inquire about what events they already knew were happening, compiled a preliminary list of efforts held, and contacted organizers of those events with an online survey. We sought to include every educational effort that was not designed to offer course credit or be needed to complete a degree program at one of the universities. Links to the survey were also sent via email to general listservs at each of the 3 MSDSE institutions. These complementary approaches allowed us to target known organizers of known efforts and to solicit responses from a broader range of efforts and individual organizers.

The survey consisted of 2 multiple-choice questions about goals and audiences (see Table 3 ), questions for logistics, and 6 open-ended questions targeting 4 main areas: (a) the description of the effort, (b) its strengths and weaknesses, (c) lessons learned, and (d) suggestions for future efforts. The exact wording for these open-ended survey questions is provided in Table 4 . This survey was designed to get organizers to think critically about their effort and elicit a balanced perspective on each effort in context.

In addition to quickly incorporating and disseminating emerging methods and tools through focused efforts that deploy quicker than curricula, ad hoc education efforts can meet other needs that have not been fully served by curricula. While many universities are innovating to address data science education (including initiatives at UC Berkeley [ http://data.berkeley.edu/ ], NYU [ http://datascience.nyu.edu/ ], and UW [ http://escience.washington.edu/education/ ]), we identified 4 key areas in which ad hoc education efforts could strive to support community needs: improving coding ability, improving practical knowledge of statistical methods, exposure to research, and mentoring and career development. Similarly, we identified 9 possible audiences that ad hoc efforts might target. Respondents were able to indicate which, if any, of these audiences and goals they had in mind, and they were able to input additional audiences and goals that we did not provide to specify effort intentions.

To extract lessons learned and suggestions for ad hoc efforts, the first and second authors used inductive coding research methods from ethnography and other qualitative research to analyze practitioner-leaders’ open-ended responses through close, iterative contact with the data [ 27 , 28 , 36 ]. These standard methods in qualitative research allow for grounded and inductive insights from open-ended data or a mix of open-ended and structured data (e.g., [ 37 , 38 ]).

The first and second authors began by reviewing the responses together. The first author then created an initial codebook of relevant themes taken from considering the answers holistically. The first and second authors then worked to refine the codebook together through another round of independent coding while discussing the codebook. The 2 authors retained the codes that both authors individually rated as applying to at least 2 distinct efforts. The first and second authors then coded the analyses together to come to full agreement on all final codes that are discussed here, similar to previous work in this area [ 39 ]. The final codebook and resulting codes formed the foundation for the analyses presented here (see Table 5 ); as noted earlier, we see the the resulting codebook as a product of this research that could be useful for future studies exploring ad hoc efforts [ 39 ].

Codes were developed using grounded qualitative methodology [ 27 ]. Because the survey relied on open-ended questions, the ratings provided here are likely lower than what organizers would report with specific multiple-choice (e.g., Likert-style scales) or polar (e.g., yes/no, true/false) questions.

Ethics statement

This study was approved by the UC Berkeley IRB, and we received written consent from participants, as according to the approved protocol.

Acknowledgments

We would like to acknowledge the immense role that the Moore-Sloan Data Science Environments initiative played in the generation of this publication and in the underlying educational efforts that it reflects. We would also like to thank Cathryn Carson, Saul Perlmutter, the members of the Education and Training Working Group at BIDS, and all of those who attended our discussion sessions at the 2016 and 2017 Moore-Sloan Data Science Environments Data Science Summits for formative discussions. We are thankful for the invaluable feedback on earlier drafts provided by Sarah Stone (UW) and Micaela Parker (UW) and their enormous contributions to growing the MSDSEs’ data science education efforts. Finally, we would like to thank the practitioner-leaders who completed our survey across all three institutions.

Funding Statement

The author(s) received no specific funding for this work.

Data Availability

What is ad hoc research/advantage/longitudinal research diff.

To do ad hoc research , you must take into account factors such as the subject of the study, its purpose, as well as the human team you have. Without forgetting another series of variables such as the methodology you want to use and even the budget.

There are two main types of studies in market research :

• Follow-up studies or long-term projects
• Market research projects that are adjusted according to needs

Let us know the characteristics of an ad-hoc research and how it differs from longitudinal research .

Difference between ad hoc research and longitudinal research

Ad hoc market research projects are usually short-term, one-time projects designed to address a specific goal.

Whereas longitudinal or long-term research is designed to study participants over a longer period of time or to measure a specific goal continuously.

In short, ad hoc projects are usually one-time projects, while longitudinal projects are more continuous research programs.

Advantages of ad hoc research

These are some of the benefits of conducting ad hoc research

1. Specificity

Ad hoc research is carried out for a specific purpose and offers high-quality data solutions for whatever problem your company faces.

Ad-hoc market research can be done as part of a single channel survey or it can be tailored to suit customer needs.

2. Save money and time

Ex profeso research studies are a unique project that quickly responds to the research needs of a company in a short period of time.

In the long term, this type of market research project saves an organization money by providing results quickly and efficiently without having to continually send surveys over a long period of time.

3. Customizable

A tailor-made ad-hoc market study can be conducted to help clients apply useful solutions to any problem. You can design a survey and select a specific method to carry out the research .

4. Ensures flexibility

Ad-hoc research projects allow the end user to modify the research and add additional questions to meet their research goals and objectives.

5. Streamline decision making

Data from an ad hoc study is used as a decision-making tool.

Depending on the client ‘s needs, you can show a preview of things to improve. Once the data is analyzed, the client and your team can take steps to make those improvements in order to make the business run more efficiently.

6. Applicable to any business

This type of market study can be carried out for any industry, be it education , healthcare, hospitality, retail, etc.

Examples of an ad hoc research

One restaurant is vastly outperforming the other 10 establishments in the country.

The store’s revenue has continuously improved in the last 12 months and there is no data to explain why.

The management team commissioned a brand image survey of 400 residents who live less than 15 minutes from the premises.

The survey tests objectives such as:

• Knowledge of the chain and its competitors.
• The perception of the restaurant in relation to its close competitors.
• What they like and what they don’t like to consume

This study provides the management team with hard data to understand why that particular restaurant is a profit leader .

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• Using abbreviations in academic writing/shortenings/Acronym September 22, 2023

Ad-Hoc Projects

Why are teams with proven project management principles at their fingertips persistently overwhelmed by poorly planned projects and unplanned tasks? Why does today's average office worker spend just 46 percent of each day performing their primary job duties? Often, the culprit is ad-hoc requests.

Table of Contents

What are ad-hoc projects?

Why track ad-hoc projects, what can happen if ad-hoc requests are untracked, what's the best way to track ad-hoc projects, making ad-hoc projects visible., using smart ad-hoc collaboration., report on the success of your ad-hoc project., frequently asked questions..

The meaning of an ad-hoc project is work that has been formed or used for a special and immediate purpose, without previous planning. Mid-project and ad-hoc requests can come from unexpected reports, project and product updates, last-minute reviews, quick emails and even coworkers walking over to your desk.

“Ad hoc” is a Latin phrase that literally translates to “for this” or “for this situation.” In other words, it refers to things that are specific, non-generalizable, non-repeatable. Ad hoc work might be a side project your line manager asks you to run, alongside your main focus area or a series of small distractions.

If people in the office occasionally ask you to drop what you’re doing to help with administrative tasks or pricing, these are ad-hoc requests. Common ad-hoc work examples include:

• Internal IT projects
• Requests to organize company events
• Finding the answers to client queries
• Quick-reaction work that responds to a trend

As long as you're efficiently  executing projects , what's the big deal about leaving those ad-hoc projects untracked? Isn't it more effort than it's worth to log a random ad-hoc project into your system?

There are actually wide-ranging benefits to finally shining a spotlight on all the extra ad-hoc tasks your team completes. Once project managers start logging everything into a comprehensive work management system, they'll be able to:

• Accurately report how each team member spends their time
• Manage resources more effectively
• Redirect time and attention toward key strategic initiatives
• Justify current headcount and/or lobby for additional positions
• Say "no" or "not this week" to less important tasks — and easily explain why

Most project managers have major improvements to make in how they clarify, manage, and renegotiate their total inventory of projects and actions. If you let yourself get caught up in the urgencies of the moment, without feeling comfortable about what you're not dealing with, the result is frustration and anxiety.

When each ad-hoc request remains untracked, it’s easy for time and money to be lost and become untraceable. If you’re wondering why a portion of the personnel budget allocated to your main project seems to have disappeared, a stack of ad hoc task requests could be the culprit.

Without tracking, an ad hoc project request can suck time and energy away from what’s important, meaning your core efforts are side-lined.

Reporting on ad-hoc projects can be so important to facilitate:

• Improved progress tracking – Last-minute tasks can quietly erode team productivity without anyone noticing. Tracking can help you keep tabs on how projects are being affected by them.
• Building a suitable team – Knowing exactly how much time ad-hoc requests are taking up can bolster your case for recruiting staff to cope with it. For instance, if an ad-hoc project requires a data expert, tracking outlines resource needed.
• Better resource management – Tracking the hours required for ad-hoc requests means the wider business can manage its human resources better, and make informed decisions on resource.

The market is glutted with task-tracking systems that make it easy to monitor these kinds of unpredictable, unplanned ad-hoc projects. A successful planning phase helps you to define scope, so use these earlier decisions to decide what to track.

Several project management solutions are designed to help teams organize and execute complex projects. But there are very few systems like Workfront that can integrate both, enabling teams to track comprehensive projects alongside these random "surprise" ad-hoc requests.

A comprehensive work management solution is the best way to go. Even if you don't have one in place yet, the four core principles that follow will supercharge your team's productivity, no matter what system you use.

1. Stop accepting “under-the-table” ad-hoc requests.

Every single task must be documented and accounted for and submitted with a  project request form . Each individual ad-hoc request stacks up to paint a picture of inefficiencies, so standing firm can reap rewards.

Ad-hoc project managers often find they’re called in to save the day when an issue arises that doesn’t quite fit into standard business procedures. When you are, you should:

• Pull together a team by speaking with departmental heads
• Source the best talent at short notice
• Define the parameters of your ad-hoc project
• Assign clear tasks and start collaborating

2. Standardize your request management processes.

Rather than accepting work requests via email, voicemail, sticky note or hallway conversation, manage the chaos of incoming projects more effectively. Start following request management best practices and create a  project intake process .

Steps include:

• Creating a centralized request hub
• Managing and prioritizing all requests
• Standardizing your request template (using a  creative brief  or similar form)
• Defining  project requirements  and clarifying expectations

3. Create ad-hoc project blocks.

Encourage each team member to regularly block out time to tackle ad-hoc work. If those one-off ad-hoc requests can be gathered together and turned into a planned combined task, they won't feel like a dozen little interruptions.

Managers who have several team members with similar or overlapping job descriptions could even designate a different person each day to be available to capture, prioritize, and complete ad-hoc requests. This then frees up other team members to focus more time on their top priorities.

4. Make every task visible.

If all you've been tracking so far are larger projects, the managers and executives above you may get the impression these large projects are all you ever do. And that they seem to take a lot longer than they should.

Once you start logging smaller requests into your work queue, a much more accurate picture of your team's daily contributions will take shape. Whether you do this with a work management solution or a  burndown chart  that's hanging on the wall (in  Agile project management ), make sure it catches the attention of the powers that be.

Both you and your boss should have complete visibility into what your team is working on now, where current projects stand, and how much bandwidth is left over.

The more you can make plans that reflect what's really happening with your team—by making invisible work visible, creating a centralized request queue, and blocking out time for clusters of ad-hoc projects—the more flexibility you'll have to make adjustments when things inevitably begin to go awry.

So-called ‘under the table’ ad hoc projects can threaten your bottom line and impact team cohesion. When things are visible, they’re more likely to seem fair. Key stakeholders can also scrutinize your plans, reducing the risk of oversights.

Collaboration is key to successful ad-hoc work. Coworkers want to know when the agenda shifts, and you also need razor-sharp processes to make communication slick and effective, once work is underway.

In person, you might pull the team into a meeting room for an afternoon. For remote teams, the software you’re using can make a big difference. With Workfront, multiple players can view data at the same time for optimal teamwork, helping manage priorities .

When a project takes off at lightning speed, it can be easy to forego the formalities. Ad-hoc projects rely heavily on reporting, however. This step allows you to measure success, learn lessons and justify your efforts to those higher up the chain.

Pull data seamlessly from your project management software to create an easily digestible log of key tasks and headline numbers. Pair with a written ad-hoc project summary and your case will be backed up even further.

What is the definition of an ad-hoc project?

An ad-hoc project is a term that covers work that is unplanned and potentially has a very tight deadline for completion. These are tasks that can arise during a project and happen unexpectedly.

The immediacy of these tasks, coupled with their last-minute arrival can cause disruption to teams and projects if not managed correctly.

What is an ad-hoc manager?

An ad-hoc manager is someone assigned to manage ad-hoc tasks when they happen. This person might not work on a specific project on an ongoing basis but can offer help to team members when they are coping with last-minute requests.

Having an effective ad-hoc manager can help workers focus on their assigned projects and keep on track with ongoing project work.

What are some ad-hoc work examples?

Examples of ad-hoc work will depend on your particular industry. However, you might consider any tasks outside of your usual focus or project work to be ‘ad-hoc’.

Administrative tasks, unplanned projects, meetings and catch-ups could all fall under the definition of ad-hoc work.

The blog for passionate planners

• Agile , Productivity , Project Management

3 Best Practices for Managing Ad Hoc Projects

In mainstream project management, you typically strive for a recurring set of tools and workflows: the scope statement, the work-breakdown-structure, the financial analysis, time and cost estimates, the risk assessment, and so on.

But any experienced project manager knows there’s no such thing as a typical project. One project type that companies often struggle with is the unexpected ad hoc project .  These quick-turnaround work requests usually arrive out of the blue, hit hard, and leave chaos in their wake before project managers can say “ estimation .”

One of the biggest challenges about ad hoc projects is establishing a process to something that feels like a mini storm system. Yes, quick-turnaround projects can feel disruptive, but you can also bring some order to them as well. Let’s have a look at how teams do this.

What makes ad hoc projects unique?

Though the core framework is the same as a larger project (you’re still driving to accomplish a goal within a constraint), there are a handful of characteristics that make ad hoc project management unique:

Shorter time frame: As you might have guessed, quick turnaround projects typically span much tighter time frames than larger, well-planned out projects. The duration of Ad hoc projects is typically between one day and one month, although this range can vary depending on business definitions.

More localized impact: Large, pre-planned projects have numerous business ramifications, affect multiple groups of stakeholders, and can even be part of a portfolio of interdependent projects. Ad hoc projects, on the other hand, are usually focused on a single goal and/or a specific group of stakeholders.

Less red tape: Because of their limited time frame and smaller scope, these rogue projects are generally quicker at getting off the ground, versus a complex, multi-faceted project that requires approval and revision from upper management across multiple departments.

Less resource intensive: Although there are certainly exceptions to this rule, ad hoc projects tend to rely more on specialized talent and resources than the wholesale supply of financing, labor or materials. That’s because they address a specific, temporary function rather than a broad initiative.

Here are some common examples of ad hoc projects in various industries:

• Implementation/adoption of new technology or workflow (such as migrating to the cloud)
• Ad-hoc system and software development (e.g. to patch a security vulnerability or fulfill an unanticipated request)
• Special events (such as fundraising dinners, auctions, or conferences)
• Ad-hoc campaigns or sprints (to pursue a temporary market opportunity or respond to a news item or trend)
• Special requests from above (a stakeholder makes a request you can’t refuse)
• Committee-based work

Collaborating on short-term projects

One of the biggest ways ad hoc projects are unique is that they depend heavily on unimpeded collaboration between stakeholders . Without time as the great equalizer, project managers can’t wait for information and requests to trickle through the bureaucracy. Everyone involved—regardless of team, department, or pay grade—needs to be on the same page about the project at each step.

Recent data from ESI International revealed that less than a third of teams “effectively drive project success,” and over 65 percent believe better collaboration is the answer. Many businesses are finding a solution to this discrepancy in project management software —especially cloud-based solutions that help teams communicate and share information and artifacts (code, blueprints, guest lists, etc.) in real time. This creation and curation of a unified repository is often referred to as “ knowledge management .”

Without a system in place for sharing knowledge, the burden often falls on one poor soul who knows everything, and then the rest of the team forms a line to ask questions.

3 best practices for managing ad hoc projects

Along with constant collaboration , there are a number of other best practices for driving timely, successful completion of short-term projects. Here are three of the most important:

• Prioritize risk assessments. The limited time frame of ad hoc projects truncates many of the procedures of traditional project management. One of the most time-consuming procedures is risk assessment. While it’s still important to anticipate weaknesses and vulnerabilities in the planning phase, be judicious about which risks you invest time into bypassing. Generally, it’s best to assess only the risks that directly relate to project values and carry high probability and high impact. This can include both negative risks (will cause harm if they come to fruition) or “opportunity risks” (could add value to the project unless they are overlooked).

Be Agile. Traditional, waterfall-style project management probably isn’t the best approach for small-scale projects on a tighter deadline. Instead, the best approach is Agile , one that provides flexibility and minimizes effort by maximizing the amount of work not done. Most frameworks and tools within the Agile spectrum fit this description and also reinforce collaboration best practices.

Have a plan. If you’re trying to put together a project by the end of the week, then you don’t have time to form a committee and hold status meetings . But a short timebox doesn’t negate the importance of planning—however concise it may need to be. In fact, you might find that if you don’t plan, the project will take longer and cost more. According to the Project Management Institute , only 50 percent of projects are completed within their originally allotted time frames, and 44 percent experience scope creep . Even if it’s bare bones, creating a work breakdown structure (WBS) is helpful in order to divide the project into its smaller components for accurate time and cost estimates.

Think of ad hoc projects as highly concentrated versions of normal projects. They’re driven by the same forces and requirements, but take place on a smaller scale, with less resources, fewer goals, and a shorter allotted time frame. With the right software tools and best practices, your organization can perform with the same efficiency and foresight you bring to larger business initiatives.

If you liked this article and would like to know more about how to successfully impact projects, download our eBook, 5 Practical Habits for Today’s Project Manager .

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• Blog Featured Post , Collaboration , Leadership

What Is Ad Hoc Reporting? Your Guide To Definition, Meaning, Examples & Benefits

Table of Contents

1) What Is Ad Hoc Reporting?

2) What Is Ad Hoc Analysis?

3) Benefits Of Ad Hoc Reporting

4) Ad Hoc Analysis Examples

5) Static vs. Ad Hoc Reporting

6) Challenges Of Ad Hoc Analysis

7) How To Create Ad Hoc Reports

8) Ad Hoc Reporting Tools Features

9) Ad Hoc Reporting Tool Example

Digital data is all around us. In fact, we create around 2.5 quintillion bytes of it every single day, with 90% of the world's digital insights generated in the last two years alone, according to Forbes.

If utilized correctly, data offers a wealth of opportunity to individuals and companies looking to improve their business intelligence, operational efficiency, profitability, and growth over time. In this day and age, a failure to leverage digital data to your advantage could prove disastrous to your business – it’s akin to walking down a busy street wearing a blindfold.

With the rate of available data growing exponentially, it's crucial to work with the right online reporting tools to not only segment, curate, and analyze large data sets but also uncover answers to new questions that you didn't even know existed. And when it comes to finding actionable answers to specific questions, ad hoc analysis and reporting are essential. We will explain the meaning, benefits, and uses in the real world. Let's kick it off!

What Is Ad Hoc Reporting?

**click to enlarge**

Ad hoc reporting is a branch of business intelligence used to generate one-time reports in the form of dynamic dashboards with real-time data. With the help of self-service BI tools, users can easily create ad hoc reports as required without technical knowledge.

Working alongside recurring or ongoing (daily, weekly, or monthly) data reports, ad hoc reporting forms a vital part of any business, brand, or organization’s growth and sustainability by offering a level of insight that adds an extra layer of substance and success to the data-driven decision-making process.

While these reports are typically developed using SQL (structured query language) by an IT department, which can take several days, some tools and platforms allow non-technical business users access to these most precious insights simply using a SQL report generator . And this lies in the essence of the ad hoc reporting definition, providing quick reports for single-use without generating complicated SQL queries. 

Moreover, a host of ad hoc analytics or reporting platforms boasts integrated online data visualization tools to help enhance the exploration process. This reduces the reliance on software developers or IT personnel for simple reporting.

After explaining the report's meaning, we will take a closer look at the analysis part in more detail.

What Is Ad Hoc Analysis?

Ad hoc analysis is a business intelligence (BI) process companies use to answer critical one-off questions in real time. It allows for spontaneous and agile decision-making during strategic discussions, making the reporting process flexible at the risk of less accuracy.

With ad hoc analysis tools, users often create a report that does not currently exist or drill deeper into an existing dashboard report to achieve a deeper level of insight that ultimately benefits the ongoing success and sustainability of the organization.

Ad hoc data analysis is the discoveries and subsequent actions a user takes as a result of exploring, examining, and drawing tangible conclusions from a report.

Typically, ad hoc data analysis involves discovering, presenting, and actioning information for a smaller, more niche audience and is slightly more visual than a standard static report. Now that you know the two main definitions, it is time to look into the benefits and, afterward, real-world and practical examples.

The Benefits Of Ad Hoc Reporting And Analysis

Now that we have answered the question, ‘What is an ad hoc report?’,  let’s look at the clear-cut benefits of using these types of data reports :

1. Reduces the IT workload: 

The self-service nature of ad hoc reporting catalyzes the report creation process by allowing end-users to work with customized reports on niche areas of the business without relying on the technical assistance of developers. This saves time and costs while minimizing any potential interdepartmental roadblocks.

2. Easy to use: 

As ad hoc data analysis platforms or dashboards are intuitive and visual by nature, uncovering the right answers to the right questions is simpler than ever before, allowing users to make decisions and roll out initiatives that help improve their business without the need for wading through daunted streams of data.

3. Ensures flexibility within the constantly changing business environment: 

Ad hoc analytics offers an interactive reporting experience, empowering end-users to make modifications or additions in real-time. As report elements are picked individually, users can ask questions and customize their needs and goals. It is of utmost importance to answer business questions as quickly as possible, and one of the benefits of ad hoc reporting provides just that - the possibility to follow the ever-changing business environment as the business moment requires and continually evolves.

4. Saves time and costs:

Modern ad hoc reporting tools are designed to save countless hours since their interface is designed to be simple yet powerful. The intuitive nature helps users create interactive visuals without waiting for a professional analyst or, as mentioned, the IT department. This self-service BI nature that enables a data-driven system completely in control by the user ultimately saves countless working hours and costs since users don't have to wait for reports and build as many types as needed.

Moreover, the team will be more engaged if they can immediately manipulate formulas and avoid multiple spreadsheets to consolidate data or static presentations that are fixed upfront and give no possibility to dig deeper into the data.

5. Completely customizable:

While ad hoc enterprise reporting is focused on gaining and keeping visibility across a large organization, it's important to consider the customization possibilities that these solutions have on offer. Some of the tools offer built-in dashboards, for instance, that already have templates that you can use and adjust based on your needs. That way, you can save even more time and focus on what truly matters: the business answer you were looking for. But not only that, the possibility to build your queries within the advanced SQL box, as mentioned, will provide you with even more freedom if you're an experienced analyst and looking for modern software solutions.

Types Of Ad Hoc Reports Examples - Analysis Applied To The Real World

There’s no doubt about it: ad hoc analysis offers a wealth of value to businesses across industries and sectors . To demonstrate its potential, let’s delve deeper into the practical applications of this invaluable data-driven initiative in the business world.

• Ad hoc financial analysis:

The first in our list of ad hoc reporting examples is focused on finance. By its very nature, the financial industry (or the financial departments) is rife with facts, figures, financial KPIs , metrics, and data. Ad hoc data analysis has offered businesses the means to drill down deep into very concentrated segments of data – or business aims – gaining the ability to spot trends that will provide the best return on investment (ROI).

In essence, you perform ad hoc financial reporting whenever you need to better understand your financial data. For instance, at the end of the month, you need to find out how much revenue you have left after deducting your direct costs. Essentially, you (or a stakeholder) want to know your gross profit margin ASAP.

What ad hoc reporting brings here is an immediate answer, without waiting for days from the IT department to generate a simple visual like the one above or complete ad hoc dashboards if you have a specific meeting or presentation planned.

While these are the primary industries that benefit from this analytical practice, regardless of your sector, by utilizing reports like this alongside interactive business intelligence dashboards , you will see notable improvements in key areas of your business by utilizing reports like this alongside interactive business intelligence dashboards.

• Ad hoc reporting in sales:

Ad hoc reporting and analysis can be used in a company with a large sales database. Let's say a user wants to determine the outcome of a specific sale related to a particular scenario. S/he would build a single report, used only once, to provide that result. This scenario can be found in companies with a large outside sales force, which then can export an ad hoc report showing results from their territory (number of clients visited or leads generated) against overall sales goals.

• Ad hoc reporting in healthcare:

Another area we can focus on is healthcare. A physician may not know how to build an HTML report or run a SQL query, but a reporting tool can easily generate data that are needed quickly and only once - a blood test report, for example, or how many people were admitted to the ER on a specific day/week.

Ad hoc analysis has served to revolutionize the healthcare sector. Utilizing healthcare analytics software by providing greater data visibility and improving accuracy while helping senior stakeholders in such institutions make swift and accurate decisions that ultimately save lives, improve operational efficiencies, and decrease mortality rates.

• Government:

Governmental entities deal with a wealth of critical information, insights, and decisions that ultimately affect many people. By gaining the ability to hone in on very specific tasks or challenges and reach the level of insight needed to make accurate, prosperous decisions while automating manual data-gathering tasks, governmental bodies across the globe enjoy improved public fund allocation while boosting productivity. A testament to the power of ad hoc analysis.

• Ad hoc recruiting reports:

Running personalized, quick, and accurate recruiting reporting is paramount in our competitive business environment. Using an ad hoc reports example from HR, companies have the chance to spot deficiencies within their human resources management and improve employee satisfaction levels, which is critical considering the lack of talent across industries .

In a practical sense, you could suspect or assume a higher absenteeism rate over a year or six months. Investigating further by generating an ad hoc reports example similar to the one above could prove to be extremely advantageous. The company can identify if the assumption was correct, meaning if rates went higher, were stable, or decreased. If there is an increment, you can easily determine the cause by engaging with employees and finding an appropriate solution to your problem. To create such visuals, you can explore our article on the most prominent recruitment metrics .

These types of solutions prove particularly effective in loss prevention in the retail sector. Through store-specific retail analytics tailored to particular areas of loss prevention, such as shoplifting or employee theft, a host of notable retailers have been able to track inventories and spot trends that have saved them a great deal of money (and time) in the long run.

In retail, it's important to regularly track the sales volumes to optimize the overall performance of the online shop or physical stores. An ad hoc report example such as the one above could pinpoint specific weeks where the sales volume was lower than usual. By examining the column chart deeper, you can conclude that the demand was lower due to external conditions, for example, such as a heavy storm that postponed deliveries and caused many cancellations.

The educational sector is vital to the future of our society, and ad hoc data analysis has played a significant role by streamlining a host of processes through focused data and analytical reporting. It also facilitates the sharing of information between departments to help engage students on a deeper, more personal level. This level of initiative results in improved success for faculty, students, and, in turn – the economy.

What these types of reports bring to the table is simple: efficient decentralization of data management and transferring the analytical processes directly to the end-user. While you can utilize numerous data analysis methods you can utilize, an ad hoc reporting system will enable you to perform analyses on the spot and immediately answer the question you have asked. This is not only critical in business intelligence but, as we have seen, in other areas such as education or government services.

• Customer service: 

Maybe more than any other department, customer service can benefit from a one-time report to answer critical questions that will guide them on the path to offering the best possible support to customers. For instance, a support manager might need to generate a report to understand how many tickets were solved in the past week and on what communication channels so they can plan their strategies accordingly. 

A deeper drill down into this data can shine a light on other elements that are interesting to look at. For example, by comparing the peak times in which customers are most likely to call, managers can ensure that agents are available at those times to cover the demand. Additionally, you can look into the average time to solve an issue and tackle any inefficiencies. 

• Marketing: 

As seen throughout this post, ad hoc reports present data visually, making it easier to analyze and extract actionable insights on the spot. This is particularly true when it comes to making the most out of your marketing efforts. When dealing with promotional campaigns, you need to make the most out of your available resources. When a promotional campaign was launched in the past, it was not known whether it was successful or not until a report was generated after a few weeks. Thanks to the speed of this kind of report, marketers can now understand in real-time how a campaign is being perceived and adapt it accordingly to avoid wasting resources.

• Manufacturing: 

In the manufacturing industry, the use of real-time data provided by an ad hoc report proves to be extremely useful. Knowing the status of the different production stages allows businesses to stay on top of any issues and ensure production runs as planned to meet customer shipping deadlines. 

For instance, a manufacturing company with a big delivery coming can create an ad hoc report to understand the share of production for the different machines. If a machine is observed to be underperforming, the report will show it, and corrective measures will be implemented. 

11. Logistics 

Probably more than any other industry on this list, logistics is the one that can benefit the most from ad hoc analysis and reporting. Getting on-the-spot information about several operational processes, such as the number of orders, inventory labels, machine performance, workforce availability, and much more, enables logistics managers to find any potential bottlenecks to ensure the daily operations are running smoothly and customer deadlines are being met. 

The ad hoc report sample above tracks the on-time shipping. This is one of the most important logistics KPIs to track, as it directly influences customer satisfaction. Generating an ad hoc document for this KPI daily to understand how the warehouse performed is a great way to spot improvement opportunities and tackle any inefficiencies.

12. Procurement 

Last but not least, we have procurement. Just like all other industries, the procurement department can benefit from ad hoc management reports to identify weak areas and streamline their performance in real time. This level of insight enables them to uncover trends and patterns to negotiate better contracts with suppliers and obtain the best materials and services.

The image above shows an example of how the department can benefit from these kinds of tools during its procurement analytics process. For instance, if the CPO needs to send an urgent order to a supplier, he or she can generate an ad hoc report about supplier purchase order cycle time and identify the supplier with the shortest cycle.

Static Reports vs. Ad Hoc Reporting: Key Differences

So far, we’ve covered some definitions and benefits and looked at practical examples of how ad hoc reports can facilitate the way average business users can manage data on their daily activities. To keep putting their value into perspective, we will compare them to a more traditional approach to data management: static reports. 

Also known as canned reports, this traditional way of reporting has been performed for decades and used by businesses to assess their past performance. These documents are usually generated by data analysts or the IT department and handed to decision-makers on a weekly, monthly, quarterly, or annual basis, depending on previous requirements. Some of the main differences between these two include: 

• Generation: The first difference between these two analytical tools is the way they are generated. As mentioned, static reports are usually created by the IT team upon request of the different departments that use them to answer vital questions. Due to their static nature, the information on them can’t be explored, which makes them less versatile. On the other hand, ad hoc reports are easily generated by the average business user on a need-to-know basis and used to make important decisions. The learning curve for users with no experience can indeed be a challenge, but with the help of the right self-service tool, it is fairly easy to manage. 
• Usability: Next, we have usability. As mentioned, static reports can’t be navigated or manipulated to respond to a specific question on the spot as they are generated with a specific aim in mind and for a wider audience. If a different need arises, a new report needs to be ordered, which can take hours or days to be completed as the IT department might already be busy with other tasks. On the contrary, ad hoc reporting has interactivity and real-time data as a base. They can include various levels of data and are easily navigable to answer any vital question that arises. This is possible thanks to interactive filters and visualizations provided by a dashboard tool .  
• Format: The format in which reports are utilized is another huge difference between these two methods. On the one hand, static documents are usually sent via email in the form of a spreadsheet or PowerPoint presentation. On the other hand, ad hoc analysis can be accessed online from any device with an internet connection. This is one of the multiple BI features you can enjoy if you pick the right solution for your organization. 
• Accessibility: Following the same line as the last point, accessibility is a key element when comparing the two. As mentioned above, a static report is usually shared via email in traditional formats such as an Excel sheet. If something is changed, the user needs to browse through several versions of the same document, which makes it confusing and harder to collaborate. Ad hoc reporting has shearability and data transparency at its core. Thanks to their online nature, reports can be easily shared between departments to implement a collaborative data-driven environment. 

All these points are not to say traditional reporting is bad. In some cases, static documents are useful for businesses, such as showing financial compliance to authorities. That said, their static nature can seem tedious and repetitive for the daily decision-making process. Not to mention, it burdens the IT department with a load of work that is not even as efficient as it could be. For this reason, BI solutions with a self-service approach present a way to manage data in a way that is time-efficient, accessible, and interactive. Regardless, the use of these technologies also comes with challenges for organizations. We will explore some of them in the next section. 

Challenges Of Ad Hoc Analysis & Reports

While implementing ad hoc reporting and analysis in the organization might seem perfect on paper, it doesn’t come without challenges. Although the use of data has become a mandatory practice for modern businesses, there is still a big knowledge gap for average users that make it a bit harder and intimidating to use data for their decision-making process. This is paired with other limitations that we will explain below. 

• Lack of literacy: Studies say that 90% of company leaders cite data literacy as a driver for overall success. However, only 25% of employees say they feel confident working with it. Considering the self-service nature of ad hoc analysis, the lack of knowledge or confidence can present a big challenge. Paired with the lack of general data knowledge, it is also possible to face challenges with employees that are simply not tech-driven or don’t have the initiative to learn. To tackle this problem, implementing training instances to show the friendlier side of analytics is a good way to start empowering employees to implement this practice into their regular workflow. 
• Incomplete data : Having all your data in one centralized location is a key element to ensure a successful ad hoc reporting system. If your information is spread across multiple locations, it can make the report-generation process a lot more difficult. Luckily, BI dashboard tools offer fast and efficient integration of multiple sources that can be visualized in an interactive report with just a few clicks. 
• Lack of governance : Not having an appropriate system to manage the massive amounts of data coming into your organization is another great challenge of ad hoc analysis. Data governance is the practice that ensures data remains secure, available, and usable. Therefore, it is fundamental to implement it to ensure efficiency across the entire reporting process. 
• Covering the needs of all departments : Another challenge is to cover the needs of all departments. This point is related to the stage in which company leaders are deciding on what tool to invest in. As mentioned earlier, traditional reports were meant for wider audiences, while ad hoc ones are more specific and required to answer particular departmental needs. To tackle this challenge, it is necessary to generate an outline in advance and select the tool with the features that will serve all organizational needs the best. To assist you with this task, you can find key features below. 

How To Create An Ad Hoc Report

Now that you know the ad hoc meaning in business, benefits, and challenges of implementing these kinds of reports into your organization, we will dive into some best practices you should follow to ensure you are extracting the maximum potential out of them.

• Define the question you want to answer

Since the end goal of an ad hoc report is to answer a question that is not already answered in an existing report, it is a crucial step to think carefully about that question before diving into the actual generation. This practice should be followed for any kind of report, especially for ad hoc analysis, as you don’t want to waste time answering a question already covered in previous reports. Plus, knowing what question or end goal you are trying to analyze will help you pick your data and layout more efficiently. This leads us to our next point. 

• Select your data 

One of the benefits of modern data analysis is the fact that you can gather data from multiple internal and external sources to get a 360-view of product performance, customer behaviors, and various internal processes. That being said, gathering too much data can be a double edge sword, as having a lot of information can mislead your analysis. This is especially true for ad hoc analysis, as those reports aim to answer a specific question quickly and efficiently. Therefore, you should start by defining the question or discussion you want to explore and select only the data that will help you find the answers you are looking for. 

• Use the right visuals 

As we saw in the challenges section, the lack of technical skills can often present a challenge for these reports. This lack of skills can translate into using the wrong data or visuals and extracting the wrong conclusions. While the self-service nature of these reports significantly mitigates this issue, it is important to carefully pick your visuals considering the end goal of your analysis. That way, you can tell a compelling and engaging story. Setting the tone to build agile and efficient strategies. 

• Prioritize simplicity 

This is a best practice that can be applied to any type of reporting-related area but is especially important in an ad hoc environment due to the need for agile and efficient analysis. When we talk about prioritizing simplicity, we mean avoiding overcrowding the report with unnecessary data but, most importantly, considering design best practices. Choose a smart layout to tell an engaging story with your KPIs, use only a couple of colors that are not too strong or vibrant, and stay away from 3D effects and any other distracting elements, among other things. This is not to say that you should generate a boring report. It is about being smart and only placing the elements to make your process more interactive and efficient. 

• Collaborate with your team 

Once you have generated your reports following the best practices we mentioned above, it is of utmost importance to make the process as collaborative as possible. Share your findings with team members and other relevant stakeholders and support any discussions that might arise during meetings and other instances. This is a fundamental part of successful analysis, as collaboration and communication will ensure your business is continuously growing and exceeding its targets. 

Now, you might be wondering, how do I make all this happen? Luckily, modern ad hoc reporting tools provide a wide range of functionalities that will enable you to not only visualize your data but take your insights one step further. To help you understand a bit more about these solutions, below we will dive into the main features and functionalities you should be looking for. 

What To Look For In Ad Hoc Reporting Tools?

To create the best possible reports, there are some features that these solutions should have on offer to ensure maximum application value. Here we list the most critical ones:

1. Self-service reporting interface

Considering that ad hoc reports are generated for one-time use,  it is of utmost importance to invest in a tool that offers a self-service interface and features. In the past, reports were created by the IT department, and it could take hours or even days to get them. That is no longer enough in today’s fast-paced business environment, where decisions must be made as quickly as possible. A self-service tool enables all users, regardless of technical knowledge, to generate reports and extract valuable insights to boost their strategies.  

2. Real-time access to fresh data 

As mentioned a couple of times already, the true value of ad hoc reports lies in their interactivity and agility. Therefore, a professional ad hoc analysis tool should offer real-time data at the center of its functionalities. Our reporting tool offers users complete access to fresh data as soon as it is generated. This way, decision-makers can generate reports in a matter of seconds and answer any critical questions that might arise efficiently. All the user needs to do is connect the data sources, and the tool will update them every couple of minutes to show any relevant insights that might arise. After all, the true value of modern reporting solutions over traditional tools such as Excel is agile and flexible decision-making.  

3. Advanced interactivity features

It's fairly easy to generate a spreadsheet, but if that spreadsheet doesn't give you the answer you're looking for, then you will have thousands of rows and columns that will cannot easily manipulate with. Interactive ad hoc reports will enable you to drill into bits and pieces of specified data analysis and ensure you can interact with your report using advanced interactive features of professional business intelligence dashboard software .

From advanced chart options and sophisticated filters to time intervals and chart zooms, the possibilities to interact with your data are immense. Besides, overcrowding your screen space is a thing of the past - interactivity features of the modern dashboard software continue to evolve and adjust to the users.

4. Access to numerous data sources

By having access to different data sources in one single place, a report can easily answer current and upcoming business questions with every piece of data a company has.

With solid ad hoc reporting software, it's possible to apply controls to specific dashboards by adding elements like screen filters, sliders, conditional formatting for filtering, and link reporting dashboards for direct comparison. That way, all data can be easily accessed and managed.

5. Basic and advanced analytical possibilities

These reporting solutions need to offer basic and advanced analytical capabilities. No matter if you're an average business user that needs to extract a simple report or an advanced analyst that creates custom queries, ad hoc analyses should cover both. That way, the business user has a chance to utilize a drag-and-drop interface where you simply need to drag the values to be able to analyze them, and the analyst has a special SQL box where s/he can build queries on their own.

6. Data visualization capabilities

It's a scientific fact that humans are visual learners since half of the human brain is devoted to processing visual information . Data visualization helps understand larger or smaller volumes of data much faster than the written or spoken word. In other words, charts are much more powerful than pure numbers, columns, or rows of raw data. For example, a sales graph will immediately show you the main developments in your sales processes compared to simply presenting a spreadsheet filled with numbers or a PowerPoint presentation clogged with bullet points and sentences.

7. Professional ready-to-use templates 

By now, you already know that one of the biggest benefits of using ad hoc reports is that they provide a flexible and agile means of making strategic and operational decisions. That is possible thanks to interactive, ready-to-use templates offered by these modern solutions. Ad hoc analysis providers think of common questions businesses must answer during their analysis process and offer extensive template libraries for different scenarios, areas, and departments that users can select and start analyzing with just a few clicks.  

8. Artificial intelligence features

Operational ad hoc reporting oftentimes also includes questions about the future. Professional software has built-in predictive analytics features that are simple yet extremely powerful. For a practical ad hoc analysis example, let's say a stakeholder wants to know what kind of revenue they can expect in the next 6 months based on the specified marketing channels. The tool will automatically calculate predictions based on selected past data points, and you have your answer within minutes. Remember that although these features are extremely advanced, no one can predict the future with 100% accuracy. The point is to gain a data overview to better prepare for potential business changes.

9. Numerous sharing options

One of the goals of business intelligence and ad hoc reporting is to simplify the decision-making processes while enabling a collaborative culture between colleagues and departments. The creation of reports is fairly easy, but the sharing process should be as well. Professional business reporting software will cover multiple sharing options:

• sharing through e-mails immediately or within a specified time interval
• viewer area that enables external parties to manipulate the dashboard based on filters you have assigned
• public URL will enable you to send a simple link
• An embedded dashboard that you can insert within an application or website, e.g.

Ad Hoc Reporting Tool Example

It's clear that ad hoc reporting offers many benefits to the ongoing success and growth of any ambitious modern business. And when it comes to ad hoc reporting software that offers freedom, flexibility, and usability while helping answer critical questions both swiftly and accurately, datapine's data visualization and reporting tool ticks all the boxes.

Aimed specifically at the end user, our different types of dashboards and self-service reporting tools are intuitive and accessible, so you don’t have to possess a wealth of technical knowledge to utilize our platforms. The drag-and-drop interfaces make handling important data sets both logical and digestible. Moreover, our cutting-edge algorithms run in the background of our applications to fortify our interface with enhanced built-in intelligence to help you during every step of your ad hoc data analysis journey.

For reporting on the go, our tools, applications, and dashboards also allow you to monitor data and generate fresh insights anytime, anywhere, with your web browser or tablet, safe in the knowledge that your data privacy and security are being preserved to the highest standards.

At datapine, we've invested an incredible level of time and effort in developing an enterprise-level security layer akin to core banking applications. As a result, it’s possible to copy existing data into our data warehouse to speed up your workload or retain your data in-house by connecting datapine to your server remotely. And as you’re free from the shackles of managing your data from one specific location, sharing your dashboards, KPI reports, discoveries, and insights with colleagues are possible with just a few clicks.

To discover more about our tools, solutions, and services, explore our business intelligence features page.

If you want to delve deeper into the power of superior data analysis, then our completely free 14-day trial will help you to start your journey towards data-driven enlightenment!

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Ad-hoc-research

Your answer to urgent requests.

what is important to us

Marcel blume.

During an initial call we define your individual requirements for the ad-hoc request, final delivery and timeline

Secondary Research

We conduct research in databases, press archives and our knowledge management tool for relevant information, followed by a thorough combination and consolidation of the results

Communication

Another aspect of importance is to ensure smooth communication flows during the project and possible next steps

Project completion

Presentation and discussion of our results via a personal phone call or on site. Upon request the results can be presented in front of a larger group and followed by a discussion about next steps

Reasons for execution

Urgent request of top management, unexpected competitor during pitch, unexpected event was happening, make an appointment.

Directly book a time slot, we´ll be happy to discuss your needs

Project examples

Ad hoc Research is usually a single piece of research rather than part of a continuous process. It is designed for a specific purpose and adjusted to the individual needs of the client. In many cases, it is conducted when existing information is deemed to be insufficient. Our team collects and analyzes relevant data in a timely fashion and delivers it to our clients as PowerPoint presentation, Excel-file or Word document. The comprehensive experience Frenus gained through the successful completion of numerous Ad hoc research projects guarantees high-quality research results collected with the help of proven best practices and fast delivery of required information.

How to Manage Ad-hoc Requests (with Tips)

For project managers working in a fast-paced team environment, careful workload planning and time management are essential in ensuring work is managed effectively and efficiently.

However, regardless of how organized a team is, they will inevitably have to deal with a certain amount of ad-hoc tasks. These last-minute projects can be frustrating and lead to poor productivity when handled inefficiently.

It is vital that your team have a strategy to deal with ad-hoc requests in order to assure they don’t become an unnecessary drain on time and resources.

In this article,  ‘How to manage ad-hoc requests: A complete guide for project managers’, we discuss the ins and outs of ad-hoc requests and a range of strategies to help deal with this unavoidable part of your workload.

What are ad-hoc requests? 

In the world of project management, ad-hoc requests are tasks or jobs that arise unexpectedly. Coming from Latin, the phrase ‘ad-hoc’ means ‘for this’ or ‘for this situation’. These projects generally arise unexpectedly due to unforeseen roadblocks or miscommunication. They are time sensitive, often needing to be addressed and resolved swiftly. 

Some examples of ad-hoc tasks include:

Unexpected internal IT issues, including security vulnerabilities

Requests and queries from current clients

Quick reaction projects in response to market trends. 

Ad-hoc projects are unique to the rest of a team’s workflow for the following reasons.

Ad-hoc projects tend to have tighter deadlines than other projects. This means they are more difficult to plan for and require pivoting and thinking on the fly. 

Having a range of established strategies to deal with last-minute requests will assist in ensuring these projects are dealt with in the most efficient and timely manner. 

Localization

Large, predicted projects tend to involve a wide range of stakeholders. They may fall under a broader portfolio of work and require interdepartmental collaboration. Ad hoc tasks, by comparison, are usually focused on a particular goal and utilize fewer team members to bring them to completion.

Less Resource Intensive

Since ad-hoc requests usually occur at the last minute, they often lack the resources needed to complete them successfully. These unexpected projects require immediate attention, which often leaves little time for networking and fewer resources at the disposal of the project manager. Managing ad-hoc requests successfully means leveraging minimal resources in a short amount of time.

Why track ad-hoc projects? 

Any project manager worth their weight understands the importance of tracking planned projects and monitoring their progress. There is a range of collaboration tools at their disposal, including project management software and meeting agenda software.

Metrics that can be used to track the team's work include earned value and planned value , which give insight into how far along a project is. Using a project management tool to track time and goals is a great way to allocate resources and keep your team on track. The problem is many teams fail to track ad-hoc projects.

While tracking an ad-hoc request may seem like an unnecessary waste of resources, the time taken to log the project will pay itself back in spades.

By tracking everything in their project management tool PMs will get a bird’s eye view of the following:

An accurate picture of how each team member is spending their time

How to best manage the available resources

How to redirect time and attention toward the key strategic initiatives

Justify to key stakeholders the current resources and lobby for more as required

Which projects to say no to and the ability to justify why

What can happen if ad-hoc requests are untracked? 

When an ad-hoc project goes untracked, the result can be disastrous for the wider business. Money, time, and effort are lost to this invisible work and become untraceable. If you’ve ever gotten to the end of a project and the financial analysis doesn’t add up, it can often be because the personnel budget has been lost to untracked ad-hoc projects.  

Tracking and reporting on ad-hoc projects are essential to understanding:

The impact on other projects: Last-minute projects can quickly cut into a team’s productivity. Therefore, tracking unplanned projects is essential to understand the impact sudden requests are having on the team’s workload. This will also empower PMs to be able to say no with evidence to new requests if they feel the benefits will be outweighed by the impact on the wider workflow.  

How to assemble the right team: Tracking ad-hoc projects allows PMs to understand precisely who is needed to complete the unexpected project in the shortest amount of time. Information is power and will bolster a PM's case when it comes to recruiting extra staff and resources. 

Where to reallocate resources:  Understanding exactly how much time is required for the average ad-hoc means the wider team can manage its human resource capacity and be better prepared to handle ad-hoc projects as they arise. 

How to Manage Ad-Hoc Projects? 

1. define the project and its deliverables.

Clearly define the scope of the project and what is expected to be delivered at the end of the project. This will help ensure that everyone involved in the project has a clear understanding of what needs to be done and can work towards common goals.

2. Set clear priorities: 

It's important to have a clear understanding of the priorities for your project and to communicate those priorities to your team. This will help you to manage ad-hoc requests effectively, by being able to quickly determine whether a request aligns with the project goals and can be accommodated within the current project scope.

3. Establish a process for handling ad-hoc requests: 

Having a clear process in place for managing ad-hoc requests can help you to handle them efficiently and consistently. This might involve defining a specific point of contact for ad-hoc requests, setting up a system for tracking and documenting requests, and defining the criteria for evaluating and prioritizing requests.

4. Communicate effectively: 

Good communication is key to managing ad-hoc projects effectively. Make sure to keep all relevant stakeholders informed about any changes to the project plan or scope as a result of ad-hoc requests, and be transparent about any potential impacts on timelines or resources. This will help to minimize misunderstandings and ensure that everyone is on the same page.

5. Use project management software: 

Project management software can be a useful tool for managing ad-hoc projects, as it can help you to track and document requests and their progress, as well as allow you to easily share information with your team. There are many different project management software options available, so it's worth doing some research to find one that fits your needs and budget.

6. Have contingency plans in place: 

Ad-hoc requests can often come with tight deadlines, so it's important to have contingency plans in place to ensure that you can still deliver on your project commitments despite the added work. This might involve identifying potential resources that can be brought in at short notice, or identifying ways to streamline your existing processes to free up time and resources.

7. Be proactive:

 Rather than waiting for ad-hoc projects  to come to you, consider being proactive in identifying potential areas where ad-hoc work might be needed. This might involve conducting regular reviews of your project plan and scope to identify any potential gaps or areas of risk, and proactively addressing them before they become urgent.

8. Set boundaries:

 While it's important to be responsive to ad-hoc requests, it's also important to set boundaries to ensure that you don't become overwhelmed and your other project commitments don't suffer as a result. Consider setting limits on the number of ad-hoc requests you are willing to take on, or establishing clear guidelines for how you will prioritize requests. It's also a good idea to delegate ad-hoc projects to other team members where appropriate, to help ensure that the workload is distributed evenly.

9. Communicate with the requestor: 

When an ad-hoc request comes in, it's important to communicate with the requestor to understand the reasoning behind the request and any specific needs or constraints they may have. This can help you to better assess the impact of the request on your project and determine the best way to accommodate it.

10. Assess the potential impact: 

Before making a decision on how to handle an ad-hoc request, it's important to carefully assess the potential impact on your project. This might involve evaluating the potential risks and benefits of the request, as well as considering any potential impacts on timelines, resources, and budgets.

11. Document and track requests: 

Good documentation is crucial for managing ad-hoc projects effectively. Make sure to document all ad-hoc requests, including the details of the request, the decision made, and any follow-up actions taken. This can help you to track the progress of the request and ensure that nothing falls through the cracks. It can also be useful to have a centralized place where all ad-hoc requests are documented and tracked, such as a spreadsheet or project management software.

What's the best way to track ad-hoc projects? 

Having effective project management tools is essential when managing ad-hoc projects. 

A good PM tool will assist in giving your whole team a bigger picture of the ad-hoc request. It will establish the work breakdown structure, will help to track cost estimates and clarify where the bulk of your team’s time is being spent. Further, it will allow team members to communicate on the key issues as you move the project to fruition. 

The following strategies will also aid in tracking unexpected requests and help you to manage projects in the most streamlined way.

Stop Accepting Under-the-Table Requests

It is vital that project managers have a clear protocol when it comes to accepting an ad-hoc project. Under-the-table ad-hoc requests are one of the biggest time and money suckers, and without visibility and accountability from the wider team, PMs may ensure that all requests come through a formal request process that justifies the project's importance and the resources that will be needed to complete the project request.

When everyone on your team is aware of these projects PMs are better able to:

Ask for the people and resources they need to complete the project

Define the parameters and goals involved in bringing the task to completion

Assign clear tasks and start collaborating using meeting agendas and PM software

Standardize The Request Process

In order for these last-minute projects to be successful and take as little time and resources as necessary to complete you should have an ad-hoc system in place, whereby all requests comet through a central channel. Request management best practice means creating a project intake process that involves:

A centralized request hub through which all requests must be funneled. This means any ad-hoc request, no matter how small must go through a formal process. This means PMs are able to prioritize tasks and say ‘no’ or ‘not now’ to projects that are time-consuming or not essential to the bottom line.

Standardize the request form to ensure you understand what resources you need, the expected timeline, and the importance of the project.

Prioritizing these requests.

Defining project expectations, timelines, resources, and budget.

Block out Resources

As ad-hoc projects will continually arise throughout your workflow, it is wise to encourage your team to set aside a certain amount of time per month to tackle ad-hoc requests. 

Similarly, encourage your team to look at how these projects can be combined so that they are tackling one larger project with clear deliverables, rather than a series of seemingly unrelated tasks.

Assigning one person to capture, prioritize and address ad-hoc requests as they arise can be a great way to ensure as few team members as possible are distracted from their standard projects. 

Create Visibility

When PMs only track their standard projects, executives and other stakeholders may get the impression that these large projects are the only things getting completed. It gives an inaccurate picture of how time and money are spent. 

Create visibility by tracking each and every project, no matter how small.

This allows everyone an accurate overview of exactly what your team is working on, where current projects stand and where more resources may be needed.

Making ad-hoc projects visible

The key to success with any ad-hoc project is simple- make the invisible work visible. By implementing a range of tools and strategies that illuminate all aspects of the ad-hoc project and facilitate transparency for all, project managers will have the flexibility to make adjustments when things go awry with these unexpected work requests. 

‘Under the table’ ad-hoc projects can threaten the bottom line and impact team cohesion. 

Allowing all key stakeholders full visibility into these projects keeps the team focused and reduces the risks of oversights. 

Using smart ad-hoc collaboration

Smart ad-hoc collaboration is a way of working together that is flexible, agile, and responsive to the needs of the project. It involves using a variety of tools and techniques to facilitate communication and collaboration among team members, stakeholders, and other key players in the project.

When dealing with ad-hoc requests, smart ad-hoc collaboration is essential because it allows the project team to respond quickly and effectively to changing circumstances and priorities.

For office-based teams, this may involve having on-the-fly meetings to discuss issues as they arise. For remote teams , using tools like project management software, real-time messaging apps, and virtual meeting platforms will allow members to stay connected and share information, even if they are not physically co-located.

Smart ad-hoc collaboration also involves using data and analytics to inform decision-making, and using agile project management methodologies to adapt to changing requirements and deliver value quickly. By using these approaches, project teams can be more responsive to the needs of the business and more effective at delivering value in a fast-paced, rapidly changing environment.

Report on the success of your ad-hoc project

As previously discussed, when dealing with ad-hoc projects, many teams tend to forgo the usual reporting formalities. However, tracking ad-hoc tasks is essential. Not only does it allow you to report on your success, but it is also invaluable in learning lessons on how you can better manage ad-hoc work in the future. Further to this it can help to justify your efforts and rally for resources for future ad-hoc projects. 

Make use of your collected data and analytics to demonstrate the key goalposts throughout the project and the numbers attached. Combined with an ad-hoc project summary, this data will help demonstrate the biggest challenges encountered and how you brought the ad-hoc request to successful completion. 

How to prep for (and prevent) future ad-hoc requests

While some ad-hoc projects will inevitably come through the pipeline, anything you can do to slow the flow of these projects is invaluable. Here are some ways to keep last-minute requests from becoming the norm. 

Establish clear processes

Having clear processes in place can help reduce the need for ad-hoc requests by providing a structured way of addressing issues and opportunities. Moving these requests away from endless email chains and water cooler conversations and into a  project management tool will ensure transparency and accountability. Make sure your clients and colleagues understand the correct channels via which to request an ad-hoc project. 

Communicate expectations 

Make sure all stakeholders understand what is and is not an appropriate request for an ad-hoc project. Determine what resources (e.g. time, money, personnel) are available for ad-hoc projects and communicate those boundaries to stakeholders.

Prioritize and plan ahead 

When an ad-hoc request does come in, prioritize it based on its importance and fit with the organization's goals and resources. This can help ensure that ad-hoc requests do not distract from ongoing work. Regularly review and assess the impact of ad-hoc requests on the organization's resources and priorities, and make adjustments as needed to prevent future requests from becoming overwhelming.

Foster a Collaborative team culture

Your team’s culture will play a large role in how you work together on these ad-hoc tasks. Teams that encourage an open and collaborative framework will be less likely to be overwhelmed when dealing with last-minute projects. 

A streamlined internal communications strategy, paired with intelligent use of collaboration software will empower your team to ask for help when they need it. 

1. What is the definition of an ad-hoc project?

An ad-hoc project is a project that is formed for a specific, one-time purpose and is not part of an organization's regular operations or business. Ad-hoc projects are typically formed to address a specific problem or opportunity that arises and are often undertaken on a tight timeline with limited resources. Because ad-hoc projects are not part of an organization's regular operations, they may involve a different set of stakeholders and decision-makers than those involved in ongoing projects.

2. What is an ad-hoc manager?

An ad-hoc manager is a person who is responsible for managing an ad-hoc project. An ad-hoc manager is typically appointed to lead an ad-hoc project on a temporary basis and is responsible for organizing and coordinating the resources and activities required to complete the project.

An ad-hoc manager may be an employee of the organization or may be an external contractor or consultant who is brought in specifically to manage the project. In either case, the ad-hoc manager is responsible for establishing clear goals and objectives for the project, developing a plan to achieve those goals, and coordinating the efforts of the team to ensure that the project is completed on time and within budget.

3. What are some ad-hoc work examples?

Ad hoc work will obviously vary from industry to industry. However ad-hoc projects may be defined as any work that sits outside a team’s usual tasks and larger, pre-planned projects.

Some examples of ad-hoc work include administrative tasks, unplanned projects, meetings, and catch-ups.

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How to Manage Ad-Hoc Projects and Ad-Hoc Requests

Projects rarely go as planned. There is always the potential to get new data, project or product updates, reviews or any number of last-minute requests. How do you deal with these ad-hoc requests?

Ad-hoc means that it’s specific—something that will not be repeated. Ad-hoc projects and ad-hoc requests will occur in project management and you need to know how to deal with them.

What Is an Ad-Hoc Project?

An ad-hoc project is one that happens unexpectedly, usually in response to a problem. Projects are almost always scheduled in advance , but an ad-hoc project is sprung upon the team without time for any prior planning.

That’s one of the things that differentiate an ad-hoc project from a traditional project in project management. Another is that an ad-hoc project usually includes a quick turnaround. Ad-hoc projects also focus on one goal (or group of people) and tend to use fewer resources, including team members.

To sum up, an ad-hoc project is when something comes up that requires an immediate response. Like any project, there’s only a limited amount of time to complete it, but the timeframe is almost always tight.

How to Manage Ad-Hoc Projects: 5 Best Practices

Because an ad-hoc project seems to come out of nowhere, it’s often not given the attention that a more deliberate project would receive. However, you still need to track and report on progress to meet your strategic initiatives.

One best practice for managing ad-hoc projects is using project management software. ProjectManager is a cloud-based software that allows you to plan, schedule and track your projects in real time. Monitor resources and your team’s time with the live dashboard. No setup is necessary. ProjectManager collects and calculates the data and then displays time, cost, variance and more. It’s like an instant status report for your ad-hoc project. Try ProjectManager free today.

1. Don’t Neglect Risk

It’s easy to cut corners when time is of the essence. Ad-hoc projects tend to have less red tape, but that doesn’t mean you should ignore a risk assessment . Any financial analysis will tell you risk can ruin a project. While you won’t have time for a full risk management plan, you must prioritize risks that are likely and could have a negative impact on the project.

2. Stay Flexible

Regardless of what methodology you apply to your projects, you’re not going to have the time for the advanced planning of a waterfall structure. An agile project approach is better suited to ad-hoc projects. They are more iterative, allowing you to quickly pivot as needed, and tend to work with a smaller group on smaller-scale sprints.

Related: Agile vs Waterfall and the Rise of Hybrid Projects

3. You Still Need a Plan

There’s not enough time to go through all the due diligence, such as cost estimates, that would get a more traditional project off the ground. But even an ad-hoc project needs direction. Not having some plan or request management in place to manage your resources, set deadlines and prioritize and assign tasks is going to backfire and create a longer timeline than you can afford.

4. Standardize Work Requests

There’s a lot of methods to speed workflows, such as email, text, voice messages or a quick exchange in person. These methods might feel as if they’re expediting the process but in fact, they create problems. Create a workflow that follows a set pattern that can be centralized, accessed by all, prioritized and even commented on to foster collaboration.

5. Facilitate Transparency

Every aspect of the project should be visible to everyone on the project team. This means updates and any changes. There must be a central source of truth that gives hybrid teams, whether they’re remote, in different departments or using different tools, the visibility they need.

Tools for Managing Ad-Hoc Projects

Project management software has features that let you control projects and ad-hoc projects alike. You can use them to assemble a team and assign them tasks, with deadlines, descriptions and priorities. This lets you get the ball rolling fast and quickly onboard your team.

Teams need a collaborative tool to let them communicate and work better together. This can be part of a project management software or chat and messaging apps that connect teams no matter where they are.

Finally, you need a tool that generates reports, both to manage the project and keep stakeholders updated on its progress. These reports should be able to filter data so you can deliver the details project managers need as well as more general reports for stakeholders. The easier to share these reports, the better.

What is an Ad-Hoc Request?

An ad-hoc request or ad-hoc task is a request that has not been planned for. An ad-hoc project is a larger endeavor, but the definition is basically the same. They are outside the project scope .

Another way to look at an ad-hoc request is as an interruption and team productivity-killer. They pull you away from the project and can cause delays and cost money. The worst-case scenario: an ad-hoc request can derail a project and lead to failure.

An ad-hoc request can be anything from a meeting that’s called at the last minute, pulling you away from deadline work. It can be paperwork, again assigned at the last minute, or re-delegated tasks. Even answering emails could fall under the ad-hoc request. Anything that you didn’t know was coming that takes you away from the main thrust of your job is an ad-hoc request.

How to Manage Ad Hoc Requests: 5 Best Practices

Just as you would manage an ad-hoc project, ad-hoc requests can be controlled with project management software.

Having a work management tool is going to help you prioritize, collaborate, monitor and report on the progress of your ad-hoc requests. Here are some other things to keep in mind when managing ad-hoc requests.

Yes, plan . While you can’t have a plan for something you don’t know will happen, you can set up enough of a cushion in your day to let you respond to ad-hoc requests without negatively impacting your schedule. Use a work breakdown structure to map the ad-hoc request.

If you permit an agile project management approach to your work it allows for greater flexibility so you can pivot from one task to the next by knowing how to prioritize that work and keeping in collaborative communication with the rest of your team. Having ad-hoc tasks managed in an ad-hoc system is one way to keep on track.

2. Filter Ad-Hoc Requests

There will always be ad-hoc requests and some of them must be dealt with immediately, others can wait and there might even be some that you could ignore. But they’ll come sometimes with great frequency and can be overwhelming.

The team leader should be the point person for all ad-hoc requests to keep the team focused on their tasks. Then the team leader can prioritize the ad-hoc requests and assign the work to the team member who has the capacity to take it on.

3. Have a Process

You need a process for the planned work and you need one for the ad-hoc requests, too. Just because it’s an ad-hoc request doesn’t mean it can’t be in the system and tracked. Make sure all ad-hoc requests go into whatever work management tool you’re using.

These requests should also be delivered in the tool, but sometimes that won’t be the case. Regardless, wherever they originate, the ad-hoc request must live in the tool to make it manageable.

4. Track Progress

Without a tool to track your progress, you’re working blind. You need to manage ad-hoc requests, which means knowing your team’s workload in real time so you can assign the ad-hoc request, and then being able to track their progress on the work.

Therefore, you want to work with a cloud-based tool that gives you live data so you know exactly where the task and the team are now and not yesterday.

5. Allocate Resources

Being able to manage ad-hoc resources requires resource management tools that allow you to reallocate resources as necessary to get the work done without impacting the other work that’s already in progress.

Sometimes that might mean requesting additional team members to handle the ad-hoc requests. Having the resource management tools that can show your team’s current allocation will better help you sell your case.

How ProjectManager Helps With Ad-Hoc Projects

ProjectManager is a cloud-based work management tool that is flexible enough to manage ad-hoc projects. Automated notifications by email and in the tool standardize the ad-hoc request process and then teams can be assigned and collaborate in real time with the transparency managers and stakeholders required to track their effort.

Intake New Requests on Kanban Boards

Ad-hoc requests can be added to the kanban boards so they can be integrated into the larger workflow. Managers can set the priority, add descriptions and assign the task to team members. The team can then manage their backlog and plan the sprint together by commenting at the task level. Meanwhile, the project manager has transparency into the process and can see any bottlenecks up ahead and reallocate resources to resolve them.

Allocate Resources Effectively

In order to know who on the team has the capacity to take on the ad-hoc request, ProjectManager has real-time resource management features, such as a workload chart. The workload chart is color-coded to make it easy to see who has too many or too few tasks assigned to them. The project manager can then balance the workload and make more insightful assignments.

Generate Progress Reports for Stakeholders

The stakeholders who made the ad-hoc requests will want to know how the work is going. That’s where ProjectManager’s reporting feature comes in. Generate a variance, timesheet and other reports with one click. All reports can be filtered to show only the data you want to share with stakeholders and then passed on as a PDF or printed out.

ProjectManager is designed to manage any kind of project, including ad-hoc projects, whether your team is under one roof or distributed. With secure timesheets, you always know the status of your team’s work on their tasks, regardless of location or department in the organization. Having this kind of control and visibility keeps ad-hoc requests from sapping your productivity.

ProjectManager is award-winning software that organizes work and connects hybrid teams. It has the flexibility to handle ad-hoc requests and keep you and your team working productively. Join the tens of thousands already using our software at organizations from NASA to Nestles and Siemens. Try ProjectManager today for free!

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Finding your place on Ad Hoc’s research team

Published on September 23, 2020

Topics: Life at Ad Hoc , Research

Laura Ellena

In 2016, I was hired as Ad Hoc’s first researcher. At the time, research was the sidecar to our design practice’s motorcycle, which was already humming along with an established team. Since then, I’ve had the opportunity to personally grow into Ad Hoc’s Research Director and facilitate the growth of our research team into its own practice with close to 20 team members.

One of the best parts of the job is hiring excellent candidates and supporting them as they grow personally and professionally. Ad Hoc researchers come from a wide variety of backgrounds from archaeology to anthropology to museums to education. We’ve also had people transfer over from Ad Hoc’s design, engineering, and product practice into the research team. The Ad Hoc research team is proudly a place where we accept and encourage the diversity of people and their experiences.

That’s all to say, even if you wouldn’t call yourself a UX researcher today, there may still be a place for you on the Ad Hoc research team and a path for you to grow into a senior research professional.

What research looks like at Ad Hoc

The most important thing about research at Ad Hoc is that it’s a valued and understood discipline. We spend our time doing research, not convincing leadership or our colleagues that talking to users is necessary to the success of a product. We do have external partners that are new to research, and successful researchers see that as an opportunity to bring the power of user research to the problems of government even if some stakeholders take more than one round of convincing.

As we work with customers, we often evolve what research looks like on their program. Showing the value of usability and subject matter expert research can open doors to doing more discovery research, and stretching our creativity to design workshops and mixed-methods projects can bring fresh insights to our customers. Researchers are part of Ad Hoc’s cross-functional teams, and colleagues from our engineering, product, and design teams will sit in on feedback sessions and bring their own skills to improve the research process.

In particular, Ad Hoc’s design and research teams work together closely. We see design and research skills existing on a spectrum, and the cross-functional nature of our teams means designers are able to contribute to research work and researchers are able to put their design skills to use.

Creativity within constraints

Being a researcher on federal government digital services does come with some constraints, and people who thrive in that environment and let their creativity find a solution are a great fit for our work. For example, while Ad Hoc staff have the freedom to use the software they need to get the job done, we’re often limited in the tools we can use when we collaborate with our government customers. This has led to some pretty amazing adaptations of Google Slides and Miro boards to tell complex stories about user journeys and research findings.

We’re also looking for team members that naturally put their creativity towards making Ad Hoc and the research practice better. That might look like designing a more inclusive hiring process, facilitating internal team workshops, or helping people outside our practice improve their own research skills.

In turn, Ad Hoc and I are committed to supporting your growth. All staff get an annual $2,000 continuing education budget, which researchers have used on conferences, workshops, courses, books, and professional organization memberships. Some folks have even used it for Toastmasters to improve their public speaking. The research practice also has a book club where we read and discuss books like Good Services and Dare to Lead .

Recently, we launched a new set of job descriptions for the research practice to help better define all of our roles and give people a clear path to advance their careers. Here’s a quick look at all of our research positions:

Associate Researcher

Associate Researchers are new to the research field and are still gaining core skills. They’ve likely taken some UX research courses or worked in fields that gave them similar experience. They will always be working on a team with other senior or principal researchers who can help them grow.

Responsibilities: We’re looking for Associate Researchers to spend time learning and practicing their research skills. Associate Researchers typically start with handling research logistics and take on more responsibilities, such as facilitating interviews, as their skills improve.

Typical week: Associate Researchers will spend time recruiting research participants, scheduling interviews, and supporting their colleagues as they conduct research. With the mentorship of a Senior Researcher, they may plan and facilitate a feedback session. They may also help a Senior Researcher take notes during interviews and assist in organizing the results.

People at the Researcher level are able to take more ownership of a research project including facilitation and project planning. They’re still mastering a range of research tools and techniques with the support of Senior and Principal Researchers.

Responsibilities: Researchers are responsible for gathering and analyzing information and preparing reports to share that information with their team. We look to Researchers to plan and facilitate feedback sessions and use their skills to analyze data and give useful recommendations to the larger team.

Typical week: In a typical week, a Researcher may decide which research methods or tools are right for a specific problem the team is working on and develop a plan to conduct that research. They may facilitate post-session debriefs with observers and note-takers, dive into data analysis for projects, and meet with other members of the team and stakeholders to go through what they learned and possible next steps.

Senior Researcher

Researchers at this level are able to confidently plan, conduct, and analyze all of the research necessary for their project. They know what tools to apply when and are able to effectively communicate what they learn to both the project team and stakeholders. Senior Researchers may be the only researcher on their project.

Responsibilities: Senior Researchers have many more interactions with our government customers and vendor partners. They’re responsible for the overall quality of research on their project and for effectively working with their cross-functional team to provide the best possible research for the product. Senior Researchers who are team leads may also take on mentorship duties and some people management, but they’re not responsible for administrative tasks.

Typical week: A Senior Researcher’s week is balanced between conducting research and sharing results with customers and their team. They may have meetings to present their findings to senior stakeholders in our customer agencies and a 1:1 with an Associate Researcher to help them learn how to best apply a research tool to a problem.

Principal Researcher

Like Senior Researchers, Principal Researchers are responsible for major research projects for our program teams, but their sphere of influence also extends to all of Ad Hoc. I rely on Principal Researchers to help improve the research practice, interview and select candidates, and facilitate senior leadership meetings.

Responsibilities: Principal Researchers are responsible for large research projects where they may oversee junior researchers. They hire and mentor other researchers, prioritize work for their team, and collaborate with other senior folks across Ad Hoc’s practices. If they’re a lead on their program, they’ll also oversee other researchers through 1:1 meetings and performance reviews.

Typical week: After delivering the results of the research from the last sprint to their program team, a Principal Researcher may meet with other Principal Researchers to refine our interview template to help reduce unconscious bias. An Ad Hoc executive may ask a Principal Researcher to help facilitate a senior leadership meeting or refine a staff-wide survey. They will also spend time conducting feedback sessions and helping Associate Researchers grow their skills.

Moving up the ladder

As an example of this career ladder, I’d like you to meet Maria Vidart. After about 10 months at Ad Hoc, Maria, then at the Researcher level, was on a small team with a Senior Researcher supporting the Department of Veterans Affairs. Given their workload, Maria and her colleague decided to each handle the research for one subject area. It was all hands on deck for their team, which meant Maria was performing similar work with similar responsibilities to her colleague with a Senior Researcher job title.

Maria came to me to talk about moving into a Senior Researcher position and what else was expected of her to make the move. She was already doing outstanding research work, but our Senior role requires interactions with customers and other contracting companies and sharing more about our work with Ad Hoc and the world. As she does on her projects, Maria took the initiative to present internally about her work and write a blog post for the Society of Cultural Anthropology about what her research on APIs at the VA had uncovered. After 10 months at Ad Hoc, Maria was promoted to the Senior Researcher position.

Being a Senior Researcher is a vow of trust in my ability, my judgement, and the value of research in an API program. There aren’t a lot of researchers in API programs. This means I get to grow in this role and grow with the field. And this new title gives me the credibility to do so. —Maria Vidart

I’m proud of the research team and practice we’ve built at Ad Hoc. If this sounds like a team you’d like to join, I’d encourage you to check our hiring page to see if we have any researcher openings that match your skills.

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