The Reality of Working With Real-World Clients


Semester-long projects involving real-world clients have numerous benefits for students, including greater levels of involvement and an opportunity to experience what it is like to do business research outside of academia; however, real-world projects have a unique set of challenges for students and professors. These challenges relate to the need to achieve clarity regarding problem definition, research expectations, and deliverables. Real-world projects also have increased potential for unexpected events during the course of the project, including issues involving problem definition, data, and communication challenges. To address these concerns, the author suggests the use of contingency planning for some more likely issues, and the use of a “one-sheet” project proposal to clarify expectations, responsibilities, and deliverables. An example of a one-sheet project proposal is included.

Learning Outcomes

By the end of this case, students should be able to

  • Describe the challenges facing projects involving real-world clients
  • Construct a one-sheet project proposal for doing student research for a real-world client
  • Identify the most likely obstacles for the completion of the project on time and develop contingency plans for potential obstacles to timely project completion
  • Connect the written project report to the original one-sheet project proposal
  • Describe a two-step process for writing and presenting project findings that results in a better-quality project experience for the client

Project Overview and Context

In a perfect world, clients with semester-long projects would approach students with well-defined business problems and all data needed for students to solve the problem. Students would start their work early, and work continuously and hard through the semester. The project would end with a well-written and insightful research report and presentation at the end of the semester that perfectly addresses the client’s problem, and everyone would finish the semester happy.

Of course, we do not live in a perfect world. Clients often have trouble articulating their needs to students, students struggle with industry-specific jargon, and both students and clients must deal with unanticipated problems that often arise during a project. The real-world client process is often messy, frustrating, yet ultimately a rewarding experience. Such projects often mirror what it’s like to work in an organization, where everything does not function according to plans and the best employees are those who can adapt on the fly and still achieve the original goals.

Research Practicalities

Projects with real-world clients are different from the cases that often are used in college business courses. From a faculty perspective, projects with real-world clients are usually more work. Real-world projects take time to find and set up, there’s no instructor guide with an optimal solution, and the logistics of coordinating student and client schedules can be challenging. From a student perspective, real-world client projects can be exciting but also confusing. Students are often presented with data that aren’t relevant and missing data they would like. It’s also common for clients to provide data in a format other than an Excel workbook format, or to supply data in a spreadsheet that has cells with “numbers” that are actually text. Finally, some clients have a hard time articulating exactly what they are expecting from students.

Given these challenges, why should students and professors want to work on projects involving real-world clients? The answer is simple—it’s the difference between practicing business research and doing business research. To use an analogy, it’s the difference between riding a bicycle with training wheels and without training wheels. In previously published business cases, there are usually preferred solutions that have been judged to be the most appropriate course of action. Students know a “right answer” exists and they work to find that answer. In a project with a real-world client, success is a function of whether the project meets the needs of the client, and there is sometimes no assurance that a solution to the client’s problem is even possible. Whether the solution is the single best solution to the client’s problem is harder to assess.

Real-World Projects, Real-World Issues

Students and faculty embarking on projects with real-world clients have several potential issues to address. These issues can be categorized as problem issues, data issues, and communication issues.

Problem Issues
Symptoms Versus Causes

Many real-world clients confuse symptoms with the underlying causes. They seek solutions to the symptoms they face, such as low sales, declining customer lifetime value, churn in the customer base, and so on. These are symptoms—the manifestation of an underlying problem. Treating the symptom without treating the underlying cause is like a doctor trying to treat a fever with an ice pack—it may lower the patient’s temperature, but it doesn’t fix what’s causing the patient’s high temperature.

Problem Definition

Real-world clients operate under significant time constraints, and many clients are understandably eager to “get on with it”—to quickly define the problem and have students to immediately start working on it. Students usually prefer this too—frankly, it is easier when a client comes to you with a problem already defined. The challenge with problem definition is that an incorrectly defined problem results in the worst type of project—a well-reasoned solution to the wrong problem, resulting in a solution that doesn’t really resolve anything.

It takes time, but a thorough understanding of the problem is critical. One of my first major clients was a state transportation department. The objective was to find ways to increase ridership within the state on all state-subsidized Amtrak trains. Amtrak had three primary target markets within the state: leisure travelers, business travelers, and student travelers. Rather than trust my own understanding of college student behaviors and motivations, I conducted two focus groups at a large public university in the state. Through the course of the focus groups, students explained that most students arranged to travel to/from the university through a university-sponsored ride-board, and that once students figured out how to use the ride-board, they were no longer interested in paying for Amtrak tickets. The focus group results changed the goal from how to convince students of the value of an Amtrak ticket to something narrower—how to convince the parents of incoming freshmen to purchase Amtrak tickets for their college-bound sons and daughters before they learn to use the university ride-board.

Data Issues

Published cases often come supplied with all data needed to solve the case, and the data are unquestioned in terms of accuracy. Students can jump right in and begin working with the data as soon as they are comfortable, and with complete confidence in the accuracy of the data. The same cannot be said for projects with clients, where obtaining data in the right format is often a significant hurdle.

Knowing What Data to Request

Many companies have large amounts of internal data that can be used to solve problems. Real-world clients may ask students “so what data will you need from us?” which usually generates a deer in the headlights look of panic from students. The solution to this dilemma is to make a list of what data you will need, see if the company has that data, and then determine how you can estimate data the company does not have.

For example, students working with a real-world client in the entertainment industry decided they needed to know the number of tickets sold to certain types of customers in certain sections of the arena. Surprisingly, the client’s data base did not include that, but it did include the number of total tickets sold and the total price paid. By obtaining a copy of the ticket prices for each type of seating and figuring out the possible combinations of tickets that would yield certain ticket transaction totals, the students were able to estimate the number of tickets sold in certain sections.

Timeliness in Acquiring Data

Students need to realize that real-world clients typically take on student projects as something that is over and above their existing job responsibilities. As a result, complying with student requests for data and student questions may not be their highest priority. Some data requests also require layers of approval, so students need to understand that data requests will take time and need to plan appropriately.

In 2017, three students and I were working on a project for a professional sports team that required access to sensitive ticket data. The team initially agreed to supply the data, but then weeks went by without receiving the data. The students became understandably nervous, as each day without data was one less day to complete the required work. In the end, we modified the project on our end by using available, non-proprietary data and then drawing inferences during the discussion of the project with team officials. The data never did arrive, but the students learned a valuable lesson—be prepared with a “work around” if the data arrive late or doesn’t arrive at all.

Data Accuracy

Just like students (and professors), clients sometimes make mistakes as well. Data provided to students are rarely clean and ready to analyze. It may contain missing values, numbers that are entered as text, or data that are labeled incorrectly. Although this is frustrating to students, it is important to remember that this is how most of the real-world operates.

In 2015, a student group received a data file from a major client and immediately started analyzing the data. After nearly 2 weeks of work, the students were getting frustrated—few of the expected correlations between one variable of interest and all other variables in the data set were close to what was expected. When we discussed this with the client, it became clear that one of the columns in the data set was mislabeled—what the client had labeled as “annual revenue” was actually “change in revenue” from the previous year. If you are a student on a project like this, what do you do? The same thing you would do if this happened to you if you were an employee for the company—you thank the client for clarifying the issue, re-run the analysis, and put in additional hours to still get the project done on time.

Communication Issues
Differing Expectations on Deliverables

“Deliverables” refers to what a client can expect to receive from a research project. Both the client and the students need to be on the same page with what the students will deliver to the client at the end of the semester. Telling the client that she or he will receive a research report and presentation is insufficient—students need to specify what specific questions will be answered by the research.

One of the most common occurrences I have experienced in research presentations are clients who listen to a research report on a specific topic and then ask, “Did you also look at …” and raise a topic that was beyond the scope of the original research. Such questions can be frustrating for all parties. Students often feel they are being judged for not having looked at the topic that was raised, and the client feels she or he still has unanswered questions.

To address this problem, my students and I create a “one-sheet” project proposal (see “Method in Action”). This was something suggested by a major league baseball client, and it has worked very well. Students discuss the project with the client, then prepare a one-page summary that specifies the problem to be studied, what data the client will supply, what data the students are required to locate, what the format of the final report will be, and when the client can expect to receive the research report and presentation. (It sometimes takes more than a single page, but the format encourages students to be concise in their writing.) This usually takes a few iterations before the client, the professor, and the students are all in agreement on the scope of the work to be done. The one-sheet then becomes the first topic covered in the final presentation. Students review what they agreed to do, then show the client the results of their research.

“Pound the Dents Out” Before Presenting to the Client

No student (or faculty!) research project is ever perfect. One of the frustrating things that can happen in a student project is having a group of students work hard in collecting and analyzing data but to make a fatal error in the analysis and/or interpretation of the data. Such occurrences are frustrating for students (low grade), the professor (embarrassing in front of the client), and the client (confusion).

In a presentation to a National Collegiate Athletic Association (NCAA) D-I athletic director, a group of my students reported the results of an independent-sample t-test that compared two groups of ticket buyers and their intention to buy tickets in the future. The student group ran the analysis correctly but misread the SPSS results of a Levene’s test and reported the wrong t-test result, reporting that the null hypothesis (no difference between two groups) should be rejected when, in fact, the correct t-test interpretation was that the null hypothesis could not be rejected. The student group’s subsequent recommendations were predicated on this faulty interpretation of a Levene’s test and were subsequently flawed.

The solution is to have students submit the paper and perform the presentation twice. The first paper submission and presentation are done in private with the professor, in which flaws can be corrected. This is described to students as “pounding the dents out”—a reference to work done on a car that is mechanically sound but has too many scratches, dings, and dents to be attractive. Based on private feedback from the professor, students correct the flaws before presenting the results in person to the client. The effect is generally a much stronger paper/presentation, a better grade, and a more satisfied client. The initial and final research report and presentation should be weighted relatively equally (or the initial may be given slightly more weight)—this encourages students to do their best work on the initial research report and presentation and not just depend on the professor to fix everything.

Method in Action

A suggested activity for keeping students, the client, and the professor on track in a project is the preparation of a one-sheet proposal of the work to be done. An example of a one sheet for an undergraduate sports marketing project is provided below, with a sample of what would be included in a one sheet provided in italics.

Sample One-Sheet Project Proposal

  • Proposal Title: A Comparison of Chicago Bears Ticket Pricing on the Primary and Secondary Markets
  • Client Contact(s): John Doe, Chicago Bears Football Club
  • Student Researchers: Mary Smith, Carlos Jones, Anthony Brown, Illinois College
  • Objective of the Research: (List the purpose of the research. If there is a specific problem the research is intending to resolve, indicate that. Be sure to use measurable verbs when possible, such as calculate, determine, create, and so on, and not understand, develop an appreciation, and so on.)

The purpose of the present research is to identify whether Chicago Bears tickets in specific sections are being underpriced or overpriced in comparison with the market price for tickets in the same section. In addition, the research team will identify the effects of winning/losing during the season on the gap between team prices for tickets and the market price for a ticket in the same section.

  • Research Plan: Overall, how do you plan to accomplish the objective? This section benefits both the client (they can understand how you will complete the project) and the professor (requires students to think through whether the research process will achieve the stated objective from #4)

The research team will record each day the average ticket price on StubHub (secondary market) for a Chicago Bears ticket in a specified section, then compares this market price with the team price (primary market) for a ticket in the same section. By also tracking both season wins/losses and the win/loss from the most recent game, the research team should be able to identify the effect that game results are associated with changes in the difference between ticket prices in the primary and secondary markets.

  • Data Required From the Client: Students would attach a listing of specific data needed (if any) from the client and when the data are needed.

The client will supply the research team with the specific section numbers for analysis, and the primary market price for a seat in that section.

  • Data Supplied by the Student Research Team: Students would include a listing of the data they will need to collect on their own. This helps to clarify what data students must collect, and what data the client will provide.

The research team will record each day the average daily price for a ticket in each targeted section (see #6 above), as well as the W/L% on each Monday and the result of the previous week’s game.

  • Specification of Deliverables: The students will describe what will be provided to the client at the end of the project. This needs to be more descriptive than “a paper and a presentation”—What will be in the report?

The research team will provide a written report that describes the methodology used in the research, and specify for each targeted section how much seats were overpriced/underpriced for each day during the season, and the effect (if any) that W/L% and a win/loss during the previous week had on whether the ticket became overpriced/underpriced. The results of the research report will be summarized in a 20- to 30-min report, to be delivered at a mutually agreeable time/location.

  • Date for Deliverables:

The research report and presentation will be provided to the client no later than 5 December 2017, with the exact delivery date and time to be determined.

Practical Lessons Learned

  • Defining the problem well is better than defining the problem quickly. Correctly defining the problem is key to the remainder of the project.
  • Create clear expectations. Specify at the start of the project what the scope of the research will be, what data will be supplied by the client and what will be generated by students, and what the deliverables will be at the end of the project. A “one-sheet” project proposal can do this.
  • Embrace the uncertainty. Projects with real-world clients are filled with uncertainty—Is the problem correctly defined? Is this what the client really wants? Can I trust the data? Is our solution the best, or is there another solution that we never considered? Students need to embrace these uncertainties and learn to live with them, as this will become the norm in making business decisions after college.
  • Contingency planning is key. Not everything goes to plan. Although all problems are not predictable, many problems are. Contingency planning refers to anticipating actions by an opponent or in the environment and developing appropriate future responses (Friend & Jessop, 1969). What steps can you take to avoid a sub-optimal performance by anticipating problems and being ready to respond to them? Also, if certain data are unavailable, how will you be able to estimate that data to keep the project moving forward?
  • Pound the dents out. Plan on submitting your research and presenting it twice—once in private to the professor so that any problems/errors can be fixed, then a second time to the client. The result is a better project/presentation that leads to more satisfied clients and students.


Projects with real-world clients bring considerable uncertainty into the project experience for both students and professors. This uncertainty can be managed through the use of an appropriate mind-set and specific in-semester activities. These in-semester activities include an emphasis on problem definition, a specific project proposal that specifies responsibilities and deliverables, contingency planning to identify possible in-semester problems, and a two-step process for writing/presenting research findings. Following these steps produces a better project experience for all participating parties.

Exercises and Discussion Questions

  • A student group meets with a real-world client in the construction industry to start a new project. The construction industry client explains “our sales are off by 15% from the previous year. What I need you to do is to find out why our customers no longer like our products—find out what are we doing wrong!” What should the student group do before starting to work on this problem? (Hint—it’s the difference between symptoms and causes.)
  • Create a list of five to 10 possible client problems/challenges that can arise while working with a particular client. This could include issues such as “client doesn’t return e-mail,” “data arrive late,” “data arrive on time but are incomplete,” “client wants to re-schedule presentation date,” and so on.
    • Next, put the problems/challenges in order in terms of their likelihood of occurring. This is your “probability list.”
    • Take the same list of problems/challenges and place the items in order of severity—which items are very serious and present few options (e.g., the client goes out of business during the semester), and the items which will challenge students but should not be fatal to the project (e.g., the contact person with the client is on vacation for a week when a response is needed.) This is your “severity list.”
    • Items that appear near the top of both the probability and severity lists are your first priority for contingency planning. What will you do if this event occurs?
  • Assume you have a client in the eye care industry who operates an eye care clinic in City A, and the client is interested in opening a second location that is 50 miles away in City B. In City A, the client has a market share of 12% in a city with 100,000 residents, while City B has 70,000 residents. Most other factors between the two cities is comparable (number of competitors, income levels, etc.) The students have asked the client for projections of how many patient visits the client would expect to have in City B, and the client indicates she or he does not know. At the same time, estimating the number of client visits and the projected margin per visit will be critical to determining whether to open the new clinic. Determine a “work around” for how you might estimate the number of patient visits that could be expected in City B.
  • Why is it important for students to closely inspect data provided by clients as soon as the data arrive?

Further Reading

Chapman, R. G. (1989). Problem‐definition in marketing research studies. Journal of Consumer Marketing, 6, 5159.
Meister, M. (2012, July 11). How to define a market research problem. Business Insights Review. Retrieved from
Wells, J. M., Souza, M., Martini, M., Brizee, A., Velazquez, A., & Ghafoor M. (2013, March 1). Steps for revising your paper. Retrieved from
Three Sigma Inc. (n.d.). Root cause problem solving. Retrieved from


Friend, J. K., & Jessop, W. N. (1969). Local government and strategic choice. London, England: Pergamon Press.
O’Hara, C. (2014, November 20). How to improve your business writing. Harvard Business Review. Retrieved from
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