A Systematic Way to Cure the Maladies of Pointless and Boring Studies
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Buday TLP report-Elevating the Insights of Thought Leadership Research-February 2025
You’ve spent months on a study your firm is counting on to renew interest in a key service or stoke attention to a new one. The first draft arrives and your heart sinks. The findings are underwhelming.
So you try to fix it. You bring in a new writer and they start with a peppy introduction – a revealing case anecdote or metaphor. But that doesn’t do much after you get past those paragraphs. Then you ask for more statistics, adding to the already-voluminous number you have. “We need more ammunition,” the thought goes. Yet that doesn’t ratchet up the insights; it only adds more data points to an uninteresting narrative. Perhaps some snazzy infographics and other charts will spruce things up, you say. They certainly provide necessary graphic relief to text-heavy reports. However, they don’t provide psychic intrigue.
The fundamental problem isn’t poor writing, a lack of data or uninspiring graphics. It’s that the insights are grossly underwhelming. In short, there is no big “aha” — no highly counterintuitive core finding about how to solve the topic issue at hand. Even the smaller insights lack requisite evidence that they work. No single insight challenges you to rethink conventional wisdom.
That’s a death wish for thought leadership research today, a time in which clients can type a prompt in ChatGPT on just about any topic and in seconds get their hands on the most insightful studies.
The result is a dull report that’s a burden to digest. Surveys of executives who read thought leadership indicate this is a big problem. They suggest such studies are the rule, not the exception. In 2022, our own survey of 5,000+ executives found less than a quarter said the thought leadership content they read was extremely valuable in deciding which firm to use. LinkedIn and Edelman PR, which together have surveyed tens of thousands of executives since 2017, found that in every year but one, less than 20% felt the content they consumed was very good or excellent.
By wasting an audience’s time, lackluster studies also waste the budgets of firms that fund them. What’s more, they neuter marketing investments meant to make the findings go viral. Your company’s marketers spend heavily on search engine ads, banner ads, and pay-to-play op-eds and speaking opportunities because “earned content” is not in the cards. Prestigious publications reject op-ed submissions on their editorial merits. Event organizers turn down speaking requests. Journalists ignore email PR pitches.
When this happens, company leaders wonder why $200,000, $300,000 – even $500,000 or more — was spent on the research, not including promotion.
It’s not likely you can fix a thought leadership research report draft that arrives this way. In my 30+ years of designing and conducting thought leadership research, those studies suffer from one or more of six maladies that begin at the very beginning: a mammoth topic, predictable inquiry, stat deluge, regression to the mundane, wandering storyline and dull prose.
But you can do a lot to make sure it doesn’t happen again – if you change the way you design, conduct and analyze your research, and how you frame and write your findings. It all requires bringing discipline to what typically is an undisciplined, chaotic, ever-changing process — if you can even call it a process. When you do this, you can overcome the six maladies of thought leadership research and greatly improve the odds of producing provocative insights that open doors with clients and impress key influencers.
The discipline you need in thought leadership research can be enforced through what we call a Problem/Solution framework (Exhibit 1). I’ve written about this before, mainly as a process for structuring a compelling argument or article. But it is equally indispensable throughout the entire research process: from topic scoping and research design, through data collection and analysis, and to findings development, narrative structure and prose writing. For more than 30 years, the Problem/Solution framework has been a tool that has kept more than two dozen studies on track for our clients and helped them avoid a path to superficial, familiar conclusions.
Exhibit 1: A Framework for Keeping Thought Leadership Research on Track
All the possible issues you could research must fit in the Problem/Solution framework. As the name suggests, the framework begins by articulating a problem in the world and who has it. It concludes with why those companies must adopt your novel solution soon. If an issue for exploration doesn’t fit the framework, you must discard it. This is crucial because researchers are (or should be) highly curious people. But downside of that trait is they can easily be distracted by data and findings that are fascinating, yet aren’t core to an inquiry.
After using the Problem/Solution framework to determine the issues to study, you need to continue using it to focus your analysis of the data you’ve collected. It will force you to dissect the problem in a new way. More important, it will force you to spend more mental energy analyzing the solution to that problem in a radically new way.
When it comes to turning those findings into the prose of a research report (or the slides of a presentation), the framework will guide you once again on how to construct a compelling narrative – a persuasive argument that begins with the audience’s problem and ends with why they need to adopt your new and better solution soon.
I’ve designed and conducted thought leadership studies for clients, and for my firms (on the topic of thought leadership itself), using a Problem/Solution framework for four decades now. For our clients, the topics have been eclectic bunch. They range from business model innovation, talent evaluation, and Internet of Things strategies to AI strategy, social media strategy, digital customer data management and project management. In other words, the Problem/Solution research approach is topic-agnostic.
The research process has often led to big wins for our clients in the marketplace: articles in prestigious management journals (one for Deloitte that made the cover of Harvard Business Review’s print edition); several digital HBR articles (for Tata Consultancy Services, RGP and other firms); praises by top editors at business publications that wrote about the research (including one by the then-editor in chief at Fortune magazine); and other bounties of groundbreaking thought leadership research.
In this article, I first explain the six maladies of thought leadership research that send studies off track. Then I discuss how to avoid them by using the Problem/Solution framework, and what the resultant studies produced for our clients.
The Six Maladies at a Glance
Thought leadership research has been the source of the some of the biggest ideas on how to run businesses over the last 35 years. Just think about the concepts born of primary research and client work: Disruptive innovation (from the legendary Harvard Business School Prof. Clayton Christensen), building companies to last and going from “good to great” (Jim Collins), the balanced scorecard (Robert Kaplan and David Norton), “challenger selling” (Corporate Executive Board’s Matthew Dixon and Brent Adamson), business reengineering (Michael Hammer and James Champy), competing on analytics (Thomas Davenport), and monetizing innovation (Madhavan Ramanujam and Georg Tacke of Simon-Kucher, authors of the popular book by the same name).
All have been highly influential ideas, born of deep primary research (including the authors’ work with clients). Disruptive innovation led to the 2000 birth of consultancy Innosight, which was acquired for $100 million by Huron Consulting Group Inc. in 2017. The same year, IT research firm Gartner laid down $2.6 billion to buy the Corporate Executive Board, at that time a $928 million revenue, best-practice research company that had produced such hits as “The Challenger” approach to selling. The concept of business reengineering, popularized by the consulting firm I worked for years ago (CSC Index) and the late, great reengineering guru Dr. Michael Hammer, ignited what became a $4.7 billion-a-year consulting segment by the mid-1990s, according to Gartner estimates. Simon Kucher’s monetizing innovation ideas and the marketing behind it helped boost revenue 83% five years after it published the book in 2016.
But for every lucrative concept like these, dozens, maybe hundreds of others that emerge from thought leadership research are duds. They are largely ignored by the media and potential clients, amounting to be the venture capital equivalent of failed startup investments. We don’t have any numbers on thought leadership studies and their ROI. But we wouldn’t be surprised if the failure rate exceeds that of the VC world. (One venture funding tracker, CB Insights, has estimated that nearly 70% of VC-funded ventures die or otherwise fail to generate a return for their VC investors.)
Why does this happen? Since 1994 I’ve worked with many clients on thought leadership studies (beginning with CSC Index’s “The State of Reengineering” report, which tracked the progress of hundreds of business reengineering initiatives worldwide). Eight studies led to articles in prestigious management journals (Harvard Business Review, MIT Sloan Management Review, and California Management Review). Through this work I have discovered big common roadblocks in my six stages of thought leadership research projects (Exhibit 2).
Exhibit 2: The Stages and Maladies of Thought Leadership Research
Here’s a brief explanation of the maladies (with images to illustrate them, courtesy of ChatGPT AI artist DALL-E):
Stage 1 (Issue Scoping): Mammoth topic.
Thought leadership research that under-delivers typically begins here, and thus on the wrong foot: in determining the exact topic to study. In many cases, a research or marketing team has a topic whose scope is too broad to explore deeply within the limitations of time and budget. With too many issues to study, the research team must skim the surface of them. The findings, thus, are fated to be superficial.
Stage 2 (Research Design): Predictable inquiry.
Even when a topic is focused to allow deep inquiry, the inquiry essentially repeats the inquiries of other studies. By this, I mean they largely ask the same questions rather than probing new aspects of the topic that weren’t explored by other studies. When that happens, these explorations often unwittingly veer off topic in the pursuit of fresh findings. Predictable inquires can also be hampered when the researchers spend more time documenting the topic problem than they do documenting solutions to it.
Stage 3 (Data Gathering): Statistical deluge.
The survey you fielded (often with the help of a survey panel firm that pays 
respondents to take it) produces raw data. The survey panel firm then turns that data into percentages and charts – lots of percentages and lots of charts: the percent of companies that are doing this; the percent that are thinking about doing this; the percent that are struggling doing this; the percent that think “this” is critical. In the final research report to come later, even when the percentages are discussed with lively explanatory prose, they dull the reader’s mind. They’re deluged with statistics.
Stage 4 (Data Analysis): Regression to the mundane.
Your researchers try to make sense of all those statistics. “What do they mean?” “What are our insights on this topic?” “Can we really say something controversial here?” I’ve found the default position is typically a safe conclusion, not a counterintuitive one – especially if the latter contradicts what the firm has been saying to the marketplace for years.
Stage 5 (Narrative Development): Wandering storyline.
Controversial or not, the research findings don’t, on their own accord, roll up 
to a compelling argument about some problem in the world and a better way to solve it. The findings may be all over the place. The incoherent argument loses the reader. The problem is the storyline wanders, with readers constantly wondering where it’s all going and looking in vain for an overarching point.
Stage 6 (Report Writing): Dull prose.
Even when a research team excels at Stages 1-5, in the last mile all their hard work can lose value when the prose is deadly dull. Yes, the words capture the argument. But the words are like listening to a monotone speaker, or a karaoke singer who can’t carry a tune. In this case, it’s an unenjoyable read.
In the next section, I’ll say more about these maladies, why they lead to mediocre research content, and how to cure them. I’ll illustrate how to do things right with examples I am most familiar with: my work with clients.
Shifting from Boring to Riveting
Once you recognize them, the six maladies are easier to anticipate and avoid. But the first thing is not to be embarrassed about them. They are a natural consequence of extremely smart, curious and ambitious people working together on a study. Each can have quite distinct ideas of what a certain study should explore, how to explore it, what the biggest findings are, and how to communicate them.
In this way, I’ve seen the maladies set in when a group of passionate and knowledgeable people collaborate to create something new and bold. What they often don’t realize is that thought leadership research is much different than other research they may have been involved in – e.g., market-sizing research, focus group research, and competitor research. Importantly, thought leadership research is also different from working with clients on projects, whether on a strategic, legal, technological, operational, human resource or other issue. On those projects, the source of the problem can and often does shift upon deep inspection.
The goal of thought leadership research is different and singular: to shed light on the best ways for organizations to solve a specific problem in the marketplace. The goal is not to size a market opportunity. (That’s the role of market-sizing research.) It’s not to gauge what client executives think about the problem. (That’s the role of focus group or attitudinal research.) And it’s not to understand what your company’s rivals are doing about the issue. (That’s the role of competitive intelligence.)
Thought leadership research must be a narrow, deep and carefully orchestrated inquiry. It needs to identify what the most successful organizations did differently than the rest on the topic. That’s why case studies of companies that have addressed the problem – some with great success (the ones to learn from the most), and others with little if any success (with lessons on what not to do) – is at the heart of thought leadership research. And that, in turn, is why any thought leadership research method must put case study research at the center.
However, such narrow and deep inquiries can easily go off track if for no other reason than a detailed survey, a dozen or more case study interviews and extensive desk research generate so much data. What’s more, given that researchers by nature are extremely curious people, they can easily go down topic side streets that look fascinating but turn out to have nothing to do with the original topic.
The Problem/Solution research approach has been a big help in keeping potentially chaotic inquiries on track. In the section that follows, you’ll see how the process comes into play in each research stage. (See Exhibit 3.)
Exhibit 3: Curing the Maladies
Stage 1: Carving a Small Slice from a Mammoth Topic
A request to execute a study — on topics like “The keys to retailing success” or “How businesses across every industry worldwide are using AI” – in a few months and on a constrained budget is an impractical one. With limited resources and time, you are competing against great odds to discovering anything very new and very important on broad topics like those. The reason is you can’t plumb the recesses of any facet of such topics.
So what can you do when the “ask” comes for a study with multiple issues, multiple people in each firm to survey, and multiple sectors (or subsectors) to study? You must narrow the topic. This is where the Problem/Solution framework first comes into play: in getting a precise understanding of the problem to be studied, and whether you have enough time and resources to shed new, important light on it. Consider these three questions to clarify and narrow “the problem” to be researched:
- What exactly is the problem? What narrow aspect of it can be studied in the time and budget allotted to it?
- Who exactly has the problem? What industries and people in them should we survey and interview – and whose opinion doesn’t matter? Another way to think about this is this: Who would get promoted if the problem were solved, and who would be fired if it wasn’t? That person is your primary “problem owner.”
- How big a problem is it? What is it costing companies?
Back in 2015, Simon-Kucher & Partners, a pricing strategy consulting firm whose revenue was €209 million at the time, began to develop content on product and service innovation based its client experiences, surveys and desk research. Its goal was to publish a book that captured its expertise. However, product innovation is an extremely large topic. Simon-Kucher wisely narrowed its topic to this: How did companies that launched hugely successful new products decide how to price them? In other words, it focused its inquiry on the pricing decisions in innovation. That was its unique toehold into the broader innovation issue. (Its research was broader than that and covered the entire product development and marketing processes.)
After studying product innovators, they discovered that the most successful ones designed their products around a price that customers were willing to pay. They saw that pricing should be done at the front end of the product development process, not the back end, where it typically is done. The idea – and the 2016 book (“Monetizing Innovation,” by Madhavan Ramanujam and Georg Tacke) – were big market successes. The book, two Harvard Business Review articles they published on the book’s content, and dozens of marketing events the firm held worldwide to promote the content helped increase Simon-Kucher revenue 73% between 2015 and 2020, to €361 million.
Narrowing the scope of a topic enables you to dig deeper into it. In turn, it increases the chances you break new ground on it. In 2002, another client, Deloitte, faced a challenge in determining the scope of research on topic of “business model innovation,” which has an even larger scope than product innovation. The firm identified business model innovators as companies that changed what customers they targeted; brought innovative products and services to market; and re-invented how they brought those innovations to market.
They came to me then to develop a Harvard Business Review article based on their business model innovation research. Their research had included desk research – published articles on companies they designated as “business model innovators” – and financial research that identified those that outperformed others. Deloitte looked at the market capitalization performances of companies across a large set of industries, all to determine the standouts that grew on the back of business model innovation.
After I looked at their research presentation, I told them their findings didn’t reveal anything terribly new on the topic. Their researchers were indeed innovative thinkers, and not just on this topic. (One of them, Doug Tomlinson, later left Deloitte and launched the Vino Volo airport wine tasting store.)
The first reason why their findings were nothing new was that they scoped their topic too broadly, and ended up covering the same ground as previous researchers. The second was that they had done no deep primary case study research – only financial and secondary research to sprinkle a few company examples in the mix. That meant they had little additional information beyond what the case study writers (professors and journalists) had already revealed about these companies. I told the Deloitte researchers they would have to talk to these companies themselves and ask them things that others hadn’t.
But the first step was to narrow the scope of their topic. After reviewing all the companies they labeled as “business model innovators,” I noticed that more than a handful were much different than the others. They made their fortunes by going after markets others considered marginally profitable or unprofitable. These were companies such as Paychex (focused on small-company payroll processing), Walmart (in its early years, building stores in small towns and other rural locations), Dermalogica (skin care products sold to the small market of estheticians – shops doing cosmetic and cleaning procedures), and WellPoint Health Networks (a California health insurer with a highly profitable segment that issued policies to small businesses, which were considered an undesirable segment in the state at the time by other health insurers).
We interviewed some of these companies’ CEOs about why they found riches in niches that other companies regarded as unprofitable or marginally profitable. They gave us illuminating information. This case study research led to a focused research report on “bottom-feeders” of business model innovation. We submitted an article based on this to Harvard Business Review, and it made the cover of their March 2003 print edition.
It was a big win for Deloitte. It happened because the firm dramatically narrowed the scope of its research.
The learning is this: When time and budget are limited, a broad topic must be narrowed. If it isn’t, steps 2-6 are not likely to produce a groundbreaking research report.
Stage 2: Avoiding a Predictable Inquisition
Even when a research team narrows a topic enough to go deep and unearth new insights, unless the team delves into unexplored aspects of the topic, it is likely to merely repeat the insights others have brought. In addition, studies can be designed with too much focus on “the problem” aspect of the topic (e.g., “Why do most companies not rethink their entire business model when they have to?”) and too little on “the solution.” What’s more, without guardrails to bound the inquiry, these studies can swerve all over the road on their topic and even veer off it altogether. This is the equivalent of changing the topic to be researched.
The way to avoid veering off the topic road is making sure every research question fits with the Problem/Solution framework structure. Every research question must shed light on one of the five questions (Exhibit 4). Questions that won’t shed light on these five areas need to be tossed out. While they may be interesting to you, they are not relevant to your inquiry. If left in, your research will meander off topic.
This will bring much-needed discipline to the inquiry. It will be harder to “wander off the ranch,” so to say, if a passionate researcher wants to pursue new questions that are irrelevant to core research issues.
Exhibit 4: Driving Research Design
How do you not go down the path of a predictable inquiry, shedding little new light on a topic? This requires developing initial hypotheses to guide which questions you ask — hypotheses that buck conventional wisdom. Counterintuitive hypotheses can lead to highly counterintuitive findings (assuming that the research data supports them). Sometimes the initial hypotheses are disproved but lead to other counterintuitive findings that you didn’t anticipate in your research design. These findings often turn out to be the most counterintuitive of all. The reason: Even when you think you’ve created counterintuitive initial hypotheses, they can be based on things you’ve read – meaning, others said them first.
You need to focus your inquiry more on the “solution” (parts 3, 4 and 5 of the Problem/Solution framework) than on the problem and existing approaches to solving it (parts 1 and 2). The reason is that thought leadership research must shed new light on how companies are solving a particular problem in the world – and much less on establishing how many have the problem. Generally speaking, about 25% of your research questions should be focused on the problem and existing solutions, and 75% to determine the new and better solution.
When you design thought leadership studies this way, you must also make two other design decisions:
- Determining which research questions would be best asked through different research channels: a largely close-ended online survey, open-ended case study interviews, secondary research (such as generative AI tools), and discussions with internal and external subject experts.
- Figuring out how you will separate “best practice” from “rest practice” or (even better) “worst practice.” Your research has to identify what companies that were most successful in solving that problem did differently than others. At the very least, to do this you’ll need a survey question that asks participants about the impact of the initiative you are studying (on costs, revenue, quality, cycle time, customer retention, etc.). The survey participants with the biggest impacts can be designated as “leaders” and the ones with the smallest impacts can be designated as “followers” or “laggards.” Comparing how the groups answered the survey can unearth big differences.
Back in 2015, we helped Tata Consultancy Services design and conduct a study on how large companies around the world were using so-called Internet of Things technologies, such as digital sensors embedded in products and able to transmit data over telecom networks. We advised TCS to focus the study largely on manufacturers, and specifically (meaning focus even more) on the IoT technologies they embedded in their products so they could understand how those products were performing for customers. They could have also focused on how IoT was used in the supply chain of getting products to customers. Instead, we suggested that TCS focus on IoT technologies that big companies were embedding in the products they sold. The firm then opened doors to case study interviews at Intel, Hewlett Packard, General Electric, and other companies. We also did substantial secondary research to understand the IoT best practices at Cummins (a truck engine manufacturer), DisneyWorld, Tesla and other firms.
That research focus – how manufacturers around the world were using IoT technologies to determine how their products were performing for customers – proved instrumental to the ability of TCS’ IoT experts to say something that others hadn’t said at the time. It was that the biggest value of IoT technologies for manufacturers was to improve their products by using the data that their products were transmitting from the field on how they were performing in customers’ hands. The way TCS put it was that IoT technologies gave companies the “ultimate truth”: how their products are actually performing for customers.
That insight caught on quickly in the marketplace, including the media. Fortune’s editor in chief at the time, Alan Murray, in the magazine’s email newsletter said the study was worth the time of “anyone running a bigger-than-a-bread-box business.” Another big win: HBR ran a TCS-authored article on the research in their digital edition.
Needless to say, the TCS IoT study was a big hit in the digital marketplace.
Stage 3: Making Case Studies as Prominent as Survey Stats
Most thought leadership studies are overrun with statistics, gathered from surveying hundreds or thousands of companies on a topic. The researchers’ thinking seems to be this: “No one can argue with us if we show that the preponderance of companies believe that this [fill in the blank initiative] is a great business opportunity.”
The data collection tool most companies rely on is a survey that collects answers to close-ended questions (“Which of the following is your company investing in this year?”). The survey results then spit out percentage after percentage – e.g., “38% are investing in CRM; 46% in customer experience design software,” etc.
A survey of, say, 25 questions, whose findings are sorted by industry, region of world, country, and other parameters could easily produce 100 charts, graphs and their associated percentages. Even after wrapping the best-written prose around the charts, the text still largely recites survey percentages. No matter how well wrapped in words, the numbers become mind-numbing.
Surveys that divine what best-practice companies do differently than the rest are far more valuable than surveys that just recite practices of all companies (best-practice, worst-practice and everyone in between). But what’s better is research that interviews best- and worst-practice companies, for the sake of understanding exactly what the best companies did to solve the topic problem at hand, and exactly what the worst companies did that made them fail or fall short of solving the topic problem.
For Deloitte’s research on business model innovation “bottom-feeders,” we spoke with the then-CEOs of Paychex, Dermalogica, and Wellpoint Health Networks. In 2017, we did similar case study-driven research for a small human resources consulting firm, Talent Dimensions. The topic was about how large firms determine which talent to develop and retain. We interviewed executives or former executives from LVMH, Vail Resorts Inc., Stanley Black & Decker, and Ecolab. We also did extensive desk research on Apple, Google, Tesla, and other companies. We helped our client turn the research into an article in the digital edition of Harvard Business Review, and another one in a popular HR journal, Human Resource Executive magazine.
Without those case examples and the insights that we and our clients derived from them, neither article would have resonated in the marketplace, and neither would have made it in HBR, the world’s most prestigious management publication.
Using an icing and cake analogy, thought leadership research that produces the biggest insights treats case studies as the cake and survey statistics as the icing – not the other way around, which is what most studies do. When we polled senior executives three years ago about what aspects of thought leadership content were most important to them, by far they rated as No. 1 “proof” – defined as case study evidence of the beneficial impact of the purported solution. (See Exhibit 5.) That was even more important than having a novel solution.
Exhibit 5: Consumers of Thought Leadership Value Case Study Evidence of a Solution More Than Anything
152 respondents; # ranking these elements 1st, 2nd, or 3rd
Source: Profiting From Thought Leadership 2022 Study, by Buday TLP et al
In many cases, case study-only research is more than enough data to gather. The case studies that we conducted for Deloitte on the “bottom-feeding for blockbuster business” topic was largely case study-based. So was our study for Talent Dimensions. This research was on companies that determined the most important jobs in their organizations. The evidence was the case studies.
Stage 4: The Search for Riveting Findings
Earlier, we labeled the malady here as “regression to the mundane.” It’s, of course, a riff off the statistical expression “regression to the mean.” The latter refers to statistics from a study that at first appear to be outliers to the average results, but after additional measuring move closer to the average (also known as the “mean” in statistics terminology).
Many thought leadership researchers are under intense pressure to publish research that validates their organization’s existing beliefs about client problems, and the methods used by their experts to solve them (consultants, lawyers, architects, accountants, software engineers, etc.). This is a particular problem when thought leadership research reports to marketing. Marketing’s job, of course, is to put the best light on the company’s current service offerings. When a new study effectively shows that the firm’s prior expertise on a topic is obsolete, that puts marketing in a difficult position with the leaders of the practice area that delivers that expertise.
The ability of thought leadership researchers to conduct groundbreaking research will be hampered if all their studies must confirm the firm’s existing practices. They will culturally operate to “regress to the mundane” out of fear of internal criticism, and even ridicule. This will come at a significant price when a competitor’s thought leadership research births a big new idea, making existing practices obsolete.
As I wrote in my book “Competing on Thought Leadership” and have said numerous times, the primary roles of thought leadership research are to a) create compelling content for marketing and b) fuel service innovation.
We’ve seen the tendency of regression to the mundane happen a lot in thought leadership research. In particular, it happens when:
- The survey findings and case study examples point to a solution to a topic problem that is significantly different from the one hypothesized in research design, and
- The initial hypotheses of a study reflect conventional wisdom.
When these conditions exist, the research team essentially will design survey and case interview questions merely to confirm conventional wisdom. That’s why we recommend starting in Stage 2 with a few counterintuitive hypotheses – especially about the solution to the problem. (We realize that these hypotheses may not be confirmed when the data comes in.)
But at the very least, those counterintuitive initial hypotheses are your first line of defense against data analysis that is a regression to the mundane. But the second and most important line of defense comes from looking for important trends that the research team didn’t anticipate even in its counterintuitive initial hypotheses.
The best place to find counterintuitive trends is through deep case study research that compares the best and worst organizational practices on a topic. That kind of research helped legendary Harvard Business Professor Clayton Christensen discover the trend of “disruptive innovation;” reengineering guru Michael Hammer and his research team to discover the business reengineering trend; and Deloitte to identify its bottom-feeding blockbuster businesses trend.
When a thought leadership research team’s radically different solution must stand up to hostile internal questioning, such real-life case examples will become the team’s best evidence. It will be difficult for others to refute the real examples they have collected of companies that generated big results from doing something different.
Stage 5: Creating the Powerful Argument
By this point in the content development process, if you followed the four steps above, you should have a multitude of findings about the problem, current solutions and their failures, a new and better solution, adoption barriers, and reasons why companies need to move faster than they might think.
Since you focused your inquiry and gathered in-depth case study examples, you have both the stats and the stories to make a powerful argument about a superior way that best-practice companies solved the problem you studied.
You will have the research equivalent of a bounty of riches. However, you will have too many findings to put into your research report. You most likely will have data and charts that aren’t necessary to make your argument, and case examples that aren’t strong.
Throwing it all in the mix will make it difficult to create a cohesive, coherent narrative about your findings. It will be easy to provide too much data and examples in some parts of your narrative, and not enough in others. How do you write an engaging research report and research presentation for both your internal and external audiences – one that tells them only what they need to know about your research, and in an order that helps them make sense of it all quickly?
The answer is actually right in front of you: It’s the same Problem/Solution framework that you used in Stage 2 to determine the issues you set out to study. By stage 5, you will be very familiar with the framework. Now, of course, some of your initial hypotheses may be invalidated, and after analyzing your data you may have come up with whole new ones.
But the way to report your findings should follow the exact same structure, one that begins by starting with the audience’s core problem that you researched. Beginning with that piece of your narrative – not your solution – will ensure your audience realizes that you deeply understand their pain.
The Problem/Solution framework is the tool that prevents the wandering storyline as you structure the narrative about your research findings. But before you draft thousands of words of prose or dozens of PowerPoint pages, you should write this narrative in an outline. When you do that, it will be easier to identify what data you need – and don’t need – to make a compelling argument. Invariably, you will remove certain statistics and company examples that are not needed because you have others that are better.
In fact, my experience is that of all the statistics and stories that could be used in a research report, you’ll need only 30%-40% in your final report – even if that report is 5,000 to 10,000 words or more.
With an outline that you may need to iterate one or two times to get your logic crisp, the data and examples you need in place, and your stakeholders’ input on the draft that will follow, you will then have a key tool for Stage 6: writing the final report.
Stage 6: Turning the Argument into Compelling Prose
When Steps 1 through 5 go swimmingly, Step 6 becomes the easiest in the whole process. That’s because you have your entire argument nailed, with all the data and examples in place to make it in a deep research report.
Whoever will write the report must religiously follow the painstakingly created outline you created in Step 5. No wandering beyond the outline is permitted here – no coming up with other interesting assertions, and certainly not a new solution. The job here is akin to painting by numbers. The writer is painting a draft by adhering to a rigorous, detailed outline.
Now that doesn’t necessarily solve the biggest malady of Stage 6: prose that, while making a solid argument, is a bore and a chore to read. Here you want to use writing devices that make dull copy engaging: analogies (generative AI can be particularly effective at helping you find them), clever turns of phrase, paragraphs that start with questions for the reader, varying sentence lengths, popular examples and other instruments of gifted writers.
Here’s an example: For the executive staffing and consulting firm RGP in 2023, after designing and helping them execute a study on the staffing of strategic initiatives in three regions of the world, we recommended they use a Hollywood example to illustrate their core finding: that companies with the most successful projects used a much higher percentage of external people on their teams. We pointed them to the so-called Hollywood model of work: where very few people on a movie set work for the same company. RGP CEO Kate Duchene used that example to lead her article about the study, which ran in a September 2023 digital edition of Harvard Business Review, and which you can see here.
How Conducting Research “Inside the Box” Helps Generate Insights “Outside the Box”
The Problem/Solution approach is a structured process for conducting thought leadership research. It’s a proven way for a research team and the stakeholders in their company to remain focused on the core market problem they sought out to study and, over the research process, not wander into researching other tempting but ultimately irrelevant issues.
The approach also forces them to dive deeply into the data they collect so they can uniquely understand what the best companies did differently from the rest in solving the problem.
By following this approach, thought leadership research teams can increase the chances they develop findings that are “outside the box” – i.e., much different than the prevailing wisdom – by keeping their inquiry “inside the box” of the issues they set out to probe. (See Exhibit 6.)
Exhibit 6: Conducting Research Inside the Box to Think Outside of the Box
Here’s how the approach does this, stage by stage:
- Stage 1 (Issue Scoping): It forces the research team and internal stakeholders to agree on what business problem in the world they will and will not be investigating. That reduces research “scope creep” – i.e., the natural tendency of a research team to broaden its inquiry and sometimes pursue issues that are out of scope.
- Stage 2 (Research Design): Although the Problem/Solution approach begins with the problem, it puts the inquiry’s focus on the solution. We recommended having about roughly 25%-40% of research issues be the topic “problem” and “why existing solutions fall short,” and roughly 60%-75% on the new solution and how to adopt it.
- Stage 3 (Data Gathering): Multiple data gathering techniques are necessary, not just one (typically, this means a close-ended survey). These techniques include not only surveys, but also case study interviews and extensive desk research — especially to identify potential case studies. The Problem/Solution approach helps the research team understand which research techniques are better at collecting certain data.
- Stage 4 (Data Analysis): The approach increases the chances that the research team stays rooted on solving the original problem — not shift away from it (as can easily happen). It encourages the team to dig deeper into the data it has collected to “connect the dots” on what the best-practice companies did differently. For example, for Deloitte’s study on business model innovation, I advised their team to focus on a subset of the most successful business model innovators: companies that made fortunes catering to customer segments considered undesirable by others. In other words, we kept the focus on business model innovation (the core problem being how companies do that successfully). They could have shifted the core problem to something outside the bounds of the data they collected: e.g., how companies were using the Web in the early 2000s to create demand. However, that would have been only one facet of business model innovation (if that). Instead, we want back to the list of companies whose financial performance they charted and targeted a subset of them (and others) to further analyze after talking to executives in those “bottom-feeding” companies.
- Stage 5 (Narrative Development): The approach accelerates the research team’s task of turning their core findings into a clear and rigorous storyline. At this point, narrative development is straightforward; framing the analysis in the five parts of the problem/solution framework makes it far easier to then turn it into a narrative outline.
- Stage 6 (Report Writing): With a clear and rigorous outline in hand, the people writing the prose merely need to follow the storyline outline. That enables them to concentrate on writing style (e.g., coming up with analogies, varying sentence lengths, injecting clever phrases and other writing devices), and not trying to determine the core argument of their research paper and how to unpack it.
Time for Thought Leadership Research to Get Much More Thoughtful
The practice of thought leadership has been discovered. On many business topics today (AI, digital business innovation, marketing, product innovation, and more), you no longer have just management consulting firms spouting off from the studies that they’ve done. From studies they have conducted on the same topics, today you have technology services, venture capital, software, manufacturing and even the occasional large law firm weighing in.
This ratchets up the level of quality that thought leadership research groups must strive for.