Q&A
Below are the answers to a number of questions you may have about Fad-Free Strategy as a business executive or strategy professor. For any additional questions, don’t hesitate to contact us.
For business executives
Fad-Free Strategy is different from other business strategy books in three major ways. First, Fad-Free Strategy is full of real-world cases that illustrate how the methods and tools explained in the book have been applied by the authors during their combined 50+ years’ management consulting career. These illustrations are based on doing and improving from within rather than observing as an outsider.
At the same time, the methods are rigorous yet practical and totally open book. The Fad-Free Strategy™ approach is scientifically founded and has been proven to work across industries and regions in the real world. By way of contrast, most academic textbooks provide theoretical constructs of limited practical applicability in the real world; and most business books by practitioners provide simple yet ad hoc tools with little theoretical foundation. This book bridges the gap in a totally transparent way so that managers can use it confidently over and over again.
Third, the book provides an exhaustive approach and tools to make better decisions in the entire strategy process, not just when strategizing at a high level but also in the evidence-based validation and detailing of the grand strategic choices prior to execution. No other book does this.
Plenty of popular business books that offer simple frameworks to guide the design of a business strategy ultimately turn out to be strategy fads. Fads look at the ways of working of companies that were successful for a period of time, and then generalize those into a supposedly universally applicable theory, that is, a set of rules that these carefully selected hero companies allegedly applied. The logic is that other companies, if they just were to apply those same rules, would be equally successful.
Unfortunately, following strategy fads and copying the heroes’ alleged rules is dangerous. For one thing, fads suffer from adverse selection: fads select successful companies while ignoring those that failed. Second, strategy fads cannot be generalized, as they at best “predict” the past. They typically do not make the underlying assumptions about customer and competitor behavior explicit. With such a black box, it is a leap of faith to believe that applying the rules will ensure the future success of any other company. Finally, every company’s customer and competitive situation is different, so that no single and simple set of rules will apply to all companies. Discussions with numerous executives of mainstream companies reveal that the experience of today’s hero companies (say Apple or Amazon) are of remarkable insignificance to the daily practice of executives at 99% of real-world companies that are just mainstream. And, as we all know, today’s heroes can easily be tomorrow’s villains.
Fad-Free Strategy, by way of contrast, is totally transparent. It makes all behavioral assumptions explicit. It provides a set of tools that have proven to work in the real world. It allows executives of all types of companies to generate solutions tailored to the particular strategy challenges they are facing.
It is fashionable to argue that designing strategy in detail has become pointIess in today’s volatile, uncertain, complex and ambiguous (VUCA) world. By the time one has defined a business strategy, the argument goes, the competitive environment may already have changed. Against this background, a number of scholars and practitioners advocate the “strategy-as-learning” solution: decide on a course of action, start implementing, and adjust as you progress.
We certainly agree that corporate agility is important. At the same time, there are two reasons why strategy design remains critical. For one thing, there are many markets that rarely make it in the business press but that turn out to be still relatively stable (cement, lighting, chemicals, payroll services, logistical services, domestic appliances and numerous medical supplies to name a few). Companies in those markets need strategy design as much, if not more than agility, precisely in view of the difficulty to create superior products or services that are hard to imitate.
For another, many strategies do fail (somewhere between 60 and 90%, depending on the source used). The real behavior of customers, who are the final judge of a strategy’s validity, often appears not to be in line with what executives hoped or expected to happen. Such failures are expensive in terms of cash expenditures, reputational damage and individual career prospects. That issue is not resolved through more strategic agility. Instead it requires that strategy is designed in a more rigorous and more customer-centric manner. Above all, it requires that the top and bottom line impact of the strategy is validated based on reliable customer-based evidence.
“Execution eats strategy for lunch” is a fashionable maxim used to argue that big strategic failures are often due to the poor execution of an otherwise great strategy. This phenomenon is commonly called the strategy-execution gap. We do agree that, at the end of the day, only strategy execution and delivery count. However, we also find that a strategy may sound great internally, that is, to the company’s decision-makers, but ultimately fails, not because of its poor execution but because it wasn’t that great in reality, that is, externally to customers, who are the ultimate decision-makers. Time and again we observe a lack of rigor and customer input when executives assess the feasibility and financial effects of their strategic choices before pushing the “commit” button. For example, entering a market and capturing a 5% share after 3 years sounds reasonable, until a more in-depth analysis reveals that only 1 out of 3 potential customers would consider abandoning their current best alternative (e.g., their current supplier) within the foreseeable future and that the company does not meet the minimum requirements of 4 out of 5 of these receptive customers (do the math: 5% market share requires that the company would have to capture a 75% share of these customers …).
There are quite a few studies that seek to establish correlations between publicly available data on business performance and variables reflecting the strategic choices of the companies concerned. For example, one large-scale study we know of concludes that companies should compete on differentiators other than price, such as brand. That conclusion is based on the observation that companies that created a strong brand outperformed the others “on average”.
In strategy, however, averages never matter. The rule that companies should create a strong brand may be sensible in certain situations, but in a commodity business such as chemical intermediates, brand building most likely is a value destructor. Following a simple rule that is simply not applicable to a specific situation may lead to outcomes that are not any more desirable than those that would follow from flipping a coin – and may kill a business.
We are not claiming that executives should abandon the time-honored practice of formulating what we call a Grand Strategy: an overarching vision, ambitious goals and high-level choices about where and how to compete. What we are advocating, though, is that executives should not execute those Grand Strategy choices straight away, but still consider them as hypotheses to be tested through what we call Operational Strategy. By anticipating customers’ and competitors’ behavior and using rigorous economic tools, Operational Strategy will thus either confirm or adapt the Grand Strategy hypothesis and then fine-tune the choices, or reject the Grand Strategy hypothesis altogether. In other words, it is customer choices rather than executives’ ambitions that determine whether a strategy will generate the aspired financial results.
Fad-Free Strategy™ does not advance any new theory. The way of thinking that we put forward relies solely on minimalistic microeconomic behavioral assumptions, that is, assumptions that are so reasonable that they are hard to disagree with, even though occasionally violated. One such assumption is that customers look for the “best deal” given their preferences, or, in academic terms, maximize the difference between their willingness-to-pay and price. Another assumption is that those preferences differ across customers, that is, there is no such thing as one “customer value” but differences in customer values. The flipside of being minimalistic is that we discard those microeconomic assumptions that are non-generalizable, such as the assumption of “decreasing marginal utility.” We also adopt the minimalistic economic assumption that competitors are acting and reacting in their own interest but we don’t assume that competitors are hyperrational (as in game-theory) or that their best interest is necessarily profit-maximization. It is simply not always the case.
Overall, if one agrees with those assumptions, the essence of analysis in Operational Strategy is to accurately and quantitatively measure customer preferences and willingness-to-pay, as well as to realistically forecast likely competitor responses. The strategic best choices follow solidly from the assumptions and those measurements. As a consequence, they can be implemented confidently.
Making top line forecasts of various strategic options is one of the most critical issues in business strategy. While the top line forecast for a given strategic option should be determined by the number of customers in the target market and by the number of units that these customers would buy at different prices, in many cases we find that this evaluation is done in an ad hoc and often subjective manner, with little or no customer input. Hence, what is needed are tools to extract preferences and ultimately willingness-to-buy at different prices for any offering that a company can bring.
People do not necessarily know their preferences. They find it hard to express them, and definitely so for new products having a variety of features and benefits that they never encountered before. To uncover and craft those preferences, we use a preference, willingness-to-pay and willingness-to-buy elicitation method. For scientific reasons and so as to minimize bias, the method does not rely on any direct price questions. In essence we conduct in-depth interviews with a sample of potential customers to identify switching values, also called indifference points, between pairwise options and with the customer’s (possibly unexpressed) best alternative. Using these indifference values and the minimalistic assumptions referred to above, we craft an individual customer’s entire preference structure. That allows us to accurately forecast choices that an individual customer would make between any of the company’s possible offerings and between these and the customer’s best alternative. We also derive how choices will differ across customers. Fad-Free Strategy explains tools like these in great detail, fully transparently and through many successful real-world cases.
No two potential customers can be claimed to be identical, at least not upfront. Two different customers a priori have different preferences. They may choose totally different offerings even if they have a number of common characteristics (in B2C markets: in terms of age, gender, income, hometown, professional occupation, …; in B2B markets: in terms of industrial application, geography, size, profitability or any other parameter that can be used to cluster people or companies in “segments”). In our experience, belonging to a defined segment is often not a good predictor of customer preferences or of the choices that a given customer will actually make. Ultimately it is the preferences of individual customers and the differences therein that count in strategic decision-making.
After having measured those preferences, though, segments possibly could be identified. This is the case only when (1) groups of customers can be identified with relatively similar needs and willingness-to-buy, and (2) the similarity of preferences can be linked to observable characteristics. In our experience these evidence-based real segments, if existing at all, often differ significantly from the a priori segmentation made internally.
Potential customers have needs, and a company aims to meet those needs through its products or, more generally, its offerings, including solutions, services and intangibles such as the brand. The product is the means by which the company creates value, and by which it can possibly capture a significant part of the value created. In other words, the core of business strategy is product strategy, and surely not a decision that should be passed on to the guys in Product Planning or Marketing, once the big shots in the C-suite have concocted the company strategy. It also means that the other assessments should logically be made afterwards. Those may include: the needed investments, partnerships or acquisitions; the pricing strategy, the definition of the unique selling proposition and the communication strategy; the organizational design, culture and values; the financing arrangements; and the company’s environmental and social goals. It does not mean that those assessments are less important, since they do affect the actual strategic choices, but in terms of strategic reasoning they should be subordinated to “the products to meet customers’ needs”.
To start with, the validity of the approach in general and the trade-off method in particular follows from the minimalistic behavioral assumptions made – they are so reasonable and hard to dispute that they have been used in all methods of decision analysis for over a century, and have been widely used in what is known as “standard sequence decision analysis”. Next, the reliability of the antecedent of the method has been empirically validated by Wakker and Deneffe (see, for example, their 1996 seminal article in Management Science) and later references. We have subsequently adapted it to business settings, and applied and finetuned it in numerous real-world situations for some 20 years in a very wide range of both B2B and B2C markets, for both age-old commodities (think cement), innovative packages (think advanced battery materials), services (think payroll processing) and platforms (think speed camera information exchange platforms).
Fad-Free Strategy will be a useful tool for smart business executives at mainstream companies who are disappointed with strategy fads and simplistic solutions based on cherry-picked, anecdotal evidence from today’s hero companies. Fad-Free Strategy shows in a practical and transparent way how managers can make better business strategy decisions by using rigorous economic tools to generate tailored and evidence-based solutions. Fad-Free Strategy will also appeal to economics faculty members teaching graduate courses in business strategy who are looking for an economics-based strategy textbook that is both rigorous and comprehensive.
For strategy professors
Many economics faculty members teaching graduate courses in business strategy are not comfortable with the popular strategy books written. The key reason is that these books – faddish best-sellers and others alike – typically do not make the assumptions explicit, if existing at all, to justify their statements or framework. This is at odds with economics, which derives conclusions or recommendations from a number of simplifying assumptions that are made explicit: if one agrees with the assumptions, the conclusions do follow.
At the same time, those same faculty members are also not quite satisfied with the economics-based textbooks when teaching strategy. While those books may be more solidly founded, they are just not comprehensive. Admittedly, they have plenty of merit when addressing a number of selected topics in strategy (such as vertical integration, dynamic pricing, competitive interactions or entry deterrence) for which the (industrial) economic literature has generated rigorously founded conclusions. But they have little to say about many decisions in the entire business strategy process, such as: how to analyze numerous strategic options, how to actually generate a business plan for a newly launched product, or how to operationally set up a defense strategy against new entrants. This is not surprising, since the focus of economics is more about markets and how they work, and less about identifying firm-specific matters (firm-specific demand or firm-specific capabilities).
Fad-Free Strategy, by way of contrast, not only uses economics thinking and makes its assumptions totally explicit, but also supplements this thinking with other solid methodologies that are needed to understand the missing firm-specific information (decision analysis, preference elicitation and the like). It also provides practical real-world methods when the (rationality) assumptions of economics are just not appropriate. The outcome is an approach to strategy that is rigorous, practical and evidence-based.
Fad-Free Strategy is particularly suited for a core course in (E)MBA or continuing education programs or for an elective on real-world business strategy. The appeal of this book is particularly strong for economics-based faculty members teaching strategy. On the one hand, they will have an economics-based textbook with a way of thinking that they will embrace. On the other hand, they will get a comprehensive textbook for doing strategy that addresses issues where econ is rather silent and where rigorous methods that are tangent to economics will be covered (e.g., utility elicitation methods from decision analysis to derive firm-specific demand). In addition, they will see how these tools have been applied within the context of real-world cases, not by observers but by doers.
This culminates in the following benefits: more confidence in teaching strategy comprehensively yet rigorously; more respect from students because of the true disguised real-world cases and applied frameworks; more respect, credibility and impact, even with the more critical experienced students; significantly higher ratings; more demands for consulting projects; and higher pay.
These are not promises but reality. They just all come from the experience of one of the authors, Daniel Deneffe (PhD, Cornell Economics). He started his professional career as a full-time faculty member at the Fuqua School of Business at Duke University in the MBA and EMBA programs but then moved to consulting, advising companies worldwide in the areas of corporate and business unit strategy, marketing strategy and pricing excellence. Loaded with this real-world experience, he gradually added teaching back to his professional activities (currently at Harvard University’s Division of Continuing Education and at Hult International Business School), and his teaching performance skyrocketed. He received the Professor of the Year award a record 20+ times. He attributes his impact on students entirely to the real-world cases and questions that are covered in the book and to the rigorous, yet applied and practical tools that have been used to address them.
Fad-Free Strategy™ is solely based on four selected behavioral assumptions of microeconomic utility. Those assumptions are on the preferences that customers have when facing product alternatives, whether those are goods, services or solutions. The first three assumptions are those of completeness, transitivity and highest deal value. Without them, one would not be able to do any customer analysis at all. Those are the best possible assumptions to make, relative to any other ones, even if people violate them at times in more complicated settings. The fourth assumption is that of additivity (or separability of the utility function). It does not always hold but can be handled by testing with customers beforehand which items need to be treated separately and which ones must be treated as one. Fad-Free Strategy™ does not rely on any other assumption of microeconomic utility theory. Out go assumptions such as “more is preferred to less” or “utility diminishes at the margin”, because those do not appear to hold systematically in the real world.
Making top line forecasts of various strategic options is one of the most critical issues in business strategy. While the top line forecast for a given strategic option should be determined by the real-world firm-specific demand curve that captures the number of customers in the target market and by the number of units that these customers would buy at different prices, in many cases we find that this evaluation is done in an ad hoc and often subjective manner, with little or no customer input. Hence, what is needed are tools to measure such demand curve based on customer preferences.
To craft people’s preferences and eventually willingness-to-buy, we conduct in-depth interviews with a sample of potential customers to identify indifference points between pairwise options and with the customer’s (possibly unexpressed) best alternative. Using these indifference values and the minimalistic assumptions referred to above, we craft an individual customer’s entire utility function and preference structure. That allows us to accurately forecast the choices that an individual customer would make between any of the company’s possible offerings and between these and the customer’s best alternative at different price levels. We also derive how choices will differ across customers, which is the foundation of the demand curve. Fad-Free Strategy explains tools like these in great detail, fully transparently and through many successful real-world cases.
Conjoint analysis and the trade-off method share the objective of understanding customer preferences, that is, how variations in features influence customer preferences. While the two methods at first sight may look similar, the trade-off method is fundamentally different. All forms of conjoint analysis record customers’ preferences (be they choices, ratings or rankings) for a controlled set of packages (products, services or solutions) and then process them by means of some type of regression analysis (linear, logit, Hierarchical Bayesian and the like) to infer the impact of the levels of various attributes (specific own and competitors’ price levels, product feature levels, brand names, etc.) on customers’ utility.
The trade-off method has several important benefits over choice-based conjoint analysis and its wide range of sub-types, thus leading to radically fewer sources of error. First, the trade-off method measures not only which of two packages is preferred by the customer but also by how much. Second, the trade-off method only measures the impact of feature level changes within the scope of the company’s capabilities. Third, the trade-off method also provides an indication of the value improvement required to make a customer switch from his or her best alternative to a company’s offering. Fourth, the trade-off method not only measures preferences over feature levels presented in the choice questions but also captures the switching value, that is, the sum of all the tangible and intangible value differences between any proposed offering and the customer’s best alternative. Fifth, the trade-off method, rather than having to specify discrete levels of continuous variables in the choice sets, infers the critical switching values and thus captures more accurately the non-linearities of preferences. Sixth, the trade-off method does not rely on any regression analysis, hence does not assume a functional form for customer preferences that may deviate from the true form, hence does not suffer from statistical estimation bias. Finally, the trade-off method does not make any implicit assumptions about the shape of the demand curve (that is, individual utilities in relation to that of the population) but infers the demand curve bottom-up.
The Fad-Free Strategy book uses a multitude of real-world cases to explain its way of thinking and methods in a rigorous, detailed, practical and fully transparent way. There are two main differences between the cases used in Fad-Free Strategy and those used in many faddish strategy books. First, none of the cases relates to (today’s) hero companies. The cases used in Fad-Free Strategy relate to the 99% of the companies that are mainstream, in a very wide range of both B2B and B2C markets, for both age-old commodities (think cement), innovative packages (think advanced battery materials), services (think payroll processing) and platforms (think speed camera information exchange platforms). Second, the case examples are not embellished a posteriori stories drawn from watching from the outside (desk research and selected interviews) but from doing from within: they reflect factual strategy consulting work that has been done by the authors for real-world companies.