Friday, September 11, 2020

The Disruptive Power of the Ends Game, Part 2: Invite the Customer to Help

The best way to understand how to best provide value to your customers? Ask them
(This is slightly expanded from the version published in Inc. magazine on 9/11/20.) 
As we discussed in Part 1 (at Inc., and slightly expanded here), The Ends Game argues that today's organizations are addressing "only half the battle" concerning the central question of "What are we asking customers to pay for?" The other half, which has only recently been made practical by new ways of collecting real-time information, is to evaluate how you're helping a customer achieve desired ends.

There is another important aspect to answering that question still to address. That is to directly engage the customer's unique ability to help you be even more efficient and adaptive in understanding what you are asking them to pay for.

FairPay shows how we can more fully enlist the customer as ally in understanding impact, outcomes, and ends, and in modeling value in terms of satisfaction of their needs and wants. FairPay is a rich framework for increased cooperation with the customer in playing the Ends Game. The proven principles underlying that framework make a strong argument for enlisting each willing customer in helping to determine what you should be asking them to pay for. 

I do not argue here for the specific methods of FairPay. My point here is simply directional -- that the strategies of FairPay point to how the unique wisdom of each customer can help cut through the most knotty challenges of the Ends Game.

The breakthrough in the FairPay framework is to restructure the price-setting process using the continuity and context of an ongoing relationship to get customers to cooperate with you in determining what is a fair price. Why is that vitally important? Because, as Marco and Oded say, "[t]he ultimate outcome, of course, is value...Actual satisfactions." The customer is the final arbiter of which of their outcomes matter and how much value and satisfaction they deliver. They decide to become and remain your customer on the basis of their perception of value, and of the fairness of your price. You can use all the modeling and impact data you can find, but until you are able to know what is in your customer's mind, you may not get to the answer that counts.

FairPay begins as a price-setting matter (and so may seem of relatively narrow interest). But price is just the monetary balancing of net value exchange. FairPay works for two reasons:

  • Each customer has insights into the value they obtain that you can only understand if they share those insights.
  • You can draw those insights out because most customers (especially your best customers) want to be fair about what they pay you -- if you gain their trust and motivate their cooperation. 

FairPay centers on the point of price-setting, by asking each participating customer to have a say in what the fair price is. How much of a say is determined in the context of the relationship, recognizing that the game of commerce is usually a "repeated game" that involves repetition of transactions over time. A repeated game works best when both parties benefit from cooperation, and so can be motivated to build on that in a virtuous cycle.

FairPay makes that motivation to cooperate central and explicit: "You, the customer, can have a say in what the price is for each transaction, but we, the business, will continue to play that kind of FairPay game with you only as long as we agree that your pricing is reasonably fair. We agree to have ongoing dialogs about value -- so we can agree (or not) whether the price for any interval of service is fair." But wait, there is more...

Price-setting is just the start of how FairPay changes the Ends Game

Price-setting can only be fair if the revenue model is fair. The FairPay dialog is not just about the price, but also about "What are we asking customers to pay for?" The customer has an intuitive, but richly multidimensional, model of what value they want, what value they are getting, and what they think is a fair price for that value. Dialog can surface whatever outcomes or other value metrics the customer thinks are relevant to justify their sense of what is fair for them to pay at any given stage in the game. The business may suggest and counter with any factors that it thinks relevant. This creates a new dynamic that opens up the kind of inter-party negotiating range and nuance that is familiar in traditional bargaining, but with a key difference: the ends of the negotiation are explicitly on lifetime value over the relationship rather than on one-time transactions.

That ongoing cooperation simplifies the challenge of finding proper metrics of value. That effort becomes more nuanced and forgiving, because it is just a stage in an adaptive process that emerges as this dialog unfolds. Different value metrics may be posited by either party. Any working agreement on fairness can be reopened as the context changes and other metrics emerge as more relevant. The exact choice of metrics (and of price) at any point in the game becomes just a working approximation in an ongoing process of continuous learning. The process of identifying and eliminating barriers to access, consumption, and performance is no longer just a process of one-sided inference by the business, but also of asking the customers what barriers they see.

The process becomes more fuzzy -- but that is its benefit. Modern business abhors fuzziness as unpredictable and hard to manage, but value to humans is inherently fuzzy. The "proof" of the value is in the customer's agreement to that value as being fair, not in some abstract mathematical construct of value metrics. Those constructs are only a tool for reaching human agreement.

As Marco and Oded say, "The challenge lies in accountability, which means cultivating the relationship between organization and individual in a manner that is sustainable and mutually beneficial. The right revenue model is what sustains that relationship." FairPay is a method for enlisting the customer in a process for converging on accountability and agreement on the right revenue model (and adjusting it when needed) -- even if that model is a fuzzy one.

Managing an emergent and cooperative process of value discovery

None of this is counter to the lessons of The Ends Game. To manage this process at scale, a business must be able to reduce decisions to algorithms that can be automated in a way that requires more nuanced human judgment only on an exception basis. We need to study the barriers and be creative about finding the right metrics of value and combining them with the right weights.

That is how we evaluate whether the customer's assessment fair value is one that we should consider fair enough for us to be able to benefit from doing business with them. We work with all the impact data we can glean, and use it the best way we know how.

[Not included in the Inc version: Without FairPay, we have to slog through the swamp of incompleteness that Marco and Oded allude to in describing the Pay per Laugh example: " organization that uses a performance model lives and dies by the 'quality' of the metric it adopts. Some people may enjoy the show immensely but laugh very little, while others may attempt to stifle laughter in order to save some money. These concerns are always going to exist unless the metric is a perfect, tamper-proof proxy of the actual value derived by customers. Finally, the right technology is essential to make pay-by-outcome work."]

FairPay dialogs provide a way to work heuristically around the limitations that Marco and Oded describe in how our impact data inform us about the outcomes and their perceived value -- when they are not meaningful, measurable, robust, and reliable enough, or lacking in breadth and depth. We build a tentative valuation model for each customer, and use that model to suggest a price that seems fair based on what we know about the value they received. But then, if the customer disagrees with our assessment of value, that is where we work to build in a new level of learning. We can use multiple choice dialogs to ask the customer why they disagree.

The power of FairPay to draw out the customer's perspective in a trustworthy way can be better understood by considering the three building blocks that drive this process (a formulation Marco contributed to in our journal paper on FairPay):

  1. Empowerment to participate in pricing. (Asking customers to participate in pricing decisions is empowering, and empowerment is known to foster engagement and satisfaction.)
  2. Dialog that is open to considering the price in terms of all aspects of value, including needs, wants, features, services, pain points, barriers, and price levels.
  3. Reputation, as the way to build trust that the customer's use of that empowerment will be acceptably fair. (Develop a fairness rating for each customer. continuously update it, and use it to decide how to reward generosity and when to warn or restrict customers who are repeatedly unfair.)

This drives the new form of repeated game structure of FairPay, and informs it to serve as a cooperative value discovery engine that iterates to be adaptively win-win (as explained in detail in my book and the many works listed on my blog).

Algorithms can become increasingly effective in understanding how the value metrics of the customer differ from our models for that customer, determining if that is fair, and if so, adjusting our model for that customer, to build a new and better model for them. We can apply heuristic thresholds (simply, or with machine learning) to determine what price is fair enough to continue the game profitably and what is not. We can also draw on human intervention to deal on an exception basis with an ordinarily fair customer that surprises our algorithms by seeming unfair in a given context.

FairPay might appear to each customer as a "bot" that acts as a customer contact who knows them as an individual -- representing the business, understanding that customer's needs and values, interacting with them in whatever way works best for them, and managing the relationship.  This FairPay bot serves as an approximation of my value demon, to learn how the customer thinks about value -- and to nudge them to see the value that the business would like them to pay for. It manages a 360 degree relationship of cooperation (a much expanded level of CRM), to co-create value in whatever way is desirable to both parties, and to divide the value surplus fairly. (Again, for exceptional cases where the bot hits its limits, human managers can intervene.) This adaptive learning process can drive service improvements, bundling, up-selling, and development.

What the customer knows and thinks

This dialog with the customer about value should be central to all business. How can you expect to understand the value and satisfaction your customers perceive if you don't ask them? How can you make it easy and natural for them to tell you when you don't seem to get it?

Sure, even without these formalized dialogs, some subset of customers alert you with complaints about the most egregious outcome problems, but how many don't bother -- because they don't have an easy mechanism, and they don't think you really want to hear from them (or that you will not really listen if they do tell you). Instead, it seems that, outside of small, carefully managed focus groups, businesses are afraid to talk with customers, to ask what they think about value, and seek only to talk at them about the wonderfulness of their offerings.

As Marco and Oded say, "There may be factors that contribute to an outcome that the organization cannot observe, measure, or control. To the extent that there are significant differences in the value customers derive from a product or service, then the chosen outcome measure must be 'personal' enough to reflect this." Making that personal enough will be a tall order for the foreseeable future if we only look through a one-way glass, and don't find a good way to ask the customer for help.

This FairPay process helps to more fully address "...the trillion dollar question...the extent to which customers are willing to share their information with firms and fuel the Ends Game ...companies must be able to communicate that sharing one's data has never been a more valuable investment." The FairPay repeated game structure seeks to constantly drive that communication and generate the proof to the customer that it beneficially results in value at a fair price. In parallel, you can use whatever impact data you can glean to validate what the customer reports, and determine if they are being honest with you or trying to game the system.

Marco and Oded argue that "when customers know firsthand that an organization can use these [impact] data to deliver the outcomes they desire, it puts both parties in the exchange in an enviable position." The deeper cooperation of FairPay gives businesses a way to play the Ends Game in a way that is seen to be win-win -- to deepen their relationship with those who want to play fairly, and to cull out those customers who choose not to deal fairly. Some businesses, and some customers, may be slow to recognize how powerful this is, but those who do will find new power to co-create and share in value that more one-sided approaches cannot equal.

Opening this level of dialog with customers will take learning and experimentation. But finding the right impact data and using that to build the right revenue model without asking the customer will also be very challenging -- especially wherever customer needs and wants are diverse and subject to change with context and time. FairPay points to ways to harness what the customer can tell you, combine it with what you can figure out for yourself, and continuously adapt your revenue models accordingly.

This kind of deeply cooperative relationship can enable you to play the Ends Game more effectively -- to attract and retain more customers, make them better customers, and increase the lifetime value that you and they share in.


More about FairPay

A very brief and simple introduction is in Techonomy"Information Wants to be Free; Consumers May Want to Pay"
(FairPay is an open architecture, in the public domain. My work on FairPay is pro-bono. I offer free consultation to those interested in applying FairPay, and welcome questions.)


To stay updated and interact with others interested in FairPay, please join the LinkedIn group, “FairPay: Adaptively Win-Win Customer Relationships.” 

Tuesday, September 8, 2020

The Disruptive Power of the Ends Game (Part 1 of 2)

Why businesses should not just ask what customers want, but measure whether they are getting what they need.
This is a slightly expanded version of Part 1, published in Inc. magazine on 9/8/20. This Part 1 concentrates on what is in the book, The Ends Game. Part 2 takes off from there, to explain how FairPay strategies can enable businesses and customers to play the Ends Game in a way that is even more efficiently win-win -- and thus create and share in even more value.  (See the Inc. version of Part 2, or slightly expanded here.)
The Ends Game is the title of an important new book that explains why now is the time to focus on helping customers achieve the ends they seek, and sharing in the value that they co-create with them. It argues that the ways enlightened and sophisticated companies currently attend to their customers are excellent, but only half the battle. This book presents a concise and clear manifesto of what is missing, why it is essential to focus on it now, and how to embark on the path to do that. It is written by Marco Bertini and Oded Koenigsberg, professors of marketing known for their insights into pricing strategy.

I had the pleasure of reading a pre-release copy because Marco co-authored with me two articles about the FairPay framework. This new book by Marco and Oded concentrates on how to think about "What are we asking customers to pay for?" As they say, that is essentially a question of revenue models. (It is also foundational to how FairPay addresses a related question: how do you harness new levels of cooperation with customers to be even more efficient and adaptive in doing that?)

Why read -- and play -- the Ends Game now?

This is a deeply researched and insightful work, offering a coherent vision of why playing the Ends Game is the future of business. It lays out a concise manifesto for business model disruption, centered on revenue models, and explains why pricing models are the essence of business. It offers conceptual grounding supported by a wide range of examples, in a style that is neither abstract nor buried in anecdote.

Marco and Oded show how businesses have been focused on the means for serving customers, but rarely focus on the real ends that customers want. It explains how all the work of customer care, market research, design of customer journeys, and operational skill and responsiveness are typically directed at the means not the ends. Businesses pride themselves on their focus on the customer, the authors note, "but then the same company pays hardly any attention to customers when it decides how to earn revenue from them."

This focus on ends is not a new idea, but it has been neglected because we lacked the technology and data to address the customers' ends at scale. The authors point (as Marco and I have in our co-authored papers) to the invention of the price tag around 1850 as a key turning point from which traditional business decoupled itself from consideration of individual customer value proposition in order to scale: "organizations gradually shifted their pricing decisions away from customers and what they value, which was the focus of haggling, to the one piece of information they could trust and readily collect: information on the cost of making an offering and bringing it to market." (Of course competitor pricing has also been an important factor.) Pricing for value on an individualized basis has long been understood to be the ideal in theory, but in very hard to do at scale in practice.  The compromise has been to sell the means to the ends, and hope that was close enough.

What has changed to make the Ends Game feasible is the growing availability of new kinds of "impact data." Impact data provide "information on when and how customers consume products and services, and how well these offerings actually perform." That new data lets businesses "move from promises to proof." Technology makes the achievement of ends transparent and accountable. Companies can now record consumption events and, increasingly, even observe the value obtained from them. This "post-purchase behavior" can now be "observed directly, completely, and in real time."

Marco and Oded make a strong case for the value of these new strategies to benefit not just businesses, but their customers: "The powerful combination of real-time consumption patterns, personalization, and rich contextual data--all at scale--provides companies a basis to establish and reinforce trust with their customers, one by one." I was struck by how this positive vision provides an important counterbalance to the fatalistic view of Shoshana Zuboff's influential The Age of Surveillance Capitalism, and how The Ends Game rightly highlights the benefits that could come from responsible, opt-in uses of data by businesses.

Applying impact data to enable revenue models that are accountable for the ends

The essential point of The Ends Game is that businesses profit best from relationships with customers that enable them to achieve the customers' ends in ways that are accountable, sustainable, and mutually beneficial.

To make revenue models efficient, businesses must address three levels of barriers to value co-creation:

  1. Access waste: “Customers can’t get it.”
  2. Consumption waste: “Customers don’t or can’t use it.”
  3. Performance waste: “The customer has access to it and consumes it, but the end result simply isn’t satisfactory.

The authors explore the already widely recognized and duplicated successes of addressing access waste through subscription and membership models. This is already the topic of many excellent books, but as they point out, subscriptions and other shifts from ownership to access are "only the first of many potential moves.”

Their treatment integrates this access waste with the bigger picture of consumption waste and performance waste. They expand on how consumption waste can be addressed with models that apply metering of usage, or sharing, of resources, products, or services.

From there they move on to the ultimate question: outcomes and performance waste -- and how new kinds of impact data can make the often very subjective and elusive questions of outcomes far more tractable. “[t]he ultimate outcome, of course, is value...Actual satisfactions.” That is what your customers really want.

Marco and Oded address a related question that is also central to FairPay: risk. Customers are reluctant to take risks on access, consumption, and performance.  Companies can "attract more customers by lowering barriers to purchase and boost willingness to pay by progressively taking on the risk inherent in the exchange.”

The middle part of the book digs deeper into examples of how companies are already playing the Ends Game, spanning a broad range of industries with B2B and B2C products and services of all kinds. Some of the revenue and pricing models will be familiar, some not.

Especially striking to me was the example of a Spanish comedy theater with a "Pay per Laugh" model (which had a price cap "so that no one would need to cry because they laughed more than they could afford") -- a creative use of sensing technology to measure laughs, clever framing of the model, and use of a price cap for added risk avoidance.

Pay per Laugh may seem fanciful, but as the authors observe, "Value is the ultimate outcome. If a firm could charge its customers based directly and precisely on the tangible and intangible satisfactions they derive in an exchange, then there would be no need for an intermediate measure to calibrate the exchange and access, consumption, and performance waste are minimized. Value establishes the natural equilibrium between You get what you pay for and You pay for what you get."

They come back to this as the “Existential question…What are we asking customers to pay for?” I have emphasized much the same fundamental point through a thought experiment where a value "demon" is capable of reading the minds of the customer and the provider to reveal their direct value perceptions and how that value should be shared.

Most industries are at the early stages of a process that will unfold over the next few years, with improving technology making performance models not only feasible, but also practical and profitable. The primary concern for organizations in the meantime is understanding the true source of the value they create for customers. If value itself cannot be measured, the choice of outcome is critical. There may be factors that contribute to an outcome that the organization cannot observe, measure, or control. To the extent that there are significant differences in the value customers derive from a product or service, then the chosen outcome measure must be “personal” enough to reflect this.

The quest for ends

The final portions of The Ends Game dig deeper into these challenges -- how to take action and how to define outcomes. Attention is given to collecting and analyzing impact data without abusing the privilege and to "ensuring that customers are active and positive participants in the creation of quality outcomes."

Marco and Oded outline four conditions for a suitable measure of outcomes: to be meaningful (thus valuable to customers, even if highly subjective like "enjoyment"), measurablerobust, and reliable. Metrics must address the breadth of heterogeneous customer needs and wants, and the depth of the task of meeting them, including the complexity of who contributed what when multiple parties are involved in a solution. I add a further issue to be considered in my second part: how customers can become more direct participants in defining what the relevant outcomes and metrics are, as they perceive them.

[Not included in the Inc. version: Barriers to moving toward outcomes include the "quality paradox ...when a company obsessively directs its efforts toward continuously innovating its products and services, it risks becoming accountable to its offering rather than to its customers." One important form of this is surrogation, when the metric that is the surrogate for an objective distracts from the objective itself, creating a form of tunnel vision that is reinforced by its partial and temporary success.]

The authors grant that overcoming these barriers is hard, but complacency is dangerous. They are realistic in suggesting that managers focus on the quest, not just the destination. In some contexts the quest may be long, and only partial steps will be practical now -- to be extended gradually.

Impact data present particular challenges because they are so personally intrusive and invasive compared to the more traditional market research data and data on customer journeys: "the trillion dollar question...the extent to which customers are willing to share their information with firms and fuel the Ends Game ...companies must be able to communicate that sharing one's data has never been a more valuable investment." Building trust and transparency are essential to getting customers to opt-in to truly collaborative efforts to play the Ends Game. It all comes down to accountability -- that means not only creating, but demonstrating value. This is another theme central to FairPay:  what matters is not only what a business does, but also how it does it.

Last, but not least, there are organizational obstacles to change. The authors point to the opportunity for disruptive startups that can start fresh without legacy concerns -- and also to how established businesses can begin to move before a startup or some bold competitor can steal their markets. "Often it is a newcomer that succeeds in reducing waste by introducing a revenue model conceived to improve access to the market, mirror consumption, or perhaps even guarantee performance."

[Not included in the Inc. version: That brings us back to the centrality of truly partnering with customers, with the ultimate principle being "to profit only when customers do." The authors point out that impact metrics can create a moral hazard, where customers can try to game the metrics. There are tactical measures to limit that, but at a strategic level we return to two central tasks for the business: “…questioning the gap between what it promises customers and what they actually pay for" and ensuring that the customers "benefit proportionally—if not disproportionally—as outcomes improve.”]

This quest has many challenges that will unfold in stages over time. But the authors make a strong case that this quest that must be undertaken if a business seeks lasting success -- and they provide clear directions on how to embark on it.

Part 2 of this commentary (in Inc, and slightly expanded here) explores how FairPay restructures the Ends Game -- as a new form of repeated game over the course of the relationship with each customer -- to directly motivate collaboration, transparency and trust to use impact data in this quest to define and meet each customer's desired ends -- in a win-win way that is emergent and adaptive.

(An article by Marco and Oded summarizing the book, The Ends GameCompeting on Customer Outcomes, appeared in MIT Sloan Management Review.)


More about FairPay

A very brief and simple introduction is in Techonomy"Information Wants to be Free; Consumers May Want to Pay"
(FairPay is an open architecture, in the public domain. My work on FairPay is pro-bono. I offer free consultation to those interested in applying FairPay, and welcome questions.)


To stay updated and interact with others interested in FairPay, please join the LinkedIn group, “FairPay: Adaptively Win-Win Customer Relationships.”