The prosperity paradox means that innovation destroys wealth while innovation also creates wealth. The late Clayton Christensen, who stipulated the dichotomy in his seminal work of the same name, was quick to point at an essential point of differentiation: Not all innovations are created equal. Instead, while innovation that increases efficiency diminishes prosperity, market-creating innovations create prosperity for a much more significant number of people.

Innovation is not strategy

Innovation is the quest for novelty. Strategy is choosing to perform either different activities or to do the same or similar activities differently than rivals while advancing the productivity frontier. Naturally, innovation requires experimentation, exploration, and discovery. Strategy, however, assumes a fixed value proposition, a deliberate tradeoff between activities to do vs. those chosen not to do for reasons of strategic positioning. Innovation may not require strategy, but a business with a proper strategy requires innovation to sustain its competitive advantage.

Sustaining prosperity requires innovation.

Companies that cannot innovate in response to market changes diminish in relevance over time. Blockbuster failed to innovate for the internet age and was sidelined by Netflix. Walmart failed to embrace online shopping and found itself in fierce competition with the ever-growing behemoth Amazon. All major German car makers face the fifth year of declining vehicle delivery primarily because of having failed to transition towards electric mobility. In contrast, Tesla’s vehicle delivery increased tenfold over the same five years[1]. However, it’s not that German car makers didn’t innovate. On the contrary, the German car industry leads globally in terms of efficiency, productivity, and advanced automation. If sustaining prosperity would require innovation, why does the German car industry faces a decline in vehicle delivery year after year? Why does sustained productivity innovation only lead to declining prosperity? German carmakers, similar to most manufacturing industries, often apply the following reasoning:

1. Innovation lowers costs, increases efficiency, or both
2. Lower cost and more efficiency then cause higher profit

One might think the story ends here, and, indeed, some companies fall for this easy-to-understand line of reasoning. However, see what happens next:

1. Higher profit, attract more competition or incents existing competitors to copy

2. Competitors aim to attract customers

3. Attracting new or more customers lead to lower prices

4. Lowers prices eventually reduce profits for every market participant

5. Lower profits then diminish prosperity for the entire industry

6. The second part unfolds whenever low entry barriers to an industry overlap with above-average profit margins, resulting in a price war that consolidates the entire industry. Online services often fall into this trap because the entry bar of developing a website that sells services online is relatively low compared to industrial-scale manufacturing. For that reason, the emerging crypto industry blossoms on a few original ideas and countless copycats.

However, Companies that survived a price war often find themselves in a commodity industry where the product is easily interchangeable, leaving its price the only differentiator. Airline industries worldwide went through multiple price wars and consolidations and often became a textbook example of a commodity industry.

Companies that compete only on price find themselves trapped in an industry-wide productivity contest that only requires operating efficiently at the lowest marginal cost.

On the other hand, a different kind of innovation converts non-consumption into consumption by creating new marketplaces in which people trade goods or services. Customers become sellers, sellers open marketplaces, and marketplaces facilitate the trade between all participants. New marketplaces are rarely particularly efficient at the beginning but grow profit margins inclemently with each subsequent improvement in operational effectiveness. It seems that fishing the blue ocean only requires a rowing boat to get started, but it’s getting better once the trawler arrives. Examples of market-creating companies:

• Alibaba helps small shop owners to sell online to the world.
• Airbnb allows people to make some extra money by renting out a place.
• FAANG companies operate various marketplaces such as the AppStore, several marketplaces to buy & sell advertising, and certainly an online bookstore behemoth.

They all operate a marketplace where many people trade goods and services with each other so that everyone is better off. Also, they work at the forefront of artificial intelligence to optimize the flow of goods and services. And as a byproduct, all those companies have been consistently valued above $100 billion.

Creating a marketplace alone is necessary but not sufficient to create prosperity.

Innovative requires reframing operations

When creating a marketplace, people need a reason to use that marketplace over other alternatives. When eBay started, classified advertising in the newspaper was still a viable alternative. The central question back then is the same as today: Why do people choose eBay over any other option?

A simplistic answer would be that eBay does a better job in selling all kinds of items. A less obvious answer is that eBay does a different job. Clayton Christensen stipulates that customers don’t buy products or services; they “hire” them to do a job. Understanding customers do not drive innovation success, he argues. Understanding customer jobs does.

The “Jobs-to-Be-Done” (JTBD) approach asks to frame the problem from a customer’s point of view, which means the company needs to understand what its customer tries to get done that would require a product or service. Specifically, when framing eBay as a customer’s job to be done, it would be “Help me to sell my used items.” Conceptually, each JTBD has a performance-defining component that makes or breaks the successful adoption of available solutions.

In the eBay example, it turned out that classified ads had a text limit and often charged extra for pictures or particular typesetting even though the performance-defining component accurately depicts the item for sale. In response, eBay focused on letting sellers add images, tables, and various formatting for the describing text. From a buyer’s perspective, the JTBD comes down to finding the correct item to buy, and the corresponding performance-defining component is instant and accurate search results.

Finding a JTBD only requires a handful of customer interviews to ask about the specific task they are trying to solve and what they consider the performance-defining component to get the job done. People tend to swap products and services whenever a better alternative becomes viable; however, the underlying JTDB often remains constant, with the performance-defining component serving as the main criterion to keep the existing solution or adopt a new one.

Classic strategy stipulates that operational effectiveness is more than the sum of all activities because of the deep and unique integration among all activities. This perspective remains intact when adopting the JTBD lens, although all business activities then revolve around offering a proper solution to the JTBD. Designing those activities requires a more in-depth understanding of the actual cause of the performance-defining component.

A causal relation exists if and only if when the presence of A also means the presence of B AND the absence of A means the absence of B. For example, there is a causal relationship between using the light switch and the light bulb emitting light because when electricity flows, the light is on. However, when the flow of electricity stops, the room is dark. Furthermore, there is a clear distinction between potentiality and actuality. There might be any number of reasons why people possibly switch on the light in a home, but actually, it’s because it’s getting dark. When looking at all the causes of a performance-defining component, only actual causes contain valuable information to extract. Often actual causes reduce to no more than 2 or 3 distinct causes in total, with all others being only variations.

Identifying the performance-defining component is relatively easy; people often tell the top priority that helps them decide to buy something. Forming clusters of customers relative to the most cited performance-defining component comes in handy as support for marketing to different customer segments. However, finding the exact cause of that performance-defining component requires research, experimentation, focus groups, and customer validation.

In the eBay example, creating an accurate depiction of the item to sell may lead to the idea of adding a fully-fledged typesetting system to the website allowing even more fancy descriptions. However, when conducting more JTBD interviews, two distinct customer segments may emerge. One group asks for more editing capabilities, and the second asks for a more time-efficient way to get an item listed. In a subsequent focus group, it becomes clear that people from the second group have demanding jobs, a family, and several other commitments but still want to sell some leftover items. When asking the first group about a more efficient process to list items, they might be either indifferent or slightly optimistic about the idea but certainly not against it. Therefore, adding the option to use an ISBN to download all available book data automatically and create a simple but fully customizable listing solves the relative priorities of one customer segment while offering options for the other segment.

When a performance-defining component’s exact cause is known, it is paramount to design the fastest and most efficient winning process that delivers the JTBD to customers. With that approach, businesses develop new activities and sometimes new marketplaces, knowing precisely that the resulting outcome of these processes will cause what the customer cares most about when using the product or service.

Creating a new marketplace does not automatically lead to customers. Implementing a customer’s job to be done leads to creating a marketplace. Innovation does not automatically lead to better products or services. Innovating along the performance-defining component of the customer’s job to be done leads to better products and services people want to buy.

Even with a perfectly-identified JTBD, its matching performance-defining component, and the most efficient processes underneath, prosperity may not follow.

Innovation requires novelty

Sustaining prosperity requires innovation because only a steady stream of novel products and services will generate the net profit necessary to maintain the company. Therefore, innovation is never an outcome, never a project, but rather a continuous process in search of novelty. After all, people buy the new iPhone, the new Tesla, and may even consider switching brands whenever a product or service offers a unique value otherwise not provided by the market. Companies with an exceptional value proposition charge a premium relative to the market price, but only as long as uniqueness prevails. Once enough copies make the unique ubiquitous, the original becomes a commodity.

There is one noticeable exception, though, when third-order fit spans multiple products with the combined solution offering the most optimized experience that is not otherwise attainable. While these product families are rare, each involved product will continue selling at a premium regardless of how many cheaper copies the market offers. Novelty may not necessarily lead to new and innovative products and services.

Instead, much more strategic value derives from novel ways to integrate previously disjoint products to maximize third-order fit across multiple products that offer a superior experience when combined and used. As a result, the introduction of new products then first and foremost depends on their relative novelty and usefulness w.r.t. to advancing the combined experience. A wide-angle camera in a cell phone may not be much of a novelty. However, using the wide-angle camera of an Apple iPhone to video stream a tabletop presentation from a macbook certainly adds to the integrated experience spanning multiple devices.

The intersection between strategy and innovation leads to the quest for unique and novel value required to sustain prosperity. Novelty cannot be planned nor attained through a relentless pursuit of a grand goal. Instead, the quest for originality leads to a myriad of innovations while embracing the path of uncertainty. Kenneth Stanley stipulates that innovation is not driven by narrowly focusing on a goal. Instead, we would be wiser and reach better outcomes faster if we embraced serendipitous discovery.

Specifically, Stanley states that novelty search oscillates between open exploration and deliberate exploitation whenever something of value has been found. Once exploitation ends, exploration resumes with the understanding that every iteration is considered a stepping stone. Stanley backs the assertion that novelty search leads to better results in a shorter time through countless experiments and computer simulations. When adopting the concept of novelty search, only three rules apply:

1. There is no goal, no direction, and no guidance.
2. Every stepping stone must be different from the previous one. In the case of multiple options, select the most different one.
3. The actual outcome is ranked based on applicable metrics to select the most favored result for exploitation.

The first application of novelty search was engineering optimization problems. Those problems have nearly infinite possible solutions, but only a minimal number of all solutions deliver an optimal result. Novelty search finds those optimal solutions in order of magnitude less time. Problems that took a solid computer a week to solve were reduced to 20 minutes.

Finding new graphic designs would be a more contemporary application of novelty search. There might be any number of designs in the world, but customers of a specific store may only prefer a small set of new designs. Instead of showing thousands of possible new graphic designs to a focus group, novelty search produces the top designs presented to a focus group. From there, a designer continues with the most popular selection. One cannot underestimate the amount of time saved through repeated application of novelty search.

Finding new business ideas is another area for novelty search. Instead of building an actual product or service, the key is to produce a collection of the most different business ideas. The customer may not be known, so ranking might not be possible. Instead, validate each business idea by testing the underlying assumption using wireframes, drawings, landing pages, or other mock techniques.

Once the top 3 ideas have been ranked, it’s time to conduct in-depth interviews to identify the JTBD and the matching performance-defining component. With that knowledge equipped, a drafted unique value proposition allows validation with prospective customers. During those interviews, asking for the willingness to pay helps to pinpoint pricing to a realistic range which then serves as a parameter to estimate operational cost relative to sales volume. Determining customers’ willingness to pay is particularly significant when there are several different options. Creating and testing those options using novelty search cuts short the exploration phase. Preliminary exploitation through a limited trial usually helps to identify a clear winner out of all available options.

Conclusion

Prosperity requires novelty, a defined JTBD, its matching performance-defining component, and the most efficient processes to deliver a superior experience that commands a premium price relative to the market. Once the product or service enters the market, novelty search resume either to improve the JTBD, to improve integration with existing solutions, or to find a new JTBD that may lead to the formation of a new marketplace. Prosperity follows, eventually.

Marvin F.L. Hansen

Sources:

Porter, M. E. “What Is Strategy?” Harvard Business Review 74, no. 6 (November–December 1996): 61–78.

Christensen, Clayton M., Taddy Hall, Karen Dillon, and David S. Duncan. Competing Against Luck: The Story of Innovation and Customer Choice. New York: Harper Business, 2016.

Kenneth O. Stanley and Joel Lehman. 2015. Why Greatness Cannot Be Planned: The Myth of the Objective. Springer Publishing

[1] Will German Automakers market share continue to shrink?