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37. Curt Carlson’s Systematic, Repeatable Process to Generate Customer Value

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Is successful value creation through innovation the product of genius? Or of luck? No, it’s the product of a system, applied with discipline. Utilizing the system can result in repeated success in customer value generation.

Key Takeaways and Actionable Insights

Curt Carlson is the world’s leading expert practitioner. He is the founder and CEO of Practice Of Innovation, LLC, and was President Of SRI International, identified as the most successful innovation company in the world based on its development and introduction of globally important innovations like Siri for the iPhone4 and HDTV. Under Curt’s leadership, SRI grew 3.5X and created tens of billions of dollars of new customer value.

Curt believes any company can systematically generate new value for customers, and reap the rewards of the market for doing so, when they rigorously apply three fundamental rules.

  1. They have a simple value creation methodology that everyone in the company (and its collaborative partners) can describe, understand and apply every day in every job function. (Curt’s test: ask everyone in the company what the firm’s value creation method is: if they can’t describe it, there isn’t one.)
  2. They have metrics to define innovation work that is important rather than merely interesting. While subjective value is not quantifiable, there are proxies for measuring importance and market potential.
  3. They have a system for active learning. Innovation is a learning science, and active learning is a specific, high speed, high productivity version of learning, applying the best learning science principles.

In this week’s podcast, we focused especially on the simple, effective value creation methodology that Curt identifies by the initials N-A-B-C.

NABC Innovation Process

Click the image to view and download the full PDF

N is the identification and quantification of the important customer need. In B2B businesses, it’s possible to monitor financial flows and identify needs based on quantifiable elements – cost savings, time savings, and measurable quality improvements. In consumer businesses, need identification is much harder, and quantification impossible except by proxy, since needs are subjective and individual. Importantly, they are also multi-dimensional, and need identification must encompass all the dimensions.

It’s important to deeply understand human wants, whether it’s for convenience, or higher order wants such as pride and identity. Surveys told Steve Jobs that consumers wanted a “new keyboard” for existing Nokia phones that were hard to use. Jobs’s intuition was that what they really longed for was convenience. The touchscreen on the iPhone provided convenience and opened a doorway to all kinds of additional services.

A is the Approach the entrepreneurial innovator takes to meet the customer need. The approach is the design of an experience that the customer will desire. The Approach mist embrace both the assembly of the right resources into a technical solution, and the business model so that the solution makes money. There’s an iterative back-and-forth between technical solution and business model that can continue for years. Nike’s technical solution for shoes is good but not unique; its business model for sponsoring athletes to inspire aspirational consumers who wanted to “be like Mike” (or today like LeBron) elevated their offering from product to experience.

B is Benefits Per Costs. Curt uses this construction to emphasize that there are large buckets of both benefits and of costs. Benefits include not just features and performance and appearance, but also the feelings produced by the experience. Costs are similarly multi-layered: not just dollars, but also the effort required to acquire the product, and perhaps to master its use, the opportunity cost of what is given up, durability, and more. The innovative entrepreneur must look at costs from all of these angles and calculate that the “benefits per costs” for customers are much better than alternatives.

Curt’s rule of thumb is 2X to 10X better. People measure perceived benefits in percentages. 10% better, 50% better, 100% better than the status quo or the alternatives. Transformational innovations are 2 – 10X better.

C is the competition and other alternatives – both today and in the future. What are all the other ways the customer can experience the benefit they seek? What are alternative ways for them to spend their money – perhaps on a different experience that’s not a direct substitute but on which they’ll spend instead of buying our solution. How does your innovation fit into their lives so compellingly as to become preferred over all these alternatives?

N-A-B-C is a simple framework, but it’s not easy to achieve results. It requires iteration at speed among many collaborators (including customers, and possibly investors), all with different and specific talents and tacit knowledge. No individual can command sufficient knowledge, so team learning – active, comparative learning, frequently updated – is critical to the outcome.

The result is transformational: for customers who experience new value, for the firms that facilitate it, and for the individuals who practice the discipline of innovation.

DOWNLOADS & EXTRAS

Download Curt Carlson’s NABC Innovation Process PDF: Our Free E4E Knowledge Graphic

Buy a copy of Curt Carlson’s book, Innovation: The Five Disciplines For Creating What Customers Want.

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31. Per Bylund on Big Data vs. Big Ideas

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Wouldn’t it be nice to predict the future? It’s tempting to reach for the analytical tools and big data sets that are newly available and for which big claims are made regarding their predictive capabilities. For entrepreneurs, small businesses and corporate innovation teams, rich qualitative data are far more relevant and collecting these data is far more productive. By this we mean talking to customers and potential customers, observing behaviors rather than collecting clickstream data, and immersing yourself in the unpredictable subjectivity of the consumer.

In this week’s Economics For Entrepreneurs podcast, Dr. Per Bylund analyzes what big data can and can’t do for entrepreneurs and the innovation process, and explains how qualitative data can generate big ideas for the future.

Key Takeaways and Actionable Insights

Predictive analytics can’t predict! That was Dr. Per Bylund’s provocative introduction to our discussion of the uses and drawbacks of big data in the context of the entrepreneurial mission.

The claims made on behalf of the analytical powers of big data may be exaggerated, and entrepreneurs should learn what they can and can not expect from the application of big data analytics to business. Otherwise there is the chance of both error and wasted spending on the tools of business intelligence. It’s important to distinguish between the different roles of multiple data types.

Big Data vs Big Ideas Chart

Click on the image to download the Big Data vs. Big Ideas PDF

Pattern recognition is not prediction. Dr Bylund contrasted what Big Data can and can’t do for entrepreneurs. He used an example of analytics predicting the outcomes of future NFL games. Here there are large sets of historical data on players, teams, plays and previous outcomes. There are limited potential outcomes (e.g. one team will win the game – there is no third team that will unexpectedly turn up to change the range of possible outcomes). The predictive analytics got the outcome right about 75% of the time. In a world of more open-ended results (e.g. predicting the outcome of a multi-team tournament), big data could be expected to be right fewer times. There is danger in over-reliance on the law of large numbers and tendencies like reversion to the mean. Pattern recognition from historical data sets (which is what big data does well) is not prediction.

In fact, in the world of economics and entrepreneurship, there is no prediction. Entrepreneurs deal with social phenomena that emerge from individuals’ actions and interactions, across billions and trillions of instances. Entrepreneurial outcomes depend on how people act, and how they act depends on their feelings, how they see the world (subjectivism) and what they feel like doing. We can’t know or predict that. There may be some general rules that apply in many cases (for example, raising prices rapidly and significantly in a competitive market will, all other things being equal, result in a reduced unit volume of sales). But those rules don’t predict the decisions of specific individuals in specific cases.

Mainstream economists and central planners long for a mechanistic world: turn a dial, get a result. But this approach is not valid. In the economy or any market, all variables are dependent on all other variables. Everything affects everything. The consequences of any action – like central bank interest rate tinkering – affect different people in different ways, and whoever is affected first or last will experience different consequences and react in different ways.

The core of the issue is that human behavior is unpredictable. Subjective choices can’t be predicted.

Prediction implies precision, and that’s not available.

Yet the entrepreneur must deal with the future. The entrepreneur seeks to produce a good or a service that consumers will consider valuable at some point in the future. Even if they tell you today that they will value your offering in the future, they may change their minds.

Is there any contribution that big data can make, any help that it can offer? We discussed these areas:

  • It’s hard to know what people might want in the future. But it might be possible to identify what specific people will not want, based on their past behaviors. Data can show you which purchases cluster together, and which don’t. Beef purchasers may also buy red wine. Vegans won’t buy beef. Facebook and other ad targeting tools (which use big data effectively) can help you avoid marketing beef to vegans or pasta to keto diet followers.
  • Data can sometimes detect dissatisfactions, which are the universal raw material for entrepreneurs.  Analysis of sentiments expressed in reviews can guide you in the right direction. Writing a negative review on Yelp or Trip Advisor is both a behavior and an expression of sentiment and data analytics can detect patterns here. But Dr.Bylund advises us that it can only provide a guide – there is no substitute for talking directly to consumers, human to human.
  • Data can help with segmentation. If you want to better understand a geographical market segment or a demographic segment or a behavioral segment, there are lots of data that can detect the differences between segments, and this can help you with targeting of communications (but not necessarily with the message).
  • Quantitative data can be combined with qualitative data to sharpen insights. Dr. Smita Bakshi, in our episode #24 described how analysis of student performance data (50% of computer science students don’t complete their first-year course) combined with personal discussions with students in class, delivered an empathic understanding of their struggles, from which her team developed a winning interactive learning tool for computer programming languages.

Sometimes an entrepreneur can skip the big data analytics, but never the empathic diagnosis. Entrepreneurship consists of understanding the mind of the consumer and understanding the economics of the marketplace. Where the market is heading and what will be in consumers’ minds in the future are more the realm of judgement than analytics.

Entrepreneurs behave differently than dig data-driven large corporates. They think harder about the customer, they study human motivation, they utilize the rich qualitative data that comes from talking to customers, and they concentrate their capital and resources on developing and extrapolating their customer understanding. They uncover subjective value – the value that only exists in the mind of the consumer. Imagination is the key to the future. Entrepreneurs try to succeed in bringing about that imagined future. Big data might help them avoid mistakes, but it’s impossible to rely on the past to produce the future.

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PDF icon Download Our Big Data vs. Big Ideas PDF (129 KB)

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Entrepreneurial Initiative Beats Corporate Innovation Process Yet Again. When Will They Ever Learn?

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According to the Wall Street Journal, Altria, maker of Marlboro and other cigarettes, is planning to invest in Juul, maker of a cigarette alternative which vaporizes nicotine-containing liquids. These devices are often called “vapes” and the practice of using them, “vaping”. A company dedicated to addicting people to smoking burning tobacco is now adding to its portfolio a company dedicated to terminating that addiction. At the same time, Altria has made a $1.3 billion investment in Canadian cannabis company Cronos Group, Inc. It will all make for interesting portfolio management.

However, for entrepreneurs, the most important aspect of the investment combination of Juul and Marlboro is what it tells us about innovation and who is capable of delivering it. Altria has been aware for a long time of the evidence that the long term future of the cigarette market is threatened by external trends, including the subjective lifestyle preferences of consumers (and the non-consumers who dislike the “second hand smoke” problem), but also including regulation, taxation and the resultant deterioration in the price-value proposition.

Faced with such negative long term trend signals, the good and wise corporation, prompted by the business school community that has populated the executive ranks in addition to marketing its tools through consulting, seminars and books, initiated an internal innovation process. This produced the idea of so called e-cigarette products, like MarkTen and Green Smoke, devices in which tobacco is heated but not burned, which purportedly makes smoking less risky. The process also produced a device called iQOS, developed in partnership with Philip Morris International, which is a sister company spun out of Altria to sell cigarettes in international countries outside of the glare of the US legal profession and its alliance with state and federal regulators.

Philip Morris International took the lead in marketing iQOS and claimed some early success in Japan, so much so that the company diverted significant resources from conventional cigarettes to the heat-not-burn “breakthrough”. After initial growth, Motley Fool in October 2018 reported “disappointing earnings” at Philip Morris International attributable to a “significant slowdown in the e-cig’s primary market, Japan”. Motley Fool reported some early trial among a younger demographic, but “a wall of resistance among older cigarette smokers”.

It looks as though Altria has seen the warning signs as an indication of failed corporate internal innovation, and has swerved to the alternate lane of acquisition of the innovative ideas of external independent entrepreneurs.

Its investment of $12.8 billion for a 35% stake in Juul Labs Inc suggests a roughly $38 billion valuation, making Juul one of the most valuable private companies. The Juul team has created this much value in about three years, while Altria and Philip Morris international were destroying value in their failed attempts at internal innovation.

The Failure Of Centrally Planned Innovation Processes.

They should have known. Corporate innovation processes are doomed to failure. That’s because innovation is not a process. It can’t be centrally planned by executive wing geniuses, no matter how much they spend on consulting and business school seminars. Innovations like Juul are emergent results of marketplace experimentation by entrepreneurs and consumers. The consumers become dissatisfied with the current set of offerings available to them – that particular phenomenon is strikingly apparent in the cigarette market. They begin to experiment with alternatives – they might try nicotine chewing gum, or patches, or snus (tobacco pouches placed in the mouth) or even iQOS. They are not yet declaring their loyalty to a new solution, but simply looking round at alternatives.

Entrepreneurs are dissatisfied with the supply side of the market. They sense the consumer dissatisfaction and match it with their producer dissatisfaction. They, too, experiment. There have been many such producer experiments in the cigarette market, and Juul is the one that has, for the moment, risen to the top. Why? It’s usually random luck combined with a co-creation collaboration with the consumer – continuously adding and changing features and attributes and measuring consumer response until the best combination emerges. There are so many experiments among so many producers and so many consumers that one combination eventually emerges as the most preferred. The outcome can not be predicted, it can’t be modeled, and it can’t be managed. The genius of the market is that all of the failed experiments result in very small losses and a lot of learning. The one successful experiment eventually incorporates all the learning, attracts a large number of customers, creates a lot of value in a short period of time, and generates a huge amount of economic progress far in excess of the losses from the failures.

The scale and reach of this experimentation, the rapid exchange of knowledge and learning in the network of entrepreneurs and consumers, the flexible adaptiveness that allows for the rapid abandonment of the resources committed to failed paths and the agile transfer of resources to the path of success, can not be matched by a centrally planned corporate innovation process. Decision-making in hierarchical structures can’t reproduce the emergent properties of interconnected knowledge-sharing networks. Processes with their stages and gates can not compete with the spontaneous order of free experimentation. Corporate investment guidelines can not compete with entrepreneurial risk-taking.

The Future Of Innovation Lies With Interconnected Individuals.

The future of innovation lies squarely in the initiatives of the independent, interconnected entrepreneur. As new technologies like A.I. and global idea exchange platforms augment individual capacity, the trend towards individually ideated innovation will accelerate.

This does not mean that corporations will not try to suppress it rather than adopt it. Glaringly, in a follow-up report in the Wall Street Journal, we learned that one of the results of the Altria investment in Juul will be collaboration between the two companies’ regulatory teams. Speaking of cronying up to government regulators, the Altria CEO was quoted as saying, “We have years of experience” in such regulatory negotiating and another spokesperson spoke proudly of Altria’s possession of  “a level of sophistication they (Juul) need”.

This reveals a downside of capitalism. Altria has enough money to invest in Juul Labs, and enough left over to smother it in corporate process and bind it with regulatory collaboration. While there is no inherent objection to scale, it usually brings with it the insidious integration with government that is anathema to further economic progress. Not to worry; the independent entrepreneurial network will nurture new innovations through its experimentation and co-creation activities faster than incumbent corporations can capture the emergent value through M&A.