Tag Archives: disruptive innovation

What Big Shoes Can Teach Startups About Jobs-To-Be-Done Marketing

People need shoes. There is a grand market for shoes. Zappos has proven it. Big Shoes dubbed “Store Sko” in Norwegian, a small shop in my neighborhood that sells (guess what) big shoes, has also proven it. The shop has been running profitable for years. Big Shoes is master of segmentation marketing.

Asymmetric motivation

Big Shoes has a positioning advantage – competitors, incumbents and mainstream shoe shops are reluctant to pursue the market of abnormal shoe sizes. First, the market is not perceived large and hence lucrative enough compared to mainstream markets. Second, customized shoes require customized inventory and production lines.

Reverse marketing

When a mainstream shop cannot provide for the customer that shoe size s/he is looking for, they refer to Big Shoes, a sales person told be. Big Shoes receives referrals from competitors because they are in fact not yet competitors – they target different segments. Rather, for the mainstream shop, it is a matter of customer service.

Customer service

Since Big Shoes is about the only big-shoes-specialist in Norway, customers come back. As customer retention is high, Big Shoes builds a stronger relationship to its customers who again share the news with new customers.

Jobs-to-be-done

People with extra large feet do not mainly need a spectacular design or shock-absorbing functions with their shoes. They need shoes that fit. Big Shoes excel at solving that problem for this particular segment. The shop has even started providing shoes that competes with regular shoes on design.

By getting the job done and solving a real customer need, Big Shoes are able to provide great customer service, keep clear of competition, and accordingly charge extra. The shop has added mail order as distributions channel and expanded into additional XXL product ranges. Big Shoes is on the disruptive track.

What are other examples of disruptive, jobs-to-be-done marketing startups?

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The Startup Samaritan’s Dilemma

Helpers of early stage startups – incubators, accelerators, angels and advisors – sleep good at night. There is something samaritan about what they do. They serve the bottom of the economic pyramid on which our society rests.  They facilitate jobs, and in turn taxes. Some get wealthy and part is poured back in to new ventures, jobs and taxes. A virtue indeed. Yet there is a dilemma. While high-end markets yields and numbers make the deal, the Startup Samaritan migrate towards helping “grown-ups” at the expense of startups. The cure: startup methodology.

While I was studying and working my own market research practice, I had the pleasure to work with a couple of fine venture finance agents. I did customer interviews, and created business plans and investor presentations. It was first when I got the assignment to carry out a method with the goal of evaluating risk in early-stage ventures that I understood the dilemma.

What I quickly learned was that there is a minimal quantifiable track record within a startup. Accordingly, analytic models get dismissed in favor of qualitative variables such as team, customer insight and technology. For a couple of reasons I believe that this creates a dilemma to the Startup Samaritan.

  • The time utilized in facilitating a startup is pretty much equal to that of facilitating a grown-up. Risk is lower and more predictable at the later stages. The stake and respectively the compensation is often higher. For logical reasons the Samaritan’s focus gradually migrates towards grown-ups. High-end markets yield.
  • With the theory of Disruptive Innovation, authors argue that most companies force teams to develop detailed financial estimates way too early, when their accuracy will necessarily be low. That using metrics such as net present value (NPV) or return on investment (ROI) as rank-ordering tools to make decisions is counterproductive [i]. Technological knowledge and qualitative unpredictability might cause a great headache to MBA scholars. Naturally such samaritans seek to utilize their knowledge and go after what is quantifiable.

Instead, early startup formation requires an understanding of entrepreneurial patterns – talking failure as well as success. Methodologies such as Customer Development and Lean Startup identify and learn from common challenges that occurs in startups and then describe methods that aid in overcoming such challenges. In exchange for meter-long spreadsheets, they embrace so-called Startup Metrics that are trackable, actionable and drive better product and marketing decisions. Of course you can not ignore financial data, but focusing on the assumptions behind the numbers is meaningful when there is no such track record. Dedication is more likely when motivation, knowledge and methods are aligned.

The bottom line:

  • Focusing on patterns [through startup methodologies] instead of numbers enable entrepreneurs to better manage uncertainty and their good samaritans to sleep even better in the future.
  • Principles of Disruptive Innovation can help explain why startup investors as well as entrepreneurs would want to educate in startup methodologies.

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[i] Mapping Your Innovation Strategy, by Scott D. Anthony, Matt Eyring, and Lib Gibson

The network economy calls for new models – entrepreneurship or management?

Technology changes. Yet, methodology remain. When managers develop strategies for their companies, many still use the methods and tools of the traditional organization. As mentioned in the previous post on the Lean Startup Business Model Pattern, there are new methodologies in town. However, the traditional business strategy formulation frameworks still fail to adapt technology change and the network economy, as well as the understanding of entrepreneurship as process but a whim. I reckon that there are some trajectories especially fruitful for adaption.

  • Take Michal Porter’s frameworks for an example. How do you apply the value chain framework to networked businesses, two-sided markets (e.g. social networks, online dating, auction sites, search marketing, credit cards, banks, etc.) where manufacturing is not the locus of value creation [1]. Management and consultants of all colors tend to stand by the former, but are the models still valid?
  • Also consider whether entrepreneurs have the time and resources to sit down and carefully lay out their long-time strategy. Or whether strategy formulation should come as consequence of processes where resources are scarce and uncertainty is extreme. This calls for new frameworks that embrace entrepreneurial learning and change methodologies. To site Steven Blank, A Startup is Not a Smaller Version of a Large Company. Instead early stage ventures require their own tools and techniques.
  • Commodification of web services, API’s and social media allows unstructured strategic models to become structured. That is, conceptual models would integrate data about your customers, such as user behavior and demographics to aid in decision support and increased responsiveness. Similarly, how does rapid collaboration and the free flow of information that are made possible with the social web affect the technology adoption life cycle?

The management challenges presented by entrepreneurship are different [2]. Nevertheless, the management challenges presented by the networked economy (read cloud computing, social web, you get it) are different. Network companies create value by facilitating connections between two or more customers. Not by efficiency in A-to-B manufacturing. Too often  managers try to use traditional strategy methodologies when dealing with new technology paradigms. Similar to what Clayton Christensen & co may think of as cramming. When dealing with the introduction of disruptive technologies of any kind, managers still have to align with entrepreneurial approaches. Indeed, there is a need for change methodologies.

[1] There are some excellent work on value networks and multi-sided markets by among others Ø. Fjeldstad and E. Andersen‘s Casting of the Chains , Tom Eisenmann, and the contributors at the Catalyst Code blog.

[2] This post was also inspired by Is Entrepreneurship a Management Science? by Eric Ries for Harvard Business Review

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