Advisor

Hypercompetition and Hollywood Economics

Posted November 17, 2016 in Business Technology & Digital Transformation Strategies
Borys Stokalski

Your digital transformation journey’s proper starting point is the “business” part of “digital business.” Whether you are a decision maker who sees “the digital” as a strategic necessity or a midtier enterprise “digital enthusiast” who wants to help your company become the Google of its industry, do not start by merely replicating some practice you see emerging in successful digital businesses — be it omnichannel, big data, or Agile processes. Exactly this kind of attitude exhibited on a large scale is what led to the growth and subsequent crash of the dot-com investment bubble at the turn of the century.

What you need to drive your digital transformation is a realistic stakeholders’ consensus about the purpose, expected results (for your customers and your organization), and a roadmap of actions to deliver those results. Such a consensus requires you to create a shared understanding about the nature of the digital business economic environment.

We suggest that the best foundation for “educated intuition” supporting such consensus comes from an industry that has been for at least four decades a nexus of intense hypercompetition, deregulation, fast technology adoption, business convergence, and shifting business models: entertainment and media.

There are a couple of noteworthy research efforts relating to hypercompetitive business and entertainment. One such effort is the Experience Economy, a strategic planning framework developed by Strategic Horizons cofounders James H. Gilmore and B. Joseph Pine II. At the center of their work is a model relating economic value to the progression of value proposition categories: from commodity goods (e.g., coffee beans), to a product (coffee), to a service (a cup of coffee offered in a cafe), to an experience (a cup of select coffee offered in an exceptional environment). Gilmore and Pine argue that this progression of offerings is correlated with growth of unit margins/transaction profitability. This is due to the fact that the pricing mechanism moves from “objective,” based on supply versus demand and established externally by the market, to personalized “value pricing,” which rewards those who provide premium experiences. The authors argue that most businesses should view a market as a stage on which service providers orchestrate experiences that — if well executed — are rewarded with better margins.

If you believe that this metaphor has little to do with your digital business transformation, we suggest you think twice. Is customer experience an important factor affecting the conversion of leads to loyal customers in your business? Are the digital touchpoints — websites, mobile apps, social networking services — becoming essential for your customer relationship? Are you competing for the attention of your clients (or potential clients) with myriad other offerings trying to squeeze their messages and services into the same time-space of casual smartphone interactions? Are these offerings often unrelated to what you used to call your core business? You have just discovered that every business affected by digital transformation becomes a “show business” — sometimes literally. While your customer is holding a tablet or a smartphone in an Uber car, your m-commerce app may be competing with Netflix or CNN. Every second not spent on shopping shortens your opportunity to influence buying decisions and ­execute up-selling tactics, and is one second less opportunity to monetize your application through mobile advertising. In the digital world, the heavily standardized mobile devices become the ultimate hubs of ”business convergence.” They aggregate thousands of services across all possible industries, allocating the scarcest resource — customer engagement — to those that have the capability to stand out in the crowd.

If you find this picture familiar, then we strongly rec­ommend you pay at least some attention to the findings of Hollywood Economics by UCLA Professor Arthur De Vany, who uses rigorous research to analyze how the American movie industry generates its profits. The book, published in 2003, has a meaningful subtitle: How Extreme Uncertainty Shapes the Film Industry. One facet of this uncertainty is the fact that the life expectancy of a Hollywood movie is often significantly shorter than the time it takes to create it. According to De Vany, “a movie has less than a 25% chance of lasting 7 weeks or more in the Top-50 and less than a 15% chance of lasting 10 weeks or more. A film ... surviving more than 15 weeks on the charts is an aberration when compared to the population of motion pictures that breaks into the Top-50.”

This disproportion between complexity of the investment and short market life is a major source of risk in the digital economy, especially for mature organizations. European telecoms failed in competition with Over the Top (OTT) players not because they did not understand the opportunities. Rather, the maturity of their business processes, supported by complex IT architecture, turned into a cost multiplicator when compared to the expense of the greenfield approach taken by startups like WhatsApp or even more established new entrants like Netflix, Google, or Apple. Risk aversion made the telecoms ­incapable of investing in small niches with high growth potential — there were simply too many of them. And their long history of monopolism made them difficult business partners for those willing to take the risks. As a result, the revenues of European telecoms are systematically falling, losing more than 10% over the last five years. Meanwhile, in the same booming mobile applications ecosystem, value-added services revenues are shifting to OTT providers, which CSPs carry on their expensive infrastructure.

In Hollywood, the profit distribution is extremely skewed. It is a winner-takes-all game where “less than 20% of movies earn 80% of gross and less than 5% earn about 85% of all profit in the business.” The accumulated movie audience, which is the primary revenue and profit driver, grows over time following nonlinear patterns. Initial, small differences between the results of a movie run to extremes. The results are affected by dynamic amplification of the viewers’ sentiment — the outcome of the movie experience — which affects the behavior of potential consumers. Word of mouth, social rankings, and retransmission of opinions through social media are forces that trump marketing after the product is launched. This is further magnified by the fact that up-selling opportunities, such as movie theme franchises or related merchandise, make sense primarily for titles that gained substantial initial popularity, thus increasing the jackpot for the winners.

Similarly, nonlinear (or “long tail”1) patterns of growth are common for digital offerings. Where an innovative consumer-oriented service defines some successful new category of value proposition (e.g., social network platform, media streaming service), after some initial turmoil, a few clear category winners remain in business with one or two reaping most of the profits.

De Vany proves mathematically that the success of an individual movie cannot be predicted — marketing or “star power” cannot influence its fate. What remains is the quality of the product. De Vany concludes:

None of our results is more surprising than finding that hard-headed science puts the creative process at the very center of the motion picture universe.… There is no reason for management to get in the way of the creative process. Character, creativity, and good storytelling trump everything else.

As a caveat, De Vany observes that the quality of a movie is highly subjective and depends on expectations shaped by previous movie experiences. This is why the content components such as storytelling patterns, action dynamics, and quality of special effects need to evolve. Successful movies set new benchmarks, which again are exceeded in the quest for success. Gilmore and Pine also capture this phenomenon in their model as the continuous erosion of the value of an offering. In digital business, technology serves as yet another powerful force that speeds up commoditization; the best ideas can be automated and easily replicated in new solutions.

Finally, apart from focusing on product quality, De Vany advocates that investors focus their attention on movie portfolios rather than try to optimize the economic outcome of an individual project. He notes, “the difficulties of predicting outcomes for individual movies are so severe that a strategy of choosing portfolios of movies is more sensible than the current practice of ‘greenlighting’ individual movie projects.” Such a strategy is routine for venture capitalists and financial institutions in their management of credit risk. If you accept the idea that Hollywood is a valuable metaphor for digital business, then a portfolio approach should be an essential element of digital strategies.

To summarize, when creating consensus about the expected results of your digital transformation, you need to take into account the following factors:

  • Every business in the digital era becomes a (sort of) show business — a “tournament” of customer value propositions, business models, and brands competing head to head for customer attention and appreciation. This tournament is less and less “contained” in product category–related market niches, as digital offerings become more and more convergent.
     
  • Sustainable digital business strategies come either from outstanding customer experience leadership (a “top end” approach focused on customer value) or from significant share and influence over an attractive business ecosystem (a “bottom end” approach focused on collaborative business ecosystem platforms).
     
  • Continuous innovation becomes an essential digital business capability and should be considered a hygiene factor, not a differentiator. In top-end strategies, the critical innovations are related to customer experience, customer value propositions, and business models of customer engagement monetization. In bottom-end strategies, the innovations are related to operations and improved “collaboration architecture.”
     
  • In markets shaped by extreme uncertainty, you need to manage a portfolio of options. The casino always wins, so the more opportunities you can afford to own and test, the more likely you are to win.

Notes

1 The concept of “long tail economics” is rooted in broad academic research and was compiled and popularized by Chris Anderson in his publications. Anderson describes the nonlinear patterns in various niches of the media industry, arguing that digitization of content, digital distribution channels, and consumeri­zation of technology provide new opportunities for profiting from niche offerings. Anderson’s prediction that Web 2.0 would act as a “digital Robin Hood,” moving profits from “blockbusters” toward “long tail” niche offerings (extrapolated to other markets transformed by digitization of relationships, processes, and services) proved to be wrong, which Anderson finally admitted. Nevertheless, the long tail pattern appears to be a powerful phenomenon that affects many aspects of the digital business environment. Why this is the case can be well understood by studying the work of De Vany.

[For more from the authors on this topic, see “All the World’s a Sound Stage: The Digital Transformation Journey in the Era of Hollywood Economics.”]

About The Author
Borys Stokalski
Borys Stokalski, a Cutter Consortium Senior Consultant and partner in the digital business design studio RETHINK, is a seasoned advisor, manager, and investor with over 25 years of experience in building and managing one of the leading consulting and IT solution implementation companies on the Polish market, recently acquired by a European Top 10 software integrator. Today, Mr. Stokalski remains an active advisor and investor focusing on the… Read More
Bogumil Kaminski
Bogumil Kaminski is Head of the Decision Analysis and Support Unit at the Warsaw School of Economics and Adjunct Professor at Data Science Laboratory, Ryerson University, Toronto. Dr. Kaminski has authored over 50 research articles on theory and business applications of prediction, simulation, and optimization methods. During the last 15 years, he has delivered over 100 data science projects for the largest Polish corporations. He can be reached… Read More