Why learning is the only sustainable response to the increasing pressures of the Big Shift

In 2005, just six years before declaring bankruptcy, Borders was the second-largest book retailer in the world. Unfortunately, the company decided to invest heavily in physical stores just as the Internet was redefining commerce. In 2011, around the time Borders filed Chapter 11, Netflix was at the top of its game with a stock price moving steadily upward. Then, sensing the trend toward online streaming, Netflix attempted to hasten the transition of its customers to this new model, announcing price increases in July and a spinoff of the DVD mailer business in September. Customers weren’t happy, and analysts weren’t impressed, forcing the company to retract its plan just a few weeks later. Stock price fell from a high of $298.73 in early July to end the year at $69.29. For Netflix, this was a temporary, albeit painful, blip; by the end of 2013, the share price was at $188, and by March 2014, it reached $450.

This tale of two companies highlights the pitfalls of responding, or failing to respond, to the mounting performance pressures brought by the near-instant communication, rapidly changing technology, and empowered consumers that characterize the Big Shift. Decades-long trends, led by changes in public policy and the exponential cost-performance improvement of digital infrastructure—computing, storage, and bandwidth—are fundamentally altering the business environment across all industries. This infrastructure is not just bits and bytes, but also institutions, practices, and protocols that together organize and deliver the increasing power of digital technology to business and society.

The impact of these changes can no longer be ignored.

We quantify the trends and impacts of the Big Shift in the Shift Index. This year, we explored the most relevant and thought-provoking insights from the data in a six-part series intended to help executives translate data about pressures into positive action: Make workers more passionate, deliver greater impact with fewer resources, and find opportunities by embracing contradictions.

In the 2013 Shift Index, the unprecedented layering and rapid proliferation of new technologies, new materials, and new ways of working enabled by advances in digital technologies signaled that the pace of change and disruption is accelerating. We discuss the opportunities and risks inherent in these multi-layered innovations in From exponential technologies to exponential innovation. To turn the resulting pressures into opportunities, organizations need to be flexible and able to learn and improve from competitive challenges. Cultivating and hiring the right kind of talent can help. In Unlocking the passion of the Explorer, we see how workers with passionate dispositions engage in knowledge flows in order to solve challenging problems and to develop new skills—this behavior can radically improve the performance of the individual as well as the organization.

Many companies haven’t figured this out yet—they are still applying linear models and practices to an exponential world and failing to realize the potential resident in the workforce. The declining performance results we discuss in Success or struggle: ROA as a measure of true business performance is evidence of this mismatch and will only get worse if organizations don’t adopt new mindsets, models, and practices. Borders missed the direction technology, and its customers were moving. Netflix understood the direction but, initially, missed the preferences of their customers in the present. Hampered by fixed assets, Borders was unable to adjust to new information. With minimal physical investment, Netflix was able to gain immediate feedback and respond quickly.

By definition, the Shift Index doesn’t change dramatically year to year. Yet the updated metrics presented in The burdens of the past revealed a surprising discrepancy between the way individuals and institutions are benefiting from technology. The ability to participate in and learn from knowledge flows, often through technology, will be critical for success for individuals, organizations, and ecosystems. While institutions are held back by outdated structures and practices that limit learning and performance improvement, as consumers and creative talent, individuals have more freedom to embrace technology. As a result, we are capturing value for ourselves, but at the expense of institutions.

The Shift Index paints a picture of an increasingly complex world, one that has many moving parts and is full of contradictions. By trying to understand how both sides of a contradiction can be true at once, rather than to resolve it, an organization may be forced into new action or practices. In Coherency in contradiction, we examine how engaging with contradictions can actually catalyze learning and performance improvement.

The pressures for firms and institutions trying to navigate the Big Shift are immense. But, as we explore in Lessons from the edge, there are also opportunities for transformation and renewal as we rethink how institutions relate to and learn from the individuals they serve.

Why do we focus on learning rather than, say, strategies for taking advantage of mobile, cloud computing, social media, or the Internet of Things? The world described by the Shift Index is one where disruption happens fast, much faster than we might think possible. Prediction and forecasting can’t keep pace with the changes in the world around us. Yet, the 20th century model for mobilizing resources hinged on prediction, so many entrenched practices revolve around forecasting and pushing resources to deliver to forecast. Optimizing these misaligned practices is an exercise in futility. The continued decline in firm performance (ROA) reveals that decades of optimization have yielded only fleeting advantages and bring firms no closer to sustainable performance improvement. This is where knowledge flows come in. Participation in knowledge flows can generate new insights and practices and improve performance in ways that also yield learning and new capabilities.

This thinking extends from the individual up into the organization and beyond, into the ecosystem. Not just how can we learn, but how can we learn faster? We’re still early in the Big Shift, but if we can figure this out, we create an environment of increasing returns, expanding opportunity, and more value for everybody.

So how did Netflix come back? The easy answer is that Netflix was willing to admit a mistake. Of course, the business already depended on learning constantly from the customer, so Netflix benefitted from rapid feedback, no less valuable for being negative. In the years since, Netflix has continued to build the capabilities to use technology to learn more—about viewing preferences, content stickiness, and social influences—and more quickly, from the customer.

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