An organization’s future success depends on their decision makers’ ability to anticipate changes and disruptions in the marketplace. But how do you get information about tomorrow today? How can your decisions today account for tomorrow’s uncertainty. Sensing the faint signals that provide a glimpse of our evolving future is never an easy task. Nor is it foolproof. An even trickier job is sorting out false background radiations masquerading as information, from the true signals. There has been a mushrooming of offerings in the past decades built around on divining the future. Most have evolved as offshoots of academic research groups. Stanford Research Institute (later SRI International) is a pioneer in seeing into the future and one reputed for developing some of core futuristic technologies that have today become common language and embedded into our daily lives. Martin Schwirn, author of a new book “Small Data, Big Disruptions” works for Strategic Business Insights. SBI is the   former Business Intelligence division of SRI International that has worked with clients on opportunities and change  since 1958 to help identify and map new opportunities based on emerging technology and market insights. SBI focuses on seizing information opportunities that exist between the moment you sense early signs of emerging disruptions and when it becomes public knowledge to capitalize on. He introduces a brand of the futuring methodology, called Scanning. Scanning offers a four-step process for capturing and analyzing information from a company’s external environment, helping decision makers foresee coming changes in the marketplace:
  • Filter vital information from an avalanche of data.
  • Identify what matters most to you and your organization.
  • Prioritize the crucial changes that will shape tomorrow’s marketplace.
  • Initiate strategies that move you from vulnerability to preparedness.
Scanning uses brushstrokes, not to create a perfect picture of tomorrow, but to develop insights into the way circumstances, technologies, consumers and businesses might align to create markets. It makes the initial sketch, which evolves into a painting with emerging data on certainty.

Becoming aware of the world is the first step.

Topics and events that haven’t entered our active conscious radar, and yet have been picked up on our keen peripheral vision, have the potential to manifest themselves as factors of future uncertainty within the present business planning context of organizations. A Scanning type method often helps identify them.

The next challenge is assigning meaning to changes and disruptions.

This is quite another thing.  Identifying a laundry list of potential future trends may create quite a pile of signals. That makes the step vulnerable to the same challenges of poor signal-to-noise ratio as we have experienced in tuning AM/FM broadcasts on our radios in the past. More recently, this is the core challenge data scientists aim to resolve in applications related to deployment of artificial intelligence technologies. The task of finding those signals that matter to our organizational vision and future success must be taken as seriously as doing the baseline environmental analysis.

Equally important are choices made to filter out background noise.

Making good choices to discard, clarify or sharpen signals efficiently and lead us to a fruitful visioning session within a period of deliberation. On the other hand, lingering too long on ambiguous signals (or being lost looking for that needle within a large haystack) risks diluting the goal of convergence, and prolonging the period of confusion among senior management, seriously jeopardizes or even leads to postponement of critical strategic investment decisions. It is this efficiency of separating the true signal from background noise that proves the difference between an effective futuring process and a less successful one.

Avoid the trap of false positive signals

A specific early signal from the past provides an interesting and humorous anecdotal evidence of information to watch for as one sifts through positively evolving signals. Criminals are often early adopters of new technology, since they have a strong incentive to be innovative in that way. But that doesn’t mean the technology itself is the problem; new discoveries and their applications are inevitable. In the late ’80s, criminals were early adopters of beepers in the 1980s. This snippet from a July 1988 Washington Post report describes it – ” When a drug dealer is in trouble, he sometimes dials 911. But he isn’t trying to reach the police. Instead, this message is sent to a drug courier wearing a beeper that displays messages dialed from a phone: 911 means the police are closing in. About 6.5 million beepers are in use in the country, according to officials, although it is difficult to estimate what percentage is used for drug trafficking. Federal narcotics agents estimate that at least 90 percent of drug dealers use them. U.S. Drug Enforcement Administration officials said that beepers, which have been used by bookies and cigarette smugglers, were introduced in the drug market about five years ago by Colombian cocaine organizations. Although paging devices, or beepers, have grown in popularity throughout the labor force – doctors, delivery people and journalists often use them, they also have become a staple in the drug business, posing fresh problems for law enforcement and threatening to tarnish the image of a booming high-tech industry.”

Doing environmental scanning the right way identifies key mosaic pieces that point to evolutionary dynamics of a certain future.

The author appears challenged to provide a clear path forward here. This book is replete with examples repurposed from well-known past business school cases and those used in other contexts. As with most “disruption” examples in the book (visible post facto), using them to make the case for a method to evaluate futures doesn’t quite convince the reader of its value, that future outcome being already well known widely. On the other hand the author’s situation is quite understandable. It is certainly a challenge to demonstrate the power of this futuring process by identifying key uncertain trend signals of the future, and then observing them play out as a certain future, all in the same time-frame of the present. Therein lies the absurdity. How does one navigate this?

Identify some cause-effect relationships between narratives

One option to do this may be by identifying and fleshing out cause-effect or correlational relationships between identified narratives. This brings us to the point of using broader narratives to describe each signal rather than short specific statement of facts. To acknowledge that these signals to the future are still ambiguous within our present time-frame. Also to acknowledge that some or many of these signals may well not play out as we expected, or even turn out to be downright false. Identifying these cause-effect relationships require that narratives (while ambiguous representations of the future) must be worded precisely enough so as to separate them from others in the box. As things progress, futuring workshops often see groupings of narratives over time, as new information presents itself to emphasize such relationships. Another benefit of mapping such cause-effect relationships is that it forces futuring teams to deepen their quality of research and insights into each signal/narrative identified, and leverage the knowledge & experience of subject matter experts. Martin Schwirn shares other important insights in his book. He emphasizes the importance of casting a wide net while gathering raw materials before filtering them and to discern the faint signals to the future. Having good peripheral research vision is a very strong skill-set here. There is place for subject specialists here, but there is an equally important leading role that generalists must play in helping connect information-dots and developing the most effective narratives, during the process.

The difference between complex futures and contrasting futures.

In helping us make the case for this futuring methodology, he discusses an important difference between complex futures and contrasting futures.  While one potentially lends itself to big data approaches for resolution, the other necessarily relies on small data. While one is about perfecting the outcome as it existed in the past – repeatable, predictable, actionable in the short term, where looking at huge historical data sets certainly help clarify signals from the noise very efficiently and cost effectively, and with an accuracy and breadth the human brain could not handle. The other is about peering into a foggy road ahead, armed with robust conceptual aids to sharpen focus, and to put just enough boundaries around the scope of vision to avoid creating scenarios that distract from the planned outcome of futuring sessions. He points out how big data is not a suitable approach to evaluate potential futures, when dealing with forward looking uncertainty. Why use of big data has the missed the signal to many profound environmental changes that affect organizations. The author also rightly emphasizes the criticality of involving multidisciplinary teams. Scanning requires organizations to lend their best informed experts to participate in the generation and evaluation of futures narratives. There is place for subject specialists here, but there is an equally important leading role that generalists must play in helping connect information-dots and developing the most effective narratives, during the process.

Evaluate Trend Signals along Impact and Emergence dimensions

This is a significant insight. Generating many early signals and narratives naturally leads us to the need to manage them in a hierarchy in order to make sense and prioritize them for requirement of the organization. He proposes an objective way to do so using clear metrics and criteria. While Impact may be easier to assess in somewhat quantitative terms, using known financial or operational measures. Qualifying the Emergence requires an assessment of its relative uncertainty in playing out as well as the period over which this may happen, a qualitative skill. We also observed the book left a few areas wanting. It makes passing references to some evolving significant technology trends that are in midst of creating the most profound impacts on the way we live, work, manage our business and (in some cases) even how we think. The potential of technologies such as the internet-of-things, artificial intelligence, robotics, intelligent cities, cryptocurrency, virtual reality, gaming, evolution of metaverses, and many others that are still playing out their disruptive potential. However the reader does not quite come away with any significant understanding or insight into how and why the potential of these technologies are important narratives in our presently evolving futures. Barring passing mentions of the terms, the book does not appear to have leveraged any deep research or subject matter expertise for interpreting those trends. [ Author’s note: I may carry a personal bias here. My firm ArcInsight Partners specializes in studying technology trends such as industrial internet of things, evolution of intelligent cities, artificial intelligence applications and autonomous manufacturing. It carries out deep industry research and supports clients in making critical high value high impact business decisions that concern its mediun to long term future – assigning relevant market trends and weighting them for business units, strategies for taking new products/services to market, identifying acquisition targets, strategies for monetizing new business models, even providing interim strategic leadership roles for their internal planning teams. ] The book stops shy of examining the profound impact on our society and our environment brought on by fast evolving technology. What are the imperatives that global shifts such as the recent global socio-political protest movements and rapid climate change events bring into the futuring process. Could they be harbingers of profound shifts? It misses the opportunity to walk the reader through the experience of a futuring session, how some of today’s strong contemporary trends that are sure to feed into signals for our still evolving future. , how an assessment of narratives are organized to paint a future. Perhaps even make few bold predictions about the future, standing in the present. Knowing well that many do not play out as expected. It makes a weak attempt to acknowledge the possibility that companies act to shape futures (as it emerges), as much they adapt to them. Large successful transnational corporations and mega multilateral organizations cannot afford to rely on an exercise of future-generation tools as their only risk management tool. They are the most vulnerable to generational shifts, and consequently deploy a plethora of tools and risk-mitigation techniques to manage the future. Successful companies are increasingly grabbing a bigger share of the future signals by investing in corporate venture capital funds, in order to turn those signals into a portfolio of experimental businesses and venture investments some of whom it expects to fail. The failures would be their greatest success in generating verifiable data to identify and filter signals.

Where should futuring teams reside within a complex enterprise?

How does one know a Scanning session has been successful? How does a business enterprise make the case to have its futuring thinktank as a separate organizational entity? What milestones indicate progress towards progressively improving interpretations of the future? These remain unaddressed questions. Without some clarity on these questions, the task of futuring inevitably returns to its small corner within the corporate strategy fold. And as strategists go, they are sticklers for evidence, quantification and actionable steps. The very things that may be stumbling blocks for Scanning as a stand alone methodology. We look forward to Martin Shwirn’s follow-on discussion that might go deeper than cursory explorations of future narratives identified in the book, especially covering those those yet to play out entirely. Perhaps it would delve into specific anecdotes and cases the author experienced directly as practitioner. These we believe could certainly make an exciting reading journey of exploring hidden signals to the future all around us, and make a few bold predictions of how they might unfold within our lifetimes.