unprecedented data

Unprecedented? With Data, Analytics And Scenario Planning, There’s No Such Thing

This article was originally published on Forbes.com

Unprecedented. This word we all have been seeing and hearing a great deal lately is intended to encapsulate the enormity of surprise and the magnitude of change the world is undergoing at the moment. But it has another implication. It admonishes many of us who are too comfortable with our ignorance of history, too intellectually lazy to comprehend how one event deterministically leads to another, or too fixated on “riding the wave” to envision and plan for its eventual crash.

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Every occurrence and situation has a precedent. Unusual or uncommon? Certainly. However, we have experienced and recorded instances of pandemics and market crashes and inept leadership before. Indeed each occurrence is different, but much can be learned by gathering and analyzing the data from them, rather than just throwing up one’s hands in complete inattentive ignorance.

Alan Simon, author and managing principal of Thinking Helmet, observes how complacency can set in, especially in a long period of economic boom. He contends that “this leads to ‘unprecedented’ mega-events that aren’t actually unprecedented, and which might have been interdicted, at least in part.”

Take the Texas-based grocer H-E-B for example. Its own pandemic planning began back in 2005 when the H5N1 virus first appeared, and the plan was first executed in 2009 when the H1N1 swine flu surfaced. According to Justen Noakes, director of emergency preparedness, “We’ve continued to revise it, and it’s been a part of our preparedness plan at H-E-B ever since.” He says the first week of February they dusted it off and started working on step-one immediately. From hurricanes to pandemics, H-E-B has modeled potential effects of these potential major disruptions upon its supply chain, customer demand, and employee availability. When the situation warrants, H-E-B activates its Emergency Operations Center, which in addition to Noakes includes a director of government and public affairs, and even a chief medical officer and medical board.

Even when no specific precedent exists, human imagination can fill the gap. At the beginning of the 2008 financial crisis, BMC Software, then under the leadership of CEO Jim Beauchamp, devised a set of simple-to-understand, color-coded scenarios for the various directions the economy might head. A historically military tool dating back thousands of years, scenario planning imagines a set of “what-ifs” each triggering particular actions. Not only did this scenario planning enable BMC to respond quickly, even proactively, but it gave comfort and a needed morale boost to its employees.

While scenario planning enables a rapid sense-and-respond capability for businesses, the technique is designed to anticipate, not “see” the future. According to Kishor Gummaraju, the chief customer officer at Tiger Analytics, most forecasts have been built in a certain way, factoring in long term trends and averages. “Today,” he says, “all of those models are useless,” and that companies have scrambled to implement more real-time models which also consider proxies of business activity. Gummaraju believes this abrupt switch to more sophisticated forecasting will be here to stay, not a temporary one.

For too long, many organizations in the industries suffering today have been navel-gazing at their own data with little interest or ability to ingest the vast array of external data available.

Improved forecasting, however, requires broader, faster and deeper data, not just fancier models. For too long, many organizations in the industries suffering today have been navel-gazing at their own data with little interest or ability to ingest the vast array of external data available. With an estimated 10 million public “open data” sources, billions of websites with content ready to be harvested, thousands of commercial data products, emerging data marketplaces, and data to be bartered for from your business partners and suppliers, there is no excuse for ignoring the wide range of global economic factors and their impact on your business. A handy rule of thumb: For every one lagging indicator of past performance, your business should strive to identify at least two leading indicators of future performance.

So how can IT leaders support their organizations in shifting from being paralyzed by the unprecedented to catalyzed by the precedented?

  1. Help the business acknowledge that current forecasting models are likely broken and that continuing to rely on them may do more harm than good.
  2. Work with data and analytics experts along with data product vendors to identify external leading indicators so that new driver-based models can be constructed. Recognize that traditional trailing indicators like jobless claims may now be leading indicators.
  3. Identify the temporal and affinity relationships among the purchases of even seemingly unrelated products. This will be of more predictive value than ever before.
  4. Increase investments in identifying and developing digital versions of your products and services that eliminate or reduce manual, hand-on, and face-to-face requirements.
  5. Track and understand the evolving customer journey across channels. For example, continuing to separately report on online versus in-store activity increasingly will become ineffectual.
  6. Keep a close eye on customer sentiment and social consumer social media activity, as this will be a key bellweather for resumed and diminishing consumption in most sectors.
  7. Begin gathering multi-level (or “n-tier”) supply chain data about your suppliers’ suppliers to identify weaknesses or resumption of material availability. And expand the information you gather and analyze about alternate suppliers.
  8. Factor-in the effects of prior events like severe weather or other economic bubble bursts to improve forecasts locally and nationally or globally.
  9. Coordinate with the executive team and an economist to identify a range of economic scenarios and execution plans for each.
  10. Implement (then never disband) a formal crisis or emergency response team and operating model which includes key individuals from marketing, sales, finance, legal, operations, HR, public relations, and IT to coordinate these above activities. This team should be supported by experts in economics, data science, third-party data products, and data integration/engineering.

That said, the most capacious and enduring opportunities arising from this current global crisis, perhaps even “unprecedented” ones, won’t come from improved analytic models, but rather from new innovative business models and operating models. No doubt meant as a spiritual challenge but just as apropos in a business context, Vanderbilt University Chabad’s Rabbi Shlomo Rothstein observes, “We now have an incredible opportunity to reimagine the future and envision those wonderful new realities that we can’t usually see when stuck in the limitations of success, routine, and predictability.”