Sep 24, 2020
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5 Lessons On Making The Leap From Big Data To Wise Decision Making (Part 2 Of 2)

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From his vantage point as someone who evolved from a collector of large amounts of data to a sensible decision-maker at high levels of commercial and government few are more qualified than Vince Barabba to offer guidance on how to bridge the chasm that often separates big data and wise decisions


Vince Barabba VINCE BARABBA As I mentioned in the first part of this series Barabba s new book Wise Decision Making: During the Systemic Use of Knowledge and Imagination (his sixth book) explores how all participants in a decision process can (and must) work better as a team. Success depends on not just great data but also on how well the enterprise coordinates its efforts to realize benefits which are more than the sum of individual contributions


Here are a few key lessons I drew from Wise Decision Making: 1. Get behind the curtain. Wise Decision Making VINCE BARABBA Behind every enterprise are people who actually design and make things and who ultimately translate market intelligence into products. These are the people who create value — everyone else just shuffles it around


When Barabba led market research at Kodak it was the crowd of chemists and scientist who knew what could and couldn’t be done with film chemistry. At General Motors where he led strategy development it was the engineers who could translate customer feedback into engineering design requirements. Who are the wizards behind the curtain on your organization? PROMOTED Office Depot OfficeMax BRANDVOICE | Paid Program
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A New Partnership Aims To Help If you re in the business of collecting and leveraging data make sure that you re partnering directly with the scientists engineers designers and others who can use it. The enterprise needs data infused with their knowledge and imagination to improve products and services


Otherwise the models built and the data collected maybe worthless. (This challenge is consistent with what Tom Warden an expert on the use of big data in insurance described to me as one of the biggest mistakes his industry: too often data scientists are clueless about how the business makes money


) 2. Understand the operating design of your enterprise. Alan Kay s dictum that Context is worth 80 IQ points is especially relevant for wise decision making. The most important dimensions of context is what Barabba calls the operating design of the enterprise. As depicted in the following figure there are a range of possible operating designs


A Range of Operating Designs SOURCE: VINCE BARABBA Does the enterprise operate in an atmosphere characterized by relatively slow and evolutionary change for example? That puts it in a make and sell operating model where success depends on economies of scale and correctly predicting demand. The automobile business to illustrate used to be a prime example of the make-and-sell operating design


Or to demonstrate any other end of the spectrum does the enterprise operate in a very complex and uncertain environment with imminent disruptive opportunities and challenges through technology regulation demographics etc. ? Success in these circumstances requires an anticipate and lead operating design where the enterprise needs to reinvent itself according to both customer s articulated and unarticulated needs and lead customers there


Success in the future auto business given the possibility of connected electric and/or autonomous vehicles and millennials changing attitudes towards car ownership depends on the anticipate-and-lead operating design. 3. Never say The Model says. Remember that no model can accurately capture the complexity of a genuine situation and therefore can never provide definitive answers


Wise decision making depends on analyzing and interpreting model results into valid conclusions. The way to aid reach wise decisions is to deliver robust findings while being clear about how the analysis was done and what its limitations are. The way to put the whole enterprise at risk is to blindly follow the findings


The way to discredit the whole analysis effort is to rely on what The Model says to justify an idea. 4. Ensure people who will implement the plan are eager about developing the strategy. How often have you seen talented strategy teams work hard to develop good plans and then present them to a management team that was too experienced and comfortable in the old ways of doing things? Too many notes Barabba with the outcome that many strategic plans become not being implemented


How to avoid this outcome is to reengineer the method making process. Strategy teams should not make plans; instead they should guide the process that engages those responsible for reaching a methodology allocating resources and implementing the associated process action. Otherwise it will never be their strategy—no matter how good


The method team s job is to give you the relevant information track underlying assumptions and confirm progress. 5. Don t just close the loop; do double-loop learning. In Billion Dollar Lessons Paul Carroll and I documented how numerous strategic failures may need been averted if the principals had followed the easy rule of creating core assumptions explicit and knowing when those assumptions had changed


Barabba vividly illustrates how this happened for Kodak. In the mid 1980s Kodak s market researchers led by Barabba rightly determined that digital photography couldn’t compete with film on numerous key dimensions including quality cost and simplicity of use. Their research traced those findings to express technological factors and forecasted when and how those factors might change


Unfortunately those findings guided Kodak strategy for decades—long Barabba had left and long after the underlying factors were no longer true. Kodak never closed the loop. In Wise Decision Making Barabba extensively illustrates the virtues of closing the loop—and the drawback of not doing so. He offers tools and examples about how to do it


He also shows how closing the loop is not enough. Instead he argues for the ability of what Harvard s Chris Argyris has come to name double loop learning. Closing the loop is necessary but only helps to detect and correct errors for the method in question. It doesn t help transfer learning around the organization


Double Loop Learning Double-loop learning encourages and helps the whole enterprise learn how to actively question and modify existing values norms processes policies and objectives. It’s a concept that’s very compatible with Doug Engelbart s ABC s of Innovation which I ve previously discussed. It’s the key to making a learning organization


Perhaps the wisest part of Vince Barabba s Wise Decision Making is that the writer doesn t claim to have a recipe for wise decision making. Instead he urges readers to benefit from his experiences and then reinvent his tools and frameworks to slot their unique circumstances. These five lessons are the ones that spoke to me; your opportunity is to find the ones most relevant to you


Part 1: Are You Making The Leap From Big Data To Wise Decision Making?

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