Over the past decade, advances in digital analytics have transformed the way businesses operate.
NB: This is an article from McKinsey & Co
From marketing and pricing to customer service and manufacturing, advanced analytics is now central to many corporate functions. The same, however, cannot be said for strategy—at least not yet.
While strategy development will always require creative and thoughtful executives to set aspirations and make bold choices, analytics tools can give you an edge. Advanced analytics can be used to accomplish the following:
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- Reduce bias in decisions by calibrating the likelihood of your strategy succeeding before you allocate resources.
- Unearth new growth opportunities by complementing traditional brainstorming methods to reveal hidden pockets of growth.
- Identify early-stage trends by painting a real-time picture of how your business context is unfolding so that you can trigger big moves before your competitors do.
- Anticipate complex market dynamics by generating proprietary insights about the combined impact of myriad forces.
Each of these applications can sharpen business leaders’ views of the competitive arena and how they can position themselves to win. But that requires putting advanced analytics front and center in the strategy process.
Reduce bias in decisions
When Daniel Kahneman and Amos Tversky observed that even experienced planners tend to underestimate the cost and time required to complete projects, they termed the phenomenon “planning fallacy.” They argued that this tendency results from people making forecasts based on the specifics of the case at hand combined with their personal experience and intuition (commonly referred to as “the inside view”), without taking into account the distribution of outcomes of similar cases (“the outside view”). As a result, many forecasts are overly optimistic. The two collaborators went on to propose a corrective procedure called “reference class forecasting” that involves complementing the inside view with data on real-world outcomes, or “base rates,” from a reference class of similar cases.
In the past 20 years, the use of this technique has gathered impressive momentum, with hundreds of articles highlighting the methodology’s application in both academic and practical settings. To date, such calibrations have been limited largely to the field of project management, but forecasts made during strategic planning confront similar challenges. Strategic plans, too, involve estimating the future costs and benefits of investments, making an outside view just as valuable in informing those decisions.
In our recent book Strategy Beyond the Hockey Stick (Wiley, February 2018), we introduced the idea of using data analytics to bring an outside view to strategy. By embracing the outside view, you can estimate your strategy’s odds of success before you allocate resources to that strategy. For example, if your target is to grow economic profit by $100 million per year in the next decade, would it not be helpful to know that only 35 percent of large companies managed to achieve that over a decade? And if we told you that companies which implemented programmatic-M&A strategies and reached the top quintile in productivity improvements were 1.5 times more likely to achieve that profit target, would you not consider prioritizing those two areas in your strategic efforts (Exhibit 1)?
