Decision-Driven Analyics

Looking for a purpose for your data? Think decisions first.

Are you turning to data to confirm your beliefs, or are you truly exploring the possibilities?

Data Culture
Data Strategy
Author

LiqC

Published

Tue, Mar 14 2023 10:00

Decision-Driven Analytics

Data-driven decision-making has become a common practice in modern companies. Despite the good intentions, the outcomes of analytics initiatives are often disappointing. The problem lies in the habit of treating data as a hammer in search of a nail. Time and again, the pre-ordained decision has already been made—perhaps based on intuition, or on what’s been sold to customers/investors, or some other desired view of the reality. Now the leadership turns to data for a nod. We must move forward and make progress, but sure, we’ll take a quick look at what we know.

The result? Preexisting beliefs, biases, and incentives are reinforced. Though important data gaps may be exposed, investing in better data or better data analysis never gets prioritized, because the end product of the data supply chain (the decision) is already at hand.

Bart De Langhe and Stefano Puntoni call for replacing data-driven decision-making with decision-driven analytics. It starts from a proper definition of the decision that needs to be made and the data that is needed to support or reject that decision.

To shift to decision-driven data analytics, a company should start by identifying the business’s key decisions and the people who make them, and finding data for a purpose. Leaders can take three steps:

  1. Form a narrow consideration set of alternative courses of action,
  2. Identify or gather the data needed to figure out which course of action is best
  3. Choose the best course of action.

As you retrospect on the decision that was made, this process can help separate the quality of the outcome from the quality of the decision.

“Decision-driven data analytics emphasizes the importance of asking questions. This approach draws attention to unknowns and the value of additional data collection and analysis. Companies and leaders who take this approach benefit by ensuring that analytics initiatives are tied to action, are focused on answering the questions that matter, and challenge rather than bolster executives’ beliefs about how the world works.”

Read the paper, watch the interview with MIT Management Review.

Also published on: LinkedIn