Skip to content

How Decision Intelligence Will Finally Change Decision-Making From Mystical To Mundane

Erik Larson Apr 11, 2022 10:31:01 AM
Decision Intelligence

Technology research and consulting firm Gartner, Inc. identified Decision Intelligence as a top strategic trend for 2022. Analyst Dr. Pieter J. den Hamer begins his detailed report with this call to action:

“To deal with unprecedented levels of business complexity and uncertainty, organizations must make accurate and highly contextualized decisions more quickly. IT leaders must create capabilities to rapidly compose and recompose transparent decision flows.”

Few would argue with the idea that businesses have an ever greater need to make better, faster decisions. However, the report has an underlying insight that portends the fundamental disruption of this most important leadership activity. The decision intelligence concept shifts the decision paradigm from the fuzzy, unmeasured realm of leadership to the concrete, measured realm of management.

In short, decision intelligence suggests that companies should treat decision-making just like any other modern business process. Decisions become first-class data objects and set the frame for understanding and improving business performance. As a result, leaders need systems to model and track how decisions are made, metrics to measure their performance and feedback loops to learn about and optimize the process.

In the report, den Hamer makes a distinction between three different types of decisions:

  • One-off strategic decisions like mergers and acquisitions.
  • Repeated managerial decisions like planning and resourcing.
  • High-volume operational decisions like customer service interactions.

Notably, he makes these distinctions for clarity, not to exclude any of these decisions from the need for transformation. He doesn’t give big bosses or the middle managers a way out because, as he says, “​​Increasingly, decisions at different locations and levels impact each other.”

From Mystical Decisions To Mundane Systems

The analogies for this idea are everywhere in business.

For decades, finance executives have used software systems to manage and track the precise numbers of budgets, expenses and revenues. For almost as long, it’s been business as usual for sales executives to start their day checking in on their CRM systems for critical deal progress and pipeline coverage. The digital transformation of marketing has even taken the most creatively fuzzy of business endeavors and turned marketers into tracking geeks who measure and manage almost every step in the marketing process.

Yet managerial decision-making, the most impactful business process of all, has resisted such systematization.

There is no system of record where executives can check in on the progress of pending decisions and outcomes of past ones. There are no ways to compare the performance of business units based on the quality of their decision-making processes or understand the relative power of data, intuition and experience. Incoming leaders have no way to learn from the weft and warp of past decisions, and outgoing leaders carry all of that tacit decision knowledge with them, leaving no trace behind.

Most decisions today are far better described as “unpredictable black boxes” than “transparent decision flows.” But, if Gartner is right, companies will be investing more and more in new technologies to change that.

Data, Analytics and Artificial Intelligence As Catalysts

As long as the IT industry has existed, new technologies have claimed “improved decision-making” as a primary value proposition. In particular, data, analytics and artificial intelligence technologies have purportedly provided decision-makers with first more data, then analysis and insights, and now recommendations. Yet nowhere in these systems, neither in the underlying data nor the user interfaces, can you find records and metrics about actual decisions.

The decision intelligence trend turns this situation on its head, building on these technologies to finally address the decision-making process as the fundamental frame of reference.

Transparently tracking and optimizing decision flows was not the most important problem when most companies lacked sophisticated analytics and insights capabilities, let alone artificial intelligence to help provide recommendations. Today, however, such technologies are largely in place, especially for analytics and insights. Companies must now measure how well those analyses and insights are used by the leaders responsible for making decisions and begin tracking the results to learn from the outcomes.

Tracking And Measurement Will Open Our Eyes

A groundbreaking study by Bain & Company found that business performance is 95% correlated with decision effectiveness. A GrowthAQ study showed that decision-makers only use 22% of the insights and recommendations they receive. Cloverpop research found that 98% of managers fail to apply best practices when making decisions, and their decisions fall short of expected results 70% of the time.

Those studies are important data points, but they were also labor-intensive one-off research projects. As companies begin to implement decision intelligence, those same types of analyses can be applied to specific business decisions and performance challenges in the regular course of business. For example:

  • What insights are most impactful when making brand positioning decisions?
  • Who was and should be involved in pricing decisions?
  • When should innovation investment decisions be made?
  • How are planning decisions linked most effectively to business goals?
  • Which data sources are used often, missing, or never used at all?
  • Where are the best points to speed up the decision-making process?

Companies that can answer and act on such questions will have a significant competitive advantage in the marketplace. And den Hamer believes this advantage will be enough to drive action, predicting that 33% of large organizations will begin implementing decision intelligence by 2023.

For every far-seeing business leader who’s struggled with today’s black box decision-making world, that change can’t come soon enough.