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Keys to unlocking great decision-making

Keys to unlocking great decision-making

by Aaron De Smet and Greg Jost

You can tell an organization has problems making decisions when you hear these complaints: The organization is “too complex,” possesses a “meeting culture,” or has “too much consensus.” “Too complex” can simply be code for “it’s too hard to get things done.” And while people often finger too many “cooks” as the culprit, we’ve seen matrix structures where, despite many people being involved, roles are clear, how things work is straightforward, and decision-making is fast and effective.

For agile organizations, getting decision-making right is critical since their foundation rests on an action-oriented decision architecture. The result: Organizations with high decision-making velocity and quality generate 2.5 times higher growth, 2 times higher profit and 30 percent higher return on invested capital, our research shows.

Still, decision-making is hard. An unclear or poorly defined process can trigger decision “churn,” where previous judgments are revisited; a “fog of accountability,” where no one is truly answerable; “death by PowerPoint,” where decision-making gets lost from too much information sharing; and bureaucratic governance.

We’ve identified three common myths that contribute to difficulties in decision-making:

Myth #1. You must choose between quality and speed.

Good decisions are often made quickly. Usually, it reflects a decision-making system designed to maximize engagement of the right stakeholders but minimize the number of decision makers, accelerate the entire process through decision execution, provide ruthless role clarity, orchestrate key points of collaboration, and streamline governance to keep meetings and approvals to a minimum.

Myth #2. Good decisions are easier using technology, big data, AI, etc.

While these can help, in many cases they don’t. In fact, more technology and more data can lead to information overload and analysis paralysis. Also, beware of big data and analytics creating a belief that decision-making can be entirely rational, thus taking emotion out of it. Emotion can be very helpful in determining what is good and desirable and what isn’t.

Myth #3. Applying best practices will improve decision-making.

In fact, most “best” practices are conditional. They are good in some situations and not others. Different types of decisions require varying approaches, and advice helpful for some decisions can be terrible for others.

What’s the key to unlocking great decision-making? As we advise in “Untangling Decision Making,” any organization can improve the speed and quality of its decisions by paying more attention to what it’s deciding. We recommend segmenting decisions into four basic types and applying a different set of best practices for each:

  1. Big bet: Infrequent high-stakes decisions that affect the organization broadly (e.g., mergers, acquisitions, big investments). In these instances, healthy debate among top team members is more important than data.
  2. Cross-cutting: Frequent decisions that affect multiple areas in the organization (e.g., budget allocations across products/regions, sales and operations planning, new product development). Clarity of process is more important than who gets the decision right.
  3. Ad hoc: Day-to-day decisions by individuals as part of their job (e.g., interactions with customers). An open and trusting culture with personal ownership and role and strategic clarity are more important than formal accountabilities.
  4. Delegated decisions: Day-to-day operational decisions made by a team or individual closest to the information vital to making the decision (e.g., deciding on regional or site level promotions, adjustment to local manufacturing operations). Here, clarifying delegation of authority is only half the battle; leaders need to learn how to empower and let go.

Recognizing these impediments to decision-making and targeting action against them helps improve the choices organizations make. In three forthcoming blogs, we will focus on different decision types and share tested approaches for ensuring the best results.