Decision-making is happening faster than ever in our rapidly pivoting world. Tt’s apparent to ask: is one style of decision-making — git-driven or data-driven — now more effective than the other? In covering this topic, I pulled from interviews I’ve conducted with guests on the Strategic Momentum Podcast. Here’s what I found out.
For today’s business leaders, the old axiom “knowledge is power” should probably be amended to say “knowledge is power ONLY IF it reflects a strong understanding of real-time information, enables meaningful foresight, and results in prudent business decisions”. Okay, this is a mouthful but you get my point. More and more, companies are making significant investments in business intelligence systems and services to ensure that executives, line managers, and individual contributors alike have access to, can make sense of, and can act upon the most granular data relevant to their day-to-day operations. This data is analyzed and compiled in executive dashboards reflecting key performance indicators (KPIs) and used to update driver-based forecasts with the overall aim of providing proactive and precise support for critical business decisions.
Unfortunately, what often results is analysis paralysis…too many variables, not enough insight, and an inability to distinguish the forest from the trees. No matter how sophisticated or crude a company’s analytical capabilities may be, knowing what to focus on and what not to, ultimately determines success or failure. In a sense, simplicity is always best.
There may be hundreds of variables impacting a business at any given time but effective business leaders typically focus on only a small handful of key drivers. As any decent golf instructor will tell you, the best players limit their thoughts to two or three basic mechanics before striking the ball and rely on muscle memory to do the rest. Similarly, most successful business leaders will tell you that 20 percent of the key drivers produce 80 percent of the results. Knowing how to eliminate the other 80 percent of variables with marginal impact is critical to robust business planning and strong decision making.