This is the how you can implement the first step. The concept is that the importance of the decision should dictate how many critical data points you need before taking an action. For small decisions, you need just one key metric, for medium-sized decisions, three metrics, and the most important decisions need nine pieces of quantitative support. This formula yields the decision-making curve:
The “1-3-9” rule applies to organizations of all sizes; however, determining the importance of a decision is relative. Opening a new product line for a well-established market leader is a much smaller decision than for a new start-up. Make-or-buy incremental analysis takes on a whole new meaning when you are realizing incremental gains in one year versus two years and you have yet to at least break even on your P&L.
Once you’ve determined the magnitude of a decision for your organization, adhering to the decision-making curve will keep you from analyzing a decision from every possible angle, constantly second guessing yourself, and ultimately missing out on a time-sensitive opportunity.
While it’s a straightforward solution, the power is in its simplicity. Comment below on the success you have when implementing the decision-making curve. In the meantime, find out common misconceptions about analysis paralysis by keeping an eye out for one of my upcoming blogs: Analysis Paralysis: Mythbusters