In a perfect world, there is no error — the ε in the Six Sigma breakthrough equation. Unfortunately, Six Sigma managers are faced with managing risk. The input Xs and transfer function f would completely describe the output Y. In this world, weather forecasts would be exactly right, financial stock charts would display perfectly smooth and predictable trends, and a card player’s selected strategy would determine the outcome of the game.
But the world isn’t perfect. Every system, scenario, and situation has some amount of uncertainty and risk. Although the f(X) term in the breakthrough equation represents exact determinism, the ε term captures all this uncertainty or risk. It expresses the fuzziness around which the final answer always varies.
You must match risk to the business decision you’re making. In some situations, risk (ε) must be painstakingly minimized. In making go/no-go decisions for space shuttle launches, the control center painstakingly minimizes uncertainty in its temperature forecasts because a small variation in temperature can create more risk than the system can tolerate.
Other situations or decisions can tolerate much more risk. If the mission control director misjudges the temperature as he’s picking out his clothes on launch day, the fact that he’s overdressed or underdressed isn’t going to pose significant risk to the mission.
Business processes are exactly the same. Some require very tight risk control; others don’t. One of the arts of Six Sigma is knowing how much of the ε in the breakthrough equation must be reduced to fit a business decision. Six Sigma gives you the tools needed to quantify risk and know whether you’re making an accurate analysis or have succumbed to the ravages of the disease of analysis paralysis!
