Imagine this scenario: You are embarking on a weight-loss journey. You dust off the bathroom scale, make an effort to eat right, and begin to exercise regularly. At the end of the first week, the scale shows that you have lost three pounds. But have you really?
Suppose on the first day, you got on the scale fully dressed, including your shoes. On the last day, you stepped on the scale right after you got out of the shower, wearing nothing at all. Can you honestly brag to your friends that you lost three pounds on the first week of your new regimen? No. The only way to know for sure exactly how much weight you lose is to be consistent in measuring. In the case of weight loss, the easiest thing to do is to measure naked.
Businesses like yours face the same challenge when evaluating performance; unreliable measurements can be a major issue. Companies that want to measure progress accurately need to compare apples to apples. Accounting systems and other systems of data collection—both quantitative and qualitative—must be set up so that they consistently measure from the naked level.
As a decision-maker, you also need to be able to analyze changes and accurately assess their causes. For example, perhaps you initiated a new advertising campaign last year and saw a substantial increase in sales. However, you might be forgetting that you also replaced one of your sales reps when he or she retired. Did your higher revenue really come from the advertising, or was the new salesperson responsible for part of that change? There might even be other factors that you have not considered.
Consider a seasonal business, such as a Christmas boutique, which would naturally do its highest volume of business in the fourth quarter, a moderate amount of business in the first quarter (largely due to during postseason clearance sales), and the least business in the second and third quarters. Comparing one quarter’s performance to the previous one is not logical. Furthermore, what if you hire a new sales associate in May and note at the 90-day review that his or her sales were far lower than those of the previous associate you hired? You need to consider that the previous employee was hired in October, at the beginning of the peak season.
While these are simplistic illustrations, rest assured that other similar variables exist that are far more complex and may avoid detection by employees who are not trained to look for them. A consultant who is an expert in performance measurement can view your data with fresh eyes and strip that data down to get reliable analyses that will truly reflect the position of your company.