I’m a fan of the logic model because it emphasizes outcome KPIs that monitor impact rather than output metrics that track activities. I also like strategy maps because they are simple visualizations that force scorekeepers to recognize multiple points of view (aka perspectives).
A few months ago, I combined the two ideas while working with a software team to design KPIs for a product launch. The traditional measures of units sold, market share, and revenue do a good job of measuring success from a vendor’s perspective. However, just because software is sold or even installed doesn’t mean that it’s used, and just because it’s used doesn’t mean it adds value. We needed to think about the customer’s point of view.
Good metrics sometimes come from better metaphors and, in our case, we settled on the consumption of software. The analogy with eating was intentional. Humans don’t eat all the food that they purchase. Sometimes they eat large meals and sometimes they just want a small snack. Eating with a group at a restaurant is a different experience than eating alone at home.
Since we expected people to consume (use) software in different ways, we recognized that we needed to sell it in different ways as well. Following the food theme, stores became our analogy for sales representatives. The warehouse was best for larger purchases when the customer wanted to stock up on products, especially ones with longer shelf lives. The warehouse could also distinguish itself with a larger selection and a better return policy. We also needed specialty stores to support less common or newly launched products that required specialized functionality and deeper domain knowledge. For example, it’s unlikely that the big box retailer knows as much about a music amplifier as the specific electronics manufacturer outlet. As a third sales channel, we debated creating an on-line store to act like a convenience store: drop-in purchases during extended hours and small snacks instead of main meals.
How would we know if customers who purchased software from our specialty sales reps were actually using what they bought? While it might be tempting to just ask the customers, we decided that a repeat purchase of the same item was a good proxy metric. People were unlikely to buy the same specialty item from the same specialty outlet over and over again unless the product was actually used and fit their needs.
Thinking about the impact from the customer perspective forced us to segment our audience into multiple consumption patterns. It also reinforced that the default metric of units sold was inappropriate for our specialty store audience. The group launched their new product a few weeks. I’m looking forward to seeing if our consumption metric works.