Much of our organizational reporting today looks only at the past. It shows us what happened in the past month, most recently completed quarter or year-to-date. This information has value, but in many cases it would have more value if it helped us look in to the future. Often, when decision makers look at past information, they use it to estimate a likely future state.
For example, a CFO looking at the following chart assumes that $2.676M represents three-quarters of the total fiscal year sales:
Using that logic:
2.676 / 3 * 4 = 3.568
So, the CFO will conclude that the organization is likely to exceed the sales goal by $18K. The sales department can coast to the finish.
But, what if we add some intelligence into our key performance indicator (KPI) to allow it to make a better prediction of the fiscal year-end value based on past performance. Suppose the sales of the organization for the past three completed fiscal years looks like this:
We can see that sales always seem to decline in Q4 of each fiscal year. Therefore, the total sales through the first 3 quarters of the fiscal year is not likely to be three-quarters of total fiscal year sales.
We can use this information about past sales to build an estimation of total fiscal year sales right into our KPI. The following ratio will give us an educated guess as to the fiscal sales for Q4:
Adding this calculation to our KPI we come up with the following:
The CFO can now clearly see that, rather than exceeding goal, the sales are likely to come up $40K short of the goal based on sales performance in the recent past.
In this case, the forward-looking component of the KPI was created using some very basic trending knowledge. No complex data mining or predictive analytics was required. Of course, those types of advanced algorithms could be used to provide a more accurate prediction of the future, but they are not essential when simple trends can be readily discerned.
In other cases, information that is already know about the future can be used to predict a dependent value. For example, the number of work days and scheduled equipment maintenance can be used to predict production capacity. Scheduled vacation days in a period can be used to predict personnel needs.
Adding this type of simple predictive capability to a KPI can provide decision makers with a powerful tool to help them plan ahead and therefore help an organization ultimately succeed.