The first part of being smart is to be aware. Aware of what’s going well and what’s wrong, and how you are evolving. I’ll try to go over the most basic element of indicators, and how you can structure them.
Take a car manufacturer. For the business person, it’s important to know sales numbers, revenue, and overall customer loyalty. But those numbers can be meaningless and even counterproductive for a factory worker who is actually building the car. Yes, the quality of the cars affects the satisfaction of a customer, and thus impacts sales and consequently revenue. However, tracking that for the worker has little value in daily operations. Each car will take at least a few days to be finished and sold, and at least a month to show up on sales reports. Also, there are many other people involved in selling a car and providing assistance besides the worker. It will be hard, then, for the factory worker to know how he’s doing based on customer loyalty - also because there are many more variables at play. It’s much more important to know how fast he finished his tasks, or how many faults his work contained.
So how should one approach indicators for a given role? In the example above, we see that faults in the car production is a very immediate indicator of the performance of the company, whereas loyalty takes some time to be affected. We say that the number of production faults is a leading indicator and that loyalty ratings are a lagging indicator.
Dividing indicators into leading and lagging for each function to be analyzed is to me a crucial task of Business Intelligence.
Leading Indicators characteristics
Example of leading indicators for the performance of our car factory: speed at which the worker picks his screws to be bolted on to the car. Speed at which which he bolts each of them. Number of retries due to error. Number of screws needing fixing due to low quality work. Number of break pauses and time spent in break pauses. Again, these should be relative to a standard measure. Leading indicators mean that they improve before the system as a whole improves.
Lagging Indicators have the opposite set of characteristics
Example of lagging indicators in our car factory are number of cars produced, average total cost per car, customer satisfaction with cars, revenue for the factory (in case it’s tracked). Lagging indicators change after the company has internally improved.
We can establish finer levels between Leading and Lagging. Which means that between Performance and Outcome we can have other measures, like Productivity. Examples for the factory workers could be cars per hour, accidents per month, and throughput.
Both types of indicators are very important. Leading indicators are good to establish the root causes for improvement, and lagging indicators are generally about the outcome of all actions, and what investors want to hear. The most frequent mistake is to evaluate workers by their productivity (pieces produced per hour), when many times this process is not entirely under his control. Maybe the worker has to wait for parts to arrive, or part feeding varies greatly according to personel available and hour of the day.
It takes time to build a fair Indicator system that can motivate people into doing a better job, but it’s absolutely necessary if you want to consistently improve your business. Keep your leading and lagging indicators in check for an optimal and fair process.