3 Steps to Find Lead IndicatorsDecember 9, 2014 by Stacey Barr
Lead indicators, to some, are the holy grail of performance measures. They are mysterious, difficult to find, and yet upheld as the ideal and most treasured of performance measures or KPIs. What exactly are they, why are they valued so highly and why are they so elusive?
Humans have an obsession with the future, and in particular, predicting it. We forecast, we model, we extrapolate. Of course, it’s little more than guessing.
Patterns from the past can give us clues about the future, but we have to make lots of assumptions about how conditions in the future will shape those historic patterns.
Lead indicators aren’t the same as forecasting or extrapolating.
We’re not using historic data about a measure to predict how that same measure might behave in the future. It’s not the same as using historic patterns in staff turnover to predict future staff turnover.
A lead indicator is a measure that suggests how another measure, the lag measure, might behave in the future.
If we want to predict future Staff Turnover we could look to other measures that have a known impact on Staff Turnover. For example, we might look to an Employee Engagement Score, or measures of new recruit satisfaction with their work or with their manager or with their coworkers.
These results can predict Staff Turnover because usually they start turning down well before people decide to leave. There’s a time lag. So a lead indicator has a cause-effect relationship to the lag measure you’re interested in predicting, but it’s a cause-effect relationship with a time lag. And they give us, therefore, the power to change things now, to influence the future we want.
You can guess or hypothesise what the lead indicators might be for your lag measure. But the best way is to use data to confirm the strongest relationships, and the size of the cause-effect time lag. Here’s the process:
Step 1: Check the research for known explanatory factors.
Research to find out if anyone else has established a list of factors that do have a relationship with your lag measure. For example, if your lag measure is Staff Turnover, you’d read articles from HR journals and magazines to find out if anyone has already tested the factors that most affect the likelihood of staff leaving an organisation.
Researching is important, because it will save you lots of time you could otherwise waste in chasing very weak potential lead indicators, should you just brainstorm them.
Step 2: Check your business processes for new potential explanatory factors.
Flowchart the business process that your lag measure relates to. If your lag measure is Sales Revenue, then you might flowchart both the marketing and the sales processes to identify potential steps that have a significant impact on sales revenue.
For each of the early process steps, you’d describe the result that has the impact. For example, in the marketing process you might decide that your content creation step impacts significantly on Sales Revenue. You might describe the result that has the impact as ‘relevance of our content to the target market’. You could measure this result in two ways: Average Visit Time on Content Pages, or the Email Newsletter Open Rate. These two measures are potential lead indicators.
Using your business processes naturally helps you find lead indicators because the early steps in a process occur earlier in time than the lag result does. But beware, because sometimes powerful lead indicators can lie in other business processes that don’t directly produce your lag result. You could imagine without much difficulty that if the service delivery process consistently over-promised and under-delivered, Sales Revenue would eventually nose-dive alongside the organisation’s reputation.
Step 3: Choose the strongest of your potential lead indicators.
When you’ve got your list of potential lead indicators, you then gather data for these and look for the strength and time-lag in their relationships with your lag measure.
Perhaps you’ve listed several potential lead indicators for your lag measure of Customer Retention Rate:
- Speed of Resolving Customer Inquiries
- Frequency of Customer Contact
- % of Customer Contacts Made by Assigned Customer Relationship Manager
- Days Between Broken Promises
Gather together the data for all these potential lead indicators and for the lag measure and start plotting. A scatter plot will help you see the strength of the relationships, and a time series plot will help you see the time lags.
While there is some science and method to finding lead indicators, there’s also a touch of art, too. It takes practice and experience to build the wisdom to find very powerful lead indicators. So start practicing!
Do you have lead indicators? What are they, and how did you find them? How well are they working?
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