Key performance indicator (KPI) is, arguably, one of the biggest buzzwords of the decade. According to Investopedia, KPIs are “a set of quantifiable measures that a company or industry uses to gauge or compare performance in terms of meeting their strategic and operational goals.”
For some individual practices—financials, inventory, sales—KPIs are relatively standard. For example, a company may measure revenue growth year after year as a standard KPI. As we bridge into operational practices with varying numbers of employees and levels of risk, however, it can become more difficult to understand not only how to establish KPIs but also where to get the data.
Leading vs. Lagging Indicators
Technology can help to create a pull-to-push methodology that puts site-specific leading KPIs at stakeholders’ fingertips. This correlates to leading and lagging indicators.
- Leading indicators signify the direction performance is going. Because leading indicators come before a trend, they are often seen as business drivers and should be incorporated into the business strategy. The forward-looking nature of leading indicators may make them harder to measure and they may change quickly; however, leading indicators are generally easier to influence. A good example of a leading indicator in determining the most common causes of an incident before it happens to prevent future recurrence, thereby impacting performance.
- Lagging indicators measure and help track how the company is performing in comparison to its goals. Lagging indicators are usually fairly easy to measure—but they can be hard to influence because what they are measuring has already happened or performance data already captured. In this way, lagging indicators are backward-focused. Many standard performance metrics are lagging. In safety, for example, the Recordable Incident Rate is a lagging indicator. Important information to know but hard to change.
Pull vs. Push Metrics
With a push approach, metrics are literally “pushed” to end-users, who then extract meaningful insights and take appropriate actions for themselves. Push metrics can have a number of components that trigger when (and who) metrics are sent to, including threshold, capacity, severity, and timing.
Conversely, with a pull approach, data is pulled in order to answer specific business questions. Pull metrics generally require someone with analytical skills to dig deeper into the data to identify the desired metrics.
While pull metrics may be more time consuming to identify and obtain, that doesn’t mean pull metrics aren’t important to have. In fact, organizations often need to pull data in order to create the push metrics that provide for standard KPIs. And push metrics may demand you circle back and pull further information. In reality, the process is cyclical: pull produces what should be pushed; push cycles back to pull in order to dig deeper into the details.
Creating Standard KPIs
Kestrel employs data analytics and technology to create a pull-to-push methodology for creating standard KPIs. This requires a number of things:
- The program must be well-established and designed with the operational requirements, capacity, tools, and skills to effectively integrate the program itself and associated data with technology.
- Assuming a program such as this is developed, initial reports can be pulled to check the program’s effectiveness based on a number of key attributes/metrics. This yields analyzable data.
- This data should be explored in many different ways. This allows the company to start seeing the interaction between stakeholders and the data and, eventually, creates the “a-ha” moment of understanding as to what metrics are important and meaningful.
At this point, it becomes possible to begin comparing data and metrics on a periodic basis, while continuing to pull information from technology. Remembering what queries are effective will aid in establishing initial leading KPIs. This process also will yield improved understanding of how the data gathering process (e.g., incident investigation) needs to be improved and standardized for a more reliable pull of information.
This comparison of data should then be used to discover what data is beneficial and what information needs to be more granular to really hone in on the standard KPI. Walking through this process and leveraging available technology makes it possible to effectively transition from pull methodology to push reporting—putting leading KPIs in the hands of decision-makers and identified stakeholders.