Capturing the expertise of high performers in your organization provides a rich repository of information that describes optimal work performance. We call this the Profile of Exemplary Performance (PEP). 

In the last blog post, we discussed collecting data through business analysis and alignment, as well as looking for the internal benchmarks of your stars. The final part of this data collection involves leveraging the insights of your stars.

The critical steps involved in conducting a performance analysis to leverage the insights of exemplary performance include:

• determine the key accomplishments that exemplary performers produce

• collect data on those accomplishments

• produce a task list for each accomplishment

• collect key data on each of the tasks.

This is not an area where you want to skimp on time or specifics of each data point. In an ideal environment, it’s best to collect data on accomplishments and tasks by interviewing and observing exemplary performers.

Guidelines for data collection

Don’t rely on a task force or focus group for reliable and valid information—because characteristics or behaviors that differentiate the exemplar from the average performer are often subtle and intuitive. These nuances will not be self-reported through an interview process alone. Instead, the process requires observation, combined with debriefing after the performance, to “get inside the skin” of the star.

If actual observation is not possible or impractical, case-based interviews are a good alternative. Case-based analysis works well if you are able to walk the star or team through real cases, while they answer questions based on actual data and project documents that can be accessed during the analysis process.

When stars aren’t available

Sometimes exemplary performers may not be available due to atypical circumstances, such as new technologies that have not yet been deployed, new processes yet to be launched, or new roles that need to be designed. In these cases, you might work with the technology provider to find noncompetitive organizations that have already implemented the technology or process. 

Sometimes performance analysis is required to create or support a new job. In this case, you might benchmark some of the accomplishments of the new job against similar accomplishments in existing positions.  Or you might spend time with exemplary performers who are currently performing parts of the new job. Often the analysis for a new job situation will be a composite and based on multiple current stars that are performing portions of the new role or, at least, are doing work that is analogous to the new role.

There are also occasions when you don’t have access to any exemplary performer, either inside or outside of your organization. In these cases, you’ll have to rely on other data sources such as a task force of people currently performing similar work. You might also try interviewing the process or technology designer to gather needed data for your analysis. Please note that none of these alternative data sources provide the quality of data you will get from a superstar who has developed deep expertise by codifying years, if not decades, of experience.

For more on how to shift the performance curve, check out Paul’s previous blog article in this series.

On November 7, 2013, Al Folsom and I will be presenting at the ASTD Virtual Summit Webinar.  We’ll walk through this process in detail. Meanwhile, you can begin to collect the data.