We recently hosted a great live webinar: Reclaiming Performance Management – New Processes for a Modern Workplace with host, Edie Goldberg. During the webinar, Edie presented numerous facts and tidbits that threw a wrench into the assumptions that drive traditional employee performance management processes.
One such fact relates to how important it is to identify and develop talent. I know. That sentence has been so overplayed that it likely doesn’t register a cerebral response from most; however, if we present one change in how the distribution of performance actually looks in the majority of organizations, things start to look a lot different.
The Distribution of Performance is Anything But ‘Normal’
Our general assumption has been that performance across the entire organization should be normally distributed which means there should be a small number of high performers, a small number of low performers with the majority of employees clustered in the middle (around the mean) with average performance. Unless a company forces a normal distribution (which is an entirely different conversation) we would assume that over a large enough sample, the normal distribution would apply to analyzing the performance-level and productivity across an organization’s talent base. This has generally led to any extreme outliers being assumed bias or incorrect.
However, research by authors O’Boyle and Aguinis has taken this assumption and flipped it on its head – forcing organizations to take a closer look at how they rate and identify talent. The research has shown that across a wide-variety of samples, in different industries and professions, performance/productivity is NOT normally distributed. Performance is better represented by what’s called the Paretian or ‘Power-Law’ distribution as seen below.
Under this distribution, the outliers are embraced and result in a very small number of elite individuals who are accountable for the majority of performance in the company. This model almost mirrors the 80/20 rule where 20% of employees account for 80% of performance. This finding has HUGE repercussions for how we approach talent management and highlights the need to identify and develop that 20% – the ‘hyper-performers’.
Unless that elite group of hyper-performers is identified, developed, rewarded and retained, the company could be at risk of reducing overall productivity and performance by a much larger margin than traditionally assumed.
How Does This Affect Talent Management?
If we consider the power-law distribution, there are some small but significant changes that companies can make to get a bigger bang for the buck when it comes to talent management efforts.
Talent Development: Typical talent development initiatives are centered on moving the ‘majority’ of average-performing workers ahead in their performance because the normal distribution assumes this will increase productivity by a predictable amount. Since most workers fall into the ‘average’ category, it is assumed there will be strength (or results) in numbers if that group is developed. If we consider the power-law distribution curve, however, it is clear that focusing efforts on developing the individuals that contribute the most work will have a greater overall impact on the organization. This isn’t to say that the majority of talent shouldn’t be developed, just that development initiatives should be based on an individual’s current and potential level of performance in order for the results to have the greatest impact on the organization.
Recruitment: As any HR professional will tell you, it is impossible to locate and support an entire organization filled with hyper-performers so striving to recruit only the elite is not practical or realistic. What this research does, however, imply is that HR should understand where this high-performing class of employee is needed in the organization so the right employees can be sourced or developed to fill the gaps. Identify the roles and areas of the business that need this special type of talent will ensure the company’s bottom-line benefits from the impact.
Performance Appraisals & Ratings: I’ve been saving the scary bit until now. If the power-law distribution is considered, then the mean or ‘average’ shifts and is no longer in the middle. This means that technically, most employees would be considered ‘below average’ with hyper-performers being easily identified. If you consider a common 5 point rating scale, under a normal distribution, we would expect most employees to hover around a 3 but with a power-law distribution, most would be located closer to a 2. It is very scary for any organization to view the majority of their workforce as below average and we don’t see any value in doing this or imposing labels as such.
Since the point of the power-law distribution isn’t to demotivate the majority of employees or assign labels, but instead to make it easier to identify hyper-performers, there are some things that can be done to accomplish this.
- Don’t force ratings – guide them: Review your rating scale and processes to determine if they impose a traditional normal distribution. Instead of forcing categories and ratings, guide users and give them the tools needed to rate accurately and honestly. This will allow any hyper-performers to be identified and developed as needed.
- Educate to eliminate bias: Ensure users are trained on the process and any systems in place and are aware where common bias might affect their ratings. Click here for additional information on avoiding bias in appraisals.
- Monitor: Even if you educate managers and supervisors on how to avoid bias, how can you be sure it isn’t happening? The answer is to monitor. Using status reports and rating distribution reports, any anomalies will stand out like a sore thumb and you can catch up with that manager about his or her rating styles and/or to confirm that the anomaly is in fact the golden egg you are seeking.
- The more heads the better: Traditionally, it is the managers that provide an employee’s rating and any recommendations about that employee’s potential. Most often, this is an effective way to identify talent; however, in certain organizations or teams, you could be missing out on identifying your hyper-performers. The more people you include in the process, whether it’s additional managers, Directors, 360° evaluators, peers, clients etc., the more accurate the ratings will be and the more likely legitimate hyper-performers can be identified.
Reporting: We suggest using a nine-box to report on the relative status of performance. Just a quick refresher, a nine-box plots all employees in one of nine boxes depending on their scores in 2 criteria (usually performance vs. potential). It is a simple and effective way to not only identify hyper-performers, but those with the potential to move into that role. Because you can set your own thresholds, a nine-box allows you to identify superstars without altering your company’s rating scale.
Whether you think your organization might follow a power-law distribution of performance or not, identifying top talent in your organization should be a primary focus of HR. If there is a possibility that a small group of elite hyper-performers are shaping the success of your organization, then shouldn’t we ensure mechanisms are in place to rate, reward, and develop those key employees?
Sources: “The Best & the Rest: Revisiting the Norm of Normality of Individual Performance”
Ernest O’Boyle Jr., Herman Aguinis, Publisher: Personnel Psychology, 2012, 65, 79-119