Happy Bastille Day
Whilst the French are celebrating their Nation we are continuing our revolution of the way that data is used to bring value to the HR function. This post features the thorny topic of benchmarking and what sort of comparison is relevant in terms of HR.
The most common approach to benchmarking is to look at organizations that are broadly similar. This approach has value and relevance. If we look at organizations that operate under the same context, conditions and constraints, then how we perform relative to these groups will be accurate and any discrepancies or variations are meaningful. For example we run a comparison group of 15+ credit unions. Those involved have very valuable data to use in order to demonstrate that they are operating better or worse than direct peers. It also provides the opportunity to set goals to be the same as those who are “best in class” and ensure that their HR practices are keeping up. The capacity to monitor staff movement, staff productivity, HR spend and resources helps these organizations to both prove and enhance the effectiveness of their HR groups.
One downside of this comparison to similar organizations is that the most common result is an imitation of the best in your field. This comparison process leads organizations to match the best in their group and therefore it is not a recipe for leading the pack. It is a recipe for keeping close to your pack’s leaders. Hence the whole approach can limit the value that can be achieved through a detailed analysis of data from your own and other organizations.
A further common pitfall with this approach is that organizations take far too narrow a view of what is and is not similar. For example they seek out organizations that are like them in almost every detail down to physical location, exact mix of business and size etc and hence either completely remove the opportunity to find a comparison group. Or ensure that the results they get are so close to their own that they are only useful for the purposes of confirming that nothing is wrong. This can be a comforting outcome but does nothing to push the boundaries of performance.
Much less common is the process whereby organizations compare themselves to those that are unlike them. This approach also has a compelling logic and the potential to achieve more value than a straight comparison to similar organizations. Here is an example to demonstrate what we mean.
The table below shows the annual days lost to absence for 2010 for the Public and Private Sectors.
Absenteeism Rate = days lost per employee 2010
|10th Percentile||Median||90th Percentile|
If an organization in the public sector is at 6 days lost per employee they are likely to be complacent based on a comparison within their sector. However what the private sector numbers indicate is that it is possible to reduce their days lost by at least 40% (2.4 days) based on the 10th percentile for the private sector.
Shifting the perspective from one of being top of your class to being in the middle of a different class helps to push your strategies and thinking to a new level. You can claim the comparison is meaningless as the two sectors are different. Alternatively you can ask “What would we have to do differently in our sector to achieve this level of performance?” How you approach benchmarking and the type of comparisons you choose say a lot about whether you are looking to confirm that everything is OK or to use the data to push your performance to the next level.
To achieve the best of both worlds it is important to align your data with common standards that are most likely to provide the opportunity for like with like comparison and like with unlike comparison. This creates the capability to compare in a way that confirms your performance or compare in a way that pushes your performance. As with all data and analytic practices the right thing to do is the one which moves the performance needle for your organization. The more HR can do this AND demonstrate this the better.
 Source: HR Metrics Service 2010
Source: HR Metrics Service – Standards and Glossary
- HR analytics process: Ask better questions - January 9, 2013
- People analytics for business: In high heels and backwards - December 12, 2012
- The winds of change: Making HR measurement happen - November 13, 2012