Big data is everywhere. Anyone running a contingent workforce program with the benefit of a vendor management system knows there is an almost endless array of report templates that can provide information on virtually every aspect of the recruitment cycle — from demand forecasting to exit management. Add to this the ability to produce custom reports, and the information at your fingertips is seemingly endless.
These reports can then be forwarded easily to people who may not even have time to review them.
In fact, I posit there is such a thing as having too much data.
For example, I have been involved in situations where historical information has been provided, though no real future benefit was apparent. While it is certainly of interest to look back in time to see how trends have developed — how the last 12 months compares with the previous 12 months or how the last quarter compares to the same quarter in the previous year — the only real benefit of looking at such historical data is if having it can positively affect future program performance.
In other words, if reviewing past performance does not drive future performance in a positive way, then a significant argument can be made that your time could have been better spent.
Be objective. Your program’s overall goals should be aligned with your organization’s strategic objectives. The service-level agreements and key performance indicators  that define the success of your program should be similarly aligned.
One way to make sense of the plethora of data available within your contingent workforce program is to develop a series of what I refer to as quadrant reports.
These can be any number of easy-to-understand summaries of big data that are accompanied by actionable, short-term strategies aimed at either:
- Correcting a defect that is having a negative impact on program performance, or
- Exploiting something that is having a positive impact elsewhere.
Rather than focus purely on what isn’t working well, improved program performance can often be a result of concentrating more effort on what does work and improving on this further or looking to replicate this across the wider organization.
Employing the quadrant. Imagine this scenario: You are running a sales organization where 50% of your staff are underperforming and the other 50% are overachieving. The investment of your time will improve the performance of both of these groups by 10%. While you need to invest time developing the underachievers, you would be better off improving the overachievers’ output by 10% than by improving the underperformers’ output by 10%.
By displaying your chosen trend in the upper-left quadrant, the distribution of that trend can be broken down further in the upper-right quadrant.
The distribution of that trend will show areas of high performance as well as those areas that are underperforming.
The bottom-left quadrant would then identify four or five reasons for the distribution’s high and/or low performance, with a corresponding four or five short-term actions (aligned to each cause) that can be taken to either exploit the high-performing areas or to address root causes that are likely responsible for underperformance.
As part of your regular program reviews, this quadrant mindset will help translate big data into specific actionable items to improve overall program performance.