Validation: Overcoming Inertia to Prove the Value of Staffing as a Profit Center

Screen Shot 2013-01-05 at 2.07.24 PMTalk is cheap. Proving the real value of something is often an exercise that requires intention, dedication, focus, and effort. When it comes to demonstrating value, data and money are among the best pieces of proof one could ask for.

Clearly showing the value of hiring remains a perpetual challenge for those in the staffing game. While it is easy to talk about all of the great things we are doing, it is much harder to turn this talk into the hard proof that business leaders expect (i.e., money).

My research and experience clearly demonstrate that organizations fail to take the proper steps to evaluate the impact of their hiring processes. This is especially true when it comes to the use of pre-hire assessment tools. In fact, the proper evaluation of pre-hire assessments is actually the exception rather then the norm. This is unfortunate because a lack of effort in this area can keep a company from realizing its potential while costing it big time.

The reason most companies consistently fail to evaluate the impact of their pre-hire assessments is both simple and complex. The simple answer is that many companies just don’t care enough or aren’t willing to put in the effort it takes to make it happen. We all know that proving the value of your hiring process is not easy, but what things of value truly are?

The complex answer has to do with to the geeky side of things — specifically the methodological issues that accompany “test validation” and the science of hiring (for a through discussion of this see here).

Validation is important because it is the avenue via which staffing practices demonstrate value.  While there are several types of validation, the most effective type for demonstrating real-world impact of the hiring process involves a systematic investigation of the relationship between pre- and post-hire data. This is known as “criterion related validation” — an analytics-driven process that is essentially business intelligence applied to the hiring process ). We I/Os have been doing this type of work for a good five decades now and have found results we can really be proud of.

Despite our success with it, validation is tricky and presents some inherent difficulties that can obscure its value and therefore its popularity. These include:

  1. Small sample sizes — Due to the presence of error, it is very hard to have any degree of confidence in the impact of anything on anything else when one has only a few data points. Data-based insight requires large sample sizes, and in many situations there simply aren’t enough people in a job or position or enough hires being made to provide the data needed to have any degree of insight into the value of a pre-hire assessment.
  2. Problems measuring job performance — Our ability to clearly see the relationship between pre-hire measures and post-hire outcomes is limited by the absence or poor quality of most job performance measures. In situations with objective outcomes such as sales volume, turnover, absence, etc. it’s  easy to capture meaningful job performance data. But when it comes to the subjective performance data that is associated with the majority of jobs out there, problems begin to arise. In these cases we are left to rely on supervisory ratings of performance or ratings from performance management systems. This is a problem because subjective ratings leave the door wide open for bias and rating errors. This means that professional level and white-collar jobs present problems when it comes to validation because the complexity of these jobs makes it harder to quantify performance data and to convert it into the dollar values needed to demonstrate real value.
  3. Failure to collect outcome data — I’ve often seen situations where organizations take the time and energy to collect or use pre-hire assessments but have no interest in collecting or providing access to post-hire data needed to complete the effort. This type of attitude is truly passing over dollars to pick up pennies and is a harbinger of failure in my humble opinion. The effort made to collect and understand outcome data is directly proportional to the ability to prove the value of a staffing system.
  4. Difficulty translating geek science into business language — The outcome of the validation process is usually some index of the relationship between scores on a test used in the hiring process and job performance resulting from hiring persons with a certain score.  While this index is very meaningful, it often does not tell the whole story because these relationships are hard to express in dollars.

Making the leap from validation statistics to dollars is not easy. For example, when one is relying on subjective performance ratings that are competency based (i.e., supervisory ratings of subordinate communication skills) as an expression of job performance value, it is extremely hard to express the results in dollars. This is a problem because dollars and cents is what business understands. Failure to speak this language has served to marginalize us I/Os and staffing professionals and leads to incorrect perceptions of our value.

While all of the above are legitimate reasons why validation can be a hard row to hoe they do not mean we should give up trying. The rewards of striving to do it right are worth fighting for.

The good news here is that we are living in an era marked by unprecedented levels of analytical ability, and there is an increasing body of evidence that demonstrates that companies across the globe are finding ways to show the value in their hiring processes. For those brave enough to keep pushing to overcome the inertia of the situation, here are some things that can make a difference.

  1. Expand your mind — We live in a time where we can begin to expand the traditional concept of what test validation means to a more business-intelligence and analytics-focused mindset. These days our every move contributes to a rapidly growing trail of data. Human capital technology systems and talent management platforms have made the collection and analysis of performance related data a byproduct of doing business and provide a new way to capture and analyze data. We need to expand our traditional concept of validation to one that takes a broader focus to creatively wrangle pre- and post-hire data to find the money hidden within. Doing this requires equal parts technology and dedicated HR analytics personnel and resources.
  2. Take an integrated approach — We continually speak about the integration of talent acquisition and talent management. Now is the time to being actually aligning these things from a structural standpoint. We need to determine the organizational competencies that are of value and ensure that these are the bedrock of both hiring and development activities. This connection will make it much easier to support point No. 1 above.
  3. Go for the low-hanging fruit Validation and showing dollars and cents is easier for some jobs than for others, and every company has fires that need to be put out. I always encourage my clients with little validation experience to do a proof-of-concept validation project in an area where immediate help is needed and results will show impact. The results allow for a nice story to be told and can seed the clouds for more funding and interest in deeper work at a strategic level.
  4. Don’t be scared to use supervisory ratings — Although supervisory performance ratings are not the very best outcome data, they are quite valuable and in many cases represent the easiest way to go. Current technology makes it a snap for rating forms to be distributed and for raters to be trained on how to use rating forms correctly. We have not even begun to fully tap the potential of this data source to help us continue the success story of validation and technology.
  5. Access collective wisdom — There is a ton to be learned from the collective wisdom of the vendors in the pre-hire assessment space. Although individual sample sizes for local validation studies may be small, vendors have decades of data that can be looked at collectively to generate an understanding of what works. They are eager to help use their experience to help their clients to see the relative value of localized data based on collective benchmarks and information.
  6. Thought (and action) leadership — The ability of data to show the value of hiring systems is not a myth. It is reality and those who wish to find rewards must make the extra effort to find ways to mate science and technology to show value. Creativity, effort, and thought leadership are critical for gaining the attention of business leaders by demonstrating that staffing can be a profit center.

Any of us who have been working in staffing can find a million reasons why showing real value is not an easy thing to do. But just because something is hard does not mean it is not worth doing. Keeping your eyes on the prize and taking on hard challenges is what differentiates the pretenders from the contenders.


photo from Harbor Freight Tools

About the Author

Dr. Charles Handler is a thought leader, analyst, and practitioner in the talent assessment and human capital space. Throughout his career Dr. Handler has specialized in developing effective, legally defensible employee selection systems. Since 2001 Dr. Handler has served as the president and founder of Rocket-Hire, a vendor neutral consultancy dedicated to creating and driving innovation in talent assessment. Dr. Handler has helped companies such as Intuit, Wells Fargo, KPMG, Scotia Bank, Hilton Worldwide, and Humana to design, implement, and measure impactful employee selection processes. Through his prolific writing for media outlets such as, his work as a pre-hire assessment analyst for Bersin by Deloitte, and worldwide public speaking, Dr. Handler is a highly visible futurist and evangelist for the talent assessment space. Throughout his career, Dr. Handler has been on the forefront of innovation in the talent assessment space, applying his sound foundation in psychometrics to helping drive innovation in assessments through the use of gaming, social media, big data, and other advanced technologies. Dr. Handler holds a M.S. and Ph.D. in Industrial/Organizational Psychology from Louisiana State University.