When Should You Stop Using an Assessment?

I’m guessing that you would not expect me to write about discontinuing the use of a pre-employment or pre-promotional assessment.  But, there are instances when it is appropriate to do so.

For instance, the National Football League (NFL) has decided to stop using an intelligence test that they had been using for years to evaluate new players.  I have written about the league’s use of the test before, so I won’t rehash the arguments about it here.  However, its reasoning for not using it any more really comes down to:

  1. They did not feel it was predictive.
  2. It led to a poor candidate experience (which, to the NFL means bad publicity).
  3. And those are two very good reasons not to use a test.

Another reason to discontinue the use of a test is when knowledge, skills, abilities, or personal characteristics (KSAPs) required of a job change.  At some point, administrative assistants stopped typing pages of documents, so a test of how quickly someone could manipulate a keyboard no longer made sense.  Changes in customer dynamics can impact KSAPs as well.  When working with a call center client, our validation data showed that personality tests that predicted performance for those taking phone calls were not effective for those who took customer inquiries via e-mail or chat.  This led to a change to how the tests were scored depending on the open position.

This does not mean you should automatically drop using assessments because a job changes or has converted to WFH from an office position.  However, knowing that for many people WFH is the new normal, it may be time to see if the work has really changed and the if that impacts the KSAPs.  If the status quo has held, you have your answer.  If there are some changes, then another validation study is likely in order.

The use of assessments, like many HR procedures, tends to take on a life of its own.  Once they are in place, there is a lot inertia (we have always done it this way) keeping them there.  It does not have to be that way.  A good job analysis and validation study can help you modify your testing tools so that you get high value from them.

Equal Pay for Similar Work—A New Era in Job Analysis and Salary Negotiations?

California has prohibited gender-based wage discrimination since 1949. Courts ruled that the law applied only to exactly the same work. The state took it one step further this week by passing a law this week saying that women have a discrimination claim if there is unequal pay for substantially similar work. Some feel that the new law is good news for everyone from cleaning crews to Hollywood’s biggest actresses.

Practically speaking, the decision could lead to renewed interest in job analysis (let’s not get too excited, OK?). The law is written so that the burden is on the employer to demonstrate that the difference in pay is due to job related factors and not gender. So, if someone is going to argue that two jobs are substantially similar, there is going to need to be some data to back that up.

The law states that similarities are based on “a composite of skill, effort, and responsibility, and performed under similar working conditions.” A good job analysis will quantify these so that jobs can be compared. Who knows what statistical test tells you when jobs are substantially similar, but the data will tell you if they are the same or really different, and that’s a start. Regardless, I’m guessing that the meaning and demonstration of substantially similar will be litigated for a while.

The other impact of this law is likely to be on salary/raise negotiations. There’s plenty of data which indicates that men are less averse to this process than women, and this has real economic impacts. Companies may want to consider whether to make non-negotiable offers to avoid bias claims.

California, as usual, is setting a new standard in equal pay legislation. There’s the usual concern that this will cost the state jobs, but it may also attract more professional women. Either way, companies will need to review their compensation structures and determine which jobs are substantially similar to each other.

For more information on analyzing and grouping job titles, please contact Warren Bobrow.

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