How to stop leaders from “gaming” your system

For two decades I designed compensation and performance management systems for large and medium companies. I always had this nagging thought that after two or three years the system had run its course. Those who wanted to do so had figured out the game and turned what was intended to be a fair system into their own playground.

Quantitative performance ratings drove me crazy. Leaders would figure out the overall rating they wanted, and then go back and tweak the individual ratings so that they could give the salary increase they wanted to give.

Today, the Wall Street Journal carried an article about how companies are learning to game Glassdoor. Companies like SpaceX, SAP, LinkedIn and Anthem “encouraged” people to leave excellent reviews, causing unusual spikes in their ratings. CEOs questioned about the practice said that the ratings on the site were not representative of their company, so they fixed it.

I see a pattern here – those systems that are intended to provide helpful and unbiased data can be “gamed.”

The other nagging thought I had back when I designed compensation plans was that plan sponsors wanted to substitute a system for daily leadership. How do we make sure the tellers are upselling? Put in an incentive plan. Are tellers balancing? Put it in the incentive plan. Are they being nice…? You’ve got the idea. The plan becomes so complicated that two staff analysts are engaged to “track and manage” it. The branch manager doesn’t understand it and spends more time explaining the plan than correcting behaviors.

I see another pattern here – there seems to be more value placed on systems to manage behavior than on leadership observation, coaching, and feedback.

Systems are critical in an organization. They lay boundaries, communicate values, encourage appropriate behavior while discouraging behavior that is contrary to the mission. They are not, however, a substitute for leadership. The timely and effective use of organizational systems should be a competency for which leaders are held accountable.

How can an organization build accountability into their systems so that the data and results are intentional and not “gamed?” Here are four ways to get started. (more…)

Are you ready for artificial intelligence in HR?

It’s coming, whether we like it or not. Look at the topics and exhibitors at any HR conference. It’s coming.

Artificial intelligence has the potential to relieve overburdened HR team from decisions that can be made more easily and more scientifically through decision science.

When you think about filling a job, you are solving an equation. On one side are the requirements of the job. On the other side are the skills, knowledge and traits of the employees who fill or may fill the job. The decision to hire is a gap analysis between the two points – demand and supply.

That’s what technology does to enable more qualified candidates for jobs; matches the need to the supply of candidates. It works in a similar manner to provide employee directed growth and learning opportunities as well.

But, before we can use AI to make strategic decisions we must ensure that the data is accurate. Bad data wastes time and may lead to poor decisions. Technology doesn’t really know the data is bad; it solves for the match you asked it to solve. Now is the time to make sure that future technology has credible, timely and accurate data so that it really can help make good decisions.

The “Job” side of the equation

Take a collective look at the information about jobs that the HR team maintains. By information, I mean the knowledge, skills and abilities that have been defined. Review job descriptions, job postings, competencies used in performance management and learning paths.

By collective look, I mean working together as an HR team to review all of the job data, produced by each team, for each purpose. Ask these questions:

-Do the job requirements match across all HR platforms? If not, should they?

-Do the job requirements actually describe the skills, knowledge and abilities specifically enough, or have the jobs been clustered and combined for simplicity so that they are too generic to really explain the job?”

-Is the data accurate? How do you know, and who is responsible for timely maintenance?

The “Employee” side of the equation

Employee and manager self service takes a huge administrative burden off HR, but places it in the hands of people who don’t understand the consequences of inaccurate and untimely data.

Now is the time to educate those who enter the data on the importance of accuracy, and to implement audit trails to catch and resolve outliers.

Employee and manager self service offers a menu of choices, allowing a data field to be completed with pre-defined data. Are those choices clear and well-defined? Job codes are a key element of matching an employee to a job; are managers too hurried to use the right code?

Termination codes are important to understand retention efforts. Do you offer so many choices that the hurried manager gives up and grabs the first code that seems to fit?

Now is also a great time to make sure that the data codes you use are current, and exactly what you need. If you put 100 codes out there just in case you might need them, that’s 99 possible errors a manager can make.

Conferences and vendors paint a rosy picture of capabilities we haven’t even thought of. Let’s be ready.

How quickly can the Nebraska team learn?

Shucks. Nebraska lost to Purdue, and now has a 0-4 record for 2018, and hopes of a bowl game are…well…probably gone. So much for the silver bullet, Scott Frost.  Oh wait, I already said there is no silver bullet.

I do, however, see more leadership lessons from Nebraska. Let’s explore “organizational learning,” shall we?  I went to look for a prior article I wrote on organizational learning, because I use the term all the time.  By golly, I haven’t written one, so let’s take a whack now.

My mantra: learning occurs at the individual, team and organizational level, and higher levels of learning are not the sum of the parts.  They are greater and they are shared.  Just because everyone on the team is exceptionally good at their individual role doesn’t mean the team is effective. They may be; they may not be.

If they are, and they haven’t built a collective set of experiences, practiced together, and dissected each and every move to understand why it worked or why it didn’t work, their win is pure luck. Luck may win the game. It doesn’t get you to the national championship.

Scott Frost has repeatedly said, “I know what direction we are going.” My guess is that he’s going to the national championship. And given his record of coaching success, I suspect his experience has told him from the beginning that it ain’t gonna be easy.

Oh, there are some that are ready to give up on Frost already. They just don’t get it. It isn’t about the short-term. It’s about the long-term.  It’s about organizational learning. How can Nebraska’s journey demonstrate the elements of organizational learning? There are several ways. (more…)