Can We Prevent Top Talent From Walking Out the Door?

Biographical information (biodata) has been used to predict turnover and performance for a long time.  The idea is that certain verifiable aspects of a person’s life are indicators of future behavior.  To use an adage from an earlier time, if a person has changed jobs frequently in the past, s/he is not likely to stay with you very long.

We can now fast forward this idea to employee retention.  Or, put another way, can we predict which people are going to leave a company?  This article seems to indicate yes and it should not come as a surprise.

Putting aside privacy concerns for a moment, this approach goes beyond determining if a person is the right fit for a job due to their personality or values.  Rather, it potentially blends ideas that we would always think of creating turnover (bad boss, less pay compared to peers, length of commute, etc.) as well as those (number of startups in area, change in housing costs, etc.) that perhaps we had not thought of.    The added layer to the analysis is that it allows HR to say, “Wow, this is a person we don’t want to lose (or could not replace), let’s make some adjustments” or “Eh, that person is an underperformer anyway, so good riddance.”

More importantly, it treats retention as a dynamic, rather than static, state.  Previous biodata models would say, “This person has a 70% chance of staying 2 years or more.”  This data model might say, “Right now, this person has a 90% chance of staying through the end of the year.”  But, 6 months from now, if things change in the organization or in the person’s role, the model may say, “Right now, this person has a 60% chance of staying through the end of the year.”  This puts the onus on HR to work with managers to address the potential issues of valuable employees on a proactive basis.

From an employee’s perspective, I think there is opportunity here as well.  Imagine if they could pull up his/her “propensity to leave” score at any time.  Think of it as part of an employee engagement indicator.  This person could then see those things that may be causing them anxiety at work that might lead them to leave.  If it’s something minor that s/he feels could be easily addressed s/he could take it to a manager.  If it looks insurmountable, s/he would know that a new job search is a good idea.

The privacy issue here is real and, as with all concerns, depends how you feel about others using your data.  If I’m Amazon, Google, etc, there is a great temptation to link a person’s customer data with their employment application/employment status data to refine algorithms.  I have no idea if I’ve signed off on this when accepting their terms and conditions.  Do you?

Regardless of the “hotness” of the job market, this approach to dynamically tracking retention probabilities can be a very useful tool.  It can lead HR to being ahead of the game when trying to retain talent rather than offering the promises of a jilted lover as someone valuable walks out the door.

The Article Fallacy

Most popular press about industrial psychology topics makes me twinge.  It usually creates a train wreck between human behavior and management and makes over generalizations that fit into neat boxes which do not exist in practice.

 

At the same time, academic journals can often lag behind effective practice.  That’s not meant as a criticism.  Careful scientific study of anything takes time and if that means that a particular technique achieves acceptance before researchers give it the thumbs up, so be it.  This process is also how we debunk most of what makes it into airport books.

I bring this up because a friend of mine referred this article to me.  It was in a respectable publication and brings up a challenging idea—that feedback from other people is not all it is cracked up to be and that we gain more improvement by focusing on our strengths rather than our weaknesses.  It is a provocative idea which challenges a lot of notions in performance management, 360 processes, and coaching.

But, alas, there is very little data cited in their article, or that shows up in a search of research, that supports the ideas.  Well, except for other articles written on the topic by one of the authors which also lack data.  This does not mean that they are wrong.  Only that we have no objective way to know if they are right.  That really bothers me.  Especially when designing and executing a good study would not be difficult.

We should all be more evidenced-based in what we do.  That should also include the authors of articles and books.  But, I guess that hurts airport sales.

Overcoming Selection Buzzwords

When doing a job analysis or writing job descriptions, one of the terms that comes up that makes my hair stand on end is “multi-tasking.”  While our bodies can perform automated functions simultaneously (e.g., driving and talking), our brains cannot consciously do two things at once.  Rather, when I’m “multi-tasking” (like checking my phone and looking up data), what I am really doing is switching quickly (hopefully) between two tasks.  Oh, and recent research shows that men and woman are equally bad at it.

When seeking to understand what managers really want people to do, it is important that we challenge them on vague terms like “multi-task” and “empower.”  When we really get to the meaning of these terms, multi-tasking is being able to handle several projects at once and empower is delegating effectively.  Those are behaviors selection specialists can work with in designing assessments and interviews.

As buzzwords find their way into our conversations about what employees do, our job is to determine the behaviors behind them.  Doing so assigns meaning to the words and starts us on the path of objectively measuring them as part of validated selection systems.

What are your least favorite job description buzzwords?

Is Age Discrimination a Result of Change?

A class-action age discrimination lawsuit has been filed against IBM.  Much of the complaints in the action come from a report that purports to outline how the company has systematically replaced older workers with newer ones.  IBM is denying the allegations.

There are a couple of compelling issues here.  One is whether IBM is using sly methods to rid itself of older (read: more expensive) workers.  The other is whether workers who are in mid-career are technologically behind their younger counterparts in a meaningful way.  I’ll leave the former to the courts.  I’m much more interested in the latter.

There are some national studies that indicate that openness to new experiences does decrease with age.  However, the ability to learn does not. So, we can assume that older employees who are open to learning new technologies can certainly do so.

Whether it is how we get to a friend’s house or how we use technology, most of us like to stick to what we know and adapt to change in ways that keep our patterns of behavior.  To keep up-to-date on new technology or techniques not only requires a desire to learn, but also the willingness to give up what we have been good at.

There probably is not data to support the idea, but I am guessing that the hiring strategy at many companies is that they would rather select people who know the new stuff rather than try to train for it. If companies decide that they want to bring on those who have experience with newer technology, their layoff/hiring practices will likely show adverse impact against those 40 and older.

A person’s background is instructive in this area.  For people who have stayed up to date on technology throughout their careers, it is foolish to assume that they will not pick up (or haven’t already picked up) on the next new thing.  As such, I don’t believe that they are behind younger workers.  Senior management would have reason to be concerned about older workers who have not shown a willingness to update their skills.

Are older workers less likely to adapt to new technologies?  On the whole, probably.  However, painting them with a broad brush is likely a mistake.  Companies should do a thorough evaluation of the experienced talent before making decisions that can land them in court.

Reducing Bias Through Structure

Finding examples of racial or gender bias in hiring or job evaluations is not hard.  The latest comes from a survey of lawyers.  My sense is that the results did not come from a random sample of attorneys, so I would not quote the group differences as gospel.  The authors recommended some specific ways that law firms and companies that hire lawyers can correct the bias in their HR processes.  There were two things I took from the study:

  • Many, but not all, of the recommendations came from a solid research base. It was good to see that their hiring suggestions included behaviorally based interviews, skills based assessments, and using behavioral definitions of culture.  Each of these suggestions introduces objectively and structure into the hiring process.
  • Given that attorneys have either brought employment lawsuits or have had to defend companies against them since 1964, did it really take this long to come up with some hiring process recommendations?

My consulting experience tells me that people who hire for professional jobs seem to think there is more magic and intuition in selection than those who staff for other types of positions.  This is especially true when hiring for a job they used to have.  They could not be more wrong.  Every job has a set of critical skills and abilities required to do it well.  It is possible to objectively measure these in candidates.  Doing so will likely reduce bias.

Who Should Identify and Develop the Non-College Workforce?

On some occasions I have mentioned that companies that need blue-collar workers are in a tough spot. Their jobs are not very sexy to the millennial or Gen Z workforces who prefer tech jobs.  Also, because lifetime wages are significantly higher for jobs that require a bachelor’s degree, parents and high school students tend to have a much more favorable attitude towards going to college than training in a vocation, which is reflected in college application statistics.  We are currently in the midst of low unemployment which makes recruitment for blue collar jobs even more difficult.

Companies should think about this as a long-term, rather than an immediate, issue.  This article talks about how some firms are dipping into high schools to begin identifying students who might not desire (or be qualified for) 4 additional years of school and providing them with what used to be called vocational training.

Of course, if a specific company or industry designs the career education programs (read: vocational), there is a danger of the training being too narrow.  However, no public school in its right mind would ever turn down private money that helps kids get jobs.  And we don’t seem to have a problem with it at the college level where business schools take money (and input) from big employers and provide the students with internships.

The economy goes in cycles and it is not a matter of if, but when, the economy slows and there won’t be the same worker shortage.  However, the trend towards more interest in college and tech jobs will continue for the foreseeable future.  This means that employers of skilled, but not college educated, workers will have to find more ways to create a larger labor pool to find the talent they need.  They can do this by:

  • Aligning with local high schools and community colleges to create curriculum that is broad enough that provides students with career options, but specific enough to allow for an easy transfer from school to the employer.
  • Gauge the interests of students as they enter the program. Interest inventories are an under-utilized selection tool.  This is especially true for entry level employees.  If I’m not interested in social activities, I probably should not be on the wait staff at a restaurant, even if I need the money.  But, if I’d rather work with things than people, then becoming a welder might be up my alley. Validating these types of tests can be a good way to predict potential success by placing students in areas where they are more likely to do well.
  • Provide lifetime learning programs. One thing we know about millennials and Gen Z is that rewarding them for learning is a powerful incentive. Companies should show new recruits all of the opportunities they could potentially have, not just the ones in their trade.

Companies that need skilled blue-collar workers can no longer passively expect a deep talent pool to be available.  Rather, they should take action to identify and develop potential employees.  This will require partnerships, better pre-employment screening, and having developmental programs.  It may not solve the immediate problem, but it will ensure that they have the necessary talent in the future.

Adapting to Changes in Job Duties

I wrote a couple of months ago about how McDonald’s is changing the cognitive requirements of some of its jobs by adding channels for customers to order food. I argued that such a development should get them thinking about who they hire and how they train new employees.

If you have recently wandered into one of their stores, you probably noticed that, if it is not too busy, a McDonald’s employee may bring you your order. OK, this is not particularly revolutionary. But, to quote a franchisee in an article, “We’re bringing the employees from behind the counter out front to engage, in a more personal way, with our customers.” Maybe I am making more out of this particular example than it warrants, but this strikes me a really upping the customer service requirements of a McDonald’s employee. And I am guessing that a fair amount of the employees are not going to meet it. It’s just not what they signed up for.

This is not about whether McDonald’s employees are capable of providing the additional service or whether their ability to do it well affects the customer experience and/or sales. Rather, it appears to be an example of company changing job requirements and then assuming that people hired using a process that does not account for the new skills will be able to carry out the new duties.

Changing skills requirements is a good thing. It shows adaptation to technology and customer needs and makes the work experience more interesting for people in repetitive jobs. But, companies cannot assume that the incumbents can magically adapt without training and revised performance expectations.

This change also requires updating validation selection processes. Whether it means increasing the weight given to certain aspects or validating a new test, we must adapt our workforce to new job requirements on the front end. As jobs change, hiring practices should as well.

Technology and customers are big drivers of change in the skills, abilities, and personality characteristics required of employees. Smart companies not only redesign work to account for this, but they also update how they train and hire to help their workforce adapt.

Ways That We Punish, Rather Than Coach, Poor Performers

During the 4th of July holiday, I was binge watching an Australian cooking competition show with my family. It was pretty mindless and entertaining stuff. The gist of each episode was that contestants competed in a theme-based challenge. One was selected as the best for the day. Two others were deemed the poorest performers and then they competed to stay on the show. What I found most interesting was that they task they were given to avoid elimination (getting fired) was harder (by design) than the original one.

Of course, there is not necessarily a straight line to be drawn between entertainment shows and the work place. But this did get me thinking about how we develop poor performers. While it seems intuitive that resources spent on improving their performance would have a significant return-on-investment, data show that high performers generally benefit more from training than low ones do.

HR needs to consider how to develop all levels of talent. With the current low unemployment rates, companies are losing some of their control over their talent levels, especially now there is more job hopping. There are a few considerations in developing low performers:

• Are you rewarding progress until the person is capable of delivering results? The key here is that improving performance requires changes in behavior. If they are reinforced, the new behaviors are more likely to be learned. Telling people “try harder” or dangling a future carrot are not good strategies for improving performance.

• Are they sufficiently skilled in the tasks you expecting them to do? Before concluding that the person is not going to be a good employee, be sure that they have the basic skills/experience to perform the job. You should not expect someone to be a pastry chef if s/he does not know how to make a cake. This is where valid pre-employment testing programs are valuable.

• Are there other areas of the business that appeal more to their interests? I have a client that staffs its own call center. They have higher than average turnover in the call center, but somewhat lower in the company overall, because after people spend 6 months there they can bid for any other open position in the company for which they are qualified. Allowing easy lateral transfers helps you keep good employees who may just be in jobs they do not find engaging.

Low unemployment rates mean that new talent is going to be more expensive. It may indicate a good return-on-investment in developing under-performing talent than usual. However, getting people in the right place and having alternate reward strategies are essential to getting the most out of their development.

Can Robots Reduce Turnover By Making Work More Interesting for People?

Lower unemployment rates mean that many industries, including hospitality, need ways to attract and retain more talent. Higher minimum wage laws in many states and cities have likely encouraged people to stay in jobs they may have previously left. But, what about using automation to get them to stay?

The typical assumption is that automation leads to fewer workers, which makes sense in many cases. The cotton gin took people out of the fields and it does not take as many people to put together a car now as it did 30 years ago. What automation also does is offload boring tasks so that people can do more interesting work. We see that in offices (no longer lots of people mindlessly typing memos all day) and now we are seeing a bit of it in the hospitality sector. Granted, most of the turnover in restaurants is due to still crappy pay and low benefits. But an employer quoted in the article thinks that it is partly due to the work itself (note, I was unable to find another dataset that confirmed this, but it makes for an interesting argument). From this perspective, a restaurant can provide more value to the employee (and, presumably the customer) by having that person deliver food instead of taking orders (which customers are doing themselves from kiosks or smart phones). Perhaps these are both minimum wage tasks and the former is more interesting for the worker than the latter.

The idea of reducing turnover by making the work more interesting goes back to the 1970’s. It is pretty simple: Most people do not want to do boring and repetitive tasks and they will be more satisfied and engaged with their work (e.g., more likely to stay) if it is not mundane. This is not rocket science. However, giving people more tasks and more autonomy may also require a different skill set. Where employers who choose this approach (either through job redesign or automation) miss the boat is when they implement these changes without considering whether employees have the skills sets necessary.

Most organizational change efforts I have observed save the planning for new selection systems or training until the end (if they are thought of at all). For instance, if I have always asked workers to follow one single process but now I am giving them the autonomy to override it, I need to understand that these are two different sets of performance expectations. If you asking for new behaviors from those in a job title, you need to be sure you are hiring people with those abilities using validated tests and/or provide them with proper training.

People–Can’t Profit With Them, Can’t Profit Without Them

So, in the same week that Tesla says that lack of people is a problem in their business (too many robots!), Starbucks comes to the conclusion that people are biased and are hurting its business, everyone gets training. So, which one is right?

Let’s start with Tesla. Their statement is not as much about how wonderful people are as it is that they haven’t quite (yet) gotten the engineering down for their new cars to be built completely by robots. So, it is not exactly an “Up with people” moment as a “Well, we guess we have to put up with them for a bit longer” one.

The Starbucks situation is a bit stickier. On one hand, they clearly felt as if they had to do something after a horrible incident involving African-American customers to maintain their brand image. But, I think they are setting themselves up for failure. Implicit bias training is well meaning, but correcting a lifetime of assumptions about people in a ½ day seminar is a pretty tall order. What will they do next time a racially tinged incident occurs? Do a full day of training? Validate a test that predicts levels of implicit bias?

Where I think the training will have the most impact is on their new hires. It sets a cultural norm of what is and is not OK. Yes, this will require management support and some way of recognizing employees for being decent human beings. But, in reading the comments on their social media pages after the announcement that may not matter as a lot of people were pretty bent out of shape of having to go one whole afternoon without their Starbucks. Ah, the downsides of selling a legal, but addicting, product.

Service sector organizations will always face the challenge of directing the activities of people in a way that is consistent with their values. Manufacturers are always challenged with introducing technology (which improves efficiency), but also understanding its limits (for now). We are not quite at a point where people can be engineered out of business. So, we still need to lead them in productive ways.

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