Came across this blog post the other day and it inspired me to write about how use analytics to know when to let go of troublesome employees.
The first type I’ll blog about is ones who are habitually tardy.
“Handling employees who are constantly tardy for work is one of the difficulties of being a manager — no matter the industry. Simply firing them isn’t always the best policy when you consider the effort spent trying to hire their replacement. On the other hand, if your organization thrives on teamwork, having one team member not pulling their weight is bad for office morale.” Wise words form the blog I read.
The best way to deal with tardy employees is to look at the various data points that are generated by their behavior. This allows you to be unbiased in your decision-making when it’s time to say goodbye. The 5 data points I suggest you focus on are:
- Total Down Time. What % of their shift did they miss plus what time it takes for them to get ready to work (logging in, opening systems, etc.) plus any time out of production you use to counsel them. Take this number and compare it to someone who comes in early, is ready to go when the clock starts and you never have to pull out of production to give warnings too. You will see a surprising difference of how much less time habitually late employees are contributing for the same pay
- Distance To Work. Look at how far they have to travel every day to get to the office. I am betting its further than most. There is generally a strong correlation between schedule adherence and distance to work. Not always, but a high % of the time.
- Difficulty of Commute. Look at the commute they have every day. How much time do they spend in traffic? Do they have to switch transportation modes? Is their route full of unpredictable impediments? It’s likely that challenges in their commute also have something to do with their consistent tardiness.
- Quality Scores. Again, as a general rule, employees who have trouble getting to work on time also have lower than average quality scores.
- Primary Production Metrics. Likewise, you generally see lower production metrics from employees who don’t start their shift ready to go.
“When simply walking by their desk to acknowledge a late arrival doesn’t stop the issue, it is probably time for a one-on-one meeting with a frank discussion.” Use this one-on-one time to review these metrics. Share with the employee some insights into why they might be late so often as well as how it effects the business.
It’s my experience that when you show them the data, it generally has a much more profound impact then just talking about things in a general sense. The power of your total down time is the highest on the team. You have the longest and most challenging commute. Your QA scores and production metrics are in the bottom 25% of the entire team. All of these can either be more motivating to the employee or they can provide a good reality check.
“Being proactive as a manager while showing you understand and even relate to their personal situation might enhance that employee’s performance over the long haul. It is vital you take the steps to get to the bottom of the issue before contemplating further discipline.” Using these data points in your verbal, written and final warnings add much more weight to your counseling. And when/if they finally hit the 3rd strike, you have a lot more data-based rationale behind your final decision. See the original article here:
If you need help in coming up with a way to build more analytics in your schedule adherence and discipline process, just let me know. I am happy to help.
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