Skills Inventory = Institutional Knowledge

An Automated Labor Scheduling (ALS) solution is only as good as the data it uses and here’s the data we’re going to need. There are five different types of data:

1.    Production Plans
2.    Jobs
3.    Employees
4.    Absences
5.    Skills Inventory

Although there’s more to be covered, Production Plans are addressed in our blog post Production Planning vs Labor Scheduling. The next three types of data should be relatively easy to find and will be addressed in a following blog. However creating a real “skills inventory” usually requires some work and this is the one we’re going to start with. You can’t generate a labor schedule without it.

If the skills data is limited to what’s found in HRIS and/or Payroll systems these won’t include the fine-grain information we need for a labor schedule. As an example, for payroll, an employee may be classified as a packaging machine operator. However which machine is he/she qualified to operate? Is a packaging machine the same on one line as on the next? Operation can vary for an older machine compared to a newer one. Or, the same kind of machine provided from one vendor versus the next. We need to know. If it’s a complex machine, when did they last work this job? Has this skill become non-current? If it’s been some time, can they damage product or are they even safe? This type of data for training and job-assignment history is an essential foundation piece required for a fully ALS solution. So, for each employee here is an outline list of skills data we need:

•    Certification, if required, plus time when certification will expire
•    Qualification
•    When qualified
•    Qualified by whom
•    Last worked date
•    Currency with this qualification
•    Additional training required
•    Any special limitations? lifting, climbing, etc.

In most cases this skills data is “is institutional knowledge”. In other words, it’s known only to those front-line managers who’ve been there long enough to have it at their fingertips. As a result, this data is only available when those department heads or shift supervisors are actually on the job. So installing an ALS solution is a great opportunity to create a skills inventory database which captures this knowledge. Once captured, it’s available for two purposes; when those experienced front-line managers are not around and, when planning and modeling schedules for the future. Also notice that a lot of this skills data is time sensitive. It will expire over time. So a good ALS will automatically capture and update this skills data as schedules are executed and stored. Having the training department or training manager closely engaged with the ALS system so they can add and update skills to the system as workers are trained is a big asset.

The main point: skills data is perhaps the most critical data when an ALS system actually solves a schedule. How many people in your skills Inventory can actually fill each job assignment? If you have to move a worker from one position to another, where will they be most valuable? If they are otherwise unassigned, again where will they be most valuable? These are the kinds of questions that a scheduler has to answer quickly and usually under pressure. This is an ideal chore for an ALS.

Another observation is that we really don’t need to have this data in an integrated payroll or HRIS system. Firstly, the necessary skills data isn’t going to be found there. As you can see from the skills data listed above, this information only really supports an ALS solution. It doesn’t support payroll or benefits. As long as you have a convenient tools for exchanging data with HRIS and/or payroll, all of this data can easily be managed in a well designed ALS solution.

Without this fine-grain skills data, the labor schedule will not be reliable. Without reliability, under the pressure of last-minute changes the schedule can’t be depended upon. Without reliability, the labor schedule wont tell you if your production plans can actually be carried all the way to delivery or the loading dock.