Optimizing workforce allocation

‍

We focus on making it easier for industrial businesses to put the right people with the right skills working on the right job at the right time. In this post, we’re diving into the very tactical needs of leaders on the frontlines — supervisors, foremen, captains, shift/cell/zone/area leads, etc.

Challenge

Many industrial companies face the difficult challenge of forecasting how quickly end-market demand will ramp back up (think: business and personal airline travel, new car sales, etc.). As a result, it is difficult to know how many workers they need, which workers they need, when they need them, and then which workers are available. Now layer on the fact that daycares and schools may not reopen as planned (i.e., kids are still home), some workers have underlying health conditions, many companies have rolling furloughs where different workers are out different days of the week, or that frontline leaders that keep track of who knows how to do what — in their heads or on spreadsheets on their desktops — may no longer be with the business. All of these factors taken together are making it extremely difficult for businesses to know who can/should work on what when. It’s a very dynamic situation.

Solution

Plain and simple, it’s imperative that frontline leaders have real-time visibility into 1) who is on-site and 2) what skills they have. Without these real-time data points, it’s difficult to make operational decisions. In an ideal world, frontline leaders would get an email at the start of every shift with a skills matrix that is scoped down to their team/shift/cell/zone/area, showing coverage gaps based on who has clocked-in that shift, filtered for what work needs to be done that day (i.e., work-in-progress, aka WIP). It’s an optimization problem that can be visualized in real-time with the right data in place:

‍

‍

Now imagine if there was a gap that needed to get elevated… in response, the frontline leader should be able to easily drill-down to see who else is cross-trained but possibly working in a different area or who may be off-premise (i.e., on a different shift).

Cost Savings

• Improve resource allocation and shift planning, as ensuring coverage reduces the cost of poor quality (COPQ)
• Give supervisors critical time back pre-shift

Conclusion

Arming frontline leaders with accurate skill data can significantly improve agility and save costs, especially in volatile environments. Just as important, it’s one less item for them to troubleshoot and gives critical time back to focus on higher-impact initiatives.

‍