‘Productivity Tip: Stop Moving Your Star Workers’

July 3, 2025

Harvard University in Massachusetts has been in the news lately—and often for the wrong reasons. Yet, its publications offer many useful insights. For example, the above headline in the Harvard Business School publication Working Knowledge caught my attention.

Jorge Tamayo, Ph.D., accessed hour-by-hour data on 20,000 workers assigned to 120 production lines in six factories to reach this conclusion: Stop moving your star workers. I correlate this to AICC members, independent converters who always say yes. Yes creates opportunities for AICC members while coming with some interesting challenges.

You land a new client or take an order with a tight delivery. Do you move top performers to other lines to better meet schedules or remove bottlenecks?

The research shows that simply moving top-performing employees to underperforming or slower production lines in response to a demand surge can have counterproductive outcomes. Research in operations and workforce management shows that assigning workers based on their specific skills, team dynamics, and line compatibility can significantly boost efficiency compared with blanket reallocation.

Here are a few key insights from the research:

Moving top workers without considering their interdependence history with teammates and managers can reduce overall output.
Productivity on manufacturing lines depends not just on individual skill but also on team familiarity and task-specific learning.
Learning curves vary by worker and task; placing someone on a line they’re unfamiliar with might reduce short-term gains.
Disrupting established team structures can lower morale and create friction, especially if others feel undervalued or left behind.
High-performing teams had diverse but complementary skill sets and stable team compositions.

Train certain employees as generalists who can easily shift from one line to another, whether to help with a large order or fill in for absent employees. These floaters can be deployed to slower lines to pick up the slack without needing to transfer faster workers from other lines. The fact that they are known as floaters can reduce the possible friction moving a top performer can create.

Advanced analytics and operations research suggest using historical performance data, individual learning rates, and line-specific challenges to guide staffing decisions. This is known as “smart staffing”—allocating not the best people but the right mix of people.

Harvard is not alone as a source of ideas and research. AICC’s Packaging University, the AICC NOW website at now.AICCbox.org, AICC white papers, and the availability of AICC’s “Ask the Experts” are a keystroke away to support you as you face the challenge of productivity, hiring, training, and retention.