As shown in a recent Lab Manager survey, most labs are facing challenges centering around both budget and staff. Consequently, labs are being asked to do more with less. To accomplish this, lab managers must focus on developing data-driven processes to make effective priority decisions and schedule work intelligently. Here are some strategies for lab managers to optimize the ROI of their lab’s people, equipment, and processes through effective scheduling.

Variable workload

Most labs experience variable workloads with peaks and valleys. In labs with multiple different functions, like an analytical testing lab, each function will experience its own peaks and valleys. The overall lab workload is the sum of these different workload curves.

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To meet budget and stakeholder needs, labs should be staffed in the middle of the workload curve. 

To be cost effective, labs need to staff somewhere between the peaks and the valleys. Staffing for the peaks is too expensive and would result in an underutilization of the expertise of the people. Staffing for the valleys would result in important technical work being late or incomplete and the lab underdelivering for key stakeholders.

To meet budget and stakeholder needs, labs should be staffed in the middle of the workload curve. This middle ground provides the foundation for the scheduling decisions required for the lab to demonstrate productivity and flexibility.

Inputs to scheduling decisions

Effective scheduling decisions can benefit from numerous different inputs:

• Dynamic workload data for each different functional area of the lab. This is often available from the laboratory information management system (LIMS).
• Which staff are best suited to execute particular tasks. This is often available from training records in a quality management system (QMS).
• The number of available hours for technical work. These data involve the full-time equivalents in different areas, overhead, and paid time off.
• The availability of needed equipment. This is often available from the QMS.
• Expectations of how long different activities will require. This is often available from timesheet data.
• Stakeholder expectations and due dates. This can often be found in the LIMS.

Prioritization

Lab managers must make priority decisions to help the team optimize the workflow. An effective approach to prioritization is represented by the Eisenhower Matrix. It is a 2x2 matrix showing high and low estimates of importance versus urgency. Productivity is enhanced by driving work that is high in both importance and urgency, planning work that is high importance and low urgency, and limiting the work on low importance activities.

Example of an Eisenhower Matrix

Improving flexibility

There are several actions lab managers can take to improve the lab’s operational flexibility:

• Cross train: increase the number of people who can cover important activities. This enables greater use of staff when their primary work area experiences a workload valley.
• Monitor progress: actively track the status of all projects in a LIMS.
• Document standard methods – ensure consistent performance on important activities and reduce the time required for training.
• Consider outsourcing options – focus the lab on what it does best and find external partners to tackle the one-off projects.
• Focus on strengths – help staff develop their strengths and work primarily within them. Reduce time working in weaknesses.
• Delegate decisions and train area leaders to make good data-driven decisions

Lab managers who consistently make effective priority decisions and develop flexibility in their staff will demonstrate improved efficiency and productivity, driving their labs to success in delivering their mission and purpose.