Integrating new strategies for the optimization of lab workflows often takes place in the short term, within a year or so; however, the intent of most strategies is to increase productivity and mitigate errors over long periods. Here are several tips to help monitor and optimize workflows over the long term, so that the lab is continually improving, regardless of external circumstances.
Find the right KPIs
Knowing what to measure is the first step to maintaining lab optimization in the long run. For commercial labs, revenue, cost of analysis, and time required to perform analysis are likely three of the most valuable KPIs. However, things are not always as straightforward for academic labs. When it comes to business-centric KPIs, academic labs might want to look at:
- Number of projects currently in progress
- Allocated budget per project
- Number of research grants
- Average revenue per grant
- Number of full-time employees and/or students
- Number of oral/poster presentations given
- Number of scientific publications per year
Lab performance KPIs can also be used more granularly to determine the efficiency and productivity of lab workflows. Some key KPIs in this area include:
- Turnaround time
- Time spent doing bench work
- Consumable use and waste
- Sample throughput
- Free space available in incubators, refrigerators, and freezers
Upgrade workflows to digital
Digital workflows have become the standard in labs across the globe. With the help of laboratory management information systems (LIMS) and electronic lab notebooks (ELNs), workflows can be managed online, with samples and inventory tracked virtually, in real time, with the help of barcode and/or RFID labels and scanners/readers. These tools can help optimize workflows by making them more visible and automating data collection, tracking, and analysis. Because they make workflows more visible, they also serve as the primary facet by which lab managers and supervisors can monitor KPIs and ensure that all lab functions remain optimized for the long term.
Invest in training
Training is often an afterthought, particularly in academic labs, where new students and staff enter the lab on a regular basis and require others to help understand the basics of biological research techniques. However, training can serve several purposes: it introduces the method, allows users to practice, and by issuing follow-up sessions, it can ensure that users are performing the technique properly over the long run. By investing in additional training sessions over more extended periods, staff can ask questions and troubleshoot new problems while ensuring the technique is adopted correctly and providing accurate, consistent results.
Adopt Lean & Six Sigma
The idea behind Lean and Six Sigma methodologies revolves around improving process quality to eliminate waste, mitigate defects, and enhance output. The key to Lean and Six Sigma is that they don’t occur just once; it is a continual process that requires testing and problem solving over a lengthy period. Notably, these methodologies are adapted to the lab’s budget, which means that as budgetary limits increase or decrease, the areas where Lean and Six Sigma can be best applied will also change.
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