Backlog and efficiency

We were recently involved in the discussion regarding how much backlog is needed to ensure the lab is efficient while not making the lab itself become the site bottleneck (e.g., very small backlog means small campaign and less efficient Lab’s operation, high backlog means high cycle time). Before addressing this question, let’s try to define the lab backlog; our definition is the amount of work (in terms of hours) we have logged in the lab divided by the number of hours the lab could allocate for testing and review. In other words, if my backlog is 2 weeks (i.e., if we have 1,000 hrs required and the lab has 500 hrs available per week it can allocate per week then, the backlog is 2 weeks) and it takes 1 week on average to perform the testing and review, therefore a new sample arrives, will need in theory to wait about 2 weeks (assuming FIFO is used for simplification) and then another week for test/review; this brings us to 3 weeks in order to release the sample. We know it is not completely accurate as the sample may be campaigned with another sample that is already part of the backlog. Here are some guidance to addresses this dilemma. First is to understand the expected turnaround time from the lab; for example, if the lab turnaround time is ONE week, then any backlog more than a few days will mean the lab service level will be poor. Assuming the lab expected turnaround time is 2 weeks and the testing and review is 1 week, then having ONE week of backlog will allow the efficiency of both on-time delivery and reasonable campaigning. As long as the backlog is at least ONE week, it provides the lab the ability to campaign a week worth of samples to increase efficiency. It also provides sufficient workload for the analyst. When the backlog is too small it means the lab is most likely not campaigning as much and working at a low efficiency level. The analyst is not seeing the need to work at a high efficiency since the work will be completed in 2 days and they will not have much to do after. Companies should strive to have a relatively high backlog (which usually happens at the lab for example 1.5-2 weeks), make the proper improvements to reduce the backlog by improved scheduling, implement a continuous improvement culture and more. As the lab improves its efficiency, the backlog will drop to below ONE week. Then if no increase in overall demands, the lab can re-allocate some of its resources to another group which will bring the backlog level back to let’s say 1.5 weeks. This process can continue where the lab reducing its backlog adjust the resource level as an on-going improvement process.