Most laboratory managers are familiar with the cost of lab operations, but few are trained to think of their labs as a production system that needs optimization in the same way that a factory needs to optimize every step of a fabrication process to stay in business.
There is ample evidence in scientific and business literature demonstrating that there is opportunity to improve lab productivity1,2. This process starts by analyzing what the lab produces and the associated costs.
Productivity is the efficiency of a production process—this is the ratio of the process output over the process cost. By increasing productivity, it is possible to increase profit margins by reducing costs without negatively impacting the production levels. Another motivation to increase productivity is to gain a competitive advantage by producing more with existing resources.
Whatever the reason that motivates the need to improve productivity of a lab, implementing a productivity improvement strategy is a four-step process that starts with measuring the lab outputs and works on reducing each of the three main categories of expenses.
Measure your lab production
It can be challenging to measure the output of a laboratory. Service laboratories like core facilities, contract research organizations, or quality control labs can use the number of orders they handle monthly as a good indicator of production. Labs that provide different types of services and charge users for processing samples can use revenue as an indicator of production.
The output of research and development (R&D) labs may be more elusive. Their ultimate outputs will be measured using indicators like the number of scientific publications, patent applications, or product launches. These statistics are not useful to improve productivity because they move slowly and have long lag times. R&D labs would benefit from identifying faster moving statistics that can be used as evidence that the lab is productive. For example, the number of data points collected can be regarded as a good predictor of long-term success.
Labs with diverse activities may want to keep track of more than one metric that reflects different aspects of their operations. As an example, a biomanufacturing process development facility could track the number of fermentation conditions, purification processes, and quality control processes tested, and aggregate them to measure their production.
Whatever the metrics used to measure the activity of a lab, the lab staff will need a way to manage the data they produce. If the lab uses a laboratory information management system (LIMS), the production stats are likely to be readily available from the LIMS. Labs that don’t have access to a specialized LIMS application need to keep track of their production in a system of spreadsheets. Putting such a system in place may feel overwhelming at first but it is worth the effort. Unless there is a way to measure what the lab produces, there is simply no way to report it and improve it.
Once the lab production data are available, they should be displayed in a graphical way to the appropriate stakeholders. At a minimum, they can be used to generate charts using Excel. These charts can be embedded in monthly reports to upper management. They should also be shared with the team and periodically discussed in staff meetings.
Production gains are more likely to be achieved if the lab production figures are displayed in a visible manner where the work takes place. Business intelligence tools—such as Klipfolio, Tableau, Domo, and others—make it possible to generate dashboards that display key performance indicators in visually attractive graphics.
Finally, the more frequently production stats are updated, the more opportunities there are to improve them. Updating monthly or quarterly may not be sufficient to take corrective actions when necessary. Updating them weekly or even daily provides near real-time feedback to the team and creates greater awareness of team performance.
Optimize the use of facilities
Laboratory space is expensive and often too limited. The acquisition of major equipment requires significant investments including pricey maintenance contracts that are fixed expenses incurred irrespective of the lab production.
Infrastructure costs are among the most significant expenses for a lab, and poor facility management can limit production and create hidden costs. Many lab managers may feel that there is not much they can do about facilities and equipment because they inherit the results of decisions they did not make. Managers do, however, have control over the way resources allocated to them are utilized. Maximizing the use of existing facilities should be a constant preoccupation since it is much easier to use existing lab space more efficiently than it is to move into a new lab.
“Unless there is a way to measure what the lab produces, there is simply no way to report it and improve it.”
A common example of suboptimal use of space is allocating benches to individuals in the same way that desks are assigned to office workers. Bench space is much more valuable than desk space. In many cases, it is prohibitively expensive to keep a bench unused when an individual is not working. Organizing space around workstations dedicated to specific operations is a more effective use of limited lab space.
Holding on to unused equipment and supplies also creates hidden costs. While it may seem cheaper to keep a piece of equipment because it may be useful at some point in the future, an unused piece of equipment occupies space that could be put to more productive use. Unused equipment is also likely to incur maintenance costs. Disposing of equipment that no longer reflects the lab’s needs is the most sensible way to proceed.
Optimize your inventory
Most labs manage an inventory of materials and supplies that may include thousands of items. Poor management of this inventory can undermine productivity in different ways. First, it can generate unnecessary costs. Having similar products from different vendors increases the price per unit, uses more space, and creates some procurement overhead. Many supplies have a limited shelf-life. Ordering more than can be used by their expiration date also creates additional costs. Some lab members may be tempted to use supplies past their expiration date to save the lab money, but that is often short-sighted because a failed experiment often costs more than reordering the supply.
It can also undermine reproducibility. Some protocols have been validated with specific supplies. Performing them with similar supplies from different sources can lead to unexpected results or experiment failure.
Lastly, it can create delayed results. The fulfillment of supply orders can take weeks or months. This problem is particularly important in 2021 when the life science supply chain has been strained by the COVID-19 pandemic. Running out of a single critical supply can put a lab to a halting stop.
Putting in place a robust inventory management system that allows all lab members to know what is available in the inventory avoids duplicating orders. All lab members should be able to search the inventory to avoid unnecessary orders.
Laboratory protocols and standard operating procedures should be developed with operational costs in mind. They should minimize the number of supplies in the inventory by reusing the same supplies for multiple protocols when possible. They should also compare the performance of premium supplies with cheaper generic supplies to determine if the premium supply translates into higher performance that justifies the extra expense.
Every supply should have an ordering policy. Specialized supplies with a high price tag and short shelf-life should be ordered on an as-needed basis. Commodity supplies used in many protocols should have a reorder point (quantity that triggers a purchasing decision) calculated based on the standard use rate and a conservative estimate of the order fulfillment process. The goal is to ensure that the lab never runs out of key supplies without bearing the cost of excessive inventory.
Use an information system
Like any business, labs operate in a competitive environment in which they are expected to do more with less. Any lab operator should be motivated to improve productivity because, at some point, executives or shareholders may question the return on investment of operating their lab and compare this option with outsourcing the lab function.
Many labs lack the information systems they need to measure their productivity and improve it. Measuring the production of a lab or optimizing inventory management requires data that many labs lack. Increasingly, lab managers are managers of data captured in LIMS software. In recent years, many new web-based LIMS solutions have been developed to meet the needs of labs of all sizes. These modern options provide features and data that labs can use to measure their production, optimize the use of their facilities, and streamline their inventory.
- Baker, M., 1,500 scientists lift the lid on reproducibility. Nature, 2016. 533(7604): p. 452-4.
- Freedman, L.P., I.M. Cockburn, and T.S. Simcoe, The economics of reproducibility in preclinical research. PLoS Biology, 2015. 13(6): p. e1002165.