Evaluating performance in a research lab - from data to decisions

Laboratories are one sector that can benefit most from standardization, especially when it comes to performance. Without strict guidelines or standards to abide by, labs are often forced to rely on themselves to figure out how to produce not just a high volume of relevant results but reproducible ones too. The difficulty with standardizing KPIs stems from the nature of scientific research, as performance criteria are nearly always different from lab to lab. With that in mind, there are still a few key performance indicators (KPIs) relevant to the scientific continuum, complete with optimized methods of analyzing and reporting them to help assess your lab’s level of efficiency. 

Selecting KPIs

KPIs are specific t the type of lab analyzing them, whether it be an industrial research lab, academic research lab, or laboratory service (or analytical lab). KPIs can also be grouped according to function:

• Business-related, which account for factors related to finances and profitability. These might be things like the annual budget, monthly revenue, amount of money spent on consumables, and the number of research grants won per year. 
• Usage-related, which accounts for equipment and consumable usage and maintenance. Examples might include the number of times a flow cytometer is used per month and how many times it undergoes maintenance per year. 
• Results-related, which account for data and deliverable production. These revolve around the generation of research results and/or deliverables made in service labs, like antibodies, primers, or small molecule compounds. 

In 2018, Mahmoud et al published an exemplary article regarding key KPIs necessary for the success of research laboratories. In it, they described 161 KPIs belonging to nine categories: space, access/circulation, environmental conditions, utilities and waste, furniture, appearance/finishes/image, communications, storage within the space, and special building features. Interestingly, these KPIs aren’t all a direct result of personnel decisions; many can be altered at the level of architectural design and planning, suggesting that lab efficiency can be determined at the very start [1].

Integrating digital tools to generate KPIs

Digital tool integration will vary significantly depending on what kind of lab you work in. While academic labs may only rely on a single laboratory information management system (LIMS), personnel in industrial labs may need to coordinate data from their LIMS, inventory management system, enterprise resource planning (ERP) software, and quality management system (QMS), and equipment booking system. 

Integration should occur from the start; selecting software developed for easy integration with other systems is critical to simplifying KPI measurements. Database integration among the many platforms is key as it allows raw data to be shared, combined, and analyzed as one dataset instead of several independent ones. It is also recommended that all interconnected systems use a secure, cloud-based platform, which helps optimize data transfer and analysis throughout the lab or department. 

The recording of raw data should be fully automated to make it easy to integrate and generate a full report. Calira is a typical example of software that does this, where evaluations of a variety of different data, such as users, equipment, group, duration, cost, and the project used can be downloaded at any time via a cloud-based service. These measures can then be analyzed alongside data derived from other systems to form a full KPI report that tells the user whether they have hit their goals. 

Improving KPI performance

Though efficiency can be somewhat improved using small changes here and there, the best way to ensure productivity is optimized throughout the entirety of your lab workflow is using Lean-six sigma.

Lean focuses on a managerial approach to improve success, and thus boost KPIs. It removes waste and reduces errors by eliminating resources that have no value to the workflow. 

Lean utilizes the following strategies [2]:

• Value is specified by product family
• All steps in the value stream are identified for every product family, and steps that do not create value are eliminated
• Value-creating steps are made to occur in a tight sequence so the product (or lab analysis) will flow smoothly toward the intended recipient (e.g., the customer)

As flow is introduced, recipients can pull value from the next upstream activity, and as valuable steps and resources are identified, wasted ones are removed. This process can be repeated until perfection in the workflow, with as little waste as possible. These principles have been around for quite a while, and several examples have documented their use, including a COVID-19 testing lab at UCLA, where a series of changes were implemented based on Lean principles, reducing turnaround time by a full hour and mitigating errors along the way [3].

Overall, KPIs have the potential to standardize laboratory functions by transforming even basic functions, like equipment usage, into measurable statistics that can be analyzed to yield valuable information. By selecting the right KPIs and installing a framework to observe how they trend over time, it’s possible to make key adjustments throughout in order to increase efficiency and become more cost-effective.