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Modern technologies are making it easier than ever for labs to improve efficiency and business performance. Even non-experimental production labs that do routine testing can quickly identify bottlenecks and predict outcomes before implementing real-world changes. However, many labs still use spreadsheets or whiteboards for planning rather than leveraging one of the more robust modeling tools available. This limits the types of simulation they can do and reduces their effectiveness.
Spreadsheets present numerous limitations when used by labs for modeling. For example, they cannot easily handle increasingly complex processes when labs scale up their operations. Large datasets or intricate models can slow performance, make spreadsheets unwieldy, and lead to errors. Furthermore, relying on manual data entry and formula creation, spreadsheets are susceptible to human error — consider that a single mistake in a formula can propagate errors throughout a model, potentially leading to incorrect conclusions or decisions.
Because spreadsheets are frequently not integrated with other laboratory information systems, instruments, or databases, they can lead to redundant data entry, inefficient workflows, and a lack of real-time updates. Without robust version control, which version is the most accurate or up-to-date can be unclear. In environments with multiple contributors, spreadsheets can lead to conflicting changes, overwritten data, or even corrupted files.
While spreadsheets offer basic charting and analytical functions, they cannot match sophisticated tools with advanced visualization and simulation capabilities. This limits the lab’s ability to analyze complex scenarios or identify trends.
Finally, spreadsheets can also suffer from security vulnerabilities. They are often transferred via email or on shared drives, putting them at risk of unauthorized access or accidental sharing. Plus, they may not meet regulatory compliance requirements.
Labs that move beyond spreadsheets to use alternative digital informatics tools — such as a laboratory information management system (LIMS), specialized modeling software, or cloud-based solutions — can perform sophisticated virtual simulations for a more nuanced view of lab operations.
Three common types of simulation that could be applied in a production lab are:
If your lab wants to improve performance, you can use simulations to understand how different workflow scenarios will play out, the expected results of adjusted scheduling, the impact of lab changes on budgeting, and how to manage human resources.
Labs can apply simulations to understand how key performance indicators (KPIs) will behave under different workflow scenarios. For example, your lab could use a simulation to answer the following questions:
Virtual prototyping enables labs to safely test and refine scenarios without costly physical iterations for faster insights and innovations.
Labs can use simulations to aid in short-term or daily planning. Most labs already have a planner or supervisor who helps to develop schedules. Simulation software can assist the staff responsible for this task in making additional tweaks — based on demand, equipment utilization, or personnel availability — until the schedule is optimal. Popular features of lab scheduling simulation software include predictive analytics and visual workflow maps.
Taking simulations a step further, schedules interfaced with real-time data can adjust dynamically based on what is really happening in the lab to minimize idle time and maximize productivity.
Simulations can also aid long-term planning, helping labs forecast and plan for upcoming costs. For example, a lab can conduct simulations of growth, equipment wear-and-tear, and the use of reagents and other consumables. This can help with budgeting for the quantity and cost of consumables, new lab space, or instrumentation capital purchases.
Simulations can also help labs understand the impact of budget restrictions on output so they can make informed trade-offs.
Lab managers can also use simulation to help manage personnel changes, determining when to hire new staff or allocate staff to deal with unexpected absences for capacity planning.
Using simulations, labs can pinpoint stages where workflows slow down due to staffing issues. They can model different staffing configurations to test how adjustments such as adding staff to critical tasks could improve efficiency. They can also assess the impact of varying skill levels on operations and identify where additional training is needed.
With increasing demand for faster production cycles and higher quality control, simulation has become a vital tool for production labs striving to improve efficiency, minimize waste, reduce risk, and ensure regulatory compliance without disrupting live operations. By simulating potential scenarios, your lab can make data-driven decisions, enhance productivity, optimize spending, and maintain agility in a rapidly evolving industry.
Contact us to learn how your lab could use simulation as a strategic tool.
