The ultimate guide for lab planning and scheduling digitalization

The landscape of biopharmaceutical lab operations has drastically evolved in the last decade. With constrained budgets and accelerated timelines, pharmaceutical companies must optimize resource usage and prevent capacity bottlenecks. This guide aims to help lab operations leadership achieve operational excellence through digitalization.

In this guide, you’ll discover:

1. The Future of Pharma QC Labs

Digitalizing the lab is more than just going paperless. It’s about process optimization and efficiency gains.

In one of our user meetings, somebody summarized it beautifully: “the initial goal was to go paperless, but it’s about more than just that. The real value of digitalization is not that it replaces paper. It’s that it should make our processes more fluent, resulting in gains in efficiency and ultimately allow us to develop new medicine faster”.

Why You Need to Move Beyond Paperless

In a continuing effort to reduce costs and increase lab efficiency, many companies are looking to digitalize and automate laboratory processes, e.g. by going into more detail in LIMS and/or ELN. Such extensions can include capturing all method details (with or without a CDMS) and go as far as bidirectional instrument integration. It’s clear such digitalization helps to increase data integrity.

McKinsey published an interesting article on the vast improvement potential they see in pharma QC labs. The article positions three possible horizons for which QC leaders can aim.

McKinsey’s Three Possible Horizons for QC Labs

1. Digitally Enabled Labs: Emphasis on connected instruments and advanced planning.
2. Automated Labs: Focus on automated testing processes.
3. Distributed Quality Control: Real-time testing at the line.

Key benefits

2. Why Excel is Outdated

Many lab managers are becoming some sort of spreadsheet gurus. Though spreadsheets allow a business to set up things fast and they’re extremely flexible, at some point, they mutate into unrelenting monsters that become uncontrollable, produce errors and eat a massive number of working hours. This in turn results into hidden costs for all the 4 following reasons:

1. No Single Source of Truth: Multiple teams maintain separate data sources.
2. Data Accuracy Issues: Frequent checks and re-checks.
3. Changing Requirements and Planners: Excel sheets become outdated and require frequent updates.
4. Inaccurate Capacity Planning: Excel is not built for complex “what-if” scenarios.

The Hidden Costs of Excel

In Lean Six Sigma the hidden factory is defined as “the extra useful, positive output that would theoretically be possible if the energy directed at creating waste were released”.

We assume that the initial creation of the resource planning sheet is useful. Entering data and evaluating output to prepare planning decisions is considered as useful as well, but not if the same is replicated across all teams. Then of 5 teams, 4 of them end up as waste.

3. Six Steps to Optimize Your QC Lab Resource Planning

4. Retain Your Most Valuable Asset: Lab Analysts

With the ever-growing focus on improving lab efficiency and service levels, now more than ever, it’s crucial not to lose sight of your most valuable asset: your people.

The rule of thumb to preserve employee retention is straightforward: amid optimizations, lean lab exercises, increased lab efficiency, better service levels, etc, it’s crucial to keep reminding everyone involved that our people are not machines. Although this might sound self-explanatory, it’s often challenging to find the right balance in a lab context.

For instance how can you optimize your ways of working, within the boundaries of what is possible and comfortable for our people? Here are 4 guidelines to keep in mind when answering that question:

The Binocs algorithm is built around these 4 guidelines

Of course, we wouldn’t be talking about these guidelines without taking them to heart. People are not machines, and that’s also the idea around which Binocs is built.

5. Use Case: Building Your Business Case for Lab Automation

Using automated systems in the lab can save researchers from performing time-consuming and repetitive tasks. This frees them up to carry out more specialized processes. Also, automating laboratory tasks improves the efficiency of experimental processes by speeding up tasks, using lower quantities of reagents, cutting waste and allowing for higher throughput of experiments. This higher efficiency leads to lower running costs for the laboratory.

Sounds great! But before getting ahead of yourself, there are two critical questions to ask yourself before implementing.

Which Lab Activities Should You Automate?

Just like with anything else in life, lab work is subject to Pareto’s 80:20 principle: your lab analysts spend the majority of their time on only a relatively small number of test methods.

• Perform a Pareto analysis.
• Analyze your role-cards / standard work workflow and determine which specific activities within that workflow are ideal candidates for automation.

How Much Efficiency Will You Gain?

• Use What-If simulation capabilities to forecast ROI.
• Measure time saved and productivity improvements.

6. How to Choose the Right Lab Resource Planning & Scheduling Software

Conclusion

You now have the knowledge and tools to successfully digitalize your laboratory planning and scheduling operations. Biopharma laboratories who digitalize their lab operations management today will have a competitive advantage tomorrow over those who will start their digitalization process later. You don’t need LIMS, ERP or any other digital tool first to start your journey towards laboratory operational excellence.

Remember, “scheduling automation and optimization can be implemented quickly and start generating significant value even if a lab is not yet mostly paperless and fully digitized“. Start your digitalization journey today to reap significant long-term benefits.

They already digitized their lab planning & scheduling