Leveling-up Lab Scheduling with Digital Transformation
How automated scheduling reduces costs, increases efficiency, boosts insight, and improves operations planning
Anneleen Tronquo, managing partner of Planning Solutions at Bluecrux, has over 15 years of experience in running planning transformations. Leveraging her strong life sciences planning and change management expertise, she has led teams to deploy major supply chain planning transformations at leading global pharmaceutical and CPG companies.
Frederik Jaenen, VP Sales Binocs at Bluecrux, has over 25 years of experience in lab systems, including program managing major LIMS rollouts at various global enterprises. When he joined Bluecrux in 2017, his expertise and business development skills significantly boosted the commercial success of Binocs.
Q: What is the business case for automated digital lab scheduling?
FJ: There are three levels. At the first level, automated scheduling significantly reduces hands-on time for the people responsible for scheduling and planning, who often need to spend hours each day creating and adjusting work plans, potentially saving multiple full-time equivalents at multi-lab sites.
The second level covers the overall throughput, productivity, and efficiency of the technicians, analysts, and equipment. These efficiency improvements for lab managers can lead to a 10-30 percent increase in productivity, typically.
The third level centers on the VP of Quality, overseeing the whole operational supply chain of moving goods from raw material to the consumer. Lead times are very important here—the cost of storing products can depend on the last step on the critical path, often QC. Lengthy or unreliable lead times result in inventory holding costs (space, conditions, insurance, etc.) that can amount to 15-30 percent of the product cost annually. Automated scheduling spanning divisions can reduce lead times by days, which can represent millions in cost and capital savings.
Q: Why have scheduling solutions only recently been applied to quality lab operations?
AT: There are a few reasons. Firstly, quality departments are staffed primarily by highly skilled scientists who work from an analytical and scientific perspective—planning and scheduling isn’t always their natural habitat. Secondly, the immense pressure on supply chain and lab activities applied by COVID has led to a drive for more efficient planning, triggering the question: If we plan manufacturing assets, why can’t we also plan and schedule our quality assets? Finally, the rapidly changing global ecosystem and resulting pressure on pharmaceutical supply chains mean that quality departments are now expected to achieve far more with limited resources, placing even greater focus on efficiency, improvement, and planning.
Q: Why is traditional paper-based lean lab scheduling no longer sufficient?
FJ: We see rapidly growing complexity in many laboratories—it’s increasingly common for labs to test multiple products at various production stages in addition to ongoing stability testing; multiple laboratory sections often work in parallel on the same batch release. This introduces different priorities and often different service levels for a more complex operating model that overwhelms traditional scheduling with manual decision-making and follow-up.
By digitalizing the scheduling process, labs can effortlessly cope with large amounts of information and complex operating models while retaining the benefits of lean methodologies. This is a game changer, allowing real-time recalculation based on new information and impact predictions for different scenarios—for example, if particular analysts are sick, will there be late batches?
Q: How can existing lab systems such as LIMS contribute to scheduling?
FJ: LIMS are focused on samples and tests, so can pro-vide a detailed picture of current workload and back-log. It is a great source of data for defining short-term scheduling requirements, but effective lab scheduling must balance all tasks—including meetings and project activities—and analyze these intelligently to deliver the optimal workplan, ideally also predicting longer-term capacity-planning needs.
Q: What does greater collaboration between lab and supply chain mean in practice?
AT: At the local level, greater collaboration decreases lead time and results in a more efficient flow, faster time to market, and faster delivery of products. At the network level, sales and operations planning (S&OP) processes have traditionally assumed that manufacturing capacity bottlenecks can be mitigated via collaboration between the leadership of the commercial, manufacturing, supply chain, and finance divisions to review capacity utilization in critical overloaded assets (e.g., packaging, tableting, and compression machines).
However, I think the recent pressure on the market has made companies realize that the S&OP process needs to include the VP of Quality. A consolidated view on the manufacturing asset capacity is good but, without sufficiently staffed and skilled quality teams to perform the releases, the product will never make it to market.
Q: How can better operational decisions reduce the need for firefighting?
AT: Labs with poor visibility on operations must spend a lot of time “firefighting”—living day-to-day, constantly reacting to changing priorities, unexpected re-tests, and new work. Time off can get canceled due to unplanned and urgent tasks, and working environments can become increasingly tense, making personnel retention a major challenge.
Looking a couple of weeks ahead with digital scheduling definitely helps but labs must also consider longer-term business planning. Will production volume increase or new projects add demand? Is two weeks really enough to train an analyst or prepare outsourcing contracts?
Long-term visibility on capacity requirements helps to identify the best solution, whether investing in extra equipment, outsourcing, or moving personnel between labs. Done properly, such changes can create stability in the lab.
It also provides an advantage for retention that we haven’t yet quantified—human capital is scarce and reducing stress can help protect investments in long-term training. One customer, for instance, reported that their analysts now plan flextime more easily with the automated schedule, which contributes to a positive mood in the lab.
Q: What is the typical implementation time for Binocs?
FJ: Binocs is a cloud-based, fully-configurable solution for lab scheduling and operations management and is readily connected to other lab systems (such as LIMS and ERP) to deliver optimized workplans based on the most current data. Our three-to-four month lead time includes dedicated expert support for lab managers and planners, access to our e-learning academy, a personalized playbook, and a full customer support service.
We’ve also used our experience with over a thousand laboratory teams to develop best practices for scheduling and performance management. We’ve distilled these into a range of preconfigured workflows to handle common situations and preconfigured dashboards to report common key performance indicators (KPIs), which together facilitate implementation, increase adoption, and accelerate return on investment, allowing clients to start quantifying benefits after just three months of use.
Want to learn more? Visit http://bluecrux.com/binocs/lm