In the coming five to ten years, emerging technologies will drastically change the way analysts interact with equipment and processes in the labs. Such technologies include advanced analytics, AI/ML, robotics and advanced planning and scheduling, and automation. Those innovations will make laboratories more agile, reliable, compliant, and efficient.
What should we expect from this digitalization?
McKinsey & Company recently revealed some insights into what the impact of digitalization was for the first real-life use cases in the market. Their research is based on some of the few labs that went a long way in digitalization. In numbers …
- 30 to 40 % increase in productivity for mature and efficient lab environments
- More than 50 % reduction in overall quality-control costs
- An average chemical QC lab can reduce costs by 25 to 45 %
- An average microbiology lab would be in the 15 to 35 % range
- 65 % reduction in deviations
- Over 90 % faster closure times
- Decrease of QC-lab lead times by 60 to 70 %
- Reduction of the investigation workloads by as much as 90 %
Impressive, what is causing this impact?
These improvements can mainly be attributed to the elimination of up to 80% of manual documentation work and in parallel to the automation, and especially optimization, of planning and scheduling to improve personnel, equipment, and materials utilization.
Moreover, digital-enabled labs are typically characterized by automated data transcription between systems via direct interfaces and the possibility to create insights by applying advanced data analytics to optimize your schedule.
Why is not everybody increasing the level of digitalization in their labs?
The numbers look spectacular. Why don’t all labs engage in increasing the level of digitalization and automation? What is keeping them from implementing systems that automate and optimize their planning/scheduling? According to McKinsey & Company, there are two principal reasons.
- Firstly, many of the companies that are lagging still target fully tested end-to-end future-state prototypes rather than testing and rapidly scaling up digital solutions to obtain quick wins.
- Secondly, today we still see quality leaders often struggling to define clear business cases for the required technological changes, which makes it hard to convince the upper management on the benefits delivered by lab digitization.
What is the Binocs perspective?
At this moment, more than half of the big-pharma companies have selected or are evaluating Binocs as a digital twin for planning, scheduling and performance management of their QC and R&D labs. As opposed to four years back, when we launched Binocs, pharma companies have made their digital roadmap and prepare RFPs for massive roll-out programs. This is a clear indicator that digital lean in labs has reached the top three on the strategic agenda.
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