The role of Lean and Six Sigma in drug discovery and development is a controversial topic. Does Lean Six Sigma improve innovation or stifle it? A recent article in Drug Discovery Today offers new perspectives, analysis, and suggestions that I found encouraging.

While acknowledging the contradicting perspectives and experiences many organizations have, the authors see the value of Lean Sigma in pharmaceutical innovation, such as

· Root cause exploration that stimulates new ideas

· Powerful tools that enable staff in problem solving

· Value and philosophy that encourage learning and risk-taking

· Activities that engage the workforce

More importantly, I am glad that the authors highlighted three potential traps in the deployment.

1. Standardization. Citing The Toyota Way (J.K. Liker, 2004), they point out: “In the context of continuous improvement, however, the standardized state is not a desired final destination but is a meta-stable situation intended to provide a platform for further improvement because it makes it easier to propagate any improvements when they are discovered.”

In my opinion, standardization is one of the most misunderstood concepts in Lean. Scientific learning and advancement has always been built on standardized, rigorous processes. It’s how we conduct science and how we learn. Surprisingly, many scientists have a negative reaction to “standardization.” Maybe in practice, they confuse it with “management control.”

2. Variation. “Once the distinction between desirable and undesirable variation is recognized, the benefit of process improvements to provide fast, reproducible, stable and comparable results in a predictable and dependable manner is self-evident, as is the overlap with faster learning cycles and more effective innovation.”

The concept of “variation is evil” is also largely misunderstood by many scientists, who often argue that the discovery or innovation requires variation. Yet, they all understand the concept and role of signal and noise in their experiments. How many fewer/smaller experiments would we have done if the noise in the process were reduced by half? How many resources and how much lead time would we have saved? How much more time could people spend on actually innovating, instead of performing unnecessarily large/complex experiments? The savings and opportunities are unimaginable when you consider the costs of bringing a drug to market. [I do recognize that not all variation in this process can be controlled. But opportunities are still large.]

3. Capacity. “The disadvantages of operating at maximal capacity are not only limited to restricted freedom for exploration, however, but also include the inevitable creation of queues and waiting when problems arise; in research, because of the nature of the work, unpredicted events and problems arise frequently.”

Capacity planning is where Lean Six Sigma concepts can really help. Excess capacity and degree of variation directly affect process lead time. The common management mistake of attempting to operate the capacity (people or machines) at 100% is well documented. It not only creates waste (overproduction, inventory, waiting, …) but also makes the system vulnerable to variation (either in demand or in production), leading to bottlenecks and delays.

In the pharmaceutical industry, where the lead time to market is critical, mistakes are made every day to improve capacity utilization, which inevitably leads to long delays due to the nature of variation in drug discovery and development. Many managers seem to consistently ignore this reality and fall into the trap of maximizing resources/capacity by downsizing the workforce or adding new projects. In addition, failure to prioritize and control the size of the project portfolio (WIP) also prolongs the lead times (by Little’s Law).

To innovate and to accelerate the time to market, we must manage the capacity with Lean concepts in mind, and we must reduce undesirable variation.

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