Process Innovations for Operational Excellence

By Alfred Sherk, SherTrack

The pharmaceutical industry has made dramatic contributions to improving both life expectancies and the quality of life around the world, yet it finds itself under tremendous pricing pressure for its products.

“Operational excellence, stated simply, is minimizing waste while maximizing customer value”
-Alfred Sherk, CEO of SherTrack

This pressure is compounded by findings of a recent McKinsey & Co. analysis of the pharmaceutical industry that, "the internal rate of return (IRR) on small-molecule R&D is now around 7.5 percent, which is less than the industry's cost of capital". While increasing the pace of innovation could elevate returns, operational excellence has become a strategic necessity for the long-term vitality of the industry. Operational excellence, stated simply, is minimizing waste while maximizing customer value.

Relative to other complex manufacturing industries, there are two egregious top-level measures of operational efficiency that can be effectively used to drive operational excellence. The first measure is end-to-end throughput time of the production life cycle from the first chemical reaction through distribution. The second is the total amount of inventory. At the beginning of Toyota's long journey to becoming Lean, their leadership focused on removing inventory and wait-time from their manufacturing processes. At that time, their end-to-end cycle time was in the range observed in the pharmaceutical industry today. Excessive throughput time is caused by the lack of synchronization of key processes or operational complexity that is being ineffectively managed.

Novartis' continuous manufacturing paradigm, a component of their Lean program, has led to the reduction of their overall throughput time from 550 days to 200 days for some of their major products, and they see the opportunity to get it to just one month. If Novartis can achieve this level of performance, the implied productivity gains are gigantic. Moreover, every operational decision they make will be better informed by real customer demand.

Total inventory is also very high in the pharmaceutical industry. According to a recent IBM study, inventory turns are just 3.4 times industry wide. Unlike most other industries, the lives of patients are potentially at risk if a pharmaceutical is not available when needed. However, inventory ties up financial capital, which is increasing expensive as a result of the credit crunch. From an operational excellence perspective, excess inventory frequently masks incapable work processes. Reducing inventory exposes these incapable processes and affords opportunities to redesign them.

The Lean Six Sigma movements provide the framework and tools to identify waste and methodically address operational issues. However, the operational processes that need to be addressed for meaningful end-to-end cycle time and total inventory are usually global and cross-functional in reach. A central tenet of the quality movement is the understanding that every process has its capability limits; step changes in performance require process innovation. In this case, it is the enabling work processes that need to be re-thought.

Recent innovations in applying predictive analytics to customer demand signals and how they can be propagated down the supply and production chain have allowed the adoption of the Lean pull process in operations that previously were deemed too complex to use the Kanban type process. Demand-driven manufacturing builds on the Lean pull model and extends it beyond assembly operations into complex manufacturing. Furthermore, advances in probabilistic algorithms have led to significant performance gains in complex production operations, in terms of on-time delivery, overall equipment effectiveness and inventory. Innovations in predictive analytics and probabilistic algorithms offer pharmaceutical producers new options in their drive to operational excellence.

Alfred Sherk is the founder and CEO of SherTrack, a provider of innovative, predictive analytic solutions for synchronizing supply with demand. He is a past member of the Technical Advisory Board for Michigan State University's Graduate School of Business and is a limited partner in North Coast Technology Investors LP.