The Misapplication of Value Streams: The Pitfalls of Small Dedicated Work Groups

Throughout quality teams it is common to find resources allocated to specific work streams and sub-streams with the aim of enhancing service levels. While this approach is well-intentioned, it often stems from a misunderstanding of a core Lean principle: developing value streams.

In a truly Lean organization, all value-adding activities are aligned, with a dedicated team responsible for the entire process. This holistic approach to value streams is crucial for improving cycle time and productivity, enabling organizations to fully realize the benefits of Lean. However, many companies misinterpret this concept, attempting to implement value stream structures only within isolated functional areas. The outcome? Small resource groups dedicated to narrow, often volatile, workloads, leading to significant inefficiencies.

For example, QC functions are often divided into areas like analytical chemistry, microbiology, and raw materials testing. These divisions make sense due to the technical differences in operations and required analyst skillsets. However, a concerning trend is emerging where QC groups further segment their teams, assigning individuals or small groups to specific products, techniques or even tests. With increasing pressure to reduce cycle times, it might seem logical to create dedicated teams ready to process samples as soon as they arrive. But this strategy is flawed.

The Pitfalls of Small, Dedicated Work Groups

Creating small, dedicated work groups with volatile workloads introduces two major forms of waste: mura (uneven workload) and muri (overburdened systems). These often-overlooked forms of waste can have a detrimental impact on performance, overshadowing the more familiar muda (waste). Unless mura and muri are addressed, efforts to eliminate muda will likely fail to produce sustainable improvements.

Let’s consider an example in a QC setting. When a dedicated group receives few or no samples for a day or two, the analysts might share the limited workload, leading to suboptimal testing practices. Alternatively, if fewer analysts handle the tests efficiently, the remaining analysts are left with “busy work,” falling prey to Parkinson’s Law: “Work expands to fill the time available for its completion.”

Conversely, when a small group is overwhelmed with samples, delays are inevitable. Increasing the number of analysts to handle peak workloads may seem like a solution, but it only exacerbates inefficiency during low workload periods. In both scenarios, small, dedicated work groups with fluctuating workloads are detrimental to performance.

The Case for Combining Work Streams

Image

To illustrate, consider the resources required to process workloads for three dedicated groups. The average full-time equivalents (FTEs) needed are 5.5, 2.2, and 3.9, with coefficients of variation (CoV) of 0.36, 0.60, and 0.42, respectively. To maintain lead times, these groups would need to be staffed with 9, 5, and 7 FTEs. A total of 21 FTEs required to handle the peak workloads.

However, by combining these work streams, the CoV drops significantly to 0.16, and the FTEs required for peak workloads reduce to 15, a 29% decrease. At this lower volatility level, labs can implement defined testing sequences (like Rhythm Wheels) and standard work roles, further boosting productivity. This approach transforms three stressed, inefficient work groups into one highly productive unit.

It’s important to note that combining workloads could potentially increase the CoV if individual peaks stack up. To prevent this, tools like levelling queues can be employed.

Conclusion

While organizing along value streams is a sound strategy, dedicating resources to narrow sub-streams without considering the overall performance impact can be detrimental, especially in industries like pharmaceuticals and biotechnology, where workloads are inherently volatile. Before adopting such strategies, it’s crucial to assess the potential impact on performance and ensure that the benefits of Lean are fully realized.