Supply Chain Risk Visualization
The typical drug today is the result of very complex supply chains, with many independent participants. This carries inherent risk if one or several of the components cannot be procured/produced on time. Even if the reliability of individual components can statistically be described, it doesn't mean that the effect of one issue, in one particular area, can be understood on the level of an individual production unit (or lot). This leaves the supply chain management exposed to delays to individual customers at great expense to their reputation. It also leaves downstream activities hanging and hampered in the internal effectiveness. Say, if the disposition of a lot was planned for a given day, and on that day disposition managers discover that much of the compliance work has been carried out correctly, not only will the disposition of the lot be delayed, but, because of the context change, the effectiveness and efficiency of the disposition group suffers.
Fig 1: A highly simplified supply chain for a sterile product.
Here we are showing a system that visualizes risk to the supply chain. Visualizations exist from very high level to individual activities.
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Drill-down from high-level risks for the supply chain to the individual activities for specific lots
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Drill-down along dimensions, such as geography, different drugs or formulations
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Linkage to underlying data systems, such as ERPs, Manufacturing Execution Systems, Quality Management Systems or Laboratory Information Systems (and consumation of data thereof)
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Ability to tailor the system for each user or group of viewers through application of filters and consolidation into so-called "views". These views can be public or private, and can be shared between users. The establishment of a view does not prohibit the user from venturing "outside" the view, by lifting filters temporarily
Case Study
A multinational biotechnology company was suddenly faced with needing to release many lots of sterile material to many different markets. The company relied on CMOs for fill/finish and packaging of the drug substance. Despite intense focus of line-management on the timely fulfilment of these lots, the company was constantly battling delays and surprises just shortly before anticipated disposition.
For line managers this meant a constant context change (we can’t get this done yet, so let’s do that one instead), while senior management was exposed to pressure to meet contractual obligations. The company felt like “during a constant fire drill” (quote), with frustration among the ranks rising amid unsustainable workloads.
It was clear that the company required the capability to be aware of risks to timely disposition of material earlier to either address issues as they arise or to change management expectations as to planned disposition dates.
At the core of the solution developed by us is a system that analyzed and visualized for a given lot the risk for a timely disposition, i.e., a disposition of a lot on a given planned disposition date.
The value chain of a given lot is a long a multi-dimensional path of largely independent activities. For instance, the QC testing activities are largely independent of those of the CMO compliance activities, such as batch record review or the resolution of quality events.
Within each of these paths, the risk is multi-factorial. Milestones are stacked on top of each other, and if one is not reached, there is a high likelihood of a following milestone not being reached on time, either, unless appropriate management intervention is made. For instance, if the Manufacturing Batch Record Review is not completed on time, QA Batch Record Review cannot start on time, increasing the risk that QA Batch Record Review will not be completed on time, either.
Using this model, one can then calculate a risk score for each milestone and aggregate over each dimension an overall risk score for that dimension. If one milestone is missed, the risk in its dimension will increase. If a subsequent milestone is met (e.g., due to increased management attention), the risk along that dimension will diminish again.
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Solution
In its core, the system builds on the integration of data from different competencies, and aggreagates risk scores for individual activities necessary in the execution of the value chain of individual lots.
Figure 2: A fictious disposition pipeline. The graph shows the number of lots to be disposed of in the next several weeks, along with the overall risk to the lots meeting the planned disposition date. (All data shown in the white paper are fictitious)
It is conceivable that the above graphic would focus management’s attention on lots with the highest risk (red and dark blue). The drill-down capabilities of the tool allow the manager to determine what exactly is leading to the elevated risk to the disposition deadlines. In Figure 3 the tool tip reveals that Lot-1026 seems to have some elevated risk originating in CMO Operations and CMO Compliance. Other dimensions appear to be proceeding smoothly.
Figure 3: An excerpt from graphic in Figure 2. First level of drill-down for a specific lot shows the risk along the different dimensions.
Figure 4: The milestone risks for Lot-1026, considering the "today" is 18 May 2024. The QC Sample Tested milestone has not been met, therefore it has an elevated risk. There is a tolerance of two days after the NBD, during which a milestone has to be met to before it switches to High Risk.
Let us review Figure 4 in light of the Planned Disposition Date of Lot-1026 on 25 May 2024. The figure shows that QC Testing is starting to pose a problem for the critical path of the advancement of Lot-1026. It also shows that, apparently, internal Batch Record Review (BRR) start is delayed, contributing to an increased risk for this lot. The start of internal BRR is strongly linked to the completion of the CMO BRR. Inspection of the risk profile shows that completion of CMO BRR by QA is delayed at least since May 16. This knowledge could lead to increased management attention to this important detail, a vast improvement to the previous situation, where the delay in CMO BRR possibly only would have surfaced on 25 May 2024, throwing the overall supply chain into disarray.
Other Uses such as performance management.
Figure 5: Visualization of Supply Chain Backlog
Given the wealth of data available to such a system, the system can easily be expanded for other purposes. Below, for instance, is an example pane to show the backlog situation. Such a graph can have two purposes, once, showing the overall health of the disposition process (with all its dependencies), as well as give an estimate of the value that is currently stored in the backlog.
Figure 6: Visualization Disposition Calendar by Geographic Area
Here we show the disposition calendar by geographic area.
The figure also highlights another strength of the system. Each viewer can setup filters for their own use. Managers for one drug might not be interested in the data of another drug, etc. The resulting views can be made private or public.
This allows the creation of a system that encompasses all data, but caters to the needs of individual decision makers.