The global health crisis has shone a spotlight on pharmaceutical and medical device supply chains—and highlighted their fragility.
Yet long before the pandemic, the pharmaceutical industry was suffering severe shortages, even though drug stock-outs can be life-threatening for patients.
One may wonder about the dynamics that have led over the years to this situation: the logic of health accounting management—centered above all on costs—to say nothing of privatization and the abandonment of national or regional industrial policies. Our newspapers have been rich in analysis, and we keep our fingers crossed that governments and industrialists will draw the right conclusions.
Can DDMRP and, more broadly, the Demand Driven Adaptive Enterprise model help us?
Medical Device and Pharmaceutical Supply Chain Challenges
Drug and medical device supply chains have characteristics that are particularly detrimental to operational agility:
- The supply chains have become terribly long. Active pharmaceutical ingredients sourced mainly from China. Surgical masks, surgical drapes, surgical drapes coming from China, mainly by sea transport. Surgical and examination gloves from Thailand and Malaysia, etc.
- Sourcing teams select Asian players for their low costs, not their agility or customer focus. In these supply chains, we find monthly orders, fixed periods sometimes lasting several months, aggravated by weeks of ocean freight. Although the standard lead time is already long – say 4 months – it is not uncommon to find a depth of delay of several months. These are practices from another age compared to other industries.
- Quality and regulatory constraints are omnipresent. This is a very good thing, but adds a dose of variability related to batches awaiting release, sometimes for indefinite periods and with a high risk of failure.
- Product portfolios are increasingly complex. This is true in the life sciences as it is in other industries, which makes the forecasting exercise very uncertain. Add to this the risks of sanitary crisis leading to sharp fluctuations in demand, and replenishment lead times of several months involving long-term forecasts, as well as the risk of expiry, and you have all the ingredients for gigantic bullwhip effects.
As an anecdote, I oversaw planning a supply chain of medical devices during the H1N1 crisis: in the lapse of 3 weeks we went from a 2-year overstock to a total stock out on surgical masks…
In this context, bringing the pharmaceutical and medical device industry closer to the reality of market demand makes sense—and indeed this is the purpose of implementing a Demand Driven Flow and a Demand Driven Adaptive Enterprise model.
Few companies in this sector have a pull-flow culture, as the context does not seem to lend itself to it. Lean approaches have often arrived late and have been deployed in a very limited way.
When I took over responsibility for a medical device supply chain about ten years ago, coming from the world of automotive suppliers, the shock was staggering. When I started to introduce some pull flow practices, I looked like a wacky dreamer…
How Life Science Companies Can Take Advantage of DDMRP
Thanks to its ability to be deployed from one end of the supply chain to the other, its integration with information systems and its aptitude to respond to increased variability, DDMRP finally allows the efficient and rapid deployment of a demand-driven flow in this highly constrained environment.
Let us look at some aspects of implementing DDMRP on a pharma or medical device flow.
Designing the Demand Driven Operating Model (DDOM)
To gain agility, the first key is to reduce lead times. It’s obvious, but this has often been lost sight of by companies in the sector.
The implementation of DDMRP begins with a review of the flow mapping to define the operating target. During this design process, attention should be paid to the following aspects:
1. Positioning Strategic Stocks
- In a context where strategic raw materials (e.g. active ingredients) coming from Asia are subject to long lead times and a high potential variability of supply, the DDMRP stock positioning and sizing methodology leads to ask the right questions and to position the required securities. Agility does not rhyme with fragility; it is imperative to secure stocks in the right places.
- Pharma processes are often ideal for implementing a postponement manufacturing strategy. A bulk is manufactured which can be stored at an intermediate stage of semi-finished products, in the form of tablets, capsules, bottles, tubes, etc. At this stage, the number of variants is limited, and will be differentiated during secondary packaging, within a short lead time.
2. Frozen Horizons and Frequencies
- In the hope of stabilizing needs and securing supplies, production or supply orders are frozen over a long horizon. However, the longer they are frozen, the more they delay reacting to changes in demand, and therefore the more they amplify the variations. For example, for a flow of surgical gowns from China, we have gone from a fixed manufacturing horizon of 3 months with monthly orders to a horizon of 3 weeks with weekly orders. The result: a much more stable production program, while becoming way more agile. It is above all a question of daring, convincing, experimenting and deploying with the right processes and software.
- When designing the operating model, ask yourself the right questions about campaign sizes, batch sequence, in manufacturing or packaging, and grouped planning. Planning wheels are often very suitable in this environment.
- If you have maritime flows coming from China with high frequency, organize mixed containers to adjust the green zones to the lowest possible level, for example down to one week.
3. Capacity Constraints and Queues
- In order to be efficient the pull flow must be smooth and compatible with the constraints of your industrial model. Identify these constraints during the design phase. Beware, sometimes the actual constraints are not where you think they are – for example, they may well be in your quality analysis and release process, not in manufacturing.
- Position time buffers in your flow where required. Time buffers are controlled queues. For example, there is probably one to be positioned at QC or before sterilization.
- In the field of medical devices, suppliers are often seen as having infinite capacity… which is of course not the case. Identify the suppliers whose load/capacity needs to be controlled in order to define the right steering process, from S&OP down to execution.
- DD Tech’s solutions provide functionalities that facilitate the implementation of leveled pull flow: RCCP, finite capacity scheduling, time buffers control, buffers adjustments, grouped scheduling…
4. The Industrial Footprint
- The health crisis has highlighted this fact: the abandonment of entire sections of the industry in Europe and America and its relocation to Asia have greatly weakened our chains. Yet we had the know-how, whether it was in the manufacture of masks or in fine chemicals.
- Can DDMRP help relocate certain activities and shorten our supply chains? Probably in at least two ways: by highlighting again and again the importance of the flow, and by making it possible to calculate and simulate the impacts of this or that industrial strategy.
Effective Demand Driven Management
Once your model has been designed and implemented, DDMRP facilitates the day-to-day handling of the challenges relative to the healthcare supply chain.
- Active monitoring of stocks through continuous adjustment of zones, and execution alerts to protect the availability of buffers.
- In some cases, a raw material or strategic component is in short supply and the question arises as to which site to direct the available quantities to. The setting of the buffers of this material on each site and the red/yellow/green status of net flow easily allow allocation decisions to be made on a relative priority basis.
- The supply of some materials is not possible all year round—for example, during Chinese New Year—DDMRP makes it easy to manage these seasonal buffalo adjustments, a situation that traditional TPM tactics struggle to handle.
- Considering expiry constraints is facilitated when the stock is managed in pull flow and aims at a target range between “too much” and “too little.” If your red + green zone remains well below the expiry duration, all is well. If this is not the case, you should question this dimensioning and adjust the supply process if possible. It is not uncommon to see a green zone that is longer than the shelf life: a batch is productively manufactured and part of it is discarded… Taking into account in the net flow equation the upcoming expiry of batches makes it easy to plan their replenishment in time.
- How to prioritize quality releases? This recurring problem is greatly facilitated by the visual and collaborative execution component of DDMRP. Priority is given to items with an execution alert, and to those with the lowest execution percentage of downstream buffers. Priorities throughout the chain are aligned through stock and time buffer statuses.
- Do you have trouble balancing your inventory in your distribution network? Is the signal coming up from your network through your DRP distorted, affected by the bullwhip effect? Are you struggling to convey to your factories and suppliers a reliable demand signal? The logic of the DDMRP distribution module, pulled by downstream buffers and ensuring fair share deployment, provides an effective answer.
- What about your S&OP? Six years ago, I attended a presentation of the S&OP approach of a giant in the pharmaceutical industry. I was stunned by the presentation. In short, we discovered that in 2016 this giant of the pharmaceutical industry was just beginning its S&OP journey (where had they been since the 1980s?). Moreover, the main part of the process was centered on establishing a consensus on an official set of figures… which officialized a shortage on certain critical drugs over a multi-year horizon!
DDMRP gives S&OP back its full meaning: assessing possible scenarios and facilitating the adaptation to an ever-changing environment.
Finally, the Demand Driven model allows us to deploy an end-to-end pull flow and contribute to the agility and resilience of our healthcare systems. Examples of applications are multiplying.
