After decades of relative stability and growth, life sciences companies are finally experiencing the same kind of widespread disruptions as organizations in retail, automotive manufacturing, and engineering sectors. Faced with a mass expiry of patents, a marked slowdown in original new drug applications, and mounting regulatory pressures on their product development pharmaceutical and biotechnology firms are being forced to create more value with increasingly limited resources.
In response to these trends, we’ve seen mergers and acquisitions take place across the industry with businesses looking to create economies of scale in their research and development processes. Meanwhile, tightening margins have led corporations to outsource their manufacturing to suppliers in economies such as Brazil, China, India, and Russia (BRIC).
The increasing supply chain complexity has introduced new challenges. Companies in this space are becoming particularly concerned about maintaining consistency and efficiency of supply for short lifecycle products, and many are now attempting to assert greater control and visibility across their delivery pipelines as a result. At the same, connected consumers are beginning to take an active role in their healthcare and dietary planning. In this rapidly evolving environment, supply chain management has emerged as the key to creating more agile, customer-centric operating models.
Why Materials Planning Processes Need to Evolve
Traditionally, life sciences companies have relied on MRP (materials requirement planning) and MRP II (manufacturing resource planning) to coordinate their supply chain objectives. Both of these systems came about in the 70’s, they built on older resource planning methodologies by drawing a line between finished goods and supplied items/components. MRP uses historical sales data to forecast expected demand for a certain product. These estimates are then compared to planned production and inventory levels. Any differences between supply and demand are addressed through set quantities of safety or buffer stock. This is referred to as a “push and promote” approach to planning, in other words as long as you market a product effectively you will sell enough units to remain profitable.
Unfortunately, in today’s highly volatile operating landscape it has become almost impossible to accurately forecast demand at even a weekly/monthly level. This leads many companies to manufacture products in a completely sub-optimal mix which causes an oversupply of certain lines and an undersupply of others. The result is steep holding costs and constant service delivery failures. In order to make up unplanned shortages, companies often have to call in last minute changes to the supplier’s schedule thereby adding further costs and delays to the supply chain.
In the 80’s the JIT inventory planning system emerged to counteract some of these issues. As a pull based, JIT relied on real-time demand signals from customers to inform production rather than historically based predictions. In this approach, inventory holdings were viewed as wasteful and the ultimate objective was to match supply with demand exactly. However, JIT did not provide any visibility over the critical supply relationships that drove supply chain planning decisions. As a result, many JIT companies (particularly those operating in complex environments) experienced constant supply chain disruptions.
DDMRP Offers the Best of Both Worlds
DDMRP aims to maintain a consistent flow of materials through the establishment and management of buffers at strategic points across the supply chain. These safety stocks will help to reduce any variability in lead time, operating capacity or demand. In this way, DDMRP differs from both MRP and JIT models, in that it does not take buffer stock as a prerequisite for planning nor does it treat inventory holding as a waste. Rather, the system seeks to maintain dynamic stock positions at key points across the supply chain to ensure the optimal flow of resources.
Another key innovation in the DDMRP model is the introduction of the Actively Synchronized Replenishment Lead Time. This calculation is used to identify the ideal amount of buffer stock that should be held at each position. The ASRLT will determine the amount to be ordered, the frequency of ordering, the demand which needs to be covered, and the amount of stock that needs to be maintained. This calculation will be constantly updated with real-time data on average demand over a 3-6 month cycle, it will also account for any expected demand changes due to possible seasonal or socioeconomic influences.
Instead of focusing on demand predictions, the DDMRP model takes its cues from what has actually been sold. Daily sales orders are compared to current inventory positions to create a real-time view of stock flow through the enterprise. All production scheduling is based on these inputs. This helps to negate any supply disruptions caused by sudden shifts in demand. One of the most important benefits of DDMRP is that it prioritizes production of specific units based on the availability of buffer stock and current demand coverage.
As DDMRP removes much of the day-to-day firefighting and management involved in less flexible systems, it leaves supply chain managers free to pursue more strategic decisions that can actually add long-term value to the business. This model also takes away the focus of supply chain planning from immediate profitability to maintaining optimal material flow. Thus consistency and effectiveness of service become the main priority, which in keeping with the new customer-centric focus of life sciences companies.