At the beginning of my career, I was part of the purchasing department for a Fortune 50 healthcare company. In those days, we analyzed requirements and set safety stock levels that ensured we never ran short of any materials needed to produce a batch of product – all uncertainties were baked into our purchases, usually resulting in excess inventory and inflated inventory carrying costs. With the advent of JIT inventory philosophy, raw material inventories were cut to the bone – which required a bit more visibility into the suppliers’ ability to produce what was ordered on time and in full. The finance department was happy with JIT, but organizations with less sophisticated purchasing systems and not enough supplier collaboration sometimes found themselves with unplanned material shortages. Globalization added another layer of complexity – offshoring of supply chains to further reduce material costs. I have worked with clients that soon discovered that their ‘domestic’ suppliers also globally sourced their products and were subject to the same supply chain disruptions. However, world-wide JIT supply chain worked efficiently – until the late 2019 arrival of a COVID pandemic upended our lives and derailed the global economy.
At the height of the pandemic, existing healthcare organizations struggled to cope with supply chain fluctuations; new or expanded manufacturing facilities, fueled by government financing, added to already unmet demand for raw materials, and shipments were slowed or halted by the border closure of major API exporters such as China and India. Purchasing departments scrambled to order maximum quantities of safety stock. As a consultant, I was asked to evaluate one client’s supply chain strength and found that they had ordered two years of raw materials – at a tremendous inventory carrying cost, requiring additional external warehouse space, and almost guaranteed to face expiration before use.
Now, over three years after the onset of COVID, we are slowly starting to recover from its devastating impact on supply chains. The ability to obtain medical commodities, raw materials, even transport and equipment is slowly beginning to normalize – that is to the ‘new’ normal, not at pre-pandemic levels. Although the backlog of ships at anchor outside of the ports of Long Beach and Los Angeles has not disappeared, improvements have been made in the availability of resources (drivers, equipment, 24-hour unloading) needed to offload and deliver goods. Efforts to onshore or near-shore raw materials are underway – but meaningful results are still in the future. Exporting countries continue to experience human resource shortages but have been able to open their borders to reduced production.
So, what does supply chain management look like in 2023? How does an organization overcome unpredicted material shortages today and prepare for future supply chain disruption events? There are three activities that can take place to identify supply chain risks and help plan for whatever is next. Operational Readiness Assessment, Business Continuity Planning, and adoption of Advanced Analytics as a methodology for determining supply chain decisions.
Operational Readiness (OR) Assessment
An OR assessment is one method of supporting a vertical startup by analyzing where each workstream of a Life Sciences organization stands relative to GMP manufacturing. It is a structured way to identify a company’s gaps against regulatory and business requirements and to ensure that commercial manufacturing is operationally ready to meet market demand. The graphic below shows the impact to product release when an OR assessment is used to identify and mitigate any potential missteps ahead of commercialization.
Supply chain is an element of the OR exercise that includes all activities; from purchasing strategy to on-time and in-full delivery of customer orders. A closer look at the Supplier Management process (within supply chain) is also needed to identify specific supplier vulnerabilities. An end-to-end Supplier Management review would include purchasing strategy through supplier selection and qualification as well as monitoring of supplier performance.
While an OR assessment may focus on compliance, the integrated implementation approach to OR also provides a clear understanding of exposures beyond supply, including how products are manufactured, inspected, stored, and delivered, because each workstream poses its own potential problems. When individual gap assessment results are matrixed together from all workstreams, a clearer picture of the issues facing an organization can be developed leading to an integrated approach to risk mitigation rather than the siloed approach commonly seen.
Business Continuity Planning (BCP)
When consulting with organizations, I often find their BCP only includes instructions for what to do in case of facility and IT systems loss due to unplanned events such as fire or natural disaster. These BCPs tend to be placed into a binder at the corporate level and rarely reviewed or updated to include changes to business processes or the physical plant. A better approach is to manage the BCP as part of the change control process and to include all elements of supply chain risk such as:
- Exporting nation border closure and/or political conflict
- Facility, utility, equipment unavailability
- Facility, utility, equipment, and process changes
- IT systems unavailability including hacking and ransom demands
- Regulatory action such as product recall or poor audit outcome
- Resource unavailability – personnel and succession planning
- Supplier financial failure or inability to produce to demand
- Transportation unavailability
The BCP of today should be comprehensive, include risk and business impact assessments, have a periodic review, include a Recovery Plan based on identified risks, and be supported by senior leadership. A best practice would include a mock event response to identify anything that may have been forgotten when developing the Business Continuity Plan and the Recovery Plan. A mock event exercise is like a mock audit exercise – planned practice to evaluate procedures before an actual disruption occurs. A BCP may become part of the organization’s overall risk management program – but care should be taken to clearly differential between business risk and product/patient risk.
Advanced Analytics
Advanced, predictive analytics are the key to identifying supply chain trends and shortening the time needed to react to unplanned events. As mentioned previously, historical analytics (lagging indicators), such as sales ratios, inventory turnover, number of stockouts are often used to determine inventory and safety stock levels. While important, history alone is not actionable; what is needed for robust supply chains now are forward-looking analytics (predictive indicators) that can leverage organizational data to determine the best (optimal) supply chain planning decisions. Supply chain programs that make use of advanced analytics, Artificial Intelligence (AI), and Machine Learning (ML) can optimize an organization’s supply chain in multiple ways:
- Predictive analytics: Machine learning algorithms can analyze large amounts of data to identify patterns and predict future trends. This can help organizations anticipate changes in demand, optimize inventory levels, and improve production planning.
- Real-time optimization: Machine learning algorithms can provide real-time insights into supply chain operations, allowing organizations to optimize their operations on the fly. This can lead to better use of resources, improved agility, and reduced costs.
- Improved collaboration: Machine learning can facilitate collaboration between different stakeholders in the supply chain, such as suppliers, distributors, and retailers. This can improve coordination and reduce the risk of miscommunication or delays.
- Risk management: Machine learning can help identify and mitigate risks in the supply chain, such as disruptions in transportation or changes in demand. This can improve the resilience of the supply chain and reduce the impact of unforeseen events.
- Enhanced customer service: Machine learning can help organizations provide better customer service by improving inventory management, reducing lead times, and optimizing delivery solutions.
Finally
It is an exciting (some would say heart-stopping) time in the supply chain arena – the use of advanced analytics to support artificial intelligence (AI) in supply chain programming, the beginnings of end-to-end visibility into a suppliers’ organization to track availability and deliveries of materials, the move to sourcing raw materials with sustainability as a priority – these are new trends that will build on older methods and impact the way the supply chain of the future are managed.