Industry executives and experts share their predictions for 2023.  Read them in this 15th annual VMblog.com series exclusive.

Pharma and Life Sciences Supply Chains

By Mahesh Veerina, CEO of ParkourSC

Planning can work well in a perfect world where demand never changes, there aren't any supply chain disruptions, traffic and weather conditions are optimal, and other life sciences and pharma organizations aren't in competition for the same routes, capacity, and carriers that others are. In the real world, there have been countless supply chain disruptions, increased demand for vaccines and cell and gene therapies, and new demand for certain medicines, that couldn't be planned for in advance.

Enhanced planning cannot and will never reduce and resolve these disruptions and changes, and increasing expensive safety stock shouldn't be the answer. Operational and planning systems must be integrated to respond to these challenges, increase gross margins, and enhance patient outcomes. A new process, titled integrated tactical planning (ITP), links the right data together to make decisions and models the real-time impact of those decisions.

This isn't a data lake placing all of an organization's data into a single system, as we have seen countless times that this doesn't work. Rather, this is a process where the right data is pulled to view a situation in real-time, model options, and make strategic decisions. This operational platform must be easily changed to optimize for on-time, in full, cost reductions, and all other important variables.

To reach this new process, check out our 2023 predictions that will shape change in life sciences and pharma supply chains:

1. Planning for the Real World with Increased Adoption of Continuous Execution Planning

Annual or quarterly planning will be enhanced by on-demand, continuous execution planning. The speed of change and disruptions in today's supply chains requires the organization to continuously re-plan while ensuring alignment with quarterly and monthly integrated business plans. Changes and disruptions in sourcing, manufacturing, logistics, and distribution, along with quick changes in priorities, may dramatically affect the monthly plan and require immediate replanning instead of having operations manually resolve disruptions and go off-plan. 

Using real-time signals from your supply chain, your planners and operations specialists can more nimbly solve disruptions and get back on track or adjust plans in minutes. Companies will look for digitization solutions that combine data and execute in the gap to eliminate or minimize the variance between planning and real-time execution data. But this can only happen with a highly orchestrated supply chain embedded with digital twins and decision intelligence.

2. Moving Beyond the Limitations of "Visibility" with Deeper Partner Collaboration 

Control towers and silos are out. Multi-systems data silos, excel spreadsheets, and manual text or calls cannot be the usual process to solve disruptions or quality excursions. Vendors or suppliers must be made partners in your supply chain. Visibility must be extended from active pharmaceutical ingredients (APIs) suppliers to the patient or hospital. Everyone should be able to see the supply chain flow and where their shipments or packages are in real-time. Disruption alerts must go directly to the company or the functional department that can resolve the issue with speed.

In addition, with the increase in mergers and acquisitions (M&A) and tight partnerships between pharmaceutical companies, CDMOs, and CMOs, visibility across multiple organizations, along with better digital collaboration, is sorely needed. These various organizations cannot be siloed in data, analysis, or execution, or the entire supply chain will fail especially if there is a major disruption, change in demand, or supply that affects multiple points in the supply chain.

A shipment delay with the potential to disrupt the timely delivery of products and impact a patient outcome should alert someone other than the carrier or logistics provider, who then contacts the distributor or manufacturer, who then contacts their customer support department that can provide alternatives to the end customer patient or hospital. A modern supply chain should be something other than a game of telephone. All the stakeholders in the value chain, along with the patient or hospital, should be automatically notified, along with customer support, who will provide options for delivery using a modern automated collaboration system. Simultaneously, logistics is notified to look at rerouting options while manufacturing looks to produce another batch, depending on the delay time. Everyone in the supply chain who can help manage and solve the disruption should have visibility, whether inside or outside the manufacturing or CDMO. Pharma and CDMOs will look for digital ways to work better together.

3. Decision Intelligence and Automated Workflows

As discussed above, manual processes are inefficient and costly. Important details may get lost. We will see more use of AI and automated workflows in the supply chain to resolve disruptions. What if an AI can decide on routing or carriers depending on current real-time data, carrier performance, or the most cost-efficient routes. In fact, if you have Environmental, Social, and Governance (ESG) requirements, they can also find the best routes to minimize carbon emissions. This would be like a more sophisticated Waze or Google Maps for logistics. How much time and stress would that save your team and help meet your cost savings goals?

What if you can also use automated workflows or AI recommendations for possible temperature excursions? The system could alert you to potential temperature excursions in a shipment and then reroute the shipment to a refrigerated truck or a cold chain repackaging facility, so you meet quality compliance or not lose that drug shipment. These AI and automated workflows can initially solve predictable disruptions due to traffic, weather, delays, spoilage, and production delays and free your supply chain resources to look at priority issues, i.e., determine allocation due to shortages, long-term disruptions and sourcing local APIs.

4. Automate Response to Disruptions with Digital Twins

As more and more companies look to digitize their supply chains, provide end-to-end visibility to all supply chain ecosystem participants, and expand beyond control towers to a true supply chain command center, they will have the signal feed and infrastructure to deploy digital twin technology. 

If you have not heard of a digital twin, it is a digital representation of your real-life supply chain infrastructure and processes. But it is more than a static model; it is a living model that continuously gathers signals from real-time sensors, transactional signals, and contextual data like traffic, weather, port closures, and risk signals in your supply chain. You can view your entire supply chain in real-time with a digital twin. Location, temperature, humidity, or other quality indicators can be monitored along with contextual information on traffic, weather, and disruption events. This digital twin extends beyond your four walls to your entire supply chain ecosystem.

A digital twin allows more than just visibility but can perform predetermined actions based on embedded AI models and business rules. You can also model these automated responses before adding them to production. For example, you can model a disruption and different response options: rerouting, new production, different inventory allocation, lot sizes to manufacture, plan expedited air freight, or allow an AI algorithm to recommend the most optimum outcome. After you are confident of the response, you can put this into production workflows. Because this digital twin encompasses an end-to-end model, you can quickly identify potential problems several nodes out and take corrective action in concert with your supply chain partners. You can also better streamline the supply chain by identifying duplicate connections set up by different departments.

With the need for better inventory allocation, digital twin technology can model your worldwide allocation to match regional demands. And as you reshore manufacturing to be close to the end customer, this technology can easily add new facilities and model the new supply chain to optimize on-time and in-full deliveries.

This is a powerful tool that provides the command center view of your entire life science supply chain. As companies digitize their supply chain, they will move to digital twin technology to lower costs, improve delivery times, optimal inventory performance and minimize disruptions to their supply chain.

5. More Focus on Sustainability

In this age of cell and gene therapies and personalized drugs, each shipment is much more critical. Reproducing a lost shipment is a much higher cost and longer delay, and may put patient outcomes at risk or a clinical trial study at risk. Gone are the options of creating a warehouse of safety stock or producing a year's worth of supply in one production run. With therapies that have a shorter shelf life and require cold chain custody, each shipment must be produced and shipped Just In Time (JIT).

Because of the expense, time, and patient need, waste is much more unacceptable. The supply chain will focus more on reducing waste, shelf life expirations, spoilage, temperature excursions, etc. Quality control will be added in every process step, including in-transit real-time monitoring. This must be enacted to reduce waste, lower costs and improve patient outcomes. Better visibility with digital track and tracking will reduce waste but implementing a more agile and fast supply chain is the ultimate goal to meet the new types of therapies and improve care.

In addition, we are seeing logistics and packaging companies more focused on sustainability and adding reusable packaging and smart sensors. These packages and sensors will be part of the circular economy that produces less waste, lowers costs, and is trackable worldwide.

6. Move from Control Towers to Command Centers

The move from control towers to command centers allows you to accomplish the predictions above. We have talked to companies using control towers, and they express frustration that they are domain-specific and primarily focused on logistics and shipments but not on product sourcing, manufacturing, storage, and movement. They also complain that control towers are like watching a slow-moving car crash but have no control to prevent it.

However, command centers encompass your entire supply chain in real-time and are multi-company and multi-domain. You can have visibility from raw material suppliers to warehouses to last-mile delivery. But the most significant advantage of command centers is that you can act on real-time data or predict possible disruptions and resolve them with workflows or AI recommendations. So instead of just watching the car crash, you can act to prevent it automatically. 

Because command centers allow all participants in your supply chain ecosystem to view the data through digital twins, it can speed up decision-making across companies to resolve disruptions. Instead of just looking at shipments between locations, command centers analyze the product flow in your supply and demand side along with warehouse and in-transit inventory so you can make a more optimized decision that works across your supply chain instead of just logistics.

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ABOUT THE AUTHOR

Mahesh is CEO of ParkourSC, Inc., a software SaaS company providing real-time digital supply chain operations solutions. A passionate leader, seasoned entrepreneur, technology executive, and investor, Mahesh enjoys developing strategic vision, driving innovation, and building world-class teams. A veteran Founder/CEO, he has taken several companies from early-stage to successful IPOs and acquisitions, as well as serving in senior leadership roles at Nokia, Motorola, Google, and Nook/Barnes & Noble. Previously, he led Ramp Networks to successful IPO and acquisition by Nokia, and Azingo from startup to acquisition by Motorola. He holds several technology patents with a background in Cloud, security, data networking, predictive analytics, mobile, telecom, and hardware.

Mahesh served on several boards in venture-backed companies and industry organizations. He is a frequent guest speaker at Stanford GSB and other industry forums. Mahesh is passionate about supporting basic needs like food and education for children and supports several non-profits such as Foundation for Excellence, Akshaya Patra and other organizations.

Mahesh holds a MS in Electrical Engineering and Computer Engineering from Purdue University, and a MSc in Electronics and Physics from Andhra University.