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February 02, 2024

Supply chain software for life sciences: a cure for ‘analysis paralysis’

Five must-haves, and 4 nice-to-have features CIOs should look for in this under-used software.

For life sciences companies, supply-chain planning is everything. In this truly global sector, vendors, customers and stakeholders are strewn across the continents, manufacturing, shipping and using vitally important products against the ever-ticking clock of expiration dates. It’s hard to imagine how a life-sciences company could ever hope to survive in his dynamic, multi-factorial minefield without powerful software to manage, maintain and protect its intricate supply chains.

And yet, across the sector, we see life science companies under-using this critical technology.

A recent Gartner survey found, for instance, that less than half (44%) of life-sciences companies were using digital technology to calculate how different hypothetical scenarios might disrupt their supply chains in future. (Compare that to 60% for healthcare providers, 71% for manufacturers, and 95% or greater for retailers and tech companies.) And while 69% of life sciences companies said they use advanced analytics, only 14% are using artificial intelligence/machine learning.

Why isn’t the industry fully leveraging supply chain planning software? The problem, we’ve found, is often a dread condition known as “analysis paralysis.” Supply-chain software is a crowded space, full of good vendors with quality products, many of which offer similar functionality. Choosing is hard, especially when CIOs know the stakes are so high.

But relief is at hand. Cognizant has worked with many global leaders in life sciences over the years. We’ve listened to their concerns, assisted them on their journeys, and we’ve learned that cure for analysis paralysis is to focus on those features of supply-chain software that matter most in this most unique of industries. Here they are.

The big five

  1. Regulatory capability. Few sectors are as highly regulated as life sciences, which becomes a supply-chain issue when you factor in that countries and territories have their own rules, regulations and standards when it comes to, say, manufacturing processes. Any supply-chain planning software under consideration for life sciences needs to be able to take into account all these jurisdictional requirements and inconsistencies and be prepared for them to change.

  2. Expiry management. This is a key requirement in life sciences, and not all supply chain planning software packages handle expiration issues with sufficient granularity. Expiry planning capabilities must be able to calculate expiry dates based on both the bill-of-material and distribution networks and do so matching the accuracy of shelf-life master data.

  3. Lot-for-lot planning. For life sciences companies, each demand lot requires a corresponding plan, and managing lot traceability across all levels of the supply chain (including the alignment of supply to upstream work orders) can be a challenge. It’s crucial that supply-chain software helps companies plan packaging work orders from different bulk locations based on quota arrangements. From bulk locations, it should be possible to create work orders based on batch sizes.

  4. Production planning. Because life sciences companies follow process manufacturing, detailed planning of production campaigns is vital to improve manufacturing yields. Campaign Planning or Production Rhythm Wheel capabilities and the resulting trade-offs with inventory costs are key elements.

  5. Detailed scheduling. Most planning software considers only high-level scheduling (tactical horizon), ignoring detailed scheduling. Often, the granularity offered maxes out at the “daily” level. That’s not enough in life sciences, where scheduling at the hourly level is a must.

… The ‘nice-to-have’ four

For truly forward-looking life sciences firms, or ones further along on their enterprise software journey, we’ve also identified four features that are becoming increasingly relevant. While these features are desirable in any industry, the global and highly regulated nature of the life sciences sector makes them especially valuable:

  1. Transportation optimization. Life sciences companies should ideally have the ability to consider different transportation lanes, analyzing trade-offs and making decisions that optimize the transportation load across their entire network.

  2. ESG. Increasing regulatory requirements around environmental, social and governance factors make it likely that ESG tracking will only grow in importance. Supply chain planning software that deals with carbon emissions, fuel use, water consumption, etc. is highly desirable.

  3. AI/ML capabilities. With all today’s hype around generative AI, it’s easy to get carried away and assume that decision-making itself will soon be automated. But we advise clients to take a more measured approach. What’s more pragmatic is to ask if prospective planning software can provide insights that enable better decision-making by company leaders. A self-healing supply chain is an ideal outcome of AI/ML capabilities, but for now, basic levels of healing (such as lead times and manufacturing yields based on actual vs. system-maintained values) are a solid investment.

  4. Control towers. These identify key performance indicators (KPI) for each function; these KPIs then alert designated planners for action. Having control-tower capability in planning software, along with the other features noted here, is a powerful combination.

A supply chain, like a business, can be thought of as a living organism, with its own unique set of strengths and fragilities. And a business, like an organism, is locked in a constant battle for survival with its competition. Those leaders in life sciences who embrace the power of software to strengthen and protect their crucial supply chains are setting themselves up to survive and thrive.

Sathyanarayana Rao

Manager, Supply Chain Management

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Sathya spearheads the Supply Chain practice at Cognizant with extensive experience in successfully executing digital transformations. His in-depth knowledge spans across the life sciences and automotive industries, where he has pioneered innovative tools and accelerators as part of the Center of Excellence at Cognizant.

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