5 ways to use AI for Supply Chain Resilience in Pharmaceutical Businesses

The pharmaceutical supply chain has been subjected to its most significant pressure test in recent years, prompting those who manage supply chains to question the resilience of their own. Hit by the same delays, logjams and price-hikes as other sectors due to COVID19, Pharma supply chains also felt the burden of moving medical equipment and vaccines around the world quickly.


Even in pre-pandemic times, the pharmaceutical supply chain was fast becoming more global and complex, highlighting the need to withstand shocks and minimise risk. Digitisation is key to resilience, moving from a network of manual, siloed systems to a formula that puts real-time visibility and centralisation first, leading to operating efficiencies.


New and emerging technologies enable digitisation while helping to maintain the balance of driving growth and managing costs. One area in particular that can have a real and immediate impact is Artificial Intelligence (AI). Here are five areas within the pharmaceutical supply chain where AI can build resilience.

 

Driving efficiencies by creating data visibility and transparency

The pharmaceutical industry is somewhat famed for disordered, complex data spread across silos. But this is problematic - it can cause operational inefficiencies that ultimately impact the ability of suppliers to provide the best service levels to healthcare professionals.

Simply put, pharmaceutical operational excellence is not optional. This is particularly true in the case of moving goods which are often subject to strict temperature control and have time-sensitive delivery dates. Businesses must put quality control and logistics transparency at the forefront.

AI can bring this much needed visibility, providing accurate, normalised, connected and timely logistics data that delivers real-time insight and predictions about what’s happening next across the chain. If an AI tool identifies a potential logistic disruption, the business is able to act before it’s too late (finding an alternative carrier or route to ensure timely and safe delivery).


For example, global pharmaceutical and services company Clinigen was able to unify its logistics data by implementing 7bridges AI technology into the supply chain. Managers can now make better and faster decisions to ensure efficiencies are spotted and quickly acted upon.

 

Demand forecasting for timely and complete patient care

ai-in-retail-dynamic-switchingImprovements in the Pharma supply chain are usually stymied by its very nature: high complexity products, limited and highly regulated delivery channels. But the pandemic’s impact on the global supply chain highlighted the need for better predictive tools. Demand forecasting and planning is pegged as one of the top ten areas of technological investment for 2022. A recent study by IDC highlights that by 2023, 50% of all supply chain forecasts will be automated using AI, which is expected to improve accuracy by five percentage points.


Demand forecasting plays a critical role in pharmaceutical logistics and supply chain management. And companies know that investing in this area helps them become more agile in response to customer/patient demand changes, allowing them to analyse data that they previously couldn’t because of the complexity or volume. This contributes to better and faster decision making and overall Pharma resilience.


In practical terms, AI-powered demand planning allows companies to:

  • Cut storage and handling costs by only holding the stock needed at the time
  • Reduce handling expenses and predict potential changes in supply and demand
  • Reduce risk and increase resilience, rapidly adapting to changes in customer/patient demand and avoiding potential bottlenecks with dynamic and predictive inventory

 

Reduce exposure to risk in current contracts and the procurement process

Since common practice within the Pharma sector is to choose one carrier for an entire contract, companies can often overlook the vulnerabilities in current contracts. AI tools can create efficiencies by identifying risks across existing contracts like missed entitlements, unexpected expiry or renewal dates, and non-compliant clauses, which can lead to unforeseen costs.


person-screenBut there’s a use-case which is even more powerful for pharmaceutical businesses - the ability of AI to improve the procurement process for new contracts. This is because procuring logistics services is not like procuring a commodity: it’s much harder. Why?


Even the best procurement professionals will struggle to assess the huge volume of critical data related to a logistics proposal. Therefore, delivering data transparency is the first benefit of an AI-powered logistics procurement exercise.

The second game changing use-case offered by AI in the procurement of logistics services for Pharma, is modelling the business impact of new proposals. 

  • An AI tool (such as 7bridges) can normalise and build a dataset from a pharmaceutical organisations internal systems and ERP tools. This data will be comprehensive and will best inform the buyer of what the business needs from a procurement perspective.
  • AI can also deliver total transparency of supplier data (pricing, compliance and service offerings) across multiple suppliers. This enables procurement professionals to accurately compare and contrast proposals - no small feat, when each supplier proposal is expressed in a non-standard way.


With AI tools like LEO (the 7bridges AI) companies can remodel logistics to meet the demands of the new age. With the ability to run simulations and utilise a “digital twin” to test new business cases before committing, companies can improve risk management and resilience and negotiate the best contracts.
Ultimately, this means that AI can speed up procurement, improve logistics carrier selection, ensure greater resilience across Pharma supply chains and lower overall business costs by securing the best rates.

 

Understand industry disruptors and prepare for all contingencies

resilience-iconGlobal pandemics, natural disasters, and economic forces disrupt any supply chain. But the pharmaceutical industry is particularly vulnerable to political instability and cyberattacks. For example, China and India supply the vast majority of active pharmaceutical ingredients. Tensions of a political nature pose significant risks to the efficient global movement of vital medical goods.

A digital twin AI technology can help companies create actionable contingency plans, by simulating potential risks and modeling the impact of all sorts of disruptions or disasters.

 

Reduce carbon footprint in Pharma

While carbon footprint isn’t strictly a resilience concern, it is a major part of future-proofing the business for pharmaceutical companies.


To date, most businesses have focused their ESG efforts on the procurement of raw materials and the manufacturing processes utilised to bring them to market. However, logistics and transportation is a huge contributor to the carbon footprint of pharmaceutical organisations.


Sustainability can be improved by reducing the number of shipments made, by using more efficient packaging, and by optimising routing of goods. It may sound simple, but these changes require hugely complex calculations that require access to big data from multiple 3rd party sources.


This is where AI can help. The right AI can calculate the best dispatch site, route and carrier for the shipment, by balancing complex real-time predictions (including the availability of inventory and packaging materials, operational capacity, carrier price and historical performance, estimated shipping times, the likelihood of route disruptions and environmental impact). This ensures that shipments arrive on time, at the lowest price and with a reduced carbon footprint.


AI is a key part of the future of green logistics, in Pharma and all other industries. It’s something we’re particularly passionate about at 7bridges, as we’re using our technology and global dataset to reduce waste in supply chains.

 


 

Visibility and decision making: two things we all know can impact supply chain performance. Investing in AI that enables both is key to resilience. And it’s only going one way: an Accenture study found that in 2022, 79% of executives want increased use of automation, AI and robotics to create complete supply chain visibility.

We're hosting a 30 minute webinar on 8th March 2022, 12:00 GMT / 13:00 CET to discuss key use cases for AI in pharmaceutical supply chains. Register here.

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