Jul 21, 2020

McKinsey: Overcoming Supply Chain Shortages due to COVID-19

McKinsey
Supply Chain
Manufacturing
covid-19
Sean Galea-Pace
4 min
Supply Chain Digital examines McKinsey’s article “Overcoming Supply Shortages for Diagnostic Testing” to observe the shortages in the supply chain.
Supply Chain Digital examines McKinsey’s article “Overcoming Supply Shortages for Diagnostic Testing” to observe the shortages in the supply chain...

As one of the biggest challenges in recent history, the COVID-19 pandemic has disrupted industries across the world. In a bid to combat this obstacle, testing is recognised as one of the main components of efforts to contain the virus and mitigate its impact.

There are two main testing technologies: molecular assays, which identify viral genetic material and signal the presence of a viral infection, and immunoassays, which identify antigens or antibodies.

Many regions globally are experiencing a shortage of laboratory-based molecular-assay tests. In the United States, testing capacity stands at between 3-3.5 million tests weekly, a figure well below even some of the most conservative estimates of the number required. The estimated number needed ranges from 6 million tests a week to 20 million a day. In perspective, the current global capacity for molecular tests within laboratories is estimated to be around 14-16 million tests a week, with the number of tests actually conducted being less than 10 million weekly. As a result, scaling the supply of tests, in addition to ensuring that they reach those that need them, is crucial. Even as disease-prevalence rates fall and economies reopen, identifying those that are infected will likely remain a priority, both to treat and isolate them and to further epidemiological knowledge of the disease. 

There are five main activities in the process for delivering laboratory-based molecular-assay tests: sample collection, logistics, test execution, data management and testing-capacity management. All should be executed harmoniously to maximise supply in a complex testing ecosystem, but bottlenecks can occur at each point.

Sample collection is needed for all diagnostic testing. A shortage of the supplies needed to collect samples, such as swabs and viral-transport mediums, and a limited number of testing sites have sometimes led to long waiting times for a COVID-19 test and for key workers going untested. Some progress on addressing these issues has been made, with an increase in the supply of swabs, traditional manufacturers increasing capacity, with some manufacturers using 3D printing. Some health authorities have approved alternative transport mediums, and different types of samples. Studies have indicated that the test results from such alternatives could be as accurate as those taken from swabs.

Logistics firms play an influential role at two points in the testing supply chain: the shipment of components from sources globally to testing laboratories and the transportation of samples from collection points to laboratories. Neither issue has proved to be as significant a constraint on testing as the other issues highlighted in the article. They could become more problematic as countries expand testing, which means both issues could be monitored more closely. 

Three short-term measures

McKinsey’s three short-term measures that could help maximise the utilisation of existing resources in as few as three months are:

  1. Establish visibility into testing capacity

A clear view of the unused testing capacity available is crucial if it is not to go to waste. Here, the establishment of information nerve centres that collect data on local capacity then match it with demand on a daily basis could help. As more capacity comes on stream, a nerve centre’s overview could also help health authorities expand testing quickly—for example, offering tests not only to healthcare workers and those in hospital but also to vulnerable members of the community. Nerve centers could also act as repositories for critical data on the inventory levels of consumables and testing reagents and on potential suppliers, helping governments and healthcare providers plan ahead and prevent shortages.

2. Maximise existing laboratory capacity

Local laboratories may not be fully utilizing installed equipment for a number of reasons, ranging from suboptimized workflows to lack of trained personnel. Unlocking all available capacity starts by compiling a full inventory of the installed equipment base, distinguishing between open and closed systems, then calculating the maximum theoretical laboratory capacity, given the installed base. That allows companies to locate and address bottlenecks, be it by establishing new workflows, hiring additional personnel, or finding alternative suppliers of reagents if open-source systems are used. Universities and major diagnostic manufacturers could perhaps partner with local laboratories to help with some of those issues—providing open-system equipment they have in their own research facilities, reagents, and trained personnel, for example.

3. Establish new laboratory capacity

Laboratory capacity can be raised by increasing the equipment footprint in existing laboratories and by establishing new, high-capacity laboratories. Collaboration among governments, public-health organisations, equipment manufacturers, and private laboratories can accelerate such efforts. Novacyt, a UK and French diagnostics company, has collaborated with AstraZeneca, GlaxoSmithKline, and the University of Cambridge to increase testing capacity in the United Kingdom, for example.

Interested in reading McKinsey’s full report? Click here!

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Jun 11, 2021

NTT DATA Services, Remodelling Supply Chains for Resilience

NTTDATA
supplychain
Supplychainriskmanagement
Procurement
6 min
Joey Dean, Managing Director of healthcare consulting at NTT DATA Services, shares remodelling strategies for more resilient supply chains

Joey Dean, the man with the coolest name ever and Managing Director in the healthcare consulting practice for NTT DATA and is focused on delivering workplace transformation and enabling the future workforce for healthcare providers. Dean also leads client innovation programs to enhance service delivery and business outcomes for clients.

The pandemic has shifted priorities and created opportunities to do things differently, and companies are now looking to build more resilient supply chains, none needed more urgently than those within the healthcare system. Dean shares with us how he feels they can get there.

A Multi-Vendor Sourcing Approach

“Healthcare systems cannot afford delays in the supply chain when there are lives at stake. Healthcare procurement teams are looking at multi-vendor sourcing strategies, stockpiling more inventory, and ways to use data and AI to have a predictive view into the future and drive greater efficiency.

“The priority should be to shore up procurement channels and re-evaluate inventory management norms, i.e. stockpiling for assurance. Health systems should take the opportunity to renegotiate with their current vendors and broaden the supplier channel. Through those efforts, work with suppliers that have greater geographic diversity and transparency around manufacturing data, process, and continuity plans,” says Dean.

But here ensues the never-ending battle of domestic vs global supply chains. As I see it, domestic sourcing limits the high-risk exposure related to offshore sourcing— Canada’s issue with importing the vaccine is a good example of that. So, of course, I had to ask, for lifesaving products, is building domestic capabilities an option that is being considered?

“Domestic supply chains are sparse or have a high dependence on overseas centres for parts and raw materials. There are measures being discussed from a legislative perspective to drive more domestic sourcing, and there will need to be a concerted effort by Western countries through a mix of investments and financial incentives,” Dean explains.

Wielding Big Tech for Better Outcomes

So, that’s a long way off. In the meantime, leveraging technology is another way to mitigate the risks that lie within global supply chains while decreasing costs and improving quality. Dean expands on the potential of blockchain and AI in the industry

“Blockchain is particularly interesting in creating more transparency and visibility across all supply chain activities. Organisations can create a decentralised record of all transactions to track assets from production to delivery or use by end-user. This increased supply chain transparency provides more visibility to both buyers and suppliers to resolve disputes and build more trusting relationships. Another benefit is that the validation of data is more efficient to prioritise time on the delivery of goods and services to reduce cost and improve quality. 

“Artificial Intelligence and Machine Learning (AI/ML) is another area where there’s incredible value in processing massive amounts of data to aggregate and normalise the data to produce proactive recommendations on actions to improve the speed and cost-efficiency of the supply chain.”

Evolving Procurement Models 

From asking more of suppliers to beefing up stocks, Dean believes procurement models should be remodelled to favour resilience, mitigate risk and ensure the needs of the customer are kept in view. 

“The bottom line is that healthcare systems are expecting more from their suppliers. While transactional approaches focused solely on price and transactions have been the norm, collaborative relationships, where the buyer and supplier establish mutual objectives and outcomes, drives a trusting and transparent relationship. Healthcare systems are also looking to multi-vendor strategies to mitigate risk, so it is imperative for suppliers to stand out and embrace evolving procurement models.

“Healthcare systems are looking at partners that can establish domestic centres for supplies to mitigate the risks of having ‘all of their eggs’ in overseas locations. Suppliers should look to perform a strategic evaluation review that includes a distribution network analysis and distribution footprint review to understand cost, service, flexibility, and risks. Included in that strategy should be a “voice of the customer” assessment to understand current pain points and needs of customers.”

“Healthcare supply chain leaders are re-evaluating the Just In Time (JIT) model with supplies delivered on a regular basis. The approach does not require an investment in infrastructure but leaves organisations open to risk of disruption. Having domestic centres and warehousing from suppliers gives healthcare systems the ability to have inventory on hand without having to invest in their own infrastructure. Also, in the spirit of transparency, having predictive views into inventory levels can help enable better decision making from both sides.”

But, again, I had to ask, what about the risks and associated costs that come with higher inventory levels, such as expired product if there isn’t fast enough turnover, tying up cash flow, warehousing and inventory management costs?

“In the current supply chain environment, it is advisable for buyers to carry an in-house inventory on a just-in-time basis, while suppliers take a just-in-case approach, preserving capacity for surges, retaining safety stock, and building rapid replenishment channels for restock. But the risk of expired product is very real. This could be curbed with better data intelligence and improved technology that could forecast surges and predictively automate future supply needs. In this way, ordering would be more data-driven and rationalised to align with anticipated surges. Further adoption of data and intelligence and will be crucial for modernised buying in the new normal.

The Challenges

These are tough tasks, so I asked Dean to speak to some of the challenges. Luckily, he’s a patient guy with a lot to say.

On managing stakeholders and ensuring alignment on priorities and objectives, Dean says, “In order for managing stakeholders to stay aligned on priorities, they’ll need more transparency and collaborative win-win business relationships in which both healthcare systems and medical device manufacturers are equally committed to each other’s success. On the healthcare side, they need to understand where parts and products are manufactured to perform more predictive data and analytics for forecasting and planning efforts. And the manufacturers should offer more data transparency which will result in better planning and forecasting to navigate the ebbs and flows and enable better decision-making by healthcare systems.

Due to the sensitive nature of the information being requested, the effort to increase visibility is typically met with a lot of reluctance and push back. Dean essentially puts the onus back on suppliers to get with the times. “Traditionally, the relationships between buyers and suppliers are transactional, based only on the transaction between the two parties: what is the supplier providing, at what cost, and for what length of time. The relationship begins and ends there. The tide is shifting, and buyers expect more from their suppliers, especially given what the pandemic exposed around the fragility of the supply chain. The suppliers that get ahead of this will not only reap the benefits of improved relationships, but they will be able to take action on insights derived from greater visibility to manage risks more effectively.”

He offers a final tip. “A first step in enabling a supply chain data exchange is to make sure partners and buyers are aware of the conditions throughout the supply chain based on real-time data to enable predictive views into delays and disruptions. With well understand data sets, both parties can respond more effectively and work together when disruptions occur.”

As for where supply chain is heading, Dean says, “Moving forward, we’ll continue to see a shift toward Robotic Process Automation (RPA), Artificial Intelligence (AI), and advanced analytics to optimise the supply chain. The pandemic, as it has done in many other industries, will accelerate the move to digital, with the benefits of improving efficiency, visibility, and error rate. AI can consume enormous amounts of data to drive real-time pattern detection and mitigate risk from global disruptive events.”

 

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