Eyes on the prize24 May 2023
The idea of an intelligent supply chain with end-to-end visibility has been talked about for years. But how much of this potential has been realised in the supply chain of the pharmaceutical industry, a notoriously slow mover when it comes to adopting new technologies? Peter Littlejohns asks Karen Taylor, research director of the Centre for Health Solutions, Deloitte; and Emily May, life sciences insight lead, Centre for Health Solutions, Deloitte just how intelligent pharma supply chains are currently, and what’s stopping the industry from going for full adoption.
Phrases like ‘end-to-end visibility’ and ‘intelligent automation’ are often met with nods and applause at pharmaceutical industry conferences. In the holy grail scenarios presented by speakers, visibility along each link of the supply chain is guaranteed, with data collected from the manufacturing floor to the moment a product leaves the delivery vehicle. The value of this level of supply chain visibility is easy to imagine; with eyes on every link in the chain, a company can better manage their inventory, forecast demand for products and minimise the risk of temperature excursions – just to name a few benefits. But back in the real world, the suite of technology necessary to make that possible – sensors, devices, AI, data processing and a user interface – carry a cost, and that’s why the apparent support for these advances isn’t reflected in the level of investment necessary to achieve them.
“There’s a nervousness about being a first mover in this space, spending lots of money and it not working,” says Karen Taylor, research director of the Centre for Health Solutions, Deloitte. “Pharma companies tend to be more conservative. Each [company] looking at each other nervously wondering whether they should be the first to move, is the feeling I get.” The research wing of Deloitte’s Centre for Health Solutions curates reports on digitalisation in the pharma industry, showing real-life cases where visibility was achieved in the supply chain. The reports also look at the role of AI and digital twins in going beyond visibility to add predictability to the supply chain. But for this scenario, Taylor says when she and her team worked on the 2020 report ‘Intelligent drug supply chain: Creating value from AI’, use cases were few and far between. “For each of the use cases of AI that we identified across the supply chain, there’s a case study,” she says. “But finding those examples was really tough. What we do see is [companies] doing it piecemeal, so a team or even a country really invests in it, but that doesn’t give you the global visibility.”
The biggest companies in this market were established long before the idea of visibility, let alone end-to-end visibility, in the supply chain. For a business the size of Pfizer, GSK or AstraZeneca, for instance, there’s far more risk to the bottom line from making the necessary investment for a full digital transformation. On the other hand, a company started within the past few decades, like Moderna Therapeutics – identified as one of the few case studies in Deloitte’s report – is able to scale their technological capabilities alongside their growth. “They’re not like some of the pharma companies that have been around since the 1700s or 1800s and have a huge infrastructure to change,” says Taylor. That’s not to say that the benefits of an intelligent supply chain are out of reach for the larger companies. They just have to ensure they get the full picture and not just pieces of it, explains Emily May, life sciences insight lead, Centre for Health Solutions, Deloitte. “If you do it part by part, it’s important to make sure that as you scale it, those parts are interconnected and not in silos,” she says. Without that interconnectivity, she adds, “you won’t get the visibility benefits you would by doing it at scale.”
The cost mounts up when you take an intelligent supply chain apart to reveal its components, but companies aren’t typically building the capabilities in-house. Instead, they tend to partner with the likes of Amazon AWS, Microsoft and IBM for the necessary digital tools. Of course, availing of these services carries a cost too, but Taylor says it’s come down significantly over the years, likening it to the cost of sequencing DNA. “15 to 20 years ago it was over £1m for every piece of DNA you were trying to sequence,” she says. “Now, you can sequence whole genomes for under £1,000 and some even claim under £100. That scale of cost savings is reflected in the capacity of the technologies we’ve been talking about.” But despite there being a lower barrier of entry to adding intelligence and visibility to the supply chain in pharma now than say, ten years ago, the choice to implement it still has to be justified at the board level, meaning it must be cost-effective. For Taylor, the answer comes down to the following: “How important is having data every second instead of data every minute?” Drug companies will always prioritise the work that goes into discovering drugs that improve patient outcomes, especially in life-threatening diseases, and this will be reflected in their spending. “If you make a super-duper digitally-enabled, state of the art company, but you haven’t got any drugs to push through it, you’ve wasted a lot of money,” Taylor adds. Of course, this is an extreme scenario, but it outlines the types of cost-benefit analyses undertaken by pharma companies and helps us understand why the industry as a whole isn’t rushing to become fully digital.
“Now, you can sequence whole genomes for under £1,000 and some even claim under £100. That scale of cost savings is reflected in the capacity of the technologies we’ve been talking about.”
Karen Taylor, research director at Deloitte
Where is the value?
For small molecule drugs without strict temperature requirements, how much value is there in having data every second as opposed to every minute, or even every hour? The answer to this will vary from organisation to organisation, but it’s unlikely that heavy investments are being made for low-risk products. On the other hand, for biologics like cell and gene therapies (CGT), where the supply chain is much shorter and a temperature excursion can render a product useless or even dangerous for the end user, data every second becomes a necessity. “Your patients aren’t all going to be sitting in one hospital, there might be 100 of them in 100 different places,” says Taylor. “Then there’s the time between manufacturing the drug and getting it to the patient.” The supply chain for CGT products looks very different to that of small molecule drugs, which extends the level of visibility required, encompassing manufacturing as well as logistics. “You’ve got patients sending their blood one way,” says Taylor, with the genetic engineering required to create a CAR T therapy in between, and “then being sent back”. “If you’re going into that space, you’re probably building a supply chain that is already very digitally-enabled,” she adds.
So, if CGT products are the prime use case for end-to-end supply chain visibility, why should the larger pharma companies invest in it? “If you’re going to demonstrate to investors, shareholders and the public that you’re taking sustainability seriously, you’ve got to have the data to show it,” says Taylor. “That means you’ve got to have the data from an intelligent supply chain. If you’ve got that in place you can start to have ambitious targets and know where to improve.” There’s certainly value for companies in being able to prove that they’re environmentally friendly. With climate change high up in the public consciousness, being ahead of the competitors could win investors over.
“For the future, being able to scale up in response to how much medication is needed will improve not only the environmental footprint but also the efficiency and productivity of companies.”
Emily May, life sciences insight lead at Deloitte
Although pharmaceuticals is a product category that’s enjoyed less scrutiny than those of other industries, with the common narrative being that the carbon footprint is a necessary evil in healthcare, there’s a growing focus on Scope 3 emissions – those generated by companies along the supply chain, like energy suppliers and outsourcing partners. “Encouraging those companies to take measures to reduce their carbon footprint is really important,” says Taylor. The challenge is that the most environmentally-friendly supply chain partners might not be the most costeffective, and when profitability is another reason investors part with their cash, there’s a risk to being a first mover on an uneven playing field. For Taylor, the solution is to level the playing field by taking the decision in unison. “You’ve got that push and pull between having first-mover advantage versus the need to collaborate to get the suppliers to, for instance, buy green energy,” she says.
The other reason for an intelligent supply chain is simply the necessity for it, and that’s been borne out by the Covid-19 pandemic, in which companies were forced to augment the level of supply chain visibility in the manufacturing and distribution of vaccines. “They needed to know where all of their risk factors were,” says Taylor. “Having that data gave them a real impetus for transformation.” At the manufacturing level, May believes having predictive intelligence was vital for companies, and the experience of Covid-19 will only drive further adoption. “Covid really shone a light on [the need to be] adaptive in our supply chains,” says May. “That predictiveness and scaling manufacturing up and down can really be driven by having that knowledge and visibility. For the future, being able to scale up in response to how much medication is needed will improve not only the environmental footprint but also the efficiency and productivity of companies.”
It is clear that the pharmaceutical industry has a great deal to gain from augmenting its supply chains through using the latest technology, but with an understandable reluctance to implement a company-wide transformation, who will be the first mover and whether there will be a first-mover advantage, remains to be seen.