Merck sets the next destination for its ‘self-driving’ business
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Merck sets the next destination for its ‘self-driving’ business

Sooraj Shah — August 2019
Merck Healthcare’s CIO Alessandro De Luca has driven the automation of the company’s supply chain. Now he wants to dial up the pharma giant’s competitive advantage by taking it on a journey towards autonomous business operations.

As the CIO of Merck Healthcare, the German pharmaceutical giant’s largest division, Alessandro De Luca likes to slice his responsibilities three ways.

A core challenge is, naturally, applying digital technology to accelerate the discovery and launch of new drugs. Alongside that is a focus on the provision of cutting-edge sales, marketing, sales and commercial systems and services designed to deliver a multi-channel view of all of its many different types of customer.

But it is the third part to his role that has raised his renown among his CXO peers: De Luca has executed on a vision to build a ‘self-driving’ supply chain at Merck that has made extensive use of AI, sensors and analytics to automate large parts of Merck’s manufacturing and logistics processes.
A self-driving journey   

The self-driving supply chain not only removes many manual processes (and their inevitable human error), it also importantly includes a substantial “value element,” says De Luca.

“DeLuca-Merck”

“We want our operation to be a source of competitive advantage while delivering on the company’s overall vision to put the patient at the center [of all our activities]. The self-driving operation eliminates waste — whether material, personnel or energy waste — and ultimately that helps us ensure that our patients receive the drugs they need, when they need them and at an affordable price,” he says.

Merck’s self-driving supply chain took shape four years ago when the notion of leveraging machine-learning capabilities to automate the balancing of supply and demand became a reality. To achieve its goals, De Luca and his team drew on the expertise of several technology partners, most notably a specialist in cognitive systems, Aera Technology, whose software promises to “make real-time recommendations, predict outcomes and take action autonomously.”

De Luca, who joined Merck in 2012 as head of supply network operations before segueing into the CIO role three years ago, maps out the journey. “We started by first ensuring that every element of the end-to-end supply chain was being monitored and visualized in real time. Then we built the predictive element using machine learning to give us a better signal of demand that would automate and simplify existing processes. The ultimate step of the self-driving supply chain came when AI ensured we could automatically synchronize supply and demand,” De Luca says.

He emphasizes that both the technology backbone provided by Aera and Merck’s development of new processes were equally important. Now, driven by that combination, Merck’s supply chain is prescriptive (advising planners or operators), so the AI actually decides the right level of demand and supply.
Follow the leader

De Luca classifies the analytical capabilities underpinning that self-driving model in three distinct categories: descriptive, predictive and prescriptive. Merck is working with Aera for the descriptive elements (which use data aggregation and mining to provide insight from existing data) and for the prescriptive category in order to prescribe optimal actions as different situations arise. For predictive capabilities, Merck uses the best of breed machine learning algorithms from the SAP IBP demand module, Aera and Palantir. The company is also planning to leverage Tracelink serialization data for advanced analytics.

 “There is no single supplier that is capable of solving all of these areas, so it is about choosing what the business needs,” he says.

While technology plays a crucial role, De Luca is only too aware that the lifespan of any tech-driven differentiator is short; what was once state-of-the-art is now commodity. While Merck may have devised the revolutionary concept of self-driving supply chain three years ago, he says, today almost every company in Merck’s sector is pursuing a self-driving supply chain agenda.

Even as that tech-enabled differentiation is diluted new opportunities are emerging. He argues that the real source of competitive advantage is in how new technology is applied and, critically, rapidly tied into business processes.
Mastering change

But as any CXO knows, applying new technology always has its challenges, not least of all change management.

“Apple has been successful because its products are so easy to use and the adoption is fast. So when we look for technologies that create value, the one KPI we focus on is usability. This could be for an operator on the shop floor or the planner in the control tower but if the technology is easy to use and manage then it typically creates value,” he says.

But it’s not always immediately apparent which technology partners or solutions are most appropriate.  “Our approach is to partner with a selected few vendors and learn, fail, succeed in a continuous loop. That means there’s a fast cycle that enables us to identify which technology, which vendor and which solution is really successful,” he says.

Inevitably the move to AI automation has meant a shift in the company’s mix of skills. For example, as a result of the self-driving supply chain, there has been a reduction in the number of planners; conversely, instead Merck now needs more supply chain and solution architects — which in some cases has meant reskilling.

While not all projects will deliver great outcomes, De Luca says the determinants of success are change management and collaboration in design. “Any technology [adoption] should go hand in hand with the change management and the designing of tools should be done in partnership with the business. We believe there are no technology projects, just business-driven projects that are enabled by technology solutions,” he says.

That is reflected in some of the company’s metrics on supply and demand.  In recent years, forecasting accuracy has risen by 6% while the inventory carried has been reduced by 5%.
Self-driving business ops

Having seen the benefits of a self-driving supply chain, the next step is to apply the same principles of AI-driven automation to business operations and new product launches. “This would expand the scope behind the supply chain to manufacturing, procurement, customer service and management,” De Luca explains.

“The [self-driving] project is only complete when we’ll be able to serve every single customer around the world with our medicine at the highest service level — and to ensure that even if there is a shortage of supply, we’re still able to supply patients,” says De Luca.

And that applies to new as well as existing products. “No company in the world ever really knows what the demand is going to be when they launch a new product. So leveraging AI to crack not only the self-driving supply chain but also the launch of a new product will help our people realize how much their product will be in demand,” he says.

De Luca may have borrowed the self-driving analogy from the technology changes that are already disrupting the car industry but what he is proving is that the potential for AI to remould business operations is equally impactful.

First published August 2019
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