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Decision-making technologies come to the forefront of the AI space
Decision Intelligence was not a term I was overly familiar with before attending this year’s Gartner Supply Chain Symposium (London, Sept. 27–29) and I admit that on hearing it I thought it was somewhat tautological. Don’t intelligence and decision-making go hand in hand? Surely you can’t make decisions without intelligence… (That was rather naïve of me; anyone who follows politics might say, “Clearly, some decisions are made without intelligence.”) But anyway, I was missing the point. Decision Intelligence is a term used by California-headquartered company Aera concerning the application of artificial intelligence (AI) and applied analytics (AA) to the decision-making process.
Aera leverages technologies, including AI and machine learning (ML), and domain expertise to “improve and automate decision-making across supply chains for pharma companies.” The idea is that the technology relieves decision-makers of the burden of making the less crucial decisions; companies get automated messages about shortages and spikes in demand, as well as recommendations on how to fix the issue. ITPro Today noted that Aera’s cloud-based search and data modeling platform “can ingest data from any enterprise system, aggregate the data and perform predictive analytics along a company's supply chain, correlating demand, inventory .and revenue streams.”1 The company counts among its clients Big Pharma firms such as Merck KGaA, Darmstadt, Germany, whose head of group smart manufacturing, Michelangelo Canzeroni, told the conference how using this technology has helped the company streamline its 49 data sources in an attempt to “get to a single source of truth.”
Canzeroni explained, “I don’t want to spend so much time analyzing my data that I am too late to make a decision.” He added that the impact of the new technology has been a 10% reduction in inventory and a 3% reduction in waste.
Decision Intelligence is just one of the analytical decision-making technologies that are set to transform the pharmaceutical supply chain. Gartner has observed that the next three to five years “will see an increase in the adoption of digital supply chain technologies, as well as technologies that improve human decision-making.”
By 2026, across all industries, more than 75% of commercial supply chain management application vendors will deliver embedded AA, AI, and data science. As well in decision-making, AI, ML, and robotics are set to make strides in supply chain areas such as inventory management and warehouse automation. Gartner also predicts that by 2026, 75% of large enterprises will have adopted some form of intralogistics smart robots in their warehouse operation and 25% of supply chain execution (SCE) vendors will have rewritten their core application to a microservices architecture. There is also a warning, however: “Through 2026, 80% of companies will suffer significant value loss due to a failure to merge their digital supply chain twin and control tower initiatives.” 2
Those companies who believe that the AI-driven supply chain is still some way into the future might need to sit up and start making some intelligent decisions today.
1. “Aera Brings AI Decision-Making to Merck Supply Chain,” Oct. 14, 2019, itprotoday.com.
2. “Gartner Predicts the Future of Supply Chain Technology,” April 20, 2022, gartner.com.
Julian Update is Pharmaceutical Commerce's former Editorial Director.