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Gartner: Top Supply Chain Organisations Adopting AI Fastest

Graham Turner

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ai use in supply chains
New survey finds that top performers prioritise productivity over efficiency in digital, resource and people investments.
Top performing supply chain organisations are investing in artificial intelligence and machine learning (AI/ML) to optimise their processes at more than twice the rate of low performing peers, according to a survey by Gartner, Inc. The survey also revealed that the best supply chain organisations are using productivity, rather than efficiency or cost savings, as their key focus to sustain business momentum over the next three years.Gartner surveyed 818 supply chain practitioners across geography and industry from August through October 2023 to understand how the supply chain is adapting to changes in economic values, fostering sustainable growth, harnessing digital assets’ potential to enhance productivity, and revitalising the workforce and network of people.

“Top performing supply chain organisations make investment decisions with a different lens than their lower performing peers,” said Ken Chadwick, VP analyst in Gartner’s Supply Chain Practice.

He added: “Enhancing productivity is the key factor that will drive future success and the key to unlocking that productivity lies in leveraging intangible assets. We see this divide especially in the digital domain where the best organisations are far ahead in optimising their supply chain data with AI/ML applications to unlock value.”

In the survey, organisations were scored across five key metrics measuring business and people outcomes to determine their performance level.

Among the key findings, the data showed that high-performing organisations are far ahead in automating and/or optimising processes that utilise supply chain data using AI/ML. “High performers” were those reporting performance that exceeded expectations over the last 12 months across the five measurements in supply chain outcomes.

Supply Chains Must Extract Value from Intangible AssetsThe divide between high and low performers in optimising processes with AI/ML hints at a deeper rift in strategy among organisations. Top performers increasingly prioritise extracting value from their digital assets to drive productivity, rather than making digital investments to achieve efficiencies such as cost savings.Among the top five digital investments expected to deliver value, high performers are farther along in implementation across the board. These include (high performing vs. low performing organisations):

  • Partner with IT to establish unbreachable data security mechanisms (74% vs. 61%)
  • Create ethical and binding data privacy frameworks for use of customer data (68% vs. 50%)
  • Write cybersecurity measures into supplier and staff contracts (66% vs. 57%)
  • Capture supply chain specific customer satisfaction data (58% vs. 40%)
  • Analyse and leverage supply chain specific customer use and satisfaction data (57% vs. 35%)

“Capturing, protecting and then leveraging an organisation’s data through the use of AI/ML is an example of how organisations are increasingly turning towards intangible assets to extract new sources of value,” added Chadwick. “High performing organisations are moving beyond the initial implementation stage to full adoption, resulting in better decision making that unlocks new sources of value.”


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Gartner’s survey found similar trends in how top performing supply chain organisations are achieving intangible value from their people and resource investments. Chadwick noted that rapid tech advancement will drive the necessity for organisations to upskill their talent, with investments in learning and development needed to achieve the full benefits of the organisation’s digital investments.

When managing resource investments, top performing organisations were far ahead in collaborating with suppliers to maintain supplier consistency and working exclusively with suppliers that have their own risk controls. These characteristics are typical of organisations that have achieved increased supplier visibility through the use of mature data and analytics capabilities.

Graham Turner

Sub Editor

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