Can AI transform the supply chain?

By | 2 minute read | March 9, 2020

Chief Supply Chain Officers (CSCOs) and their organizations often struggle to optimize decision making and manage disruptions because they lack end-to-end visibility. More than 75 percent of CSCOs and supply chain leaders report that they have “very limited” supply chain visibility[1] — and 65 percent say they have limited or no visibility beyond Tier 1 suppliers.[2]

The overwhelming amount of data spread across siloed systems and external sources is a familiar challenge among CSCOs – but they don’t always know how to address it.

AI has emerged among best-in-class supply chain organizations[3] as a textbook solution to enable end-to-end supply chain visibility. It correlates data across siloed systems and external sources, making it easier to quickly implement control tower solutions that provide a single view of data in a personalized dashboard.

However, just one in three supply chain leaders in the retail and manufacturing sectors recognize AI as one of the “next major steps” in digitizing supply chain.[4] While adoption rates may lag among some, AI is poised to enable industry-leading supply chain organizations. Gartner recently identified AI as one of the top strategic supply chain technology trends that can affect broad impact, noting that the technology has reached a critical point in terms of supply chain capability and maturity.[5]

Several years ago, IBM began applying AI to its own supply chain when it launched a strategic initiative aimed at improving visibility. The primary objective was to connect supply chain professionals with data and intelligence from across silos and disparate sources, to better prevent disruptions, manage events and quickly respond to any issues. The IBM Supply Chain team believed it was critical to establish a single, end-to-end view of the company’s many Enterprise Resource Planning (ERP) systems, as well as other internal and external sources of data including third-party logistics providers (3PL).[6]

The IBM supply chain team recognized that AI could help address visibility challenges by drawing data directly from the organization’s ERP systems and other relevant sources, analyzing it in real-time, and serving up actionable insights. This would help them to make better decisions faster and take more confident action to resolve disruptions. They also understood that AI could help aggregate key performance indicators (KPIs) and produce smart alerts for specific personnel.

Benefits of AI across the supply chain

Since the IBM supply chain organization began leveraging AI, the company has achieved exceptional results, successfully:

  • Avoiding any major supply impacts.
  • Shortening critical supply chain disruption management time from 18+ days to just hours.
  • Maintaining greater than 95 percent of serviceability targets.
  • Reducing expedite costs by 52 percent.
  • Realizing an 18 percent reduction in inventory levels.

Over the past year, IBM also saw a 5 percent decrease in year-over-year operational costs and an 11 percent reduction in year-over-year structural costs.

The success of this AI initiative led IBM to commercialize its related AI capabilities as IBM Sterling Supply Chain Insights with Watson and as blueprints for purpose-built control towers. If you’re interested in learning more, read how global electronics manufacturer Lenovo is harnessing AI to reduce global supply chain costs, complexity and risk.

 

[1] Supply Chain Worldwide Survey (Geodis), 2018 [2] Deloitte Global Chief Procurement Officer (CPO) 2018 Report, Q1 2018 [3] Forbes and ARC Research, January 2019 [4] Retail Technology Review, Trends in Digital Supply Chain [5] Gartner, Top Trend in Supply Chain in 2019 [6] IBM, Manufacturing Leadership Award Nomination

 

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