This past Saturday morning, I had the pleasure of joining panel of analytics and supply chain experts on the Clubhouse social media platform for a discussion on artificial intelligence (AI) adoption in supply chain planning. The panel included Jay Koganti—Vice President Supply Chain COE at Estée Lauder, Mike Hulbert—VP of Consumer Business at, and Sivakumar Lakshmanan—COO of

AI Adoption in Supply Chain Planning

Saturday’s discussion is the first in this series aimed at spurring faster innovation and adoption of AI in solving traditional supply chain problems, such as:

  • How can we improve planning effectiveness?
  • How do we reduce waste from supply chains?

These questions are compelling many to look for breakthrough innovations. The panel’s broad themes will focus on clarifying the misconceptions about AI usage in supply chain planning, as well as challenges, opportunities, and the road ahead.

Let’s highlight some key takeaways from Saturday’s discussion.

AI Promotes Better Use of Data

The evolution of planning is an ecosystem of three components: cloud technologies, algorithms, and data. Currently, however, the technology and the use of algorithms are advancing faster than the data.  Further, many essential data points are not being captured. Examples include external competitive information and macroeconomic variables. To capitalize on this new approach to AI-driven supply chain planning, companies cannot wait to begin capturing and preparing this data. The deep science and algorithms behind AI systems necessitate—and excel with—a variety of data to deliver usable results.  This data must be captured, cleansed, and managed in order for AI to deliver the expected value.

AI Augments the Role of Planners

Due to existing systems, most current planning is highly clerical. Traditionally, planners input a single number into their ERP or planning systems, which was never more than an educated guess. These numbers were often wrong due to insufficient data and incomplete science. The role AI can play will be to augment the role planners play in the business because they will be informed with science-driven information. Because planners have deep knowledge of the business, the new role planners will play is solving problems that the analytics engines will inform, but that cannot be solved by a machine, especially when considering cross functional collaboration.

Introducing AI into the planning function is not a matter of “human vs. machine.” Rather, AI provides the ability to automate mundane tasks and let the planner role perform more value-add activities. Essentially, as the role of the planner evolves strategically, many of the more clerical tasks may indeed be obsolete. Further, because supply chains are becoming increasingly complex, AI has the opportunity to elevate the planner role through the ability to make smarter, more strategic decisions.

AI Drives Supply Chain Collaboration

Supply chains cannot operate in autonomy. The ability of AI technologies to make projections in real time provides the ability to make quicker, yet more strategic decisions across all functional areas, such as marketing, pricing, and finance. This transformation towards more nimble, collaborative companies—albeit drastic—is long overdue.  More importantly, the value is amplified where touch points between these functions are connected.  We talked about this in a recent blog post, “Demystifying the Centralized Demand Signal.”

Further, the S&OP cycle can be greatly reduced. The monthly cadence around the S&OP cycle will be reduced to real time coordination between functions.  Moreover, S&OP will be facilitated by AI models that incorporate inputs from across the organization.

If you have any questions about these topics, how you can begin to strategically use AI in your supply chain, or if you would like to join our next chat on Clubhouse , please reach out.

Sam Iosevich, Chief Analytics Officer & Managing Partner

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Published On: May 6, 2021Categories: Agility, Analytics, Planning, Sam Iosevitch, Supply Chain, Tailored Intelligence