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Gartner's Six Levels of Supply Chain Planning Autonomy

Posted by Jeff Bodenstab on Jun 22, 2017 8:04:49 AM

Gartner levels of Supply Chain Planning Autonomy.jpgSource: Andrew Downard, Gartner Supply Chain Executive Conference, May 2017

Business is moving fast and there is so much new data now speeding through the pipes that Gartner says it’s not possible to plan a supply chain without some level of automation. So they now offer a scale (a maturity curve) to measure the level of automation in your supply chain planning. In a presentation at their most recent Supply Chain Executive Conference, Gartner analyst Andrew Downard described their six levels of “algorithmic” decision support:

  1. General information consists of straightforward facts, like historical data from sales and production
  2. Specific information adds on suggestions and recommendations; such as from statistical forecasting
  3. Advisory guidance incorporates automated alerts that help the supply chain planner as he or she plans and executes tasks
  4. Opt-in automation occurs when systems perform the complex tasks themselves, such as simulating multiple models and recommending the best approach
  5. Automation that can be overridden takes responsibility for the task unless told otherwise; such as automatic reorder points for replenishment
  6. Non-optional automation takes responsibility for the task, and planners don’t review the decisions

The highest stage of supply chain autonomy is when the supply chain acts on its own, says Downard. But in transitioning to this level, he recommends starting with scenarios where cause and effect are better understood, such as “sense and respond”, and then progressing to more complicated situations that require testing, probing and learning.

In a recent report, Gartner analyst Noha Tohamy adds that synchronized, end-to-end supply chain planning decisions "must be made faster and more dynamically, taking into account more factors that can be feasibly manually analyzed.” She says that Chief Supply Chain Officers (CSCOs) are using analytics and machine learning to not only advise planners, but to generate and execute autonomous decisions without human instruction.

This “algorithmic supply chain” she says requires “the organizational maturity and cultural readiness to embed and constantly rely on algorithms….” It is evolving toward fast autonomous actions and decisions which execute based on your predetermined goals such as customer service level targets and margin attainment. Downard adds that leading companies are very proactive about this, “looking aggressively for places where they can do algorithmic planning and get people out of the process.”

Conference keynote speaker John Philips, Senior Vice President of Customer Supply Chain for PepsiCo, described his vision of such a highly autonomous supply chain, adding that he sees additional impact from emerging disruptive technologies such as digital connections to the home, virtual shopping experiences and crowdsourced delivery.  In a separate presentation, Gartner analyst Tom Enright used Lennox as an example of a company that is leveraging data from increased connections and analytics, pointing to their use of machine learning and their plans to tie data from on-site equipment into their planning algorithms. Enright offered the advice, “Shift your thinking from big data to big answers.”


Click below to read more about transitioning to more autonomous algorithmic supply chain planning.

Improve your planning process productivity - Supply Chain Planning Brief

Topics: Supply Chain Planning

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