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80% of Supply Chain Not Accounted for in Current Digital Decision Models

80% of Supply Chain Not Accounted for in Current Digital Decision Models

Oct. 2, 2023
Digital models are missing the vast majority of the supply chain environment.

Digital models are missing the vast majority of the supply chain environment, according to analyst firm Gartner.

This incomplete view of the supply chain results in digital trade-off analysis failing to improve decision makers’ outcomes, despite the potentially transformative capabilities of these new tools. Digital trade-off analysis includes things such as what-if analysis, scenario modeling, or simulations. Digital trade-off analysis offers improvements in analytical power and clarity when processes are adhered to and enabled with high-quality data. 

“The ‘digital-to-reality gap’ will continue to hamper supply chain performance objectives unless technology investments are complemented by enabling decision support for local, cross-functional decision makers, who have better visibility into the hidden and often undigitized elements of the supply chain,” said Suzie Petrusic, senior director analyst in Gartner's Supply Chain Practice, in a statement. 

Gartner’s research, based on an analysis of 600 survey responses of supply chain decision makers received in December 2022, found that current use of digital models to analyze trade-offs made no meaningful impact on the rate of good decision outcomes.

Slightly more bad decisions were made with the use of digital tradeoff analysis than without and marginally increased the percentage of bad decision outcomes. The research defined a “good” decision as one that led to and met the decision maker’s expected supply chain performance and cost outcomes with low decision maker regret.

“More than half of supply chain leaders reliant on digital technology to make a recent strategic decision (e.g., S&OP decisions, network design decisions, or disruption response decisions) told us that they felt they would have landed on better decision outcomes without the use of their models, and our analysis suggests that they are correct,” said Petrusic.

“The fault is not just with technology itself, but rather with the incomplete picture of the supply chain that these digital tools capture,” added Petrusic. “Up to 80% of the actual, on-the-ground processes that these technology investments are meant to be ‘optimizing’ are not even reflected in current digital models.”

The Case for Localizing Supply Chain Decisions

CSCOs are faced with two primary paths forward to improve end-to-end visibility and better decision outcomes: global or local, cross-functional strategies. A global strategy continues down the path of full digitalization including distilling complex end-to-end processes into a fully digital model and achieving a level of process adherence that has thus far eluded supply chain leaders.

A second strategy calls for empowering localized and cross-functional leaders already present throughout an organization’s supply chain with decision rights. These decision makers, who benefit from visibility unavailable to their global counterparts and can make use of the technology already available to them, have been shown to make good decisions 11% more often than global, end-to-end decision makers. By augmenting this human visibility through digital trade-off analysis technology, these local decision makers are 83% more likely to make a good decision than a bad one. 

“A shift to relying more on a localized approach does not mean that CSCOs’ digital or globalization playbooks need to be reinvented, but it does suggest that some adjustments can be made where localized, bottom-up processes can provide both a more realistic picture on the ground and a better basis for digitizing process segments that would otherwise elude a top-down, global approach,” said Petrusic.

For CSCOs concerned with improving strategic decision-making and digital ROI, Petrusic recommends: 

  1. Localizing more strategic decisions to a cross-functional level
  2. Digitizing the human element of local, cross-functional decision models
  3. Accelerating the digitization of supply chain’s end-to-end processes

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