By Stephen DeAngelis
The business environment is getting more complex and uncertain. The team at John Galt Solutions observes, “In today’s economic landscape, uncertainty across the supply chain is inevitable, whether due to the effects of climate change, demand and supply variability, or global unrest. To keep up, supply chain leaders need to continuously make good decisions quickly that consider the ever-changing circumstances, emerging opportunities and disruptions, to improve how responsive and adaptable they can be.”[1] Making good decisions quickly lies at the heart of every business. In fact, Bain analysts, Michael C. Mankins and Lori Sherer, insist, “The best way to understand any company’s operations is to view them as a series of decisions.”[2] They add, “We know from extensive research that decisions matter — a lot. Companies that make better decisions, make them faster and execute them more effectively than rivals nearly always turn in better financial performance. Not surprisingly, companies that employ advanced analytics to improve decision making and execution have the results to show for it.”
Unfortunately, journalist Joe McKendrick reports, “More than three-fourths of supply chain executives are not prepared to observe and predict changes that may disrupt the flow of their business.”[3] Which means, they are unprepared to make good decisions in a timely manner. McKendrick makes another interesting point. He writes, “Part of the problem is that much of [the decision-making process] is not automated — these professionals report spending nearly 14 hours a week manually tracking data on inventory and shipments.” Artificial intelligence (AI) solutions can help. In today’s fast-moving, always changing business environment supply chain professionals can take advantage of AI-powered decision science. At Enterra Solutions®, we are advancing Enterra Autonomous Decision Science™ (ADS®) which is a new way of problem-solving and decision-making, going beyond advanced analytics to understand data, perform analytics, generate insights, answer queries, and make decisions at the speed of the market.
Why Autonomous Decision Science is Necessary
Bernard Milian, Managing Director for Europe at Demand Driven Technologies, insists that supply chain professionals, due to their nature and circumstances, tend to rush decisions. He explains, “If you’re in the supply chain business, you’re even more inclined to anticipate — you’re resolutely forward-looking. If you’re in the supply chain business, you like to get things done, and make decisions — you’re resolutely action-oriented. These two qualities combined, plus a little friendly pressure from your professional environment, can lead you to a serious mistake: making decisions too early! Of course, you don’t want to decide too late.”[4] He advocates “just in time” decision-making. One way to help supply chain professionals make just-in-time decisions is to let AI-powered solutions make routine decisions so that humans have more time to concentrate on more nuanced and consequential decisions. And AI-driven solutions can even help professionals make those decisions. The team at John Galt Solutions observes, “As technology has evolved, new approaches to create value and drive competitive advantage have emerged — one of them is decision intelligence powered by AI and machine learning, to help inform and shape the steps of decision-making amidst increasing levels of complexity and variability.”
The Logility staff observes, “Supply chain executives make vital decisions daily. Disruptions … just add to what is already a complex undertaking. A holistic approach using reliable, properly analyzed data is required to achieve [their business] goals. Data is useless if it’s not actionable.”[5] McKinsey & Company analysts suggest that the best place to use AI-aided decision-making is in a corporate nerve center. They explain, “By bringing top management together in a single, flexible structure, a nerve center enables companies to navigate more efficiently through dynamic situations, guiding the whole organization to understand, react, and improve in a timely manner. For the supply chain, the nerve center will cover multiple priorities, ranging from conducting scenario-based sales and operations planning to overseeing parts availability, logistics, and supplier qualifications. Across all these activities, however, the nerve center acts as a single, authoritative information source, point of contact, and decision-making venue.”[6]
Better Decisions Lead to Better Results
The John Galt Solutions team reports, “Leading companies that thrive across business climates [focus] on higher quality decision-making that helps them master uncertainty and harness complexity.” Jan-Willem Adrian, Executive Director Supply Chain & Logistics at NEOM, insists too many supply chain professionals believe that better supply chain visibility will solve most of their problems. It won’t. He explains, “It is true that supply chain visibility is critical — but it is only the first step. While you may start by asking ‘how do we create visibility across our supply chain?’, your real question is probably ‘once we gain visibility, how do we make well-informed, timely decisions whilst understanding their full impact on the supply chain?'” Like the McKinsey analysts, he believes leveraging a control tower (or nerve center) will help; and, like the McKinsey analysts, he also recommends scenario planning as a big part of making better decisions. He explains, “Making good decisions requires understanding inter-related trade-offs. However, the typical siloed supply chain setup leads to sub-optimal decisions, moving the problem from one area to the next. Therefore, having the ability to view the impact on the end-to-end process chain, rather than a single operational silo, will ensure that decisions take into account the entire value chain, keeping the end goal in mind. As such, being able to simulate various scenarios across the supply chain in real-time, will allow users to analyze the impact of decisions before they are made.”[7]
At Enterra®, we offer a set of interconnected business applications that span the value chain of an enterprise and work in concert to perform end-to-end optimization, planning, and decision-making at scale and at the speed of the market. We call this the Enterra System of Intelligence™. This system of intelligence works alongside existing client systems by sending instructions to and coordinating the actions of client Systems of Record and then learns from the outcomes. Enterra’s system autonomously performs end-to-end optimization, planning, and decision-making at scale and at the speed of the market with human-like intelligence and reasoning. The Enterra System of Intelligence is comprised of the following business applications:
• Enterra Consumer Insights Intelligence System™
• Enterra Revenue Growth Intelligence System™
• Enterra Demand and Supply Intelligence System™
• Enterra Global Insights and Decision Superiority System™ (Enterra Business WarGaming™)
This System ushers in a new era of AI-enabled management science by merging cutting-edge analytical techniques with a business’ data and knowledge to Sense, Think, Act, and Learn® on enterprise data to meet the changing needs of the market. Enterra’s System acts as central “brain” within an organization, ingesting diverse datasets, business logic and practices, and strategy, to uncover unique insights and generate autonomous recommendations across the enterprise at market speed.
Concluding Thoughts
The Logility staff insists, “You must be sure that the decisions you make don’t just work for today but will continue to work in the future to meet your economic goals. The economic sustainability of your company is at stake as much as anything else.” Autonomous Decision Science technology can autonomously analyze data, generate insights and make subtle, contextually informed, judgment-based decisions quickly, accurately and with limited human intervention, and then learn from the results of those decisions. It can effectively reshape the way companies structure and optimize their value chain. It can also help business leaders rapidly explore a multitude of options and scenarios to make sure decisions support today’s operations as well as those in the years ahead.
Footnotes
[1] John Galt Solutions, “Embrace Uncertainty and Complexity with Decision Intelligence,” SupplyChainBrain, 5 August 2024.
[2] Michael C. Mankins and Lori Sherer, “Creating value through advanced analytics,” Bain Brief, 11 February 2015.
[3] Joe McKendrick, “Technology Still Doesn’t Supply The Insights Needed For Supply Chains,” Forbes, 17 March 2024.
[4] Bernard Milian, “Mastering Timely Decision Making in Supply Chain Management,” IntuiFlow Blog, 9 April 2024.
[5] Staff, “The Rewards for Accelerating and Improving Your Supply Chain Decision-Making,” Logility Blog, 7 July 2022.
[6] Didier Chenneveau, Jean-Frederic Kuentz, and Martin Lehnich, “Coronavirus and technology supply chains: How to restart and rebuild,” McKinsey & Company, April 2020.
[7] Jan-Willem Adrian, “Moving Beyond Supply Chain Visibility to Continuous Decision Making,” C3’s Yard Management and Dock Scheduling Blog, 25 September 2017.
