How Decision Intelligence is Transforming the Supply Chain

With technology that automates decision making, companies can avoid risk and capitalize on opportunity, making it possible to keep pace with the volume and velocity of decisions that must be made each day.

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If the past few years have taught us anything, its that the past simply does not predict the future for supply chains.

Supply chain professionals and technology providers have been hyper-focused on firefighting in response to the unexpected. The reality is, its the ability to be predictive, prescriptive, and proactive— identifying issues and responding with the right actions at the right moment in time — that will reveal a new source of competitive advantage for supply chains.

With that in mind, what can we gain when we stop focusing on responding to disruptions and, instead, reimagine the way we make decisions?

A recent BCG report found that, in an analysis of supply chain KPIs from 2011 to 2020, delivery performance declined independently of inventory and staffing levels. Even though companies boosted inventory and staffing levels at the start of the COVID-19 pandemic, they still could not prevent a steep decline in service.

The core issue is a need to improve decision making. As the report authors note: Most [companies] still focus on using AI for analytics and prediction—for example, to forecast demand and plan production. Companies have not pursued the more valuable application of using AI to make recurring decisions by recognizing patterns in big data that humans cannot see.”

This is the opportunity for decision intelligence, which Gartner defines as a practical domain framing a wide range of decision-making techniques bringing multiple traditional and advanced disciplines together to design, model, align, execute, monitor and tune decision models and processes.”

To put it in laymans terms, decision intelligence makes it possible not only to gather and harmonize data from enterprise systems and data sources, then use it to provide data-driven recommendations — but also to execute those decisions by writing back to transactional systems, capturing the outcomes of decisions and their context for the future.

Decision making at scale: The new competitive advantage

This unlocks a new opportunity for supply-chain planners by giving them the ability to automate decisions based on business rules and strategy.

Historically, planning solutions have been focused on identifying and providing a suggested response to an event, and they are very good at that. But the problems we should focus on fixing are the inefficiencies of performance across supply chains that prevent companies from making better decisions at the moment of maximum impact.

With technology that automates decision making, companies can avoid risk and capitalize on opportunity, making it possible to keep pace with the volume and velocity of decisions that must be made each day.

As BCG states in its report, Planners need to understand the insights they receive, but typically they do not have enough time to digest all the inputs and make good decisions.” The authors recommend moving toward a new approach of piloting AI tools and automation to generate decisions.

Think about the growth opportunities that can be game-changers for a business — prioritizing inventory thats about to expire to drive greater profit  or aligning with more consistent suppliers to ensure better OTIF performance  or unifying optimal payment terms across purchase orders.

In many cases, the window of opportunity to capitalize on these decisions is small. But it can take hours or days for teams to analyze data, align on a course of action, and execute, and thats assuming they have the bandwidth and visibility to see the opportunity at all.

The human element: Less ‘firefighting,’ more strategic planning

Not only does this technology deliver faster, better decision making at scale, but it also helps supply chain planners excel at their jobs.

Workforces have typically managed decision making through a patchwork of data science, spreadsheets, planning and modeling, data warehouses, and collaboration, all while relying on fragmented data sources. Today, these processes and technologies are no longer sufficient to effectively respond to changing conditions, or even to support fast, reliable decision making at the best of times.

Decision intelligence changes the paradigm by leveraging AI to understand, recommend, predict, and act with machine speed and precision. The AI becomes a virtual business analyst — working 24/7/365 to interpret the data at scale, make recommendations, and execute decisions. This frees up supply chain professionals to focus on value-added strategic tasks that help companies remain competitive.

Whats more, decision intelligence fills the need to capture internal knowledge by recording not only the data, but the context and outcomes of decisions made. This is critical, as the number of employees who left their jobs during the Great Resignation highlighted the need for long-term knowledge retention. This will continue to be important as the younger workers taking these roles lack the decades of experience their predecessors had and are more likely to move on to different positions in a shorter time.

As more companies begin to augment and automate supply chain decision making, theyll begin to see the benefits throughout their enterprise ecosystem — with a level of visibility that goes beyond planning. This investment can scale beyond the business to enable resource optimization, waste reduction, improved customer service and more.

Companies will benefit within mere weeks by reducing complexity and accelerating their decision cycles, while simultaneously reducing their reliance on multiple people, processes, data models and disconnected niche technology investments.

Early adoption of decision intelligence will pay dividends by enabling companies to address problems and make decisions they couldnt consider before or didnt think were possible with the status quo.