Scaling AI in the supply chain to improve intelligence

New demands are stressing the supply chain

It’s certainly no longer “business as usual” for supply chains. A convergence of factors has placed significant pressure on organizations’ supply chains to address a wide range of new challenges and priorities that, in many cases, existing supply chain capabilities aren’t capable of handling.

Most existing supply chains were built for a different time, when scale was achieved by delivering truckloads of goods en masse to warehouses and then big-box stores. This model relied on a high level of demand predictability (so visibility was less important) and valued efficiency over resiliency. With supply chain disruption everywhere, this model must change—but how?

At the core of this transformation are data and artificial intelligence (AI), which are uniquely positioned to provide the insights, agility, and speed companies need to build a completely new supply chain that’s fit for today, tomorrow, and years to come.

Building an intelligent supply chain network

Companies that can put data at the core of their supply chain and apply AI at scale can create a connected and truly intelligent supply chain network.

An intelligent supply chain network can benefit companies in numerous ways.

• It can help them gain visibility to late-breaking supply disruptions or demand blips, providing the information needed to resolve issues in near real time.
• It helps increase agility so companies can deliver on unique customer requirements with speed, specificity, and scale—boosting product availability and service levels, reducing lost sales and inventory costs, and increasing production and fulfillment efficiency.
• It can increase resiliency (e.g., maintaining On Time and In Full service metrics) while reducing companies’ carbon footprint and overall sustainability risk.

The below illustrates, at a high level, what an intelligent supply chain looks like.

Challenges to leveraging data and supply chain AI at scale

Despite recognizing the power and value of data and AI, companies will likely continue to find it difficult to leverage their investments more broadly. In fact, a full 79% of COOs acknowledge they know how to pilot AI, but struggle to scale it across the business.

Why? A number of obstacles may be holding them back.

Breaking through obstacles to achieve greater impact

Overcoming these obstacles isn’t easy—but it must happen for AI to scale and deliver genuine business value. In our experience, three things can help minimize the roadblocks and allow AI to flourish across the enterprise.

The first thing a company needs for AI to have a large-scale impact is a clear and integrated vision of where the enterprise wants to go with AI—its North Star, so to speak. It can’t be limited to one function, department, or business unit—that’s the antithesis of scaling. Also critical is the ability to translate this vision into the major initiatives the company must executive to achieve the end goal. Both are vital to taking the subsequent steps to build the foundation that enables a company to realize short- and long-term value from AI and, importantly, to get C-level buy-in to fund such a mega-investment.

AI and advanced analytics can process massive and diverse data sets from all functions to provide better visibility across the supply chain. But with more data sources, more computational power and more server capacity will be needed. With the cloud, a company can connect this data to create one single and trusted source of truth. The cloud also enables organizations to tap into new data sources to extend and enhance visibility and, thus, create greater opportunities for AI to deliver value.

As mentioned earlier, many companies find they don’t have the right talent in place to successfully scale the use of AI in supply chain. In fact, Accenture research found that only 38% of supply chain executives feel their workforce is ready to leverage the technology provided to them. Thus, upskilling or reskilling people to be proficient in applying AI to specific use cases that generate significant value is absolutely vital to the scaling of AI.

Ecosystem partners such as technology vendors and consulting firms also can be great sources of important skills, supplying talent who can augment a company’s existing employees where needed. Such companies have already gone through the steep learning curve required to scale AI and learned the lessons. Their insights and guidance can be extremely valuable in helping companies through what’s often a difficult and complex undertaking.

The future of intelligent, self-driving supply chain networks

Intelligent technologies and connected end-to-end data, when combined and scaled, can add immense value to any company’s supply chain. The combination unifies the supply chain, creates new efficiencies and operational capabilities, and unlocks capital to reinvest in new business models that enrich customer experiences, build competitive advantage, and support profitable growth.

Longer term, this powerful combination of technologies and data will fuel a shift toward truly self-driving supply chain networks—which take value and innovation to a whole new level.

AI can automate demand planning, supply planning, inventory optimization, and execution with a focus on making decisions automatically, without human intervention (i.e., a shift from human driving the machines to machines guided by the humans). Meanwhile, ML enables self-learning, predicting, prescribing, and optimizing supply chain performance automatically across functions. And in a self-driving supply chain, automation can flag and resolve exceptions in real time—for example, ML-based algorithms can predict exceptions and supply chain outcomes and if the process changes over time, cognitive computing learns and adapts to it.

AI truly has the potential to transform any supply chain—and in today’s environment, such a transformation isn’t an option anymore. With the right combination of people, processes, and technology, companies can stop piloting AI and start scaling it so the supply chain network can begin to realize its full potential value—both in the short term and longer term.

Explore how Accenture can help power more intelligent supply chains with analytics and AI. Visit www.accenture.com/ai