Over the last couple of years, we’ve endured an unprecedented time. There’s been the pandemic, above all, along with a steady increase in the effects of climate change and the fallout from geopolitical events, culminating in the Russian invasion of Ukraine. All are unfamiliar events that are disrupting supply chains in multiple ways. With the increasingly volatile and fast-evolving nature of the market, most enterprises expect their supply chains to make faster, more accurate and consistent decisions in real-time (see Figure 1).
To achieve this goal, CSCOs need to design a new supply chain operating model that is geared around real-time data availability and people enablement for better decision making. Digitalization is the critical enabler, not only because it helps automate tasks originally requiring some form of human judgment or action. But also, because it helps unleashing employee’s trapped talent by freeing up their time from nonvalue-added tasks and by augmenting their decision-making capability. Leading supply chains are already on their way:
- Intel’s autonomous planning uses machine learning (ML) to analyze results from the planning engine and explain plan changes cycle over cycle, including what drove particular changes. It can identify the need for a new plan and then start an autorun. If the scenario meets all stated goals, it can autonomously publish it as the plan of record for the company. It’s also able to create a knowledge base that gets stronger over time by accumulating supply chain knowledge and expertise.
- Nestlé is deploying technology to make its order-to-cash process more automated and intelligent. The company is exploring ML technologies that can predict different customer ordering patterns, estimate risks, forecast short-term customer orders, propose different allocation scenarios and autonomously make real-time adjustments to the allocation.
The Path Towards Supply Chain Autonomy
Most CSCOs from global supply chain organizations agree that over the next 10 years the most advanced global supply chains will be leveraging hyperautomation — a combination of technologies including robotic process automation (RPA), ML and many others — to become more autonomous.
Business-driven hyperautomation requires a disciplined approach to rapidly identify, vet and automate as many business processes as possible. The opportunity is twofold. On one side, there is an extensive and expensive set of business processes — across many functions of the end-to-end supply chain — that still require humans to perform manual tasks and mundane decisions. On the other, the massive and growing amounts of data that are being created each and every moment around global supply chains, make it impossible for humans to perform sensible, fact-based decisions. Unless augmented by technology.
CSCOs must create a multiyear, integrated digital supply chain strategy and roadmap to experiment, pilot and roll out hyperautomation. CSCOs should consider organizing their roadmap in three steps: automation, augmentation and autonomy (see Figure 2).
The path is determined by how fast these technologies will mature and when they’ll become mainstream. In Gartner’s Hype Cycle for Supply Chain Strategy Research, technologies such as RPA are expected to become mainstream in two to five years. If you haven’t started yet … well, you are very late. Machine learning is expected to reach mainstream adoption in supply chains in five to 10 years. This means you must develop your machine learning strategy now, within your current supply chain strategy planning cycle.
Although it’ll be a 10-year journey, CSCOs are advised to start working on this transformation now. Technology is developing really fast, and there is no time to wait and see. CSCOs should continue pushing for more process automation through RPA, while combining it with ML to also automate more complex decision making.
The final destination in this journey might be full supply chain autonomy. However, none of the CSCOs we interviewed expect a lights-off supply chain, with no people at all. CSCOs agree that hyperautomation is an opportunity to free up people’s time for the value-added work that only humans can perform. The ingenuity and empathy of the human brain can’t easily be replicated. Defining supply chain strategy, driving innovation, taking care of customers and controlling data biases and autonomous decision making are among the tasks that CSCOs expect humans will be responsible for delivering in the supply chain of the future.
Gartner Supply Chain