AI in supply chains: when resilience requires more than technology

As the global economy continues to open up after COVID-19, the disruption that we thought was temporary has become stubbornly persistent.

2021-12-13OperationsRetail & Consumer

At the close of 2020, 57% of businesses were reporting serious disruption as a result of raw materials shortages, a limited workforce and high shipping costs. Nearly a year later, this disruption is still here. And demand is still increasing. Add to that wider challenges such as the energy crisis and geopolitical tensions, most executives would agree that the so-called ‘New Normal’ is ringing in a new era of constant crisis for the supply chain. 

Driving value has always relied upon the supply chain, but with a new level of risk threatening the bottom line, senior executives are now seeking greater visibility and resilience in their operations. But according to the World Economic Forum, an estimated 88% of companies fail to meet the requirements for ‘strategic resilience’. 

As with any major challenge, organisations often look for a quick fix solution, whether that’s the latest software tool, outsourcing or hiring an expensive consultancy. Artificial intelligence (AI) is no different. We see it touted around as a buzzword to fix all problems. But simply buying a one-off AI solution will not translate to a future-proof supply chain. AI needs to be embedded within an organisation as part of a long-term strategy to secure a competitive advantage and end-to-end resilience. And operational teams need to be able to use the technology itself, which means building capability.

How to adopt AI to build supply chain resilience

AI systems appear to be the obvious answer to supply chain uncertainty, with 67% of businesses accelerating their AI strategy in 2021. But when AI isn’t applied fully, it doesn’t just drive up costs without return, it can also create deeper fractures between operational teams and stages of the supply chain: distrust of AI among employees driven by lack of understanding limits its potential use cases; uneven skills gaps across teams can beef up silos further; and poor quality data can generate inaccurate insights, resulting in the wrong decisions being made. 

The AI-powered supply chain

The real value AI can generate resides in its ability to drive impact across the entire supply chain. From inventory optimisation, to delivery and logistics, to resource allocation, AI-based demand forecasting can minimise uncertainty while maximising competitive advantage by highlighting potential scenarios and how to respond to them. 

To make supply chains more resilient, AI needs to be integrated horizontally across the supply chain and also integrated vertically – that is, from the boardroom where the strategic imperatives are set, down to SKU-level through the operational teams. 

Constant, unexpected disruptions lead to risky, reactive decisions, generating excessive costs and prolonging the impact of external crises. But by connecting the boardroom to individual operational teams, decision-making can unite the separate stages of the supply chain and, in turn, can create a proactive, disruption-proof culture of innovation. It can link planning to constraints on the ground, connecting strategy and execution.

On a more specific level, AI can optimise inter-linked decisions across operations to more readily meet KPIs, help make trade-offs, and respond in real-time to supply chain shocks by using a range of indicators of demand, such as historic sales data, internet searches and mobility.

Now, clearly none of these things come overnight. Today’s executives need to be prepared to invest in AI for more than a few months’ worth of quick fix. It has to be part of a mindset where forward-thinking leaders want to embed the long-term benefits of modern technology into their business. 

As with any digital technology, it needs to be embedded directly into an organisation’s way of working. This requires time, energy, commitment and communication to make it happen.  Insufficient change management is the most significant risk to the implementation of AI in the supply chain. But getting it right can secure a competitive advantage in the short, medium and long-term. 

To find out more about preparing your business for the next crisis, get in contact with our team.