If there’s one thing that supply chain managers can trust in, it’s that uncertainty is here to stay. The global supply chain crisis that was exacerbated by the pandemic is now being followed up by other international problems exposing how fragile they really are.
So much so, the problem no longer sits under the duress of supply chain managers or even the COO. The impact of this crisis on top and bottom lines has propelled it to the top of the executive agenda.
Navigating these problems requires short-term fixes and a long-term strategy. The focus is getting spiralling costs under control and reinforcing supply chains before we are faced with yet another problem to contend with. In fact, it’s estimated that 88% of companies fail to meet the requirements for ‘strategic resilience’. And for a quick fix, they’ve been pointed to technology solutions, especially Artificial Intelligence (AI).
But here’s the problem: technology isn’t the solution. It cannot protect your business from disruption, nor arm it for resilience. However, the insights derived from AI as a part of a digital strategy that connects with your entire team, can be the answer.
Applying powerful insights extracted from AI in supply chain management
AI can underpin significant efficiency gains across the manufacturing supply chain, from planning demand to optimising manufacturing and workforce decisions, and managing inventory and logistics to get goods to customers around the world.
A connected system that syncs up demand planning with workforce allocation, for example, ensures changes are reflected across the rest of the supply chain. By forecasting the probability of different future demand outcomes, the teams on shift can be optimised according to their skills, availability and labour regulations. And to save on costly warehouse management, guidelines for minimum and maximum safety stock can be determined by AI.
When integrated, it can ensure every decision, every forecast and every piece of analysis is informed by a complete, up-to-date picture of every department’s challenges, goals, and most recent performance.
This kind of clarity naturally generates advantages including optimised capacity planning, higher productivity, lower costs and greater output. But does AI adoption alone translate to connectivity?
Just as AI can connect the different stages of the supply chain, it requires the staff working within the stages to maximise its potential. This is no small feat, with some global shipments moving between 30 different businesses and 200 interactions. Investment in using AI in supply chain management is just as important as the investment into the technology itself.
This visibility among partners enables collaborative decision making which makes for tougher strategies and an organisation-wide culture of innovation. So far, this kind of supply chain visibility is near impossible; tier one vendors are unlikely to reveal who their tier two suppliers are, and they don’t want to reveal who their tier three suppliers are… With modern supply chains extending through multiple touchpoints, any insights are difficult to extract. The alternative is to rely on a wide range of indicators and use them to make holistic, strategic decisions.
The limitations of AI in the supply chain
Yes, AI is now a must-have to overturn uncertainty. But it does raise new challenges. Overcoming these, in turn, outlines opportunities to fully maximise the potential of AI along the entire supply chain.
So, how can you solve these major issues and create a connected, visible supply chain?
- Distrust of AI: Clarify how AI makes its decisions with training and explainable AI. Visible data and understandable, reliable recommendations can ease concerns of this ‘mysterious’ technology.
- Growing skills gap: Only 27% of UK executives believe their non-technical workforce can do a digitalised job. Effective training and encouraging technology use is key to bridging similar gaps in the supply chain.
- Not enough data: Pull siloed data together through collaborative efforts across departments that prematurely connect prior to the supply chain. Manufacturers, shippers and suppliers must keep in close contact to allow insights to be reliable, accurate and effective in the future.
Investing in the culture of a connected supply chain
Getting the most out of AI to create a connected supply chain relies on a thorough, company-wide approach to technology. As with any investment into a digital strategy, organisational changes, updates to business processes and upskilling are required to navigate digital transformation.
From adopting the new AI solution to maximising its full potential, company culture is a key focus. Many factors need to be considered including analysing existing technology stacks against stakeholders and breaking down the siloes embedded in internal processes.
Firstly, each department looks at data from a different perspective and for a different purpose. AI-based technology can create a single source of truth that spans these siloed departments. But incentives to utilise this data are required to maximise its impact. Encouraging interaction with this data and the communication of the extracted insights across the supply chain necessitates a revised internal culture. Moving towards this is the only way to capture the full value of AI.
Secondly, change management and capability building are key to addressing the skills gap limiting the application of AI. If you want to encourage employees to embrace the new way of working, you need to make sure the data science tools are easy to use and understand – whether you have a STEM PhD or not.
AI-based technologies give businesses the opportunity to build a digital version of their entire organisation. They can capture in real-time the decisions that flow from ‘top to bottom’ (i.e. from boardroom to SKU) and from ‘left to right’ (i.e. linking handover from demand planning to production planning).
Overall, implementing AI and overriding the challenges it presents requires a significant investment. The time and money required to create a connected supply chain need to balance the scope of short-term revenue gains and long-term resilience. The biggest challenge is committing to change that alters not only the digital strategy but reconfigures the organisation’s culture.
A truly connected, resilient supply chain requires a strategy that utilises applicable insights derived from AI, staff that can maximise AI’s potential and an organisation-wide culture of innovation. It’s not about the AI – it’s about how you use it.
About the author
Neha Puri leads the supply chain and logistics team at Faculty, an applied AI technology company.
With over 15 years’ experience in transport and logistics across Europe, US and Asia, Neha is focussed on helping operations leaders build more resilient supply chains.
