The supply chain triangle is a simple framework representing the biggest challenge of supply chain management: balancing high service levels, low costs and healthy cash flow.

For the past forty years, supply chain leaders have gotten better at balancing all three corners by standardising product portfolios and aggregating spend with suppliers. As long as there were no disruptions to demand or supply, they could confidently make the right decisions, like knowing (with a reasonable degree of accuracy) the right amount of inventory needed to meet demand. 

At the same time, this highly-specialised supply chain was becoming increasingly complex and, therefore, fragile. Disruptive events, like the 2011 Tsunami in Japan, proved this framework couldn’t handle shocks: it triggered shortages of components and parts for automotive manufacturing that couldn’t be sourced elsewhere, leaving manufacturers unable to fulfil customer orders and forcing them to pay more for alternative supplies. 

It took the pandemic to show that there’s a fourth dimension that needs to be considered: resilience. The permanent disruption left in its wake, mainly volatile demand and supply, confirmed the other three elements of the triangle couldn’t be managed if your supply chain isn’t resilient enough. What the supply chain triangle needs is a redesign, and resilience should be front and centre (see below).

Resilience adds an additional dimension to the framework which encourages supply chain leaders to focus on risk alongside service, cost and cash. From potential labour shortages and geopolitical tensions to surging freight and energy costs, the New Normal has a range of risks you need to surface in every decision you make. The problem is, your current systems and technologies can’t help you do that. Your ERP, for instance, might be able to support the motions of planning and make it more efficient, but the burden of making those increasingly complex decisions ultimately rests on you and your team.

So, you’re left with slow, error-prone, manual decision making across thousands of SKUs. This doesn’t just generate sub-par decisions that, in turn, impact service, cost and cash. It also incurs additional management overhead as planners and supply chain managers have to navigate this manual process. If you don’t have the bandwidth to perform this function, you’ll probably end up setting simplistic blanket rules and targets across your portfolio which fail to delineate between different products, markets, and customers, eventually driving lost value.

This new triangle requires new technology. Technology that automatically generates optimal decisions for each individual SKU and directly factors in the trade-off between service, cost, cash and resilience. And artificial intelligence (AI) can do just that.

How can AI improve supply chain resilience?

(a) It helps you understand what’s really happening in your business

Right now, organisations have a vast amount of data to process. Manually bringing together data from all of your systems and then extracting useful insights is impossible without an army of analysts and endless review meetings. But AI can do this for you. It brings together data from all your systems and blends it with external indicators and in-house expertise to give you an accurate, bird’s-eye view of what’s happening in your organisation. More importantly, it can tell you why these things are happening. It does this by unpicking cause and effect in your business so you can probe how your decisions affect your organisation and therefore make truly informed decisions.  

It can also tell you what will happen next with massively improved accuracy: AI-enabled demand forecasting leverages all that connected data to generate granular estimates that directly surface uncertainty into each prediction. It doesn’t just give you a clearer view of the demand signal, however. AI decodes the different drivers behind each forecast, enabling you to understand why something will happen and therefore what you can do about it. So, you can more precisely identify the best action for each individual SKU.

(b) It rapidly translates this understanding into optimal decisions

Today, a majority of organisations set blanket targets across huge portions of their product portfolio and aren’t optimising for the trade-off between service, cost, cash and resilience. What AI can do is automate the process of going from the prediction of demand to the likelihood of supplying it and, given your objectives, determine the optimal amount to buy or produce for each SKU in each location across the entire portfolio. 

You can still review and adjust production plans for priority SKUs that generate the most revenue, but can be sure you’re making the best possible decisions across your entire portfolio without having to manually make decisions for every SKU. 

(c) It connects those optimal decisions with your teams

Having automated optimal decision making, you then need to translate the decisions into actions for your teams. Today, this would mean another manual process, like updating spreadsheets and systems with the decision for SKU X, and then conducting alignment meetings to ensure it will be executed correctly. AI can automate this entire process and get the right insights to the right people and systems for you.

For example: everyone gets a record of assumed level of demand, production receives updated plans for the factory floor and customer service knows it needs to notify their customers of a smaller shipment. No more time-consuming spreadsheets or organisation silos. Your optimal decisions are disseminated widely, executed correctly and quickly, without error or excess management overhead.

Build a more resilient, agile supply chain with AI

By replacing poor-quality insights and manual processes with high-quality inputs and automatic optimisation, AI can dynamically adjust the way you plan for each SKU in each market for you. And it doesn’t just ensure the new triangle is balanced across your product portfolio; thanks to automation, it results in faster, less erroneous decision execution, too. So, your supply chain can react to the next shock optimally, as-and-when it hits.

All of these capabilities are at the heart of decision intelligence. This new category of technology is already being used to streamline planning processes across the entire organisation, from demand and supply planning to logistics management and inventory optimisation. 

Click here to find out more about how decision intelligence can help you reprioritise for resilience.

Recent Blogs


Subscribe to our newsletter and never miss out on updates from our experts.