After 18 months, stories about supply chain issues just won’t go away. It feels like it’s been relentless. Bad story after bad story and you get the sense of a grudging acceptance of supply issues being some sort of new normal.
It’s made those of us who work in the supply chain business busier than ever, helping organisations to respond reactively to the issues as they occur. Fire fighting each new crisis.
And it’s certainly on the mind of CEOs. In our 2021 UK CEO Outlook supply chain risk has rocketed up the agenda this year to become the number 3 issue for UK CEOs. 59% report that they have experienced disruption in the last year, with the same proportion saying they plan on increasing their supply chain resilience.
It should be a wake-up call then to look at what we can do to break out of the fire-fighting cycle to provide that resilience CEOs are looking for. Because the reality is that we’ve never had a better suite of tools in the armoury to stop these problems.
For me there are three key issues right now:
Visibility of supply chain data
It’s an old adage that you can’t manage what you can’t measure. It’s as true in supply chain as anywhere else.
We’ve never had as much data about our supply chain as we do right now. However there’s now so much data the problem has become seeing the wood for the trees. Getting clean data, and then properly linking data sources together and visualising it have become the key issues holding us back.
Few organisations truly understand issues below the first couple of tiers of their supply chain. And yet it’s often in these lower tiers that problems occur and bring operations to a halt. Many organisations we speak to, for example, only have the address and postcode for a supplier’s invoice receipting, not where production operations are. Hard then to predict disruption due to weather or other events if you don’t know the actual locations of your supplier’s operations.
We now have a range of digital tools that enable us to drill down into the lowest tiers of supply chains. And supplier intelligence systems that can integrate multiple data sources to provide an updated view of suppliers. With AI driven analytic platforms to clean up data held within our own systems.
Building integrated platforms populated with clean data is the first crucial step to avoiding future supply chain issues.
Predicting, not forecasting, supply chain problems
I received a number of responses to a LinkedIn post recently, arguing that many of the issues we have faced couldn’t have been predicted. I disagree.
A respiratory pandemic is a predictable event, we’ve had them before after all. A ship getting stuck in a canal is a predictable event. Fuel supply issues have happened before and are predictable. Labour shortage in critical skills groups, especially following significant changes in immigration policy for example, is predictable.
As human beings we are conditioned to worry about the negative events that are most likely to happen and push the other ones to the back of our mind. Statisticians call it regressing to the tail, reflecting the much lower probability of them happening. So, whilst the events of the last 18 months were eminently predictable, we allowed ourselves to think they wouldn’t happen and certainly not all at the same time. Consequently, we didn’t plan for them (certainly not for them happening all together) or mitigate them.
Humans are limited by only being able to manage so many things at once. In supply chain risk terms this has meant that for a long time we’ve only planned for the events that we thought most likely to happen.
The latest predictive supply chain risk tools overcome this. Powered by AI and machine learning they have almost infinite capacity to think through all the what ifs. Running endless scenarios, including all those seemingly improbable events in the tail, and flagging early the impact if they occur at the same time.
Building predictive rather than forecast driven supply chain tools will give us a much better chance of being less on the back foot when future issues occur.
ESG management for the supply chain is the natural evolution of supplier risk management
ESG will have a more profound impact on the supply chain function than any other. Organisations will need to verify and validate ESG metrics throughout their supply chain, either because regulators demand it (as we’ve seen in recent announcements from the UK Competition and Markets Authority) and because consumers will expect to see it too.
In our survey 65% of UK CEOs say they face increased demands from stakeholders for increased reporting and transparency on ESG issues.
Transparency and visibility of the end-to-end supply chain is critical to delivering this as it will likely be those lower tiers of your supply chain that cause the issue. Often the reason that major brands appear in the headlines due to ethical or environmental issues is as a result of issues caused by their suppliers, rather than their own operations. How much do you know about the ESG credentials of your supplier’s supplier, and then their suppliers after that?
Getting clear ESG data from all those tiers and bringing it together into a single view where risk can be assessed and prioritised will be essential.
Many organisations are repurposing existing supplier relationship management systems and approaches to do this, but they simply aren’t up to the job. The data they generate is too one-dimensional and doesn’t take into account data sources such as news feeds to spot ethical breaches, often in other far-flung jurisdictions. Auditing data across thousands of suppliers is labour intensive at a time when supply chain teams are already stretched. And once again the more data you gather the harder it is to gain clear insight from it.
The latest ‘Know Your Supplier’ solutions have the ability to link internal supply chain data with publicly available data (such as company ownership) and data from suppliers themselves, and then visualise this in an easy-to-understand way. An always on capability means the system is looking for problems all the time, and picking up on those issues that are easily missed by busy human resources.
Fixing physical supply chain supply issues is front of mind right now. Consumers however are increasingly unforgiving of ESG breaches, so getting ahead of the curve on this is important to avoid future shocks.
So, now that we have digital solutions that are capable of crunching vast amounts of supply chain data into usable insight, that can use AI and machine learning to predict events that humans overlook, and can help drill down into the lowest tiers of our supply chains to deliver ESG commitments, it’s time to break out of the current cycle of reacting to problems and let the machines do the heavy lifting to avoid future crises.