Meeting availability targets has always been tough, but today it just feels harder. Every day headwinds hit. Supply chain teams scramble to revise forecasts, switch suppliers, increase safety stock, but somehow they’re still left with the same central problem: uncertainty.
The only thing guaranteed is uncertainty, what should supply chains do?
Article from | Peak
Meeting availability targets has always been tough, but today it just feels harder. Every day headwinds hit. Supply chain teams scramble to revise forecasts, switch suppliers, increase safety stock, but somehow they’re still left with the same central problem: uncertainty.
Look at consumer demand, for example. Expectations just keep going up. A product can go viral on social media and leave you moving and heaven and earth to stock that SKU or at least make it available in much higher quantities.
The supply-side isn’t much better. Products are now composed of raw materials procured from multiple continents, meaning even businesses that trade in just one region can be impacted by disruptions on another continent.
To tackle this uncertainty we respond with blunt, sub-optimal strategies. If we’re seeing supply-side uncertainty, we might reduce the size of our supply base. If we’re dealing with demand-side uncertainty, we might compensate by holding excess stock. But reducing our supply base creates new risks and holding excess stock ties up working capital. These are commercially damaging downsides.
So how should we respond to uncertainty? First, we have to find out what’s causing it.
Is complexity the culprit?
Simply put, yes. The world is getting more complex, making it harder to forecast and satisfy demand. To understand complexity, we have to see supply chains as systems. Each layer of complexity is another interdependent component, and the greater number of interdependent parts a system has, the greater the risk it has of failing.
But the way many supply chains confront complexity lacks nuance. See, there’s a difference between internal complexity and external complexity. External complexities can’t be controlled. But we can manage internal complexity, through various levers.
Often supply chain leaders pull those levers of internal complexity, hoping it will help them meet their availability targets. But this can be a mistake. Internal supply complexities are often created to respond to external complexities.
By simplifying our supply chain we may miss the upsides of supply chain complexity, like the ability to diversify risk with a larger supply base or delivering a larger product range that meets more customers’ needs.
Ultimately, supply chain leaders are faced with reality: most uncertainty stems from external complexities. So, what do we do now? Rather than wrestling with reality of an uncertain world, perhaps the answer is to embrace it?
The world is only going to get more complex and more uncertain. The simplification solution isn’t going to cut it as a long-term strategy. Instead, we’ve got to embrace complexity and uncertainty as enduring features of our supply chain. Embracing uncertainty in a complex world means building our capabilities so that we can thrive through it.
On a practical level, that means being able to forecast accurately, smoothing out the peaks and troughs of demand and supply, and being able to respond operationally, replenishing stock in the right place, at the right time.
In reality, supply chain teams have been on an endless pursuit of greater forecast accuracy for years, discovering there are limited levers they can pull to improve it. One of those levers might be improving the size or skillset of your supply chain team.
But if you ask most supply chain leaders if their team has enough or can easily get more resource, the answer will be a predictable “no”. Ask them if their team has the time to research or upskill and you’ll likely face the same answer. So that’s a non-starter.
Another lever we might look to pull is technology. Everyone’s talking about artificial intelligence (AI). We hear how AI can analyze in seconds what would take a human hours. But if you ask most supply chain leaders whether they have the budget or inclination to invest in AI, you’ll be short of affirmative answers.
So why are supply chain teams so understaffed that they can’t accurately forecast? Why aren’t leaders investing in AI? Here, uncertainty is the enemy too.
With so much uncertainty around the global economy, many leaders are risk averse. They’ve already had to implement layoffs, so the last thing they want to do is increase the size of their supply chain team only to face the painful dilemma of potentially downsizing.
When it comes to AI, leaders only want to invest in it if they can guarantee it will provide a return. It’s a new technology, they worry that their teams won’t use it, they worry it won’t improve availability, meaning they’ll have wasted their money. That’s understandable. AI doesn’t come with a guarantee, does it?
Embrace uncertainty with guaranteed results
That’s why we’re introducing a performance guarantee to Inventory Intelligence, our suite of AI applications that businesses use to forecast, order and balance optimal stock levels across their supply chain network.
We’re Peak. After levelling up availability for businesses like Speedy Hire, Marshalls and Eurocell, we’re certain our AI can deliver the same results for you. We’re so certain, we’re willing to guarantee those results.
The Peak performance guarantee promises that overall availability for your products will not fall below an agreed rate during the guarantee period. If your availability falls two percentage points below your agreed availability rate, we will refund the price of the AI application you’ve bought from us.
The only way to embrace uncertainty is by building the capabilities to deal with it. For this, we don’t just believe AI is the answer, we’re guaranteeing it is.
The content & opinions in this article are the author’s and do not necessarily represent the views of ManufacturingTomorrow
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