My mum used to say that if you wait long enough, the same things will come back in to fashion. I suppose that is also true when you blog long enough about supply chain.

In 2012 I wrote a short blog about demand driven & agile supply chains, which seems to be all the hype back then. Some of the quotes I picked up from social media then; ‘you have to be agile to survive in today’s global competitive environment’ and ‘you’re agile or you’re dead!’

My point back then was that it requires context on where you need to be agile in the supply chain. Supply chains need to be segmented according to product and customer behaviors. There is indeed a difference if I locally acquire and produce short shelf-life milk, with high volume and stable consumer demand, or innovative technology products, with a six-month life cycle and components sourced from all over the world.

Even within the same company, it is wise to apply different supply chain strategies. Lee’s matrix from his 2002 article “Aligning Supply Chain Strategies with Product Uncertainties”, provides a good starting point for a segmentation conversation.

Fast forward to today and agile is back in the supply chain, with a vengeance, and with good reason. COVID showed us that when you cannot sense early and respond quickly, you are in a world of pain or even face an existential threat.

Now I read quotes from very respected supply chain leaders. For example, Ivanka Jansen, Chief Supply Chain Officer (CSCO) at Royal Philips:

‘We’re really looking to design the supply chain from the customer back and create and test our own agility.”

And Unilever’s CSCO Marc Engel:

‘At the end of the day, every dollar we spent on agility has probably got a 10x return on every dollar spent on forecasting or scenario planning.’

These leading companies are transforming their supply chains with agility being a clear element of focus. This is possible because a lot has changed in the last ten years.

Artificial Intelligence (AI) and Machine Learning (ML) have matured and are widely available, including open-source algorithms on-line. Big Data has become…well really big…and feeds AI and ML algorithms to extract value.  The Cloud now provides almost unlimited data storage and computing power. Innovative SAAS platforms are making the technology available in an integrated fashion, on-demand and within financial reach for most businesses. Process automation, probabilistic planning and cognitive automation at scale for complex international enterprises, have now become a reality.

This creates a new foundation on which AI is starting to augment and automate the knowledge worker and increase agility in the supply chain.  AI algorithms will not only sense changes quickly, but also response fast by taking over short-term cognition and decisions from the supply chain professional.

AI will automatically gather data, analyse it, interpret, make a probabilistic trade-off, judge, decide and execute. Only at a much higher speed, at a larger scale, with more consistency and precisions, and with more endurance than any human is ever capable off. We’re in the age of the automation of the knowledge worker, which will change the way we work forever.

What has not changed is that companies still need to segment their supply chains and the operating model that runs it. An operating model where human and machine work together as a Humachine to sense quick and response fast will require different technology, processes, human capabilities, talent, rewards & recognition, and human-machine interaction, to name a few.

There is enough work ahead, but the agile supply chain is back. Only now it’s for real!

Photo credit: https://www.tcs.com/