Transform your S&OP with Machine learning

First of all, I think in an S&OP process, there’s no such thing as traditional.

The first step in everything is data gathering. And for me, machine learning plays a pivotal role in supporting data preparation, data gathering, and data-driven analysis.

Ultimately, AI and machine learning can really revolutionise the data side of the S&OP. AI can also help automate the process.

S&OP essentially is about bridging gaps, and that’s very much a people process.

But the one thing I don’t think will happen is that AI will replace people. It should support your processes and provide the insights required for your people to discuss gaps in the business.

How can businesses embrace Machine Learning and AI to reduce waste and create more sustainable business outcomes?

With AI & machine learning, decisions become more fact-based.

Machine learning can help attain more accurate forecasts of future demand. But more importantly, embracing the technology should also help businesses identify where things go wrong, why the reality differs from the plans, and provide practical advice to improve business performance.

And clearly, as you leverage such technologies to improve, waste will also be reduced. For example, by helping you optimise planning and consolidate orders to reduce the number of shipments, seemingly small improvements can have a significant positive impact on your footprint.

It’s my personal hope that people remain core to the operation. The end goal of S&OP is always to help your people break down silos to collaborate more seamlessly. By bridging teams together and facilitating better communication with data, machine learning can help drive sustainable business outcomes.

How can Machine Learning accelerate bottom-line growth?

So, if we look at growing the bottom line, the better your data, the better your ability to match sales and the supply chain, and the more profitable you can be.

One consideration is cost; the other is turnover.

Any company’s goal is profit maximisation, and lowering supply chain costs is critical. S&OP highlights areas for improvement. By driving operational efficiencies across the supply chain, you can cut waste, optimise your investment in working capital, and reduce operating costs.

How do you see the role of machine learning in improving forecast accuracy?

There’s so much data out there, and processing it is incredibly difficult. You must find and apply patterns to improve forecasting and supply chain planning capabilities. This is simply too big for humans to handle, but not for machines.

You can easily integrate data sources and identify trends that would otherwise be impossible to understand, let alone act upon.

There can be rapid benefits here because machine learning can help improve forecasting.

It can help you plan your promotions, introduce products, and create the basic layers you need to implement the first processes.

It can also show the gaps quite clearly.

It can examine the insights provided by Sales and Supply Chain teams and determine where there are critical differences. Comparing these can facilitate a clearer picture, ensuring that arguments are fact-based and data-driven.

If you look at this from the perspective of your CEO, machine learning can help them improve supply chain resilience. Look at the disruptions we’ve had over the last couple of years. You can identify those kinds of disruptions early and help the business prepare and act ahead of others.

Final question: With the rapid adoption of AI-enables technologies, how do businesses ensure their supply chain decisions remain ethical?

Ethically, machine learning is a new concept, and so the challenges are still evolving. Who owns the data, and what should you do with the outcomes? What if the outcomes are biased?

It’s almost a bit early to see the potential pitfalls, let alone overcome them. But you must proactively explore some of the possible dangers.

The role of people in the supply chain is still vital. And I expect that won’t change. In fact, at Slimstock, our customers are the main driver of a product roadmap. And developing AI-enabled solutions that help people make smarter, faster decisions remains at the heart of our product development.

I love connecting with customers, so I’m really pleased to be part of this fantastic S&OP community event.

A huge thank you to Daan Majoor for giving us his time and so much detail on Machine Learning in S&OP and what the future might hold for businesses in the supply chain.