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Unilever’s move to “being digital” - how Aera’s Decision Intelligence offering is transforming market agility

Stuart Lauchlan Profile picture for user slauchlan November 14, 2023
The global giant has re-thought its approach to data-driven decision-making.

Unilever logo © Unilever
(© Unilever)

Global conglomerate Unilever underwent a major re-organization last year, part of which involved the ambition of moving from “doing digital” to “being digital”. What does that mean in practice? According to Wendy Herrick, Head of Customer Operations, North America, Unilever:

Doing digital means that you understand what needs to happen, but being digital is actually making it happen. I think when we started our journey, we were talking about it a lot. But I think as we've learned and progressed in this space, we're actually being digital. That doesn't mean just in our technology, but also with our people and our jobs and the organization and how we're choosing what technologies we use in the organization to fit within that.

One major digital transformation initiative has involved the firm’s supply chain management strategy, with the company partnering with Decision Intelligence platform provider Aera to develop “an end-to-end, self-driving supply chain”.

It’s a major transformation and one that’s delivered results, according to Herrick: 

Within our four walls we've done a great job on getting the right data, having the ERP, the system differentiation, but when you look outside, we need external data to be able to even expand our operation from, I call it, field to fork. Everything in between those points are super hard, to enable your demand forecasting to be effective and efficient. Customers are a part of that and a big maker of demand, but so are consumers. The program [is] to really expand our data set to help us solve the problems we're trying to solve and making sure we're on the shelf or online each and every day for a consumer when they when they want us.

What is digital?

Flash back to 2010/2011 and Uniliver started to contemplate what its digital program was all about and what it meant in real terms. Herrick recalls:

We did a lot of research on what does it really mean? If you look back of course, there's the web, then there's the iPhone, and then the data just continued to grow. So how are we going to capture that data and make it lucrative for us? A lot of companies said, 'I'm going to be a tech company', like pizza companies and stuff like that.

The amount of data out there today has increased enormously, she adds:

When I was in college, it was bits and bytes, you know, megabyte, gigabyte, all that kind of stuff. And now we have a Yodabyte!

The constant here is change, she argues:

It’s not like you capture a data lake and then there it is. It's just a constant continuous thing that you need to build on. That journey for us was super-important, but you get to the stage where you have so much data and you get data paralysis. So what are we going to do with with this to help our teams? That's really where we started exploring automation. Everyone went on the journey of Robotic Process Automation, using some of the data. And then we nailed down what our tech stack looks like to make sure we could get to that human in the loop, on the loop and out of the loop.

So, what does that loop differentiation mean in practice? Herrick explains:

The reason for the human in the loop on the loop and out of the loop is because how do you explain it to those people who weren't on the journey already? So from the top to the bottom of the organization, it was an easy way to explain what we're trying to do. That's where that came along. It's like, how are we going to educate everyone in the organization to be on the journey? When I look at the benefits, I would say when we initially started, we weren't great at it. We were on a learning journey together and it's like picking a pilot, where there was already Robotic Process Automation, something simple to get quick wins to do that.

But having bold ambition also matters, she adds:

We initially were like, 'We're going to automate the Top 100 decisions". Well, we had a lot of learnings on the way it's automating decisions. It's about putting decisions where you do want the human. Mergers and acquisitions - you're not going to probably put a decision automation on that kind of thing. But I think the benefits that we measure is decision velocity. It's not only the decision itself, but how quickly you can then push that decision. So you're given a competitive advantage when the market changes or your customer changes or your consumer changes.

Growth is a big enabler, and cost effectiveness, but I think importantly as well customer success is super-important in this. What are you doing in the decisions you're automating to make sure you're meeting their needs, but not only meeting them, but predicting and prescribing what could be next to actually delight them.


In terms of driving adoption of the new way of thinking, Unilever has learned lessons along the way:

I think the ambition was right, but [in terms of] stakeholder management and change management, I think we underestimated how difficult that might be because everyone wasn't on that journey. It's all well and good being a champion, but if you don't bring others along with you it's going to be like pushing water uphill all the time. So I would probably set up a little bit differently in how we managed our stakeholders, and that change management across the board.

I think we're there now. But again, really educating people is really important. And what I love about Aera, and this was a key thing for us to really move forward, was we've been used to technologies where it's a black box. It's great that this black box figures it out and pops out in the answer, but if the employee or the talent that you have doesn't understand what's going on behind the scenes, there's more of a rejection to it instead of acceptance.

Aera is more of a transparent box, she says, with technology so users can actually see what's going on with a decision:

You have to foster that decision. It's not that you create that and you go because of the volatility in the ecosystem. You have to constantly and continuously upgrade those algorithms or that intelligence as well. So that transparent box and the ability for your employees to really be on that and guiding the machine is super important.

When Uniliver started its transformation journey, its systems and processes were not as standardized and harmonized as they are today. Herrick says:

Every market the customer is different, the consumer's different. How you operate is a little bit different - the carriers, the suppliers you use, the factories you have, the collaborative manufacturers. All those differences have to be there, but there's still a base process that you standardize and harmonize to be able to scale more quickly.

As to learnings that Herrick would pass on to other organizations, she has some simple findings:

The advice is, this isn't easy. It's hard. People are used to getting technologies and it's like, 'OK we're going to have a big bang implementation, and it's going to be beautiful, and we're going to get it right and have a few change requests and all that'. It doesn't work like that. That's not what Aera is about. It's about bringing the people along and it's a learning journey. That culture of being able to fail has to be okay and it's hard work and you need to keep at it. Understanding that and creating that culture is super-important - to learn, unlearn, and relearn, because it's all a learning journey.

The second [piece of advice] is, do not underestimate stakeholder management and change management. I definitely think we could have done a better job. Like I said, it's great being a champion, but if you don't bring the organization along with you, it makes it super-hard to move faster. I think we've done a lot better at that now, but start upfront, create an ambition and a vision, but really, bring those stakeholders along.

And then finally, I would say talent, talent, talent, and your employees. It's really about making sure you're building that talent internally, because it's about the human guiding the machine now. That sort of skill set is not easy, and it's not so easily available to find in the marketplace. But you also need to show that it's not getting rid of their jobs. It's about creating the jobs of the future and the jobs that are going to be here for years and years to come.

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