How Wacker Chemie is using data to transform a traditional chemical company into a digital one

Founded in 1914, Munich-based Wacker Chemie AG is a €5 billion chemicals firm with operations around the world that provides specialty chemical products for many applications and everyday items, from cosmetics to solar cells to paint colours. Its portfolio includes more than 3,200 products, including numerous silicone products and polymeric binders. Though publicly listed, the company is still majority-owned by the Wacker family, and is classed in German company terms as a mid-size corporation, though at the upper end of that.

The markets in which Wacker operates are both highly diversified and complex. And to help keep on top of all this complexity the company's relatively new (in post five years) Chief Information Officer and Chief Digital Officer Dirk Ramhorst has been looking for new ways of working to improve efficiency.

That isn't to say that information technology wasn't seen as a key tool: it's more of a subtle shift in emphasis, he says:

When I came in, IT here was perceived as a utility. It was recognised as a reliable, cost effective provider of commodity services like heating, water, energy, but we are now being recognized as a much more of a business enabler.

Though there are multiple moving parts to Ramhorst's drive to go digital inside the company, the central plank is its use of what he defines as AI-powered digital commerce technology. Provided by key Wacker strategic IT partner PROS, this takes the form of SaaS sales support software that claims to leverage intelligence from every aspect of a buyer's engagement, helping businesses like Wacker's deliver fast and personalized buying experiences across all sales channels.

Why would a firm like this need such an application? For one thing, e-commerce at Wacker had gotten tired; the existing package had been in place for 15 years, and so the company wanted a digital reset on this central part of its business. But the volatility of the cost of the input versus the output the customer sees meant that the solution would have to be a lot smarter, too. Ramhorst explains:

We have a very complex pricing structure because of our dependence on raw materials, and there can be a lot of price changes over the time of that raw material. Some of the things we source are based on stock prices which can change from day to day, even from hour to hour, so that we really need the very latest price information. The idea was to use a price-matching system we can use internally and we selected this software in order to both improve our pricing process and the overall quality of our offer to customers.

A very complex statistical exercise

If you think (as we did) that that sounds like some kind of customer marketplace, Ramhorst is quick to say it isn't. That's because this is not about offering the most attractive price to customers on a portal like in the airline business, but more about the workflow within the Wacker process of writing offers to its customers. Romhorst says:

It's more the way of how we come to an end price for the customer rather than comparing the end products with other products; we don't want to sell you something not related to any figure that has not been thoroughly vetted internally. It also means we have a more consistent pricing model rather than very individual prices from an individual salesperson.

Couldn't that calculation be done in a more conventional app than in AI? Ramhorst points out that the intelligence is all down to a high-scale statistical model that can handle a very large number of data points that need to range from previous offers, development of the market price of certain raw materials, the calculation or formulation of a certain product, and so on, which adds up to a very complex statistical exercise.

And the software has been effective, with more than 80% of Wacker's offers based on this approach to pricing and margin calculation. It's also important to note that this use of AI is well bedded-in to a set of interlocking enterprise applications, he adds, which include SAP and Salesforce. Romhorst says:

You can't digitalize the end product, the chemical product. But you can provide services around the production of the product that makes you more sustainable, that makes you more efficient and makes you more intelligent.

Thus, the pricing algorithm isn't the only application of Artificial Intelligence in internal Wacker manufacturing processes, either. During the fabrication of silicones for industrial use, the firm used to check quality with a manual inspection during the production process by a team of experts. The problem here was that though production runs on a 24x7 cycle, these human colleagues only operated during the week, during one shift, overnight and at weekends - and a lot of stock piled up for review the next working day. But now, he says, a new AI-based visual inspection tool is in place that means the expert team only now manages the exceptions it can't immediately pass or reject.

Unlocking the next digital business ‘level'

Where does Wacker plan to go next in terms of its ambition to digitize? It's now in the fourth year of its digital programme, he says, and there's still a long way to run. But the prize is there and can be achieved-or as he says:

My son, who's 20, says what we're trying to do is unlock the next gaming level, which means you end up with more treasure. This is what we are aiming for, as we go from standard performance to customized performance.

This vision is also based on an interesting up-turning of a metaphor we've all got maybe a bit too comfortable with in enterprise IT: that data is a form of crude oil that we can ‘dig' up and transform into useful (but also problematic?) new forms. Ramhorst says:

When I brought up the topic of digital within Wacker, it was very much all about data, and you might know about the saying that data is in new ‘oil'.

But I rephrased it to data is the new ‘water'. Why? Privately, as well as business wise, we all try to be more sustainable; we actually want to get rid of oil in our daily work. But as human beings we know how important it is to have pure drinkable water; it's the same as with data.

It's much easier for people to understand the value of data in terms of not being only seen as data protection but how important it is now for our corporation, for our personal lives, but also for economies-people talk about potential wars because of water. So that's how we now see data at Wacker.