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5 min read . Updated: 24 May 2022, 06:11 PM IST Germany’s Bayer AG is working to improve its forecasting capabilities with the help of new technologies and data. While the company doesn’t rely on fully automated forecasts for its divisions yet, it is experimenting with advanced forecasting and predictive analytics, according to Chief Financial Officer Wolfgang Nickl.
That is proving easier in the company’s consumer-health segment, which sells over-the-counter medication and other related products, than in its agricultural business, which is more exposed to commodity prices and weather changes, Mr. Nickl said.
CFO Journal talked to him about Bayer’s data lake, a storage repository that holds a vast amount of raw financial and other data. He also spoke about anticipating Black Swan events and why it is important to stick to forecasts produced by algorithms.
This is the sixth part of a series focusing on how chief financial officers and other executives digitize their finance operations. Prior installments focused on a push by Alphabet Inc.’s Google to automate as many finance tasks as possible, how Unum Groupgot rid of spreadsheets, and Microsoft Corp.’s use of artificial intelligence.
Edited excerpts of the conversation with Mr. Nickl follow.
WSJ: What are the main changes you have made in the finance function since you started four years ago?
Mr. Nickl: We started creating a powerful data lake [in 2018]. It basically includes the notion that we want to have one data lake for all the commercial and finance functions. It’s extremely detailed and multidimensional. In certain areas, you can even go down to the receipt level.
Another [change] is what we call Finance 360. We’re basically using intelligent management and reporting software. I can pretty much see all the sales, I can see profitability, but I can also see the whole balance sheet. I can see head count development, I can see spending categories. When I have a discussion with board members, I don’t bring any paper. We just go live into the system and I’ll show a few things.
WSJ: How are you forecasting?
Mr. Nickl: When it comes to midrange forecasting, a lot of people [at other companies] use static forecasting, but that then gets translated into PowerPoint. We have changed that. We only have a few PowerPoint [slides], and then we run basically the forecast [with] a simulation model. We created a dedicated organization called “record to report" that’s really focusing on efficiencies and automation in our reporting process.
WSJ: How effective is this process in the case of Black Swan events, like the Covid-19 pandemic or the Russian invasion of Ukraine?
Mr. Nickl: When Covid-19 hit or also when the situation hit in Ukraine, you all of a sudden got much more interested in more granular data. You basically want to know your accounts receivable extremely well. So I can look at it by country, by customer, what the accounts receivable are and what the due date is. It is helpful.
WSJ: Can you automate parts of your forecasting?
Mr. Nickl: We have started to put some intelligence in on dynamic forecasting, but in the pandemic we used it less because historical data usually doesn’t help you. We use it much more to assess short-term topics like receivables, payables, liquidity and so forth.
We have projects in our consumer business where we have seasonality, weather patterns, where you would know your inventory levels. That lends itself much better to forecasting automation. In pharma, we have invested in customer-facing applications that go as far as suggesting to sales [representatives] which practitioners to visit next.
It’s more difficult in cyclical businesses with significant macro impacts like currencies and supply-demand disruptions like in the crop business. It’s more difficult the more cyclical the business is.
WSJ: Would you still draw up a manual forecast?
Mr. Nickl: When you automate the forecast, you’ve got to be prepared to use the automated result because if you automate a forecast and in parallel do a human manual forecast, you have actually created more work and not made things simpler. That is a standard organizational hurdle that everybody needs to overcome. We’re not at the point where we say we’ll do a fully automated forecast for a division.
WSJ: Is this impacting the type of skills people need to bring?
Mr. Nickl: The requirements for people change and what people do in the departments. In our controlling department, the biggest organization is now called Financial Modeling and Analytics. And these are not your traditional bookkeepers anymore. They’re very tech-savvy people. It is also very important that everybody understands how the finance strategy links to the overall purpose of the company, what our ambition is and how we get there. [To be sure], we need traditional accounting skills. We need traditional treasury skills.
WSJ: What else are you working on?
Mr. Nickl: The re-implementation of our enterprise resource management system. We have a very old and complex system [with] about 140 instances. I think this will occupy us for the next five years plus, potentially seven years. It’s probably the biggest program that we have done in the last 20 years or so. This is a staggered rollout where you go and implement, learn, implement, learn and go, country by country.
WSJ: How many people do you employ in finance?
Mr. Nickl: When you look at all the accounting, record to report, global finance, tax [functions], across all the countries, including the shared service centers, you’re talking above 2,000. And when you look at controlling, we have about 1,000. So all in all, we have about 3,000 people in finance. That’s a pretty reasonable number.
WSJ: Have the changes you described resulted in a lower head count in finance?
Mr. Nickl: As a company, we did go through a massive transformation program. In 2018, we announced a program to take out €2.6 billion in cost [equivalent to $2.75 billion]. And in 2020 we topped this up with another €1.5 billion. We took approximately 25% of the cost out over four years. This is also being done by elimination, by structural changes. But digitization played a major role in that.
This story has been published from a wire agency feed without modifications to the text