Key takeaways from Microsoft’s Finance Team: Excel, Automation, and Efficiency
Updated: 6 days ago
There are a lot of positive things to learn from tech giant Microsoft. After all, you have to be doing something right to be the 4th most profitable company in the US, and even more so as part of one of the most competitive and fast changing sectors such as technology.
While “the shoemaker’s kids go barefoot” applies to many companies- they don’t use their own services or at least not in the full capacity that they advertise it- Microsoft recently talked about how they continue to use Excel for many things in the finance department, despite having a big enough budget to use any other software solution they desire.
“We love Excel, and we use it often. Excel has a place and always will have a place,” Cory Hrncirik, Microsoft’s Modern Finance initiative leader told the Wall Street Journal back in February.
The interview was conducted to get a better understanding of how Microsoft is using automation tools and AI in their finance department, and of course when and why they continue to use Excel for so many tasks.
Microsoft turning to digitization
Microsoft started looking ahead to future trends and strategies more than a decade ago, and around 2014 they started moving all of their financial data to the cloud. A big part of this was understanding that the sheer amount of manual data that needed to be processed was simply too much for one of the biggest and most profitable companies in the world- and it was only going to get bigger. They started thinking about automation, streamlining the data, and creating one source of truth.
The first and most important thing that they wanted to solve was forecasting, and this was done through AI and machine learning. Although there are many ways and levels to forecast, every finance group at every company does it, and it is notorious for taking a lot of time. For Microsoft, it took 3 weeks out of every quarter and the process involved a thousand people!
Only 6 months after beginning to use ML starting in 2015, Microsoft’s AI algorithms were churning out accurate results better than human processes, and the variance rate was cut in half from 3% to 1.5%. In 2022, it takes Microsoft a grand total of 30 minutes to turn the models around!
The Human Element of Finance
But even a tech giant like Microsoft knows that technology has its limitations and where and when it’s best to be used for. In cases such as cutting down on manual work, automation is perfect for freeing up highly paid and experienced professionals’ time. This allows them to focus on areas that technology can’t replace- in depth insights and intuition, managing complex projects, and looking for new opportunities.
While automation saves Microsoft’s finance team thousands of hours of work, these finance experts are still very much involved in the budgeting and forecasting process. Reports are analyzed by different experts who bring unique knowledge of local markets or specific niches, who can then easily adjust seasonality or any other changes. Machine learning doesn’t have those human elements, and is still very far away from performing at the deep, granular level that a financial analyst can do.
After forecasting, Microsoft started using technology and automation in things like compliance. The benefits of this included speeding up their internal audit process, predicting recessions, and even using it in the treasury group for analyzing documents from governments around the world to understand possible risks.
Hrncirik explains the differences in the company and the process transformation over time: “When I started my career, I [had] to connect to 50 different data sets to pull information into Excel and then manually create insights from that data. We’ve moved all of those data sources, actually over 100 different [ones]. We’ve merged [them] in a data lake, and so you merge all of that data together in the cloud. The second step is creating standard reports and analytical frameworks so that we can talk about the same business the [same] way everywhere around the world.”
While things such as international laws and combining data from different currencies and languages pertains more to a giant global company like Microsoft, automating these types of processes and scenarios applies more and more to small companies as well. With the increase in supply chain issues and globalized disruptions, organizations need to pay far more attention to things outside of their direct control by forecasting and scenario planning.
All of these tools, along with automatic invoices and bots have greatly helped Microsoft’s efficiency in a number of ways. To begin with, their invoice error rate has gone from 2% to 1%, a huge difference when dealing with trillions of dollars.
But no less important is the head count factor.
With most finance teams, head count grows in the same linear way along with business growth- which was the case for Microsoft up until the 2008 recession. From then on, management decided to keep head count flat. This is despite revenue nearly tripling, other departments’ headcount growing significantly, and the amount of data multiplying exponentially. Being able to keep the finance department's headcount flat is thanks to automation and technology.
Excel is still very much relevant today! Through all of the automation and technological advancements, Excel still plays a big role, and keeping those skills and its useful points and combining it with newer technologies is the key to transitioning.
Automation, consolidation, and forecasting, is not only beneficial for MNCs or global companies. In today’s market uncertainty and supply chain disruptions, every organization can benefit from greater insights and scenario planning.
FP&A technologies aren’t only for large companies with hundreds of millions in revenue. Solutions such as Datarails with an Excel based platform and quick implementation time are perfect for SMBs, while Anaplan is a great option for large companies.
It’s possible to keep the finance team the same size while growing revenue. This will save money on headcount, increase existing employee’s ability to drill down and analyze, and create a far more efficient financial process.