I recently participated in an episode of Financial Excellence with Game Changers, a program sponsored by SAP and broadcast on VoiceAmerica Business radio. Bonnie D. Graham, global director of Thought Leadership at SAP Global Marketing, moderated the discussion. Joining us were two additional panelists: Dr. Karin Graeslund, a finance information management professor at RheinMain University of Applied Sciences, and Matthias Haendly, vice president, SAP S/4HANA product management.
Our conversation brought up three key themes:
- Digital technologies started out by automating finance transactional processes. The value was not just reducing cost but also giving finance professionals more time to focus on knowledge-based work. However, new technologies like artificial intelligence (AI) make processes more efficient, but more importantly, augment the quality of more complex activities like analytics and performance management.
- To get the full benefits of AI and machine learning, finance professionals must get comfortable working with “faceless” machines by understanding how they “think.” That’s going to take a while. These new tools incorporate complex algorithms while many finance teams still rely on spreadsheets for modeling.
- While AI is evolving fast, finance still needs human experts to handle the decision-making process. People take the output and turn it into action.
Focusing on strategic value
The Hackett Group’s research indicates great progress towards finance automation. We’ve also found out that greater use of existing technologies makes a significant difference in finance cost and efficiency.
Using a proprietary model, we calculated the potential impact that going fully digital would have on finance costs and effectiveness. We discovered that digital transformation can reduce the cost of finance by 20%-32%, depending on how advanced the finance function already is. It can also increase the time staff spends on analysis versus collecting data by 40%.
But it’s not just about technology. Many finance functions are also shifting the execution of transactional processes to global business services (GBS) organizations. The upshot is that finance is moving away from doing what is essentially “busy work” – thus improving its insight and the decision support it delivers to business leaders and management.
According to Matthias Haendly, automation can be done at lower costs when companies leverage AI and machine learning. Unlike robotic process automation, “We are not just programming strict rules that need to be revised over time. AI feeds on the automation data and learns from it, so that it creates new rules as soon as the process changes.”
Working effectively with machines
Before they can get the most out of AI, finance teams need to get comfortable working with machines.
Matthias said building trust is a fundamental step toward making this new technology successful in our lives. “Finance professionals are hesitant to trust [machines]. Ultimately, it’s about how we make the process traceable [or transparent],” he said. It needs to be clear that the decisions behind the numbers have some good reasoning. Another way to build trust is to track the system’s recommendations and determine how often finance staff are accepting these recommendations and using them to learn and adapt.
“AI can do remarkable things and give us insight into patterns based on very large datasets, which we would never have been able to analyze before,” added Karin Graeslund. “It frees up time so people can do what they really like to do: ask strategic questions and turn the answers into strategic advice. While the machines can produce better insight, the decision-making process is still dominated by humans.” She added, “We will still stay in charge for compliance. We are responsible for the decisions machine learning is helping us to make.”
There’s data to support the idea that finance professionals need to become more educated about how the technology works. In The Hackett Group’s Digital Transformation Performance Study conducted in late 2017, we found out that technology and data savviness are the two skills where finance professionals have the widest gap between what’s required and current capabilities.
Looking through the crystal ball
What more finance professionals should recognize is that the evolution of AI (that is, in how well it mimics the human brain) has experienced significant breakthroughs of late. “Specifically, machine learning discipline based on deep learning algorithms today can surpass average human capabilities,” Matthias said. In finance, there are a lot of tasks that require taking unstructured information and help pull it into decision-support systems. Image recognition enables machines to understand a PDF document and extract relevant data. “Today’s AI software can also give you smart suggestions on how to use the information they produce,” he said. “Finance is a sweet spot for driving the excellence in an area that not everybody understands.”
We’re not there yet. The Hackett Group’s 2018 Key Issue Study showed current adoption of AI is at six percent. But it’s expected to reach 41% in two to three years.
Adopting advanced technologies can really help finance organizations become more successful in the fiercely competitive talent market. According to Karin, the trick is to successfully attract younger people who already have a lot of the digital skills. Whether a company has adopted more advanced technologies or not can make the difference between accepting or rejecting a job offer.
As artificial intelligence takes hold, the organizations that gain a competitive edge will be those that best leverage The Human Angle.