Transforming Finance through Robust Data Analytics
This is a time of unprecedented technological change, and it has been our reality for more than a decade. These changes are happening faster than the rate at which businesses can absorb them. Therefore, it is difficult to implement new technology in our daily way of doing business. The fact that certain technology exists (e.g., robotic process automation, blockchain, artificial intelligence) does not mean that companies can implement it throughout their businesses.
The reality is that it is not easy to implement any technological solution because it requires the effective orchestration of changes beyond technology. We are talking about changes impacting people, the way people do business (i.e., process and behavior), and the financial results of an ongoing business. Additionally, in the quest for growth, companies have been very active in mergers and acquisitions, which pose additional people, processes, and system integration challenges.
Finally, we have experienced the unprecedented impact of COVID-19 in our daily personal and work lives, which has focused everyone on what is absolutely necessary to make it through the storm. Yet, can you imagine how much more difficult it would have been to conduct business if the internet and communication technology were not widespread throughout the world? For sure, this experience highlights the importance of keeping up with technology.
Finance has been in the middle of enabling technological changes that impact transactional processing and data analytics. The success of the Finance function in leading and enabling ongoing technological transformation highly depends upon how Finance leaders approach the following questions:
● What is the role of Finance in the implementation of new technology?
● How should the Finance and Information Technology functions partner to lead technological transformation and successfully implement new solutions that everyone embraces?
● How should Finance interact with other functions to enable positive change?
● What should be the ultimate objective of implementing technological changes?
● Why Robust Data Analytics enable Finance to add value in new ways?
● Why is effective master data management foundational to enable the implementation of new information system technology?
● Why understanding system architecture and connectivity is essential to building sustainable processes?
● How should Finance transform to lead the way toward efficient and effective (i.e., robust) data analytics?
Let’s reflect upon these questions. Finance is a support function embedded throughout all areas of the business (e.g., Strategy, Marketing, Sales, Supply Chain, Human Resources, etc.). Finance talent is geared toward helping their business partners to achieve their objectives regardless of function. Additionally, Finance is responsible for bringing it all together and provide a holistic vision of what the business has accomplished, where it is going, and the resources needed to achieve future objectives. As a result, the Finance function is in a great position to partner with the Information Technology function and everyone else in the business to identify which technology could have the greatest Return on Investment and then work with everyone in the difficult process of implementing the new technology in a way that is embraced throughout the business.
However, as technology is implemented in the business, in some instances, Finance teams become smaller. This highlights the importance of avoiding a silo mentality that could focus functions on the hoarding of human resources and data instead of designing processes and human interactions that lead to the best results regardless of resource assignments. As a result, Finance teams can only enable positive change if they work with all the other functions with a holistic partnership mentality that is geared toward empowering total business transformation. Finance would not be able to lead and enable technological transformation if it is perceived by other functions as selfish.
If successfully implemented, new technologies lead to the democratization of information throughout the business. Financial, operational, and market information becomes timely accessible to anyone who needs it to make operational decisions or develop scenarios to make strategic decisions. However, the potential pitfalls in a world of data abundance enabled by new technologies that provide timely detailed data (previously unavailable) along with the combination of internal and external data are confusion, misinterpretations, wrong conclusions, and ultimately bad decisions.
Finance is in a unique position to bring order to chaos. For years, finance talent has been organizing information, making it reliable and useful, and explaining its meaning to business partners. Therefore, the future of Finance is in its own strengths. However, in a world of ever-changing technology, Finance teams need to be technology savvy and uniquely adept to connecting the dots. That is where the conversation turns to master data, system architecture, and connectivity.
All of us have heard the words master data. But what is it? In practical terms, master data can be explained as the key data elements that enable connecting the dots between multiple data sets. If those keys are incorrect or inconsistent among systems, then data becomes siloed or even useless. Maintaining master data timely and accurately requires significant non-glamorous work. For that same reason, many businesses struggle with this very foundation required for system investments to add value. So, centralizing the management of master data and ensuring its integrity is of the utmost importance. Who can help in establishing robust and consistent processes and controls that bring order to chaos?
Without a clear understanding of system architecture to enable different data sets to connect in a way that leads to business insights, functional data silos are created that result in multiple versions of the truth. This leads to confusion, non-value-added fire drills, and bad or untimely decisions. Could Finance be embedded in the implementation of any new system to help the Information Technology and other functions to connect the dots and ensure that the ultimate data outputs lead to useful holistic information that can be embraced throughout the organization? Well, everyone else in the organization needs to believe that Finance is in the best position to take a leadership role in this area based on their ongoing interactions.
Still, a large, well-connected data lake is not good enough. The challenge is to bring this data to life in new ways that are user-friendly and accessible throughout the organization. If making sense of the data requires a doctorate in data science and statistics, it will be very difficult for any system solution to become embedded in the way people make strategic and operational decisions. People can only act on what they can understand. So, what would it take for Finance to transform itself to lead the way toward efficient and effective (i.e., robust) data analytics? Everything starts with being invited to the table, embracing a leadership role, and proving to everyone else in the organization that Finance talent is ready to partner with the Information Technology team and other functions to create the future.