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The future of corporate finance

The future of corporate finance

For a data-driven organization

By integrating Data Scientists within your financial organization, you allow finance to evolve towards a more strategic and proactive function. You also help stakeholders within the business to be driven by data and make better decisions every day. This allows the business to grow more profitably. Nevertheless, beyond Data Science, a data driven strategy can only succeed if the entire organization shares a single source of data and indicators. Otherwise (isolated enterprise systems, Excel spreadsheets), we end up with data silos, which prevent the sharing of information and ideas in real time.

A single source of truth for an aligned organization

The finance department should maintain a set of data models related to bookings, revenue, costs, and other financial data sets. These must be accessible through a centralized source of data, shared with other users. By working from the same assumptions and conducting their own analyses, business functions are able to speak the same language as the finance organization. The result is more effective and collaborative conversations across departments and stronger alignment around business goals and vision. For example, if marketing is generating a lot of demand from a successful ad campaign, that team can make a real-time decision and ask finance for a bigger budget.

Manage products and invest in a suitable data platform

Associating Data Scientists from finance to product management only has advantages. They can model the costs, pricing and monetization associated with launching new features or entering new markets. As for product teams, they should be able to be empowered to strategize and make decisions on their own, based on this financial modeling and their own analysis. This would result in more effective discussions and easier decision-making during a product review process or strategy development. From a financial perspective, a modern cloud data platform should be the backbone that makes all of this possible.

Powerful cloud for near real-time access and fast decisions

First and foremost, you need to start with an extremely robust and scalable cloud system that can easily ingest massive amounts of data. You can then run analytics on this data at scale and apply machine learning models to predict future business. Overall, rather than viewing a cloud data platform as a cost, it’s important to focus on the benefits of real-time data and the speed of access to that data. This power leads to more solid information and faster decisions. Many different types of data, structured, semi-structured and even unstructured data, need to be processed quickly and analyzed as a single whole. Third-party data, such as ratings, fact sets, and industry data, should complement your internal data and enable richer analysis. Again, this data should link seamlessly with what you have within the company.

Governance and security

With all of this data in one place, it’s important to know who has access to it and make sure it’s extremely secure. Whenever data is extracted, you need to be able to see who extracted it, when, and have the ability to ask why. Using a single cloud data platform goes hand in hand with my belief that you should limit the number of SaaS point solutions used across the enterprise. Everything should work seamlessly and all data should exist in a central repository in order to have a single system of truth. Each additional system adds unnecessary headaches. The fewer systems you have, the easier it is to monitor them from a security perspective, so you always know what’s going on in your internal environment.

Invest in Data Science to better exploit data

Companies have an exponential amount of data, not to mention the data they can access from their trading partners, in the form of secondary and third-party data. Perhaps one of the biggest challenges is combining ERP data with CRM data. This is why easily centralizing data on a cloud platform is an essential first step. Forward-looking CFOs know that harnessing the power of this data is impossible without predicting customer usage patterns and other critical business insights. Focusing on real-time data analysis and investing in Data Scientists helps enrich forecasting and predictability.

No matter what the future holds, financial organizations will always need strong accountants and financial analysts. But they will also need experts who can build predictive models, understand systems, data and processes to succeed and grow.