Who’d Be A Bean Counter? How CFO’s Can Tackle Their Data Challenges In 2017.
There has never been more data at the fingertips of Chief Financial Officers (CFOs) and yet their job has never been more complex.
Managing and handling the wealth of new and changing data is a daily battle for today’s CFO. In many ways, the old job description of the ‘head bean counter’ no longer applies. Today’s CFOs are increasingly looked to as Bean ’Sprouters’, i.e. incumbents of the modern CFO role must leverage their understanding and use of technology to help drive business strategy. They need to be business focused technologists: able to accurately forecast, predict, and feed into the strategy and help drive growth.
So, why the change; what’s different? Well everything really.
As a result of increasing fast market entry and the big data era, even relatively modest sized Finance Departments are expected to process, understand and leverage the data they are working with. The challenge they face is the ever-increasing volume and variation of data and the concomitant ways of looking at it - along with the continually shifting needs of the business. With such a moving target, it’s very hard to keep up, let alone leverage this data to drive agile data-driven business decisions.
However, most CFO’s are facing the problem that the IT reporting systems that underpin their operations have organically evolved and, with more product variation and streaming big data, are now creaking under the load. Whilst they may not have hit that tipping point, they are usually not far off. The effects: slow and expensive response by IT, can be felt by most CFO’s throughout their departments.
To meet the new CFO caste, agility is critical. Business needs are always shifting, and the Finance department is often the first to feel this. How often are you required to use new data to generate new reports or analysis? Working with IT can mean 12-week lead-times to incorporate new data which, for most finance departments, is unrealistic. This situation often leads to scrambling around for ad hoc data extracts and custom data processing. In turn, this is not just a source of lost time and frustration, but exacerbates the problem: spawning multiple versions of data, existing in multiple locations and reporting different outcomes.
For a CFO, accuracy is paramount, yet even the most considered decisions are only as good as the data upon which they are based. For a lot of organisations this creates a downward spiral: poor data creates poor decisions, which create mistrust in the data, leading to data being ignored or marginalised and potentially worse decisions being made.
A lack of confidence in your data creates a hidden, yet hard cost for your department. Dealing with outdated, missing, duplicate, or non-conforming data can be measured in terms of both frustration and man-hours. This swallows resources, creates layers of bureaucracy, unnecessary process and hurts your department’s effectiveness.
To get the best results you must address the core of the problem. There are a myriad of Finance and Business Intelligence tools that can overlay existing data sets but, continuing to layer on tools and make decisions on unmanaged data, is just building a house of cards that will eventually come tumbling down.
Thankfully, there is a solution out there: Data Vault 2.0. It’s a proven system of data management that provides the required accuracy of data whilst still able to work under the agility required in a modern organisation.
A recent concrete example is Commonwealth Bank’s Data Vault implementation. Even confronted with massive complexity, the bank can now balance across multiple business units with complete confidence to deliver reporting and forecasting that is accurate to one-tenth of one-percent. Here Dan Linstedt, the inventor of Data Vault 2.0 explains how Commonwealth Bank achieved this.
Thanks to the Big Data Revolution, we must accept that the world has changed and so have our jobs - we are no longer the bean counters of old. CFO’s can no longer sit back and blame IT for poor data performance: a data management strategy is so fundamental to the modern CFO, that it’s now part of the job description.