Decoding the Science of Decision-making for CFOs

Q. How has the role of the CFO evolved in a dynamic business environment?
In the last decade, the CFO’s role has evolved from a “number cruncher” to a “strategy thinker”. The CFO takes a seat along with the CEO and the board for defining and developing the overall strategy of an organization. Besides, being the voice on financial performance, CFOs need to provide insights and analysis to support key business decisions, proactively lead strategic initiatives, create efficient and effective finance functions, and effectively contribute to profitable growth. The expectation is for the CFO to be a “Business Partner” and an “enabler” for growth. With this broader mandate, CFOs need to rely on analytics to understand the past and predict the future. The traditional way of decision-making is giving way to a more data-driven, scientific and objective decision making process.

Q. What kind of data does the CFO rely on and what are some of the challenges that CFOs encounter while deriving analytics from data?
In many ways, when it comes to data, it's a problem of plenty, especially if you are in a “Business to Consumer” environment. Companies create and / or have access to terabytes of data. There's data that is internal and created based on your own transactions and there's data that you can purchase from market research companies. CFOs have access to data that relates to operations, supply chain, sourcing and procurement, treasury, customer demographics, customer behavior, sales and marketing to name just a few. Data available on the social media is fast becoming an important source of customer insights. There are multiple challenges surrounding data: quality (accuracy and reliability of data), access (data may exist in silos and reside in disparate systems that may not be integrated), timeliness (is the data outdated or is it real time?), usefulness (is the data structured or unstructured?). Even if these issues are resolved, an organization needs to have skilled staff who can mine the data, create meaningful relationships and drive actionable insights.

Q. Every CFO does some kind of analytics. In that way, data analytics is not a new concept. So what has changed?
Very true. Every CFO analyzes data. What has changed is the level of sophistication of the analytics CFOs are expected to perform. There are varying degrees of maturity when it comes to data analytics. It goes from the most basic form of MIS and dashboards to data assimilation and forward-looking scenario analysis to advanced analytics using financial modelling and statistical tools to sophisticated data mining used to discover trends and patterns and thereby predict the future.

Q. Can you give some examples of the different types of analytics a modern day CFO should do to drive objective decision making?
For example, CFOs can predict cash flows and levels of delinquent debt by building “Propensity to Pay” predictive data models based on customer demographics and past behavior. This can also help in analyzing customers that are most likely to default and thereby proactive measures may be taken to address the risk. Using sophisticated algorithms, data analytics can also help in detection and prevention of frauds. On the sales and marketing side, customer data and behavior analytics can help CFOs understand, what customers buy, why they buy, when they buy and most importantly, why they move to the competition. Marketing analytics will provide insights in identifying the most effective marketing channel – one that provides the biggest bang for the buck. Analyzing chatter on social media will help a CFO understand the customer's mind – what is working and what is not working.