Data Analytics and the FP&A Function

Technological advancements in Big Data and Analytics are having a significant impact on the business’s operating model and strategic performance.

Many companies are already exploring how best they can adopt big data and analytics technologies to improve their businesses,  reduce costs, streamline processes,  improve marketing initiatives, and pursue future profits.

In the majority of these organizations,  the marketing function and supply chain are leading the pace in applying these new analytic capabilities and serving the customers.

Unfortunately, finance is lagging behind and still holding on to its legacy systems and primitive technologies.

All is not yet lost, there is still hope for finance to embrace advanced analytical technologies and help drive business performance.

In addition to helping marketing and supply chain functions, Big Data and Analytics can too play a critical role in supporting the finance function fulfill its FP&A role in today’s dynamic business environment.

In a world awash with large volumes of data, unstructured and structured, being able to identify patterns, anomalies and derive strategic insights is key for effective decision making.

Having this ability to access, synthesize and monetize data requires the FP&A function to invest in new skills and data tools and take advantage of the potential uses of new data types.

It is therefore imperative for the CFO to consider the implications of investing in Big Data and Analytics technologies as well as the impact of using data for effective decision making.

Modern technologies are not the domain for the CIO only but also for the CFO. Finance must learn to partner with the business, understand the language of IT and develop an ability to identify and evaluate the various ways data analytics technology can help the FP&A function.

CFOs should be asking themselves, how best can they leverage Big Data and Analytics technology to help improve the organization’s budgeting, planning and forecasting processes? How best can they enrich operational and financial forecasts with the most reliable data and make them more accurate?

While everyone is talking about Big Data and Analytics these days and how they have the potential to transform the organization and create a competitive advantage, it is easier for management and executives to join the “Big Data Dream” without first formulating a clear and coherent data strategy.

In the end, these executives end up collecting large volumes of data, most of it being worthless, resulting in the business incurring significant data costs and suffering from ineffective decision making.

The value in data is found when the organization is able to collect, synthesize, analyze and retrieve strategic insights from that piece of data and improve decision-making process.

Key to consider prior making significant investment in data analytics technologies is the alignment of data strategy with the broader strategy of the organization, data access and governance issues, new skills requirements, and implementation road map.

One of the challenges facing many FP&A functions is assessing the relevant data to analyze, identifying trends and gaining valuable strategic insights. When preparing forecasts and analyzing business performance, there is need, for example, to synthesize data across operational, financial and customer information.

How can all this data be integrated and used for decision support purposes? Unfortunately,  not many finance professionals possess this ability to manage this new data and new data types in a way that creates visibility across the organization and benefit other functions.

Thus, it is crucial for the FP&A function in today’s economy to develop data mining and analysis capabilities to ensure relevant data is being used for strategic and performance improvement decision making processes.

There is a need therefore for the organization to radically change its data approach and evaluate how it fits well within the overall strategy of the business. Ensure effective KPIs, measures and metrics are designed and implemented to help managers run the business.

This approach will ensure that information requirements as well as investments in advanced technologies are not managed in silos but rather, in a deliberate and organized fashion that aligns and supports the broader strategy of the business.

Furthermore, as data becomes a strategic asset to the organization,  it is crucial that the CFO collaborates with other senior executives of the organization and engage them in planning conversations and collaboratively find ways of improving business performance.

In today’s economic environment, data is found everywhere, both internally and externally and this data can only be accessed if finance decides to leave its comfort zone and begin engaging with the business.

Unfortunately, many finance professionals have a strong technical background and are weak when it comes to soft skills. Walking around the business, initiating conversations with other functions and asking smart questions doesn’t come naturally to many finance professionals.

However, as the role of finance continue to evolve, the finance organization must learn to adapt and acquire new soft skills to avoid being left behind in the back office.

Today’s finance professional is required not only to have data skills, but also the ability  to communicate with the broader organization, have a strategic mindset and a deeper understanding of the operational areas of the organization as well as the ability to identify opportunities and help the business grow by  reducing costs, evaluating and increasing top-line revenues.

FP&A must be able to ask smart questions and identify the relevant business needs that can be addressed by data analytics. How can the business benefit from technology, make smarter and faster decisions and also become more efficient? How can an investment in data and analytics technology help the business identify emerging or unknown risks areas and manage these risks intelligently?

By taking advantage of data analytics technologies, the FP&A function will be able to identify business performance leading indicators based on the data available, adjust forecasts and drive that information into operations.

Uncertainty and volatility in the global economy  are on the rise and because of this, many business executives are worried and cautious about where to make large capital expenditures. As the support function with a larger visibility across the organization,  the FP&A function can help address this uncertainty.

By embracing modern technologies, the function can transition from business intelligence and reporting on what happened, to data mining and understanding why something happened, to predictive analytics and determining what is likely to happen and when.

This will in-turn help  management and executives put contingency plans in place and become proactive.

Taking a phased approach is necessary when implementing data analytics technologies.  Instead of going full force with the implementation,  the organization can start small and use a specific business unit as the basis for the pilot project.

Results from this experimentation can then be used to evaluate technology performance in terms of ease of use, speed and benefits. If the results are satisfactory,  the next business unit or region is selected and the process continues until there is a complete roll-out across the entire organization.