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London FP&A Board: Moving FP&A toward Advanced Analytics

By Nilly Essaides, Association for Financial Professionals (AFP)

Published first on http://www.gtnews.com and  http://www.afponline.org in February 2015

Nearly every financial planning and analysis professional understands the need to embrace big data and analytics. But how can firms move beyond basics to advanced analytics?

That challenge was on every attendee’s mind at the recent FP&A Board meeting in London. There, FP&A and business intelligence professionals gathered to discuss the state of business intelligence (BI) and FP&A analytics with Nigel Geary, BI specialist at power utility British Gas.

Key takeaways from the meeting:

  • Cloud providers and Microsoft Power Pivot provide FP&A professionals more advanced capabilities to analyse data. It is important that the FP&A function trains itself to use these tools so that they can be self-sufficient and own the function and the models.
  • To be more effective, FP&A professionals need greater insight and more flexible data and models. While there’s plenty of data these days, it is often difficult to process. New computer languages like Hadoop are emerging to make handling large data sets faster and more efficient.
  • Analytics, and the technology that supports it, typically is still driven by IT and not finance, which creates a knowledge gap.
  • There is a new era coming where users need to take back that capability in order to track, analyse and predict business performance.

“I want to understand what’s considered advanced analytics and what’s considered basic,” one attendee said. “I’m trying to understand what good organizations are doing with regard to applying best practices. To me, it feels that it’s in its infancy.”

Geary concurred. “What I see is very basic. Nobody has even thought about predictive forecasting,” he said. “That’s what the trend tells us – how a new product will affect sales and [research and development]; the next step is to take this together.”

For many companies, the first step into advanced analytics is constructing multidimensional decision support tools, commonly called “cubes”. In the past these had to be created on mainframe computers; now they can be created in the cloud, making them more affordable.

“[Cubes] allowed FP&A to build budgeting systems in their departments,” Geary said. “They also minimised the amount of IT support needed to run the models.”

Next Analytic Step: the Hypercube

The next step in analytics, according to Geary, is the hypercube. Usually with budgeting, he said, FP&A pulls down  data from the general ledger and creates with multidimensional data sets each month, refreshing the information and performing variance analysis.

The hypercube breaks down this process to show users the profitability of different activities within the business. It ties all the ledgers together to calculate profitability by day, department and other factors to provide drill-down capability by numbers and transactions, and makes it possible to see any errors.

“You can’t do that if you have sales data in one cube and cost data in another cube,” Geary said. “The idea is to roll all of that up into a single cube bring it all into one place.”

To deal with the tidal wave of Big Data, data scientists have come up with a new data storage and language called Hadoop. Using Hadoop, companies can pull data out of new multidimensional databases that are not structured in the old columns and rows, providing greater flexibility.

The Practical Impact

Intriguing as the new advanced analytics solutions may be, attendees noted that they often don’t have time to implement them. “In FP&A we talk about trends,” one participant said. “We discuss scenario planning – what would be our response in various cases. That’s a form of analytics.”

How advanced companies can be in implementing these emerging tools really depends on their current state of technological advancement. “If the planning is not great, they should be looking at the tools that perform scenario modelling and all basic tools today can give you that,” Geary said.

Companies can start by looking at historical patterns and the drivers of customers’ behaviour to identify business drivers. Users should be able to look at reports in Excel and slice and dice the data to understand the business better. In the future, Geary predicted, companies will run more predictive models relying on bigger sets of data using new language like Hadoop.

One of the areas where advanced analytics plays a growing role is in integrated driver-base planning. Larysa Melnychuk, managing director of the FP&A Club for the Association for Financial Professionals (AFP), provided an example from her past work at a bank.

“We used a ‘survival analysis’ technique for the forecasting behaviour of a complex portfolio of personal loans and credit cards,” she said. “This non-standard analysis – not typical for finance – helped generate business insights that significantly changed strategy on some of the products. It also helped us to improve the profitability of the portfolio.”