Transforming FP&A in a Decentralized Environment

Transforming FP&A in a Decentralized Environment

By Matt Poleski, CFO, Northeast and Mid-Atlantic Region at Arthur J. Gallagher & Co

Recent trends in FP&A have been to focus on data analytics and driver-based planning to provide better information for business leaders to make decisions.  Various challenges exist to accomplish this goal including the traditional budgeting culture, data quality, and outdated technology.  An often-overlooked challenge in transforming financial planning and analysis is the FP&A team’s structure and resource alignment.  This article examines how we are transforming the people part of FP&A.

My company like many companies has grown through acquisition.  In the beginning, we did not integrate, we consolidated. There were over 50 locations within the U.S. alone that sent in Excel spreadsheets to accumulate monthly results. If the three A’s in financial analysis are accumulate, analyze, and act – we spent all of our time accumulating.  As the company evolved, we began implementing centralized tools that allowed us to both process and accumulate faster and more efficiently such as centralized vendor payables, centralized travel expense reimbursement, centralized billing platforms, centralized payroll, and centralized sales planning. These platforms enabled us to process information faster and cheaper; and gave us access to big data through a data-warehouse. However, we spent all our efforts developing centralized platforms as opposed to thoroughly thinking through the reporting we wanted off these systems, or how to data-mine from these systems.

Once we had the data, we hired centralized resources to come in and analyze the data; however, a couple issue arose. First, the systems were set up to perform their tasks efficiently, not focused on reporting. Thus, while the data was directionally correct on a macro level, details of the data could easily be challenged and could not be relied upon as accurate scorecards.  For example, Micro-level data for commission payments to employee is still largely done decentralized in Excel.  Second and more importantly, data provides information for decisions making. Data doesn’t make the decisions for you.  Some of the best people to analyze, interpret data, and influence actions were existing resources in the field.

To understand what to do – it’s important to understand our management structure. Our historical management structure was very hierarchical. Each location had a manager and a financial analyst. That manager reported up to a regional manager, who reported up to a Divisional manager (both of who had their own financial analyst). Each manager is expected to drive EBITDA growth. The best way for a manager to maximize his returns is to focus on client segment where a competitive advantage exists to drive revenue growth.

When we had decentralized systems, the manager was forced to manage everything within his geographical boundaries – even those areas where we didn’t have a competitive advantage. With the new system, managers could trade underperforming segments to managers who had expertise in these areas, and could therefore grow them. This would provide the ability to pool like resources around the country, and manage it more efficiently with the appropriate level of investment to generate returns. Key performance indicators and driver based analytics could be customized for each segment to assess performance, as opposed to having uniform metrics for all locations. 

How are we transforming our FP&A resources

In the old system, financial analysts were forced to be jack of all trades and know every single transaction that hit their local P&Ls.  In the new system, that is not always possible as automated entries are hitting local P&Ls from several different systems.  Even for our all-star financial analysts who can have greater expertise in all the systems, it creates a standardization problem as we do not want information asymmetric based on the quality of the financial analyst.

Financial analysts now work in teams where they declare a major of expertise, but are still required to interpret local P&L results. For example, a financial analyst may be an expert in mergers and acquisitions and assess potential merger prospects. Another financial analyst may be an expert in producer compensation and make recommendations for implementing and standardizing producer compensation across the country.  The team approach allows each analyst to leverage each other’s expertise.  This expertise allows the analyst to focus and implement best practices for what they are good at across the country, but still allows them to influence branch managers to determine how to best grow their P and Ls.