The Finance-Function Dilemma
The business analysis expectations of the finance operations of a company are ever escalating in the new digital economy. Meanwhile, the structure of digitally enabled business is rapidly evolving, resulting in a pace of business activity that is constantly accelerating.
How should the finance function respond to these changes to ensure value-added support for the business? Inevitably, finance must transform to leverage new capabilities around systems integration, data management, advanced analytics, and modern visualization tools.
The old finance function tools are simply not good enough to keep pace with the digital economy. While most businesses have modernized their transactional systems with ERP and tackled the basic technology enablement of the general ledger, consolidations, payables and receivables, the analysis of that data remains in the dark ages. Most businesses still manage planning, budgeting, and financial analysis with spreadsheets. The more sophisticated businesses have enabled data management and reporting tools, but most of these tools require developers to build, and lack much of the cutting-edge capabilities needed for today’s fast-paced business.
Consider the typical spreadsheet-enabled planning process, and think of all the non-integrated, error-prone, manual steps needed to run the end-to-end process. Most finance managers would agree — this method of bring together the enterprise data and analysis into a comprehensive plan for the business is far from seamless. Often, executive reporting is done in PowerPoint, which creates yet another non-integrated, error-prone, manual step in the overall planning process. How can the finance function move past the constraints of Microsoft Office to speed up the planning process and keep pace with progress? The answer lies in the leader quadrant of Gartner’s Corporate Performance Management (“CPM”) applications report. There, finance managers will find applications, such as OneStream, that bring a broader set of tools for finance to specifically address the need for rapid, data-driven business analysis, planning, and reporting.
The New Tools
The most fundamental and critical linkage between historic financial reporting and go-forward planning is the metadata structure of the general ledger. This metadata describes both the chart of accounts structure and the organizational structure of the business. Together this matrix of accounts and departments represents both the financial accounting buckets and the aggregation path of those buckets for consolidation and reporting. This complicated, ever changing metadata structure must be synchronized between the accounting and planning systems. This process requires targeted data management and integration tools, which represent just one example of the expanded toolset available in cutting edge CPM applications.
The advantages of integration capabilities in CPM applications include:
One time data integration set-up for critical chart of accounts metadata
Easy maintenance of chart of accounts metadata with synchronization accelerators
One-time data integration set-up for critical organizational metadata
Easy maintenance of organizational metadata with synchronization accelerators
Seamless periodic updates to general ledger data when available at period close
Seamless periodic updates to headcount statistics and associated standard/actual costs
User-centric financial data platform for ad hoc business analysis and reporting
The data integration capabilities on the financial side of the business provides a critical part of the foundation for more advanced planning and budgeting. Another critical part of the foundation that requires data integration capabilities, is the operational side of the business. This is where finance can add value by managing the intersection of the financial and operational sides of the business through advanced analytical modeling. CPM applications provide the tools to capture critical operational data such as headcount, production volume, and sales forecasts to blend both the financial and operational data into meaningful analysis for the business. The speed, and accuracy, at which this can be accomplished is vital to ensuring that finance is adding value while supporting the business.
The advantage of integration capabilities in CPM applications include:
Productive use of operational drivers for planning and budgeting
Ability to integrate driver-based data to better understand revenue and cost trends
Use of sales pipeline data to model revenue by attributes such as product, customer category or distribution channel
Use of staffing data to model people costs based on attributes such as start date, location, pay grade and promotions
Extendable data management and modeling that supports drill down into department specific data, drivers and costs
With both financial and operational data synchronized to the CPM solution, the finance function can be empowered to support the business with a more responsive and credible modeling. The additional tool set provided by the CPM applications in the area of modeling include:
Extensive scenario management tools that support rapid forecast adjustments based on the most currently available financial and operational driver data.
Advanced reporting tools to assist with scenario management, particularly pertaining to variance analysis and forecast adjustments
Workflow tools to speed up reviews, approvals and sign offs on forecast adjustments, business analysis and reporting
Enabling Planning for Value
The tool sets provided by CPM applications are targeting enabling the finance function with better data management, modeling tools and reporting capabilities. While these tools are a means to an end, they do not provide the business logic needed to effectively create models for the business. It is up to both the financial and operational leaders of the business to establish models that accurately reflect the vectors associated with business performance.
An effective model of the business relies on key value drivers that impact both revenue and costs in a meaningful way. Each business is unique in their definition of value drivers, but similar businesses can leverage similar drivers. In this manner, businesses that have multiple locations conducting similar work, should harmonize on a standard set of drivers. Those drivers can be adjusted for complexity factors to account for nuances between similar but slightly different businesses. The critical work here is discovering the meaningful business drivers.
For example, in most staffing centric organizations, the critical driver of cost is headcount. That single driver can represent the base model for all similar, staffing centric components of the business. However, there are many nuances and variations that should be considered in the modeling. Those nuances may include attributes such as geography, pay level, promotion dates and skill level. It is critical for the entire business to converge on a common set of both drivers and complexity attributes before embarking on the modeling process. This ensures a common approach to modeling as well as consistency of results.
To carry the example one step further, consider a global technology organization that operates in multiple geographic locations to deliver strategic programs for the business. A staffing model for such an organization would have to consider the strategic priorities and associated programs to be delivered in the future in order to assign resources to each major program. The resource assignments must consider the resource skill set, job level, location, standard cost, percent of time allocation and the duration of that assignment. These critical attributes are likely to be available in the operational program management system (i.e., HP PPM or Jira). So, the finance staff must build a model that brings together both the financial data for the organization with the operational program management data to develop a comprehensive and dynamic model of the business.
These models are not easy to build. It often takes many iterations of both data and calculations to converge on a credible model. Once the models are clearly defined, it is necessary to build a repeatable process to support it. The CPM applications are ideally suited to do just that. They support model architects with the integration of the necessary financial and operational data in an efficient and automated manner. This enables a rapid response to business analysis questions and ensures that finance is adding value to the business. Over the longer term, the models are continually tested as to how well they predict the actual results of the business. When benchmarked against historical results, the credibility of the model is evaluated. Ongoing improvements to the model are required to ensure alignment with the ever-changing business environment. This is the goal of effective planning – to be able to accurately predict business outcomes and to be responsive to the business analysis questions that revolve around scenario management. Better planning leads to a more stable and predictable business, a clear indication that finance is planning for value.
About the Author
Richard Drobner is an accomplished business and technology executive with a proven track record managing strategy, governance, and execution plans for major business initiatives. Richard has over 30 years’ experience in management consulting, software, and financial services. Richard has worked at companies such as KPMG, Accenture, Grant Thornton, Mitsubishi, and Morgan Stanley. A core area of expertise for Richard is the analysis and improvement of Finance Functions from Operations to Planning to Executive Reporting.