From Rob Jenkins, SAP Global Center of Excellence
Benjamin Franklin once noted “In this world nothing can be said to be certain, except death and taxes.” Finance professionals must deal with uncertainty as they model the future and partner with the business to optimize decision making. And while taxes are a certainty, tax jurisdiction and therefore tax rates are a function of how and where a business process is executed and assumptions made by the business. And those assumptions should be well documented for regulatory agencies.
Every for-profit entity’s objective is to deploy capital to maximize the after-tax return on investment. This requires a tight collaboration between financial planning and analysis (FP&A) and corporate tax functions to provide insight into the past and potential economic profit of products and customers and the available possibilities of organizing operations to maximize after-tax profit.
Many companies are in the news for performing “tax inversions” as part of a strategic acquisition of a non-US-based entity due to U.S. rates now exceeding the simple average of other OECD nations by 14.1 points and the GDP-weighted average by 10 points. 
Modeling After-Tax Financial Impact of Business Operations
Given the disparity in global tax rates, process and asset location along with transfer prices can have significant impact on after-tax income. Various operating scenarios can result in “profit shifting” among tax regimes and the business analyst can calculate the impact on statutory results by modeling the following:
- Whether a business activity is active or passive
- Where activities occur including R&D and “management”
- The location of intellectual property
- Placement of debt and borrowing costs (thin capitalization rules)
- Transfer pricing (inter-company pricing arrangements between related business entities)
Choosing the Right Tool for the Task
A variety of tools are available to enable business users to estimate financial outcomes based on input variables and assumptions about their systemic relationships.
Spreadsheet technology is ubiquitous in finance for ad hoc modeling with some companies building complex, interdependent workbooks with macros for automation and detailed documentation for knowledge management, while others rely on a single subject matter expert to maintain the “black box”. These webs of interconnected cells and sheets are notorious for their error rates and hardwiring with one study finding “errors of at least 5% were found in 91% of all spreadsheets with more than 150 rows.” 
My previous blog post, Big Data for Finance, referenced how Big Data and analytics can be utilized to model the future based on historical data relationships and advanced analytic algorithms – though few finance organizations have yet to embrace the suite of predictive analytic tools now targeted at the business user.
Managing the Scope of Planning, Budgeting and Forecasting Systems
However, most finance organizations are using enterprise software applications for planning, budgeting, and forecasting with a large number of firms incorporating driver-based techniques for quantifying revenue forecasts and gross margin (for example, estimated product volume x selling price and standard cost for cost of goods sold).
For planning indirect operating expense including the cost to acquire, serve, and retain customers, the vast majority of companies budget expenses by function, responsibility center, and account, and rely on streamlined allocations to create a pre-tax operating margin view with most management attention focused on “controllable margin.”
These enterprise planning systems are extremely valuable for gathering inputs from decentralized sources, managing workflow, recording audit trails, aggregating actual results, calculating budget variances and reporting multi-dimensional financial statements for management.
Since FP&A teams are traditionally focused on financial reporting aligned with GAAP or IFRS requirements, these planning systems are rarely configured to calculate the detailed dynamics of how hundreds or thousands of shared indirect labor or overhead cost pools are attributed (sometimes in multiple steps) to products or customers based on usage-based drivers or activity-based methods.
Nor do these systems typically account for the tax impact of supply chain logistics, asset location, and transfer prices. Complex driver-based attributions and operational transfer pricing have been the province of cost accounting and tax accounting, respectively, and rely on specific techniques, operational data sets and levels of detail not ordinarily integrated into corporate planning systems.
The result is that most FP&A and tax teams use separate systems to plan and model pre-tax economics at a high-level vs. a granular view of profitability by customer and product vs. the tax impact of how business operations are organized.
So, what’s the solution? In my next blog, I will discuss operational transfer pricing and the rise (again) of profitability and cost management software. Stay tuned!
 Tax Foundation, OECD Corporate Income Tax Rates, 1981-2011, http://taxfoundation.org/article/oecd-corporate-income-tax-rates-1981-2011.