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One of the major issues IT executives face is how to charge their departmental costs back to each part of the business according to their usage. It’s a touchy issue that can be the source of end-user disenchantment with the performance and contribution of the IT organization. Ultimately, charge-back friction can hobble IT’s ability to make necessary investments in new capabilities and become the primary cause of misallocated IT spending. The two risks are related: Unless an IT department can calculate the real costs of the services it provides to specific parts of the business and charge for them accordingly, it is almost impossible for line-of-business department managers to assign priorities to the “keep the lights on” part of the budget, so even low-priority maintenance or upgrade efforts can crowd out all but the most pressing needs. The issue of allocating IT department costs spills over to Finance, which typically handles the allocations in budgeting and profit calculations. As a first step toward establishing an effective means of funding the IT function, I believe the finance department must establish better methods of allocating IT costs. Eventually the proper allocation of IT costs also becomes an issue for senior corporate executives as well because it has a direct impact on how effectively a company uses information technology.

To illustrate how using inept IT cost allocation methods can lead to bad results, let’s start with a very simple example. A company decides to lump together all IT costs and charge each department a prorated share based on some proxy; for example, headcount or floor space occupied or some combination of proxies. Any such proxy system inevitably will favor one department over another. Human nature being what it is, the inability to draw a straight line between the charge and the benefits delivered will leave everyone thinking they are paying more than their fair share. Moreover, in most companies, because business managers are not charged directly for their consumption of IT services, they have no idea how that impacts IT department costs. In the absence of price signals, unintended overconsumption and misaligned priorities are almost inevitable, and thus IT spending does not support the business as effectively as it should.

Our benchmark research illustrates the fundamental problem that companies have in allocating IT costs. Either they do not have the processes in place to ensure that they connect the right information to the appropriate action (for example, they do not charge costs accurately enough to end users so the users can’t make more rational decisions about what they are willing to spend), or they are not collecting the right information about the costs. Many suffer from some combination of the two. Having greater visibility into what a company actually is spending and on whose behalf and a better process for deciding what to spend money on are likely to increase the value the IT budget buys.

Our research also assessed the effectiveness of companies’ IT spending on a five-point scale from very ineffective (1) to very effective (5). The research finds that participants who said they have accurate systems for identifying and allocating IT costs have higher spending effectiveness scores (averaging 4.0) than those who said theirs were generally accurate (3.6), generally inaccurate (3.0) or very inaccurate (2.6).Tracking actual costs and charging them to specific users who incur them is the best way to be sure funds are spent well. Having visibility into the true costs of those IT resources and a process for controlling them promotes better use of the resources.

The research also finds that for IT departments there is a virtuous cycle in accurately measuring and charging IT costs. Companies that are more effective in using their IT budgets are also likely to have had greater IT budget increases in the preceding years than those that were less effective. In other words, a more accurate costing system gives a company more bang for its IT buck, which results in more bucks for IT. IT departments that give managers better visibility and control over IT costs charged back to them – and can demonstrate to their business clients that they are getting a positive return on their investment – are likely to be rewarded with higher budgets than those that do not or cannot.

Having the right data, the right analytical tools and the right allocation methods are all prerequisites to having an accurate IT charge-back system. As part of their overall responsibility to manage their portfolio of IT assets, CIOs must have the ability to track who and what is driving which IT costs. CFOs should play a larger role in the budgeting and expense allocation processes by ensuring that IT costs and cost drivers are more visible to the organization rather than relying on broad-brush allocations. Done correctly, I think this will improve the alignment of IT spending with the company’s needs. For their part, CEOs must understand the importance of achieving better alignment of IT spending and the strategic requirements of the company. They must ensure there is a formal process for periodically reviewing that alignment and capabilities to measure accurately spending on and use of information technology.


Robert Kugel – SVP Research

I recently had a briefing from Vertex on its tax data warehouse (TDW), a key component of its tax technology platform Vertex Enterprise. The TDW concept has been around for decades, but the earliest versions were custom-built and hampered by the technology limitations of their day. This made them expensive to deploy and maintain and constrained their ability to adapt to changing corporate requirements. The basic idea behind a TDW is straightforward: a data store that makes all tax data readily available and can be used to plan and provision a company’s taxes. But the complexity of tax-related data overwhelmed the ability of information technology to deliver on the concept. With today’s technological advances the basic idea is finally realizable in a practical sense.

A TDW has several purposes: to ensure accuracy and consistency in tax analysis and calculations, improve visibility into tax provisioning and cut the time and effort required to execute tax processes. It can be useful because data management is one of the biggest operational challenges facing tax departments. That is, the information necessary for tax provisioning, planning, compliance and audit may not be readily available to the tax department because accounting and other information is kept in multiple systems from multiple vendors. (Our benchmark research shows that 71% of companies with 1,000 or more employees use financial systems from multiple vendors.) In addition, not all of the data necessary for tax department purposes is captured by the ERP system. As well, data collected in a general finance department warehouse or pulled together in a financial consolidation system may not be sufficiently granular for tax department purposes.

Moreover, most companies’ ERP systems (the core technology for gathering transaction data) are not inherently “tax aware,” so tax departments repeatedly need to perform transformational steps to have data formatted and organized properly. Sometimes the data must undergo multiple transformations because, for example, the transaction information collected in an overseas subsidiary must be reported locally using the local currency and accounting standard but must be translated to the parent company’s tax books in a different currency using a different accounting standard. In some industries (such as financial services) there may be multiple local reporting standards, one for general statutory purposes and another reflecting specific rules for that industry demanded by some regulatory authority. In short, there are numerous data-driven headaches tax professionals have to address before they even get down to work.

Managing tax-related data is especially difficult for larger companies with above-average tax complexity, as I noted in anearlier blog. Complexity is produced by the number of tax jurisdictions in which a company operates, the complexity of the tax codes of some jurisdictions (Brazil and India are notorious in this regard) and its own corporate structure (the number of legal entities and their ownership characteristics).

There’s a market for tax data warehouses partly because most tax departments perform these data transformations in desktop spreadsheets. Due to the inherent problems with desktop spreadsheets, the process is not only needlessly time-consuming (even using macros and other spreadsheet automation techniques), it is also prone to errors and inconsistencies. This is especially true if the same information must be entered multiple times, which increases the chances of a mistake. In addition, assumptions made and the rationales behind formulas used in data transformations may not be documented or readily accessible to others in the organization. And finally, with spreadsheet-driven processes, auditing taxes and the underlying data and calculations also is difficult and time-consuming. The impacts of the desktop spreadsheet’s inherent shortcomings multiply with the size of a corporation. Thus, I expect that over the next several years larger companies (those with 1,000 or more employees) and even some midsize ones with complex corporate structures will find the advantages of a tax data warehouse increasingly compelling.

One of the basic sources of value derived from establishing a TDW is automating, standardizing and controlling the process of extracting data from transaction systems like ERP, transforming it into a tax-relevant structure and making it the single source of data accessible to the systems and processes that need to access to tax-related data. This need makes a TDW a core capability that can substantially increase the efficiency of a company’s tax provisioning and planning process and increase the effectiveness of tax compliance and audit defense.

Another reason for creating a TDW is that it enables the company to keep tax-related data and analyses in an “as was” state – in a virtual file box separate from other systems. There may be good business reasons to change historical data in financial systems (for example, reorganizations or divestitures), but since tax audits can take place many years after a filing, it’s handy (and potentially lucrative) to be able summon up original, error-free data.

Any company large enough to need a TDW probably has a large IT department, but I suspect that few IT departments are up the task of creating one, and it would be difficult to justify the ongoing investment required to maintain it. A TDW goes beyond the standard IT notion of the data warehouse, which focuses mainly on the high-level technical requirements of acquiring data from operational systems and putting it in a useful form for business users. Taxes are fiendishly complicated, so the details of how the extract, transform and load (ETL) steps are handled (including the required movements and validations) require a specific knowledge of the intersection of accounting and taxes. This domain expertise is necessary to enable individual corporations to facilitate the process of setting up (and later changing) data imports and exports from and to other enterprise systems to suit their specific tax requirements. (These requirements may be a function of their tax complexity or their industry.)

To address these requirements, Vertex’s data management platform brings together the key components necessary for data collection, movement and management as well as reporting and exporting to other functions and systems, including the TDW, and connectors that streamline the integration of a company’s existing financial applications with the TDW. It provides a single database designed to hold trial balance, adjustments and other direct tax data, configured specifically for tax. The data collectors have (or soon will add) prebuilt integration with common data sources, including SAP’s general ledger and Business Warehouse, Oracle’s GL and Hyperion Financial Manager and Microsoft Excel. This list is slated to expand to include other major vendors’ offerings. Currently, there are export connectors to Corptax, Vantage Tax, TaxStream, Excel and a generic flat file (which can serve as a universal connector), and Vertex will expand the array to include other vendors (such as Abacus), a write-back to general ledger journals and an XBRL-tagging capability. Vertex also provides access controls, and its security capability has built-in audit and tracking functions.

Vertex plans enhancements to its TDW this year, focusing on companies’ direct (income) tax requirements to refine functionality as well as facilitate deployment, management and maintenance. For 2013, Vertex plans to improve transaction tax (sales and use, value-added and general sales tax) capabilities.

Now that Sarbanes-Oxley and the global recession are largely behind them, executives and consultants in North America (and to some extent in Europe) are again able to focus on “finance transformation,” an approach that CFOs and finance executives – especially those in midsize and larger companies – should use to enhance corporate performance. Finance departments continue to devote too many resources to rote functions that they could automate. Consequently, they devote too few resources to improving the effectiveness of the finance function. Tax is a case in point. Most midsize and large companies’ tax departments spend their time performing manual processes that now can be automated. With all that effort they are able to achieve a minimum standard of compliance and accuracy. Today, that isn’t enough. I believe a tax data warehouse is a necessary component for any finance transformation project, giving corporations more accurate numbers sooner and enabling more sophisticated tax analyses that would enable companies to optimize their tax expense. As taxes are one of a company’s biggest expenses, the payoff derived from more effective and efficient tax management practices are likely to make tax automation investments such as a tax data warehouse worthwhile.


Robert Kugel – SVP Research

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