Optimization is the application of algorithms to sets of data to guide executives and managers in making the best decisions. It’s a trending topic because using optimization technologies and techniques to better manage a variety of day-to-day business issues is becoming easier. I expect optimization, once the preserve of data scientists and operations research specialists will become mainstream in general purpose business analytics over the next five years.

Optimization was first adopted by businesses in the middle of the 20th century, aided by the introduction of digital computers. The first technique that gained broad for a few specific purposes was linear programming, one of the most basic optimization methods. Linear programming enables analysts to quickly determine how to achieve the best outcome (such as maximum unit volume or lowest cost) in a given situation. They do so using a mathematical model that captures the key variables that go into the decision and any constraints that may affect that decision. A food processor, for instance, may use three types of cooking oil to make a product. To maximize its profit, the company needs to determine the exact proportions of the three oils that result in the lowest production cost. However, it can’t just choose the cheapest of the three in every case because for flavor and shelf-life requirements there’s a limit to the maximum percentage of each oil that it can use. Linear programming using the simplex algorithm quickly solves the problem.

As computing capabilities became increasingly affordable, companies could use more complex algorithms to handle ever more difficult optimization problems. For instance, the airline industry used it to determine how best to route aircraft between two cities and to staff flight crews. Not only can softwarevr_Big_Data_Analytics_01_use_of_big_data_analytics find the best solution for scheduling these assets in advance, it also can rapidly re-optimize the solution when weather or mechanical issues force a change in how aircraft and crews are deployed. Airlines were also in the vanguard in the 1980s when they started using revenue management techniques. In this case, the optimization process was designed to enable established airlines to compete against low-cost startups. Revenue management enabled the large carriers to offer low fares to price-sensitive but flexible vacationers without sacrificing the higher fares that the less flexible businesspeople were willing to spend. The same approach was adopted by hotels in pricing their rooms. Starting in the 1990s markdown management software, which I have written about gained ground. It enables retailers to make more intelligent pricing decisions by monitoring the velocity of purchases of specific items and adjusting prices to maximize revenue. To be feasible, each of these optimization problems require large data sets and sufficient raw computing power.

We’re now on the cusp of “democratizing” what I call optimization analytics. Big data technologies are making it feasible and affordable for even midsize companies to work with much larger data sets than they have been able to in the past. Our benchmark research on big data analytics finds that about half of participating companies already use analytics with big data. This is partly the result of more powerful and affordable data processing resources but also because companies have invested in systems to automate many functions. The rich data sets created by these business applications provide corporations with the raw material for analysis. This data has the potential to enable businesses to make more intelligent decisions. From a practical standpoint, though, the value of these large data sets can only be realized by moving optimization analytics out of the exclusive realm of data scientists and into the hands of business analysts. These analysts are the ones who have a sufficient understanding of the business and the subtleties of the data to find useful and repeatable optimization opportunities. Three-fourths of companies in our research said that they need these business skills (“domain expertise”) to use big data analytics successfully.

vr_Big_Data_Analytics_14_big_data_analytics_skillsOptimization analytics is a breakthrough technology with the potential to improve business performance and create a competitive advantage. You can’t do optimization in your head, and it’s not feasible in desktop spreadsheets for anything but the most basic use cases, such as linear programming optimizations on relatively small data sets. This is a good reason for almost any company to consider adopting optimization software.

Another reason why companies will find it attractive to apply optimization analytics broadly is that the results of applying optimization routines may be superior to using common rules of thumb or relying on instinct and experience. One of the most important lessons for executives about optimization analytics is that optimal solutions are sometimes (but – crucially – not always) counterintuitive to established norms. For instance, in markdown management, retailers often have found that smaller, more frequent price reductions maximize profits and produce a considerable improvement in sales over the end-of-the-season price slashing that was once considered to be the best practice. In financial services, charging your best customers more for loans and other services turns out to be the optimal choice for the bottom line of financial institutions. Another important insight from our collective experience with optimization is that while the value of these analytics as realized in a single event or transaction may be small, it can have a measurable impact on profitability and competitiveness when applied broadly in a business.

At this point optimization analytics is in a dual mode. On the one hand, there are proven examples of the narrow application of optimization such as those mentioned above. On the other, bringing optimization analytics to the masses is only beginning. Some vendors have made progress in simplifying their analytics, but mainstream products are only on the horizon. It’s also important to recognize that, as with past breakthroughs in information technology, there are bound to be more duds than success stories in initial attempts at using optimization analytics. Experience suggests that a small number of companies that have strong analytical skills and a rigorous approach to managing company data will prove to be the leaders in finding profitable opportunities for applying optimization technologies and techniques. Others will do well to find these examples and consider how to apply them to their own organizations.


Robert Kugel – SVP Research

Longview’s recent Dialog user group meeting highlighted the company’s continued commitment to providing much needed automation tools for improving tax department performance – tools that enable the tax function to play a more strategic role in the management of a company. The sessions also covered the capabilities contained in the company’s latest release, Longview 7.2 Update 2 and gave customers a detailed product evolution roadmap following their merger with arcplan.

Using a dedicated tax application with a dedicated tax data store to handle direct (income) taxes has three main benefits. First, it enables a company to manage its tax exposure more intelligently, potentially reducing its tax expense. This is important because usually taxes are the second largest expense in a company. Second, the tax-related regulatory environment is becoming more challenging. Taxes paid to individual countries by multinational corporations have come under greater scrutiny by local tax authorities that are suspicious that these companies are manipulating individual countries’ tax laws to eliminate or substantially reduce local tax obligations. In this environment, it will become increasingly important for companies to have global visibility into their country-by-country tax exposure and options. Longview’s tax software can help companies determine how best to allocate income by jurisdiction. Third, by centralizing all global tax-related data in a single data store as well as automating calculations and the management of all tax-related data, Longview’s tax software can enables greater efficiency in the tax provision process. By saving time and ensuring all global tax-related data is consistent, it makes it possible for companies to manage their tax exposures more intelligently and makes it practical for companies to optimize tax payments by jurisdiction.

Corporations made up of more than a handful of legal entities and that operate in multiple direct tax jurisdictions can achieve significant time savings by adopting dedicated tax software rather than using desktop spreadsheets to manage the tax provision process. That’s because companies with these characteristics face challenges that quickly overwhelm spreadsheets. Direct taxes are extremely complicated because national tax codes are complex and ever-changing. Not only do specifics (such as depreciation schedules or inventory expensing rules) vary from one country to the next, but even basic tax concepts can differ. Then there is a “parallel universe” element, because “tax expense” is not the same as “taxes paid.” Tax and finance departments must be able to track and reconcile these differences and allocate tax expense (paid or deferred) accurately to individual business units. Accounting rules specify when tax expense must be recognized, but this can lag when those taxes are actually paid. Timing differences are the reason why very profitable companies pay nothing to tax authorities in some years and write big checks when they are losing money. A company’s tax position can be fluid, so it’s important to be able to work across multiple tax periods. Adjustments to individual entity tax expenses and positions occur frequently, so accurate adjustments and true-ups across tax periods must be easy to calculate, record and retrieve. Behind this are a myriad of specific journal entries to effect changes and the need to assemble a consistent set of account reconciliations to manage the details. The complexity of these processes is a large part of why we have computers.

Yet until recently spreadsheets were the most practical approach because the scale and complexity of the data management required made it difficult for anyone to offer a workable packaged solution. So companies have grown accustomed to using desktop spreadsheets to assemble and analyze data, calculate taxes, generate reports and store the data, analyses, calculations and reports. Our research shows that tax departments rely heavily on desktop spreadsheets for analysis and calculations to support their tax provision and compliance processes. More than half use spreadsheets exclusively and just 10 percent use a dedicated third-party application.

vr_Office_of_Finance_15_tax_depts_and_spreadsheetsOne reason why dedicated tax software makes sense is that, despite talk of reducing the complexity of tax regimes, they are still complex. As corporations grow and expand internationally, their legal entity structure becomes more multifaceted and their source systems for collecting and managing tax data can become fragmented. Unless the tax function is completely centralized, companies that operate in more than a handful of tax jurisdictions can find it hard to coordinate their tax data, calculations and processes. Centralization is not a cure-all, either, as the lack of local presence poses its own tax management issues in coordinating with local operations and finance organizations.

Another reason is that national taxing authorities may be making the tax department’s job more difficult. In 2013, the Organization for Economic Cooperation and Development (OECD) published a report titled “Action Plan on Base Erosion and Profit Shifting,” which describes the challenges national governments face in enforcing taxation in an increasingly global environment with a growing share of digital commerce. The OECD also is providing a forum for member governments to take action (including collective action) to strengthen their tax collection capabilities. Optimizing tax expense across jurisdictions will grow in importance if the OECD’s initiative for global tax reporting gains traction. Companies operating in multiple countries will find it increasingly necessary to understand how best to allocate income between countries to minimize the taxes within the constraints imposed by increased external transparency. Corporations that operate globally will need to be able to gauge how best to manage their tax exposure in an environment where decisions about transfer pricing and corporate organization will require greater care and forethought than today.

Desktop spreadsheets are not well suited to any repetitive collaborative enterprise task or as a corporate data store. They are a poor choice for managing taxes because they are error-prone, lack transparency, are difficult to use for data aggregation, lack controls and have a limited ability to handle more than a few dimensions at a time. Data from corporate sources, such as ERP systems, may have to be adjusted and transformed to put this information into its proper tax context – for example, performing allocations or transforming the data so that it reflects the tax-relevant legal entity structure rather than corporate management structure. Doing this manually in desktop spreadsheets is time-consuming and prone to errors. Moreover, in desktop spreadsheets it is difficult to parse even moderately complex nested formulas or spot errors and inconsistencies. Pivot tables have only a limited ability to manage key dimensions (such as time, location, business unit and legal entity) in performing analyses and reporting. As a data store, spreadsheets may be inaccessible to others in the organization if they are kept on an individual’s hard drive. Spreadsheets are rarely documented well, so it is difficult for anyone other than the creator to understand their structure and formulas or their underlying assumptions. The provenance of the data in the spreadsheets may be unclear, making it difficult to understand the source of discrepancies between individual spreadsheets as well as making audits difficult.  Companies are able to deal with spreadsheets’ inherent shortcomings only by spending more time than they should assembling data, making calculations, checking for errors,  creating reports and auditing the results.

Applications for managing taxes such as Longview Tax are making provisioning and reporting faster, more efficient and more reliable. One of the most important elements of such a system is the tax data warehouse that is at the core of Longview Tax. Statutory and tax accounting are not the same, so it’s important for companies to keep a tax-sensitized record of transactions and balances. This speeds calculations, analysis and reporting and improves the accuracy and dependability of the tax department’s work product. By substantially reducing or eliminating the use of desktop spreadsheets, it increases the transparency of the tax process. Segregating tax data from the rest of a company’s enterprise data is also essential because of the need to keep this information in an “as-was” state. Corporations buy and sell business units as well as reorganize on an ongoing basis. They then adjust their financial and management accounting systems to reflect the current needs of the business. Tax authorities, however, are concerned with the individual legal entities that make up a corporation as they existed in a given fiscal period. Maintaining all tax data together – including all of the minutiae of individual account adjustments and true-ups within and between periods – facilitates tax audit defense.

Beyond handling data better, Longview Tax also makes people working in tax departments much more efficient and the results of their work more accurate and transparent. It ensures that the process of capturing the difference between book (statutory) accounting and tax accounting is efficient, accurate and consistent. It enables corporations to standardize processes and reporting to simplify training and streamline reviews and audits. It’s able to use the dimensional capabilities of the system to enable a company to instantly and consistently create and publish reports that conform to the requirements of different taxing authorities – including, for example, different currencies and different depreciation methods for the exact same assets. By eliminating the need for people to perform repetitive tasks that require little judgment, it enables the department to increase its value and make it more strategic to a corporation.

Longview Tax provides bidirectional integration with a company’s ERP system, data warehouses and tax compliance software to ensure the fidelity of data at every step in tax-related processes. It gives administrators the ability to define and monitor tax department tasks to ensure all steps are performed and alerts them of delays. It provides an Excel add-in to give users a familiar environment in which to work and an ability to do ad-hoc calculations while eliminating almost all of the defects associated with desktop spreadsheets. Data and formulas are stored in a central database, ensuring quality and consistency. All of this promotes accuracy, reduces the risk of errors in calculations and presentations and can substantially cut the amount of time people in tax departments spend checking and reconciling their spreadsheets, which also boosts efficiency. And because Longview offers software for statutory consolidation, disclosures and external financial reporting, the Tax application supports the creation of required financial statement footnotes and tax disclosures.

Just improving the efficiency of a tax department can justify investing in a tax application because of the time it saves, greater accuracy and increased transparency. Companies may also find that by speeding the process of assembling tax data and performing the necessary calculations they have more time to consider their options on where and when they report income. I recommend that any company operating in more than a handful of tax jurisdictions should consider using a dedicated application for tax analysis, provisioning and reporting and that they consider Longview Tax for that role.


Robert Kugel – SVP Research

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