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Tagetik provides financial performance management software. One particularly useful aspect of its suite is the Collaborative Disclosure Management (CDM). CDM addresses an important need in finance departments, which routinely generate highly formatted documents that combine words and numbers. Often these documents are assembled by contributors outside of the finance department; human resources, facilities, legal and corporate groups are the most common. The data used in these reports almost always come from multiple sources – not just enterprise systems such as ERP and financial consolidation software but also individual spreadsheets and databases that collect and store nonfinancial data (such as information about leased facilities, executive compensation, fixed assets, acquisitions and corporate actions). Until recently, these reports were almost always cobbled together manually – a painstaking process made even more time-consuming by the need to double-check the documents for accuracy and consistency. The adoption of a more automated approach was driven by the requirement imposed several years ago by United States Securities and Exchange Commission (SEC) that companies tag their required periodic disclosure filings using eXtensible Business Reporting Language (XBRL), which I have written about. This mandate created a tipping point in the workload, making the manual approach infeasible for a large number of companies and motivating them to adopt tools to automate the process. Although disclosure filings were the initial impetus to acquire collaborative disclosure management software, companies have found it useful for generating a range of formatted periodic reports that combine text and data, including board books (internal documents for senior executives and members of the board of directors), highly formatted periodic internal reports and filings with nonfinancial regulators or lien holders.
Tagetik’s Collaborative Disclosure Management automates the document creation process, eliminating many repetitive, mechanical functions and reducing the time needed to administer the process and ensure accuracy. Automation can shorten finance processes significantly. For example, our benchmark research on trends in developing the fast, clean close finds that companies that use little or no automation in their accounting close take almost twice as long to complete the process as those that fully automate it (9.1 days vs. 5.7 days). Manually assembling the narrative text from perhaps dozens of contributors and combining it with data used in tables and elsewhere in the document is a time-consuming chore. Regulatory filings are legal documents that must be completely accurate and conform to mandated presentation styles. They require careful review to ensure accuracy and completeness. Complicating this effort recently are increasingly stringent deadlines, especially in the U.S. Anyone who has been a party to these efforts knows that there can be frequent changes in the narratives and presentation of the numbers as they are reviewed by different parties, and those responsible need to ensure that any change to a number that occurs is automatically reflected everywhere that amount is cited in the document; to use the depreciation and amortization figure as an example, that would include the statement of cash flows, income statement, the text of the management discussion and analysis and the text or tables of one or more footnotes. Moreover, automated systems afford greater control over the data used. They make it possible to answer the common question of where a number came from quickly and with complete assurance. While inaccuracies in other types of financial documents may not have legal consequences, mistakes can have reputational or financial consequences.
Those managing the process also spend a great deal of energy simply checking the document to ensure that the various sections include the latest wording, that the numbers are consistent in the tables and text, that amounts have been rounded properly (which can be really complicated) and that the right people have signed off on every part of the filing. Automation obviates the need for much of these tasks. Tagetik’s CDM workflow-enables the process, so handoffs are automated, participants get alerts if they haven’t completed their steps in timely fashion, and administrators can keep track of where everyone is in the process. Workflow also promotes consistent execution of the process, and the workflows can be easily modified as needed.
In designing Collaborative Disclosure Management, Tagetik took advantage of users’ widespread familiarity with Microsoft Excel and Word to reduce the amount of training required to use its product. CDM’s workflow design makes it relatively easy for business users to define and modify business process automation. Typically, individuals or small groups work on different sections of the document. CDM enables multiple contributors from finance, accounting, legal, corporate and other functions to work with their part of the document without being concerned about other contributors’ versions. Work can proceed smoothly, and those administering the process can see at any time which components have been completed, are in progress or have not even started. Tagetik’s software can cut the time required to prepare any periodic document, since once a company has configured its system to create what is in effect a template, it’s relatively easy to generate these documents on monthly, quarterly or annual bases. The numbers relevant to the current period are updated from the specified controlled sources, and references to tabular data within the text are automatically adjusted to tie back to these new figures. Often a large percentage of the narrative text is boilerplate that either must not be updated or requires only limited editing to reflect new information. Starting with the previous edition of the report, contributors can quickly mark up a revised version, and reviewers can focus only on what has changed. Other important automation features are data validation, which reduces errors and revisions, and the system’s ability to round numbers using the appropriate statutory methodology.
CDM also handles XBRL tagging, which is essential for all SEC documents and necessary for an increasing number of regulatory filings around the world. The software specifically handles tagging for the two main European prudential regulatory filings for banks and other credit extending institutions, COREP (Common Reporting related to capital) and FINREP (Financial Reporting performed in a consistent fashion across multiple countries).
Companies can gain several key benefits by automating the production of their periodic regulatory filings and internal or external financial reports that combine text and data. One of the most important is time. Automation can substantially reduce the time that highly trained and well-compensated people spend on mechanical tasks (freeing them to do more productive things), and the process can be completed sooner. Having the basic work completed sooner gives senior executives and outside directors more time to review the document before it must be filed or made public. Time that can be devoted to considering how best to polish the narratives or if necessary lengthen upstream deadlines to handle last-minute developments and consider options for how best to treat accounting events. Automation can also reduce the chance of errors, since the numbers tie directly back to the source systems and (if properly configured) ensure that references in the narratives and footnotes to items in tables and the numbers in those table agree completely. Restatements of financial reports caused by errors are relatively rare but when they occur are exceptionally costly for public companies’ reputations.
Disclosure management systems are an essential component for any financial performance management (FPM) system. All midsize and larger corporations should be using this software to automate the production of their periodic mandated filings and other documents that combine text and data. They will find that they are useful in cutting the time and effort required to produce these documents, provide senior executives and directors more time to review and craft the final versions, and reduce the chance of errors in the process. Companies that are using older FPM software should investigate replacing it with an FPM suite to gain the additional capabilities – including disclosure management – that newer suites offer. Tagetik’s should be among the financial systems evaluated for office of finance.
Robert Kugel – SVP Research
Analytics has long been a core discipline of Finance, applied to analysis of balance sheets, income statements and cash-flow statements. However, as I’ve noted, most finance departments have not kept up with recent advances. Our recent research in finance analytics shows that few organizations are realizing the potential of more advanced analytic methods and tools such as predictive analytics and driver-based modeling. One reason for this sluggishness is that they have not looked past yesterday’s requirements to see what possible. Another is that they are distracted by the difficulties they face in simply doing tried-and-true analysis, which is the result of difficulties in accessing the necessary data and inadequate tools. A third reason is that people receive too little training in the application of analytics to business and the use of more advanced analytic tools and methods.
Companies typically do not provide training – or testing – to enhance the analytical skills of their employees. Testing skills is useful in exposing individual and organizational gaps and injects motivation into the training process. Creating analytics requires a thorough knowledge of the basics: which methods to use under which circumstances and the best approaches to take. Newer analytic approaches and tools can be complex, so it makes sense to train people to gain a better understanding of both the basic uses of analytic tools and advanced analytics. Yet the research shows that fewer than one-third (31%) of companies provide training for people who create analytics. This may be because organizations hire people who they assume already have the skills or the talent to pick them up as needed on the job. They also may be reluctant to spend money and unaware of the indirect expenses of not doing so. Because they rarely test employee skills, organizations may not be aware of the shortfalls in competence that are costing them time and money. For whatever reason, the lack of training – especially in the creation of analytics – is shortsighted.
Training is vital to building analysts’ skills, especially for creating analytics. The research demonstrates a correlation. We found that a large majority (83%) of the companies that provide training in creating analytics have staffs whose skills they deem excellent or above average, compared to only half (52%) of those that provide training only in using analytics and just one-third of those that provide no training at all.
Companies that fail to test individual skills are unlikely to discover the link between weak skills and poor performance. People may complete their assignments but take twice as long as necessary to do them. If the analysts are using spreadsheets, they may be constructing models and analyses that have unseen errors (as they did in the infamous London Whale episode) or needlessly complex models because they are unfamiliar with built-in functions that simplify tasks.
Training those who create analytics also helps ensure that time spent on analytics is used as effectively as possible. In about half (47%) of the companies that train analytics creators, people spend the largest amount of their time where they should – in working with the analytics to get answers or model business issues and analysis – compared to 27 percent of organizations that only provide training for users and 20 percent that provide no training. In about three-fourths of companies that provide only training for users (73%) or no training (76%), they spend the largest amount of time on data-related tasks (waiting for data, preparing it and reviewing it for errors) rather than on analysis. Fully half of companies that provide training for creators also use analytics and performance indicators to improve individual or business unit performance, many more than those that train only users (20%) or provide no training (17%).
Analytics can be a valuable tool for finance departments and can help them play more significant roles in their organizations, which many finance professionals now want to do. But until more of them make the often extensive changes and investments the research shows they need, this goal will be more of a hope than a promise. Training finance professionals in the creation and use of both basic and advanced analytics is essential for companies to improve their performance. Being prepared and training is the best path to be effective in finance analytics.
Robert Kugel – SVP Research