Intellectual accounting scorecard - measuring and reporting intellectual capital

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Several indicators are constructed to measure intellectual capital at organisational level and at item level. The majority of models constructed so far have not established the link between individual intellectual items and organisational intellectual capital performance. The few models that establish such a link demand significant management time to monitor them, or have established indices outside the traditional accounting system.  The Intellectual Accounting Scorecard integrates intellectual capital measuring and reporting into mainstream traditional accounting reporting. Firstly it identifies each intellectual capital item as an intellectual revenue and intellectual expenses having an impact on the statement of income, or as an intellectual assets and intellectual liabilities having an impact on the balance sheet. Secondly, it constructs ratios to monitor operational and strategic performance.  Although there is ambiguity as to whether intellectual capital represents all intangibles, the more popular definitions indicate that they refer to intangibles not recognised in the financial statements. A study in 1997 of top Canadian and US organisations reveals that non-financial will be the key to business success in the future. The organisations identified five broad categories to measure performance, and they are customer service, market performance, innovation, goal achievement, and employee involvement. The most commonly used performance measure in firms was customer service and market performance. The firms tend to rely on non-financial measures that have been used for some time and indicated that they rely less heavily on measures related to reputation, know-how, information systems, databases, and corporate culture although they play an increasing importance in the future to ascertain the performance of a firm (Stivers, Covin, Hall, & Smalt, 1997). Sveiby (1997b) outlines three reasons why companies do not want to measure intangible assets, and they are: managers themselves do not understand the importance of it; indicators can give too much information away to the competitors; and there is no rigorous theoretical model for such a type of reporting. Since accounting systems are not designed to extract such information easily, it could be time consuming and expensive to make such reporting. Even if they are measured, the research also reveals that firms did not want to share human capital indicators externally since they feared losing talented employees to competitors (Miller, DuPont, Jeffrey, Mahon, Payer, & Starr, 1999).  On the other hand, capitalising intangibles leads to increase subjectivity of cash flow analysis, difficulty in breaking intangibles into individual valuations, and almost the impossibility of determining when the recognition criteria of intangible assets are met to include them in the balance sheet (Backhuijs, Holterman, Oudman, Overgoor, & Zijlstra, 1999).  The use of non-monetary indicators can help to avoid such problems to some extent. Measuring non-financial data is still an art more than a science and in intellectual capital the choice of indicators can affect the results substantially (Roos, Roos, Dragonetti, & Edvinsson, 1997, p. 60).  Like in environmental reporting (Kirkman & Hope, 1992), there is no universally acceptable model to measure intangibles. However, various models proposed at least point to the right direction (Guthrie & Petty, 2000a). The measurement of intellectual capital is important since most of the senior executives in organizations manage what has been measured (Roos & Roos, 1997) and the organization becomes what it measures over time (Hauser & Katz, 1998). To evaluate and compare the existence of intellectual capital, researchers have used three broad indicators at organizational level. These indicators are derived from the audited financial statements of a firm and are independent of the definition of intellectual capital of a firm. There are three major indicators to measure net intangible assets at a firm level (Stewart, 1997, pp. 224-229) and they are market to net book value, Tobin’s q, and calculated intangible value (CIV). Apart from them, other methods include direct intellectual capital method, Baruch Lev’s knowledge capital valuation and Paul Strassmann’s knowledge capital valuation. Intellectual capital is the difference between the market value and financial capital of that enterprise at a given date (Abdolmohammadi, Greenlay, & Poole, 2001; Dzinkowski, 2000; Knight, 1999; Roos,Roos, Dragonetti, & Edvinsson, 1997, pp. 2; Sveiby, 1997a, pp. 3-18).  The reliability and usefulness of it can be improved by converting it to a ratio (Stewart, 1997, pp. 224-225), and is the most widely known indicator (Knight, 1999). The traditional accounting measures net identifiable assets using a combination of costing methods, such as historical costs, present value, replacement cost and market value. The market on the other hand values its net assets of a firm holistically, and they are assets and liabilities, both identified and not identified by the traditional accounting system. Some authors use market to net book value as the basis to construct indices. For example, the composite IC index is indirectly linked to the market value of the firm.  When the index does not correlate with the market value, the choice of weights or indicators or the capital forms of the index are revised (Roos, Roos, Dragonetti, & Edvinsson, 1997, pp. 78-79; pp. 92-93).  If the ratio is more than 1, it indicates that the organization contains intellectual assets not represented by the financial statements. Training as a percentage of payroll cost was significantly and positively associated with market-to-book value indicating that Wall Street values more highly firms investing in training than others.  However, if the ratio is less than 1.0, the firm may still have intellectual assets but they can be masked by intellectual liabilities (Harvey & Lush, 1999; Caddy, 2000).  This indicator was initially developed by the Nobel-prize-winning economist James Tobin to predict the investment behaviour.
Original languageEnglish
Pages (from-to)422-427
Number of pages6
JournalJournal of the American Academy of Business, Cambridge
Issue number1&2
Publication statusPublished - Sep 2003
Externally publishedYes


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