Sveiby's pioneering contribution to the field of ICM is in challenging the assumptions that form the basis of financial measurement. He digs deep to examine value judgments that are traditionally used to describe financial measures as objective, and nonfinancial ones as subjective. He explains that financial measures only seem obj ective because they are widespread and have been in use over long periods of time. As a result, standards have been set and defined and hence, enjoy a certain degree of consistency and comparability. Standards define the set of assumptions on which a measurement system is based and impart an element of objectivity. What proves Sveiby's point is that such nonfinancial measures like the number of units produced per hour or room occupancy rate seem more objective when compared with the relatively recent ones like employee and customer satisfaction rates.
Sveiby resists expressing performance measures whenever possible in monetary units. He explains that financial measures use money simply as a "proxy for human effort". What financial try to measure is the efficiency of the organization in using its capabilities regardless of what it produces. Thus, though monetary measures are suitable in some situations, like in the ROI ration, other nonmonetary units may be more effective in expressing the efficiency of the organization in using its capabilities, especially the intellectual ones, or as Sveiby prefers to call them, intangible assets. Therefore, Sveiby explains, proxies other than money are needed to measure intangibles through the development of performance measures (e.g., units per hour). One problem identified by Sveiby is that despite the development of measures, they were not developed by academics and thus lack a coherent theoretical framework that fits the knowledge economy. Sveiby attempts to develop such a framework by providing insight into what he calls intangible revenues and the nature of investment in intangible assets.
A third tendency that Sveiby strongly warns against is the use of performance measures to monitor employee performance. According to Sveiby, use of such measures to "control subordinates" is the "legacy of a long passed industrial era". This will only stifle the employee's capacity to create and adversely affect performance. Alternatively, to monitor the performance of employees and the organization as a whole, Sveiby designed the IAM model, to create a new language that informs management of what to focus on.
In conceiving the IAM model, Sveiby examined the goals of financial measurement systems to determine yardsticks for IC measurement. Financial measures, according to Sveiby, attempt to measure the efficiency of the organization in general. Similarly, the IAM model attempts to measure intangible assets by a standard of efficiency. The degree to which an organization can sustain its performance in a certain area is its stability/risk standard. The third standard is that of growth/renewal, which indicate performance in areas of growth.
The three standards—efficiency, stability/risk, and growth/renewal—are then applied to the three forms of IC in Sveiby's model, namely, external structure, internal structure, and competency. The crossover between these forms and the three standards creates a matrix of nine cells, where a few measures are chosen under each cell. Because the IAM model aims to create a new language, Sveiby favors the use of one to two indicators in each cell. Though the indicators should be designed to reflect the strategy and goals of each organization, Sveiby provides a view of some typical measures, which follow. It should be noted, however, that Sveiby's examples are based on the service industry and hence some of the examples do not apply to other industries.
External Structure. Measuring external structure under the three standards will enable an organization to monitor its performance in relation to customers and other external players. First, the growth standard measures the increase of business from existing customers, while renewal focuses on growth resulting from innovating new products, gaining new customers, or entering new markets. Under this criterion, Sveiby includes "image-enhancing customers" as a measure that introduces intangible revenues into the business.
Efficiency is measured in terms of profitability and sales per customer. Sveiby explains that costs and profitability are usually monitored in reference to products or functions and not customers, despite the fact that 80 percent of customer sales are not profitable. Again, this seems to be specific for the service industries, though it may also be applied to customer service segments in other industries.
For stability, the IAM model includes indicators like a customer satisfaction index, the proportion of business from big customers, and the frequency of repeat orders. All are designed to show the level of risk associated with the customer base.
Internal Structure. Measuring internal structure involves monitoring the support structure, taking into consideration general management, administration, accounting, personnel, maintenance, information systems, and other routine operations. Indicators showing how investment in new systems, such as IT systems, improves performance monitor growth of the internal structure. Internal structure can be calculated as the increase in percentage of sales or percentage of value added. Celemi,38 a Swedish company that produces learning products, expresses product research and development in terms of a percentage of value added as another indicator. Under renewal, the typical indicator is percentage of products introduced in the last few years. IAM adds to this the number of new processes implemented regardless of their size to show that new processes are being developed without any assessment of their value (see also about how to invest).
For efficiency, the IAM model looks at the proportion of support staff to the total number of employees. Sveiby explains that by monitoring the change in this percentage, an organization can monitor efficiency. However, without tying this indicator to the size of operations, it is unclear how it can reflect efficiency. Nonetheless, as shown in Celemi's 1995 Annual Report, explanations are necessary to interpret these indicators by reference to other changes in the company. For example, in 1995, Celemi's Annual Report compared two indicators under this cell, explaining that though the change in proportion of administrative staff increased by 4% compared to 1994, the rate of sales per administrative staff declined by 20%. Celemi explains that because the company is growing in size, they recently employed a large number of administrative staff personnel that have yet to jump the learning curve before their efficiency goes up. This shows why explanations are necessary to interpret these indicators. It is not far-fetched that, with time, management will become more conversant in the new language, not needing to look at such interpretations to understand how IC is performing.
For stability, Sveiby suggests adding a "values and attitude measurement" that indicates the culture of the organization and how pleasant the workplace is. Celemi opted not to use such an indicator in its reports. It is doubtful that the culture factor can be dealt with as part of a measurement system.
Instead, Celemi uses other IAM indicators in this cell, namely, support staff turnover and the "rookie ratio" (the ratio of staff employed in the last two years). The latter is used as an indicator for stability as it typically takes two years before new recruits are accustomed to the internal structure or the way the organization does business, and thus are able to sustain and improve it.
Competency. Measuring competency under the IAM model is limited to indicators that measure the competency of "professional" employees as S veiby defines them. S veiby hints that though the competency of outside experts and suppliers is not included as part of the organizational competency, that may change as organizations become more "virtual". To measure competency, the IAM model presents innovative and radical indicators. As mentioned earlier, it is in the area of measuring human capital, as opposed to the measurement of processes and technology systems, that innovation is needed. The first thing the IAM model demonstrates is how to classify competencies in an organization according to areas of expertise, then apply the suggested indicators to measure the level of competency according to the three standards. For competency, Sveiby goes against his own advice of limiting the number of indicators in each cell to one or two and uses four to six for each cell.
Under growth and renewal the number of years in the profession are measured to monitor experience, level of education, competency-enhancing customers (based on the same concept as image-enhancing customers), training and education costs, competency index, and diversity. The last three indicators are the most innovative. The competency index attempts to create a comparable generic measure of competency by multiplying years in the profession by years employed in the organization by the level of education. Sveiby explains that once these data are collected, management can then use statistical methods to track how the index develops in various fields of expertise through time.
Competency turnover compares the competency (calculated as number of years in the profession) of those who left the organization with that of new professionals, to assess the gain or loss in years of experience in the competency of the organization. This indicator limits the definition of competency to the years of experience; however, experience cannot necessarily be equated with competency.
The third indicator looks at the percentage of women who are professional employees. Research has shown that a higher percentage of professional women in an organization translates into a more innovative workforce. This indicator has been used by a number of Skandia companies. For efficiency, the IAM model divides the number of professionals in the organization by the number of employees, which is called the leverage effect, value added (or profit) per employee and per professional.
For stability, the IAM model measures the average age, seniority, or years with the same organization; relative pay position compared to other organizations in the industry; and professional turnover rate. According to Sveiby, older people are more stable than their younger counterparts in that they tend to stay with an organization longer. However, this indicator should be used with care, as an increase in average age would also indicate a decrease in drive. Like the turnover rate,42 average years should be kept in balance (see also about intellectual capital).
Talking IC? The use of standards of efficiency, stability, and renewal in the IAM model outlines the factors that should be monitored to measure IC, and thus provides structured guidance to management on the purpose and benefits of working with a measurement system. It provides different lenses through which to see measurement and imparts more significance into the quest of developing measures. These models do not merely measure human, customer, or organizational capital in the abstract, but rather measure whether the IC of the organization is being managed in a way that ensures increased organizational efficiency, stability, and growth. Over time standards help to streamline the activity measured and build consistency on what is being measured. Departments or units in an organization are assessed, as much as possible, on the same factors. Whether this is credible or not is a question that requires more research before it can be answered. Still, assessing divisions on the same measurement criteria or through use of the same indicators is not something that Skandia gives priority to in its measurement system; which it sees as a big experiment.