Intangible Asset Contribution to Company Performance: the “Hierarchical Assessment Index” Michele Grimaldi1 and Livio Cricelli2
M. Grimaldi, L. Cricelli, 2009. Intangible Asset Contribution to Company Performance: The Hierarchical Assessment Index, The Journal of Information and Knowledge Management Systems - VINE, Vol. 39, No. 1, pp. 40 - 54.
1
Faculty of Engineering, Department of Mechanics, Structure and Environment, University of Cassino, Via G. Di Biasio, 43, 03043, Cassino (FR), Italy
[email protected] Ph: +39 0776 299 4353 Fax: +39 0776 299 4353
2
Livio Cricelli Faculty of Engineering, Department of Mechanics, Structure and Environment, University of Cassino, Via G. Di Biasio, 43, 03043, Cassino (FR), Italy
[email protected] Ph: +39 0776 299 3481 Fax: +39 0776 299 4353
Intangible Asset Contribution to Company Performance: the “Hierarchical Assessment Index” Abstract Purpose - The paper defines a theoretical model which assesses and measures the intangible asset contribution to company performance. The model keeps into consideration the most meaningful elements that reflect the success factors, crucial to company business strategy and value creation. Design/Methodology/Approach - The model adopts a hierarchical structure. The strategic intangible assets of the company have been divided into value drivers; a series of measurement indicators have been selected to describe the characteristics of each aspect of the intangible company performance. The measurements obtained from numerical indicators, which express the totality of the results achieved by the organizational strategies, are combined to create the Hierarchical Assessment Index (H.A.I.), by assessing quantitative and qualitative company features, through the Analytic Hierarchy Process (A.H.P.). Findings - The H.A.I. identifies the sources of added value and competitive advantage in each business context; it traces the subordination of every element on company performance, and singles out those intangible assets which improve the company performance, at every level of the hierarchy. Practical implications - The H.A.I. provides guidelines to understand what are the key intangible factors to create the value of the company and suggests the implementation of corrective strategies. Originality/value - The H.A.I. is the expression of the combination of the objective measurements of intangible assets with the subjective contributions by the managers. In fact, besides the numerical results of the performance of every element in the hierarchical structure, also the managers’ opinions about the significance of their performance are considered. Thus, objective and subjective evaluations jointly contribute to suggest the way to the achievement of the expected objectives. Keywords Intangible asset performance; Value assessment method; Value driver; Measurement indicators; Analytic Hierarchy Process. Classification Conceptual paper
1. Introduction In the last years, managers and scientists have agreed on the fact that the assessment of company performance must be based not only on the quotation of the internal tangible resources, but also on the measurement of the available intellectual capital within the company (Kaplan and Norton, 1996). It is well known that the intellectual capital consists in those intangible assets as competences, interrelationships, know-how and processes which determine the organizational, cultural and strategic specificity of a company (Bontis, 1998; Edvinsson and Malone, 1997; Stewart, 1997). Thus, it represents one of the most difficult assets to be managed and numerically quantified. Traditional economic and financial metrics, in fact, cannot provide exhaustive information about the actual health state of companies and about their performance (Eckstein, 2004; Lee et al, 2005; Said et al., 2003), as they quantified the intangible assets economically as a consequence of the gap between the market value and the equity value of a company. Therefore, the most recent intangible asset evaluation models should be updated in order to suggest methodologies and procedures to manage drivers of intangible value creation (Andriessen, 2006; Carlucci et al., 2004; Lev, 2001; MartinezTorres, 2006). Moreover, an intangible asset evaluation methodology should go beyond the static economic evaluation of tangible and intangible assets and examine also the added value dynamically generated by the knowledge flows running among them. Thus, it is important to ascertain, define and analyse both the organizational knowledge stocks, which are the contribution of knowledge assets to the value creation, and the knowledge flows, which are the dynamic interrelations among stocks (Cricelli and Grimaldi, 2008; Ghalib, 2004). Only in this way, it is possible to single out the real contribution of every knowledge asset and its direct and indirect capability of influencing organizational economic performance. As the cognitive assets are specific of every organization, each intangible asset evaluation model must care for the fact that it is not possible to measure these assets without putting them into correlation with their business context. This suggests both the need of measuring the correspondence between the obtained results and the prefixed goals (Carlucci and Schiuma, 2007; Kaplan and Norton, 1996; Sullivan, 2000), and the necessity of defining and adopting a flexible methodology to be easily customized to the business context (Stewart, 1997; Teece, 2000). Therefore, managers should be involved in the evaluation of the performance and in the control over the alignment between the
definition of the objective and the assessment of the results, through the definition of the main strategic assets of the company. Several methodologies have been proposed to evaluate the company intangible assets. Many of them are characterized by a common element: an array structure where company intangible assets have been distributed and classified. The “Technology Broker” (Brooking, 1996) bases its analysis on a financial evaluation of four components of the intellectual capital; Kaplan and Norton (1996) relate the output measures with the performance indicators, through their “Balanced ScoreCard”; the “Intangible Asset Monitor” (Sveiby, 1997) maps the existing knowledge flows among three categories of intellectual capital. The “Intellectual Capital Index” (Roos et al., 1998) gives an index of the intangible assets measured in a holistic way. The “Skandia Business Navigator” (Edvinsson and Malone, 1997), assigns the real contribution the innovation of each organisational and structural element, by means of five perspectives of the intellectual capital. Experience has demonstrated that, besides listing and classifying company intellectual assets, it is necessary to determine those which chiefly influence company performance and mainly characterize its positive and negative trend. Since firm’s intangible asset development is strictly related to its competitive strategy and the adopted strategy reflects management’s decision on how to respond to external reality (Zack, 1999), managerial perception should shape knowledge resources and value of intangible assets to the organization (St. Leon, 2002). To this purpose, strategic considerations by managers have revealed to be of the utmost importance: their experience and acquaintance with the context could effectively help in the suggestion of the most relevant measurement indicators of those aspects which concur to the achievement of the mission and of the goals established by the strategies. Hence, management perceptions are considered imperative to the evaluation of those intangible assets, essential to the construction of the organisational core competence (Hafeez and Essmail, 2007). In addition, managers’ opinions should be taken into account for the achievement of the desired performance not only with regard to the actual state of the company performance, but also with regard to its temporal evolution. Reasonably, the choice of intangible assets to be developed by an organization is strictly dependant on its capability to make this choice fit for the business strategy of the company (Johansson et al., 2001; Skoog, 2003); not secondarily, it is relevant to understand on what specific areas the organization needs to focus and what knowledge assets of human resources need to be leveraged within each specific area (Andreou et al., 2007). Ultimately, it appears also advantageous for the management to have the possibility of selecting which company variables influence the successful or unsuccessful performance and, consequently, of being able to suggest the amendment actions to get the desired performance or, at least, to approximate it. In the light of the considerations up to here set forth, it has come out the exigency of a managerial model which could combine the most of the above cited demands. The paper proceeds as follows. Section 2 presents the research method. Section 3 describes the structure of the model in details. Section 4 discusses the assessment process and the hierarchical assessment index. Section 5 summarizes the applications of the model, while section 6 concludes the work.
2. The research method The purpose of this research is the definition of a theoretical model, named Hierarchical Assessment Index (H.A.I.), which can assess and measure company performance, keeping into consideration the strategic intangible assets within a specific context of a company. The theoretical model adopts a hierarchical structure as it can better express the graded importance of performance components, and gives the possibility of tracing the direct subordination of every element on company performance, at each level of the hierarchy. The model sets a procedure to calculate the influence of each measurement indicator on the performance (priority) and the quantitative importance of each measured intangible asset, with regard to the totality of the assets in achieving the company prefixed goals. Managers’ opinion about the evaluation of the elements crucial to the performance are taken into consideration through the implementation of the Analytic Hierarchy Process (A.H.P.). The whole procedure guides to obtain an index (H.A.I.) that, from the numerical values of the measurement indicators, properly combined in a bottom-up process, assesses the intangible company performance.
3. The Structure of the “Hierarchical Assessment Index” model In the hierarchical structure of the model, sketched in Figure 1, all the intangible assets have been arranged in such a way that each of them directly influences the performance measurement. These assets have been divided into some value drivers and a series of measurement indicators have been selected in order to describe the characteristics of each aspect of the performance. The model has the capability to show a balanced image of the intangible assets of the firm, as each asset can be allotted a priority that gives the measure of the influence on the performance. The definition of these priorities is based on a process which assembles managers’ thoughts and experiences through the Analytic Hierarchy Process (Saaty, 1980 and 1994). Take in Figure 1 The first level of the hierarchical structure condenses the company goal and holds, therefore, the highest degree of significance. This global value embraces all the second level elements (value drivers), which specify contents and meaning of the company goal; the tangible and intangible assets referring to each element of the second level are grouped into the elements of the third level (characteristics); at the last level, the measurement indicators are provided. 3.1 The Value drivers At the second level of the hierarchical structure, immediately below the total measurement of the performance, four value drivers classify the company assets: Stakeholders, Processes, Innovation and Knowledge (Figure 2). Take in Figure 2 In the attempt of not neglecting any of the intangible asset components within the value creation process of an organizational context, we have referred to the concept of Intellectual Capital, as initially developed in the perspective by Bontis et al. (1999) and Chatzkel (2001) for analyzing the value contribution of intangible assets in an organization. There are many definitions of the intellectual capital, but, over the last few years, a consensus seems to have been formed on the necessity of dividing the economic value of intangible resources of a company into three different categories: the relational capital, the organizational capital, and the human capital. The relational (or external) capital represents all the valuable external relationships with stakeholders. The organizational (or structural) capital refers to the available capabilities and knowledge mastered by the structure; it includes processes, systems, brands, culture and intellectual property. The human capital consists in knowledge, generated and owned by individuals; it refers to know-how, capabilities, skills, competence and expertise of the employees (Edvinsson and Sullivan, 1996; Roos and Roos, 1997; Wiig, 1997). In the hierarchical structure of the constructed model, the three components of the intellectual capital are defined in a more specific delineation. Firstly, all the possible relationships of an organization have been taken into consideration; these constitute the first value driver, named “Stakeholders”, which has been partitioned into five further distinct sub-value drivers in dependence of the type of the relationship. Secondly, the organizational capital has been analyzed as for its double modality of value contribution to the company: process and innovation. The former refers to the application of the operative and practical knowledge; the latter refers to the capability of a company to develop knowledge and to contribute to a collective understanding about how things work and how they could work (Lemon and Sahota, 2004). Thirdly, in the value driver “Knowledge” the traditional components of the human capital have been considered. 3.1.1 Stakeholders This value driver refers to all the internal and external relationships of the company. It is well known that the satisfaction of stakeholders’ expectations represents a crucial element which influences the company performance. Through the evolution of the methodologies of the organizational evaluation, the number of those stakeholders playing a leading role has been widened from customers and employees, to include suppliers, partners, institutions, and shareholders. In this model, the employees of a company are not considered as elements of this value driver, as they are included in the value driver “Knowledge” in dependence of their strong contribution to human and cognitive capital. The five sub-value drivers (customers, suppliers, shareholders, partners, and institutions) of the main value driver “Stakeholders” have been identified in consequence of their
different contribution modalities to the value creation process and their peculiar influence on company performance. The sub-value driver “Customers” encompasses the centrality of the customer satisfaction and all its implications in the strategic and organizational processes. This sub-value driver takes into consideration how employees perceive critical factors of customer satisfaction and how customers realize the delivered quality of the received product/service. The sub-value driver “Suppliers” describes not only the relationships between the company and its suppliers, but also the satisfaction of the suppliers themselves. In fact, a reciprocal exchange of communication and cooperation favours the acquisition of a competitive advantage for both of them, allowing a cost reduction and a better sharing of their competences. The sub-value driver “Shareholders” keeps into consideration economic and financial indicators of the performance. The sub-value driver “Partners” delineates the external interrelationships which are fundamental to company results in terms of competitive advantages and corporate reputation. The sub-value driver “Institutions” refers to the bodies of government and defines the modalities of their interaction with the activity and procedures of the companies by controlling its compliance with the regulations in force. 3.1.2 Processes The value driver “Processes” includes all the industrial processes, the organization and management procedures, and the information systems of the companies. Not only each process can influence the performance of the company, but also each phase of the processes can be of the great importance to the functionality of other interrelated series of operations: therefore, they all concur to the achievement of the proposed strategic objectives. Usually, two alternative modalities to check the achievement of the proposed objective are followed by the management: to monitor the internal alignment between the strategic decisions of the managers and its strict implementation; to measure and verify whether the processes stated in the strategic planning have reached the previously decided results. However, the second modality does not ensure the good performance of the processes, since measurements do not account for eventual misalignments between the strategy and its implementation. As a consequence, the process performance should be evaluated at each level of the process phases, strategic, organizational and operative, in order to measure and assess their efficacy, efficiency and productivity, in adherence with the business strategy. 3.1.3 Innovation The value driver “Innovation” is related to the capability of a company to keep up with the market evolution, which characterizes the today competitive context. This value driver enables companies to manage and integrate the new opportunities of the market, the new existing technologies and the specific required competences in order to improve the company competitiveness. Rather, an integrated approach of innovation management facilitates the exploitation of knowledge and technological skills and favours the new product development, the renewal of the productive processes, the enhancement of process/product standards. Then, the assessment of all these aspects analyzes the performance of this value driver. 3.1.4 Knowledge The last value driver, “Knowledge”, concerns the capability of employees of a company to create value through their available intangible resources with the purpose of distributing and sharing knowledge and generating new knowledge. Thus, “Knowledge” focuses on the fundamental role of intangible assets in achieving business goals and accounts for the modalities in which human capital elements, such as organizational know-how, expertise, capabilities, and skills improve the company performance. Such elements should be evaluated on the basis of the organizational capability to use knowledge adequately and to generate new knowledge. In particular, one of the source of the competitive advantage for the company derives from the capability to select the profitable information out of the over-information. Hence, the performance of the company does not depend on the amount of the obtained information, but on its capacity to screen and elaborate it to innovate the processes and exploit new markets. The achievement of the objectives of this value driver is evaluated trough the analysis of some features of the company, such as the internal corporate image, the perception of the company by the employees, and the corporate reputation.
3.2 The Characteristics At the third level of the hierarchical structure, value drivers and sub-value drivers are divided into four characteristics: stability, efficiency, growth, and dynamism. They are the possible expressions of the activity of the company and give a detailed characterization of all the elements at the second level. At the same time, this additional subdivision monitors specific aspects of each value driver, by means of properly defined performance indicators. 3.2.1 Stability Stability represents the endowment of the company in terms of material and immaterial talents and capabilities examined at a precise time (“as is” condition). 3.2.2 Efficiency Efficiency is intended as the capacity of obtaining the desired performance by means of the available tangible and intangible assets. 3.2.3 Growth Growth answers the demand for controlling company development and the positive trend of its continuous improvement. The analysis of growth studies the “to be” situation of the interested variables. 3.2.4 Dynamism Dynamism refers to the company flexibility, that is, its ability of adaptation and reaction to the market change and of taking chances offered by its business context. This characteristic underlines the importance for the organization to adopt ductile tools to cope with competitors. 3.3 The Measurement Indicators At the last level of the hierarchical structure, measurement indicators have the task of evaluating organizational, cultural and cognitive variables in order to monitor the achievement of the prefixed goals. The indicators correspond to each characteristic of the value drivers and sub-value drivers. In this way, the selected indicators analyze and measure the company performance. In Table 1, a list of measurement indicators, grouped by value drivers and by characteristics, is proposed. This list cannot be suitable for all the companies, as each company intentioned to apply the developed methodology should select the most meaningful indicators that best reflect the success factors critical to its business strategy. Data of the measurement indicators are always numerically expressed, both in case they are the results of a function or of a formula of quantitative data (absolute number, percentage, ratio, time, etc.) and in case they are the results of a process of numerical conversion from qualitative into quantitative. In Table 1, each measurement indicator has been characterized by type of data: quantitative continuous (QC), quantitative discrete (QD), and qualitative (Qual). Table 1: The measurement indicators STAKEHOLDERS Customers Stability Mirror analysis Profit per customer Efficiency Customer Satisfaction Index Market share Customer retention Sales contacts/Sales closed Growth Number of gained customers/Number of lost customers Revenues from new customers/Total revenue Growth in market share Growth in revenues Dynamism
QC
QD
X
X
Qual X X
X X X X X X X
Time to meet customer needs Customer complaint rate Number of satisfied customer feedback and suggestions Shareholders Stability Weighted Average Cost of Capital (WACC) Return On Equity (ROE) Efficiency Return On Assets (ROA) Current ratio Acid test ratio Efficiency & visibility on the market Growth Return On Investments (ROI) Change in capital provided by investors Dynamism Percentage of capital provided by venture capital Suppliers Stability Quality cost relating to suppliers Percentage of suppliers having certification Efficiency Input quality measures Efficiency & visibility on the market Value added generated through suppliers over total value added Growth Flexibility measures Supplier development investments Dynamism Percentage of products developed in co-operation with suppliers Partnerships Stability Partner Satisfaction Index Average duration of co-operation relationships Number of community of practice with partners Efficiency Efficiency & visibility on the market Percentage of revenues from strategic alliances with partners Coordination of projects and networks Growth Percentage of new products developed in co-operation with partners Turnover generated by co-operation partners Number of new projects from companies Dynamism Number of newly acquired contract projects Number of spin-offs Institutions Stability Investment from institutions Number of complaints Number of regulatory violations Efficiency Political consulting projects Efficiency & visibility on the market Change in capital provided by external sources of funding Growth Total number of conference attended
X X X
X X X X X X X X X
X X X X X
X
X X
X X
X X X
X
X X X X X
X X X X X X X X
X X X X X X
X X
Complaint rate reduction Dynamism Company reputation Papers at scientific conferences PROCESSES Stability Administrative expense/Number of employees Total HR investments/Revenue Absenteeism rate Efficiency Processing time Sales for support staff Number of best practices identified Re-use of knowledge Growth Structural capital development investments Number of distributed incentives Value added per employee Time to fill an open position Dynamism Number of contributions proven to have led to new business Employees’ cooperation rate in teams Mean efficient experience year of managers INNOVATION Stability Innovation Index Percentage of profit from new products Average age of patents Efficiency Number of best practices identified Success rate of new products development projects Growth New markets development investments Percentage of employees with access to appropriate training R & D investments Growth in revenue from new technology Number of obtained patents/Total number of presented patents Dynamism Number of patents pending Number of participating experts within a field Degree of expertise available in a field Number of results from community of Practice KNOWLEDGE Stability Satisfied Employee Index Employee turnover Percent of employees with advanced degrees Average age of employees Number of employees with pertinent experience Knowledge Activity Report Efficiency Sales per employee New solutions/products/processes suggested Savings from implemented employee suggestions Growth Hours of training/Number of employees Training expenses/Number of employees Growth in average professional experience
X X X
X X X X X X X X X X X X X X
X X
X X X
X X X
X
X X X X X X X
X X X X X X X X X X
X X X X X
X
Knowledge Sharing Activities (workshops, seminars, networks) Rookie ratio Number of employees with the same skill/capability Dynamism Diversity Index Competence turnover Knowledge sharing attitude Leadership Index
X X X
X X X X X
4. The Hierarchical Assessment Index The following is a description of the capabilities and functionality of the H.A.I. model to assess qualitative and quantitative company feature, its subjective and objective factors in order to support the decisional path toward the achievement of the desired performance. The assessment process begins with the determination of the numerical value of each of the selected measurement indicators (see Table 1) placed at the last level of the hierarchy. A quantitative value, which expresses the measure of its performance (mii’jk), is associated with every measurement indicator, where: i value refers to the value driver and runs from 1 to 4 (Stakeholders, Process, Innovation, Knowledge); for i =1, i’ value refers to the sub-value drivers of the value driver “Stakeholders” and runs from 1 to 5 (Customers, Suppliers, Shareholders, Partners, Institutions); j value refers to the characteristics of each sub value driver of the value driver “Stakeholders” and each of the other value drivers; it runs from 1 to 4 (Stability, Efficiency, Growth, Dynamism); k value refers to the measurement indicators that relates to each value driver, to each subvalue driver and to each characteristic; it runs from 1 to the total number of the selected indicators. In the following step of the process, a qualitative value, which expresses its degree of importance (priority) with regard to the totality of the assets in achieving the company prefixed goals, is associated with every measurement indicator. The capabilities of A.H.P. have been used to determine the degree of importance of each element of the hierarchical structure and to calculate its overall priority. In order to establish the priorities of the elements in the hierarchy, the elements are pair-wise compared against the forefather element. This comparison is performed using the A.H.P. comparison scale (Saaty, 1980), which expresses comparisons verbally, and these verbal comparisons are then represented numerically. In particular, the pair-wise comparison process starts at the top of the hierarchy to select the value driver with the highest priority. Then, at the level immediately below, the priorities of the value drivers are divided by the weighting process among their descendant, and so on. To obtain the set of overall priorities of the hierarchy elements, all the results of the pair-wise comparison need to be synthesized. The overall priority of an element is the degree of importance of that element with regard to all the other elements in the hierarchical structure and represents its significance with respect to the whole of the company performance. Therefore, the overall priority of every measurement indicator is expressed by xii’jk, where the indexes i, i’, j, and k are the same as for the value range and connotation of the quantitative value mii’jk. As for the qualitative value of measurement indicators (xii’jk), it is worth reminding that each value is expressed by a percentage value and their total sum is unitary. In the process of calculating the H.A.I., which is based on the combination of all the measures of indicators (mii’jk) with their overall priorities (xii’jk), it is necessary to take into account both the temporal variations of mii’jk and the expectations by managers for its improvement. To fulfil this objective, it is necessary to make use again of the A.H.P., but in a different application from that previously implemented. A pair-wise comparison is performed among three elements for each measurement indicator: the value of the performance calculated for the time period “T” (PT); the value of the performance calculated for the time period immediately preceding the time period “T”, that is “T-1” (P T -1); the desired performance (P Desired). The three element matrix of the pair-wise comparison is the following:
Take in Figure 3 The three values to be included into the matrix of Figure 3 are derived as it follows: P(T-1; T) is the numerical ratio between the value of the performance of the indicator calculated for the time period “T” (PT) and that calculated for the time period “T-1”; P(T-1; Desired) is inferred from the opinion of the manager about his expectation for the value of that indicator (PDesired); P(T; Desired) is determined by simply substituting one relation into the other, so obtaining a numerical value. This particular procedure helps to avoid the inconsistency that could emerge from the fact that one of the three terms of comparison derives from subjective considerations (PDesired) and, also, that some measurement indicators derive from qualitative data. By means of the same procedure as that one used to find the priorities of the pair-wise comparison matrix, the normalized values of the priorities for each of PT, PT-1, and PDesired are obtained. The priority of PT is the weight of the performance of the measurement indicator, calculated for the time period “T” with respect to its correspondent value for “T-1” and to its desired performance. By this procedure, the values of the measure of the performance “mii’jk” have been turned into the values of the desired performance “pii’jk”, which accounts for the temporal trend and for managers’ expectations. The iteration of this procedure, for each measurement indicator, supplies all the weights for all the indicators (pii’jk), where the indexes i, i’, j, and k are the same as for the value range and connotation of the quantitative value xii’jk. For each measurement indicator, the value of pii’jk is comprised between 0 and 0.5. This follows from the fact that the sum of the three weights of PT, PT-1, and PDesired must be unitary and that the value of PDesired must be higher than those of PT and PT-1, in consequence of managers’ expectations. It is demonstrable that the weights of PT and PT-1 cannot assume values either negative or higher that 0.5. At this point of the process, for each measurement indicator, it is possible to combine the weights of the performance of the measurement indicator (pii’jk) with their overall priorities (xii’jk). The sum of the products of pii’jk and xii’jk of each measurement indicator results in a unique index, the H.A.I.: H.A.I. = ∑i∑i’∑j∑k xii’jk·pii’jk The value of H.A.I. is comprised between 0 and 0.5, in consequence of the fact that every pii’jk cannot assume value either negative or higher that 0.5 and that every xii’jk cannot assume value either negative or higher than 1.
5. Model Applications The H.A.I. value is the numerical expression of the effectiveness of intangible assets in achieving the desired performance and of the results of the implemented strategies. The closer the value of the H.A.I. to 0.5, which is the maximum value that H.A.I. can assume, the more advantageous the utilization of the available assets by the company. On the other hand, the width of the divergence from 0.5 will point out the measure of the relevance of corrective strategies. The criteria of the model make it possible to distinguish the contributions of each organizational aspect (value driver) respect to the H.A.I., and to recognize the causes of the performance results by means of a top-down inspection process. In other words, a sectional analysis can be performed about successful or unsuccessful actions at every level of the structure. It is possible, in fact, to focus the attention on the performance and on the weights of the measurement indicators for each value driver, separately. For instance, in order to check the behaviour of the value driver “Innovation” (i=3), it is possible to calculate the value of the following: ∑j∑k x3jk·p3jk. Similarly, it will be verifiable the single contribution of a specific measurement indicator, referring to a peculiar characteristic of one of the value driver, in case its performance results are of strong influence on company success. This can be achieved by means of the following: xii’jk·pii’jk. The analysis can be extended by observing the time variation of the singular contributions, both at the top level of H.A.I. and at the levels of value drivers and measurement indicators. This kind of data analysis can provide useful information about the success or the failure of the company strategic
choices, along a period of time, and additional “ex post” support to possible implementation of investments. Another application of this model refers to its use as a comparative method among companies operating within the same business context. Also in this case, the analysis can be performed, at the top level of the numerical values of the H.A.I. of each company, or among those corresponding value drivers which are considered as the most significative in that specific context.
6. Conclusions In this paper, a model has been developed to support the management in assessing the company performance by the evaluation of the contribution of the intangible assets to the performance. The H.A.I. identifies the sources of added value and competitive advantage in each business context and singles out those assets which can improve the performance. Intangible performance drivers can be discerned through a process where all strategic assets are arranged in a hierarchical structure on the basis of their different typology and contribution to the performance. The modalities of the model construction and the assessment process make it possible to carry out the analysis into the detailed levels of the structure and to achieve several purposes. Firstly, the model can give a global sight of the results, obtained from the business strategy, by means of the analysis of the value of H.A.I. and of its temporal evolution. Secondly, the model can analyze and measure each single value driver quantitatively, in case the management assumes the performance to be strictly dependent on that particular value driver. Thirdly, the model enables the management to check the behaviour of a particular indicator, in case the management assumes that the company performance is affected, positively or negatively, from that indicator; in this way, the management is solicited to identify and adopt timely corrective strategies. The model is flexible and adaptable to several business contexts, thanks to the possibility of adding or subtracting elements (value drivers) in dependence of company’s needs, and to the customization of the weight selection by means of a process that considers opinions and experience by management. The effects of the subjectivity factor are controlled by the consistency analysis procedure.
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H.A.I.
Value
Characteristic
Measurement Indicators Figure 1: The hierarchical structure of the “H.A.I.” model
H.A.I.
PROCESSES INNOVATION
STAKEHOLDERS
Suppliers
Partners
Customers
Shareholders
Institutions
S E G D
S E G D
S E G D
S E G D
KNOWLEDGE
S E G D
S E G D
Measurement indicators Figure 2: The “H.A.I.” model
S E G D
S E G D
PT
P T-1 P T-1 PT P Desired
1
P Desired P (T-1; T)
P (T-1; Desired)
1
P (T; Desired) 1
Figure 3: The pair-wise comparison matrix of each measurement indicator
