Summary:
It addresses the need to apply the latest management techniques in the poorest countries, the role of organizations dedicated to science and technology, and the need to manage intellectual capital in this type of organization. To this end, it proposes a three-stage methodology: preparation, implementation and growth. Exposes the tasks to be carried out in each one of them. It classifies the indicators for measuring intellectual capital and explains the ones it recommends for each classification, obtained by expert criteria.
Key words: SCIENCE AND TECHNIQUE, INTELLECTUAL CAPITAL, METHODOLOGY, INDICATORS
Development
The framework in which organizations currently operate around the world is characterized by excess information, continuous computerization and automation of processes, modernization and updating of management techniques, sharpening of competition between organizations and how general framework the accelerated process of economic globalization. (Marrero, 2001)
In this context, the assimilation of scientific advances that are generated in any part of the world and its own technological development are imposed, as a sine qua nom condition for not falling behind in the accelerated race towards the goal.
That is why, in one way or another, the activity of science and technology must be present in any organization that claims to be in tune with modern development trends and must be organized more effectively in those organizations whose corporate purpose is precisely research and development (R&D) activity.
But in the underdeveloped world the application of new technologies and modern administration techniques is poor. There are cultural deficiencies, such as reluctance to change and a lack of innovative culture. There are also organizational deficiencies, such as poorly integrated structures and little infrastructure to support information activities. There are also management deficiencies, such as the lack of orientation towards the application of professional methods of detecting opportunities and threats in the environment and, above all, there is a weak economic base that contributes to accentuating the technological gap with the first world. (Simeon, 2002)
One might ask, then, if it makes sense to talk about business intelligence, knowledge management, intellectual capital management, innovation and development in our countries; if it would not be too pretentious to talk about the management of science and technology, and if we do not have to focus more on our economic development and obtaining better health and employment indicators, than on studying and developing new administration trends modern.
The answer is absolutely YES. Precisely for having a weak technological base and scarce economic resources, it is essential to make the most of what we have, to spread knowledge and innovation, to generalize technological advances; always on the basis of the socialization of science and technology, without the necessary protection of industrial and intellectual property becoming a brake on this process.
Science and technology organizations are precisely responsible for achieving the integration of scientific activity into social interests, guaranteeing the protection of innovation and making its generalization viable at the social level. To do this, regardless of the regulatory role they may play, they must first achieve a high scientific level of their own, based on an effective administration of scientific activity in a social role.
And to achieve a successful administration of science and technique and the intellectual potential that supports it, it is necessary to start from its measurement. You cannot successfully manage what is not measured.
To satisfy this need, organizations have to incorporate a system for measuring intellectual capital that allows the flow of value that the competencies, the organization itself and its relationships with the environment generate in the work processes, based on its indicators, to be easily revealed. strategic. To make this feasible, a methodology that suits the nature and practice of each of them must be available. The measurement must be seen by the directors of the organization as a critical success factor to which it is necessary to invest more than economic and technological resources, great efforts and convictions to achieve a cultural change in people and in themselves. (Beltrán, 2000)
The following phased methodology is proposed:
1. Preparation stage.
The conditions are prepared to implement the system for measuring and managing intellectual capital.
- Prepare the organization for change. The conviction of the utility of managing intellectual capital must be achieved as a key to success and not as a way of being in tune with academic and business discourse on administration issues. (Kaplan, 2000) Have the competencies defined (job designs, knowledge maps, diagnosis by each worker of the competences that they do not have and planning of the ways to achieve them) Have a solid strategic framework updated and communicated. At least, Mission, Strategic Objectives and Macroindicators of the organization. Have a computer system that reflects and compares other operational indicators in addition to accounting and financial ones. Carry out a benchmarking that allows knowing best practices,the indicators used in other similar organizations in the country or abroad, the measurement criteria. The conceptual models that link science and technology with society and integration and the reflections and research carried out on this link are carried out regionally, nationally and internationally must be considered.
2. Implementation stage.
Indicators are defined and the measurement system is implemented.
- Define the indicators to be used in the organization. They must be relevant, reliable, up-to-date, accurate, valid, verifiable, specific, effective and timely, and must add value to the information. The underlining indicates that the indicators thus conceived must, therefore, fuel the activity of the actors participating in the process of knowledge generation and technological development. Determine measurement criteria achievable by the organization. As the organization reaches a certain level, new measurement criteria must be established and thus go up through layers to the highest levels of management. Define the actions that contribute to improve the indicators and achieve the expected actions. Choose an area or process where it is possible to easily experience the designed system.There must be a measurement culture, the effect of the competences can be verified easily and / or quickly and that it is not part of the processes that are included in the value chain. Incorporate the experiences obtained into the system. Extend the model to the entire organization. To do this, an organization-wide knowledge of the system's objectives must be achieved, the effects that those involved in its application will receive, how useful the information will be, who to consult in case of doubts.To do this, an organization-wide knowledge of the system's objectives must be achieved, the effects that those involved in its application will receive, how useful the information will be, who to consult in case of doubts.To do this, an organization-wide knowledge of the system's objectives must be achieved, the effects that those involved in its application will receive, how useful the information will be, who to consult in case of doubts.
The system must be conceived with sufficient autonomy so that it is part of the organization's processes, that it contemplates its own adjustment mechanisms and that it easily adapts to changes in the environment.
3. Growth stage.
Constant feedback will be received from the system, the development layer will be measured and the increase in the measurement criteria will be decided to achieve new stages of development.
Classification of indicators for measuring intellectual capital
Most intellectual capital measurement models establish three classification categories: human capital, structural capital, and relational capital. (Kaplan, 1996; Sveiby, 1998; Bueno, 1998; Skandia, 2001; Galán, 2001)
Human capital for the purposes of science and technology includes development actors (may be people, groups, entities)
Structural capital includes scientific-technical programs and the products of those programs.
Relational capital basically refers to its interaction with society and its valuation within the National System of Science and Technology.
Within each category, each indicator can be classified into:
- Input indicators Outcome indicators Indicators of diffusion and technological innovation (cooperation and comparability indicators)
For each indicator, comparative analyzes will be carried out against base periods, against external leaders' indices or at the global level. We recommend the use of graphs, tables that allow for a better presentation and facilitate analysis.
The indicators listed below are only a proposal because each organization must adapt it to its development environment and depending on which are the fundamentals for measuring scientific technical management. Thirteen experts, 6 nationals and 7 foreigners, were obtained from the consultation. After two rounds of consultations, those indicators with a coincidence greater than 20% (3 or more) were chosen:
Input indicators
They are the most common and also the easiest to obtain. The methodology for its construction is based on the Frascati Manual (OECD, 1993) which has been adapting to changes in the productive structure, particularly in relation to expenses in Research and Development.
1.- R&D expenses
It is common for traditional accounting to not accurately reflect R&D expenditures but to associate them generally with areas of responsibility related to research. The best measurement will be carried out when there is an activity-based accounting (ABC), which allows registering each R&D activity, regardless of where it occurs and, in turn, discards those operating expenses from the R&D areas that are not are depending on the investigation. (Armenteros, 2001)
2. R&D expenses per capita.
The divisor can be defined based on the personnel of the organization itself or the field of action based on which the system has been designed.
3. R&D staff (full-time scientists and engineers / full staff)
4. Incorporation of R&D (people who contribute to R&D who are not full-time / total staff)
It is common that there are many people who contribute to the research processes and who are not part of the R&D areas, however their contribution can be very valuable. For regulatory entities it gives an idea in addition to the effectiveness of the work of socializing science. (Vernis, 1998)
5. Level of researchers (academic titles, research titles, experience).
6. Percentage of R&D expenditure financed by industry, by the Government, by higher education organizations and by private non-profit entities.
Structure the origins of funds for scientific activity.
7. Budget appropriations by areas of knowledge
It structures the destinies of funds of the scientific activity. It is compared with the needs and problems banks previously defined by the planning activity or with the most deficient productive and service activities.
Outcome indicators
They are the ones that measure the result of the allocation of resources and that produced by the people and institutions dedicated to R&D activities.
The best known are precisely those that measure the production of a bibliometric type and patents. However, these indicators do not have a homogeneous base due to conceptual difficulties.
At the country or region level, it is measured by the volume of technological exports and imports, the payment for patents, the effect of the globalization process and the level of foreign investment. Thus, its indicators «are represented by the income, payments and balance of technological balance of payments and by the coverage rate.
The balance of payments can be established at the organization level based on what is invested and what is obtained in the scientific activity.
Depending on the knowledge actors, indicators such as the number of events by levels, the number of prizes, the quantity and quality of new scientific relationships established, the relationship between the results for each peso invested can be used.
Depending on the science and technique programs, their economic or social effect, cost / benefit ratio, number of people involved, number of people benefited, gender indicators in relation to incorporation into scientific activity, indicators by age can be measured.
A division of indicators for production sectors should be made depending on the intensity of the use of technologies, since the differences are usually quite significant from each other.
The measurement of these indicators will allow creating and updating databases of projects, research groups and centers, innovation projects, fellows, international technical cooperation, researchers abroad and the results of technological development surveys of the industry.
Innovation and technological diffusion indicators
If it is taken into account that these are more related to technological development, they would correspond to a special classification of performance indicators. Its construction is based on the close relationship that exists between technology and industry and the need to create a favorable environment for innovation and therefore technical change.
These indicators would allow the cooperation of different agents and the exchange of information to facilitate the dissemination of information to small and medium-sized companies that due to their size would have limitations for investment in R&D, but which at the same time are a factor of dynamism in the industrial sector.
The elaboration of these indicators responds to the need to favor innovation activities as well as to monitor and evaluate them. The indicators of technological innovation and diffusion depend on the number of cooperation agreements between companies, the objectives that these pursue with this collaboration and the characteristics of those companies. (Mezza, 2001)
1. Visibility of scientific activity
It is measured by survey processes that allow knowing how other companies and society in general, knows the scientific results obtained, compares the number of organizations that put their results on the Internet, the number of scientific articles published by researchers, the news about scientific activities and results, the number of effective impacts on our public web pages (# of click / # of requests).
Management to increase visibility should be directed towards creating project banks and achieving their dissemination and generalization.
2. Dynamics of the development of Science and Technology.
Scattered matrices can be drawn up to establish the links between different organizations and scientific activities, calculate cohesion indices between the source and destination activities of the research, or use any other technique that allows determining the dynamics of growth in R&D a organization level and social level.
3. Degree of integration in world science.
It starts from analyzing the number of fellows, researchers participating in international projects, cooperation projects.
4. Degree of dissemination and adoption of knowledge.
Project databases, generalizations made, modifications made to projects by other researchers are evaluated.
5. Impact of technology
Considering that this is one of the aspects with the greatest political sense, we must work deeply. Measure the number of people with access to NICT, classified by age, gender, social background; evaluate as far as possible the use of technologies for growth or leisure purposes; the economic impact of technological investments (cost / benefit).
6. Dynamics of technological change.
Determine the periods of use of the same technology, the levels of investments by area or sector, technological updates, the time it takes for the area under study to assimilate technological advances worldwide. The dynamic differences between the different technologies must be taken into account.
7. Evolution of productivity and competitiveness.
Indicators specific to each sector will be used, profitability, productivity, goodwill and any other comparative indicator will be calculated. (Santandreu, 2000).
8. Rhythm of innovation.
Chronological analyzes of the activity of innovation structured by sectors or areas will be carried out and results will be obtained comparing the growth rate of that same sector or area worldwide.
BIBLIOGRAPHY
- (Armenteros, 2001) Armenteros, Martha. ABC versus traditional system. Notes of a postgraduate. ISRE, Havana, February 2001. (Beltrán, 2000). Beltrán, Rafael. How to measure individual-centered intellectual capital.. (Bueno, 1998) Bueno, E. Intangible capital as a strategic key in today's competition. Economic Studies Bulletin, Vol. LIII, August, 1998. Pp 207 –229. (Galán, 2001) Galán Soteres, Francisco. The KEA model, a model for knowledge management. In New Value Patterns for a new economy. Fundación DINTEl, Madrid, 2001. Pp. 413 - 415. (Kaplan, 1996) Kaplan, RS and Norton, DP Using de Balanced Score Card to work. Harvard Business Review, Sept. - Oct., pp. 134-137 (Kaplan, 2000) Kaplan, Robert S. and David P. Norton. Balanced Scorecard. Ediciones Gestion 2000. Barcelona, 2000. 330 p. (Marrero,2001) Marrero, Abilio. Accounting model for measuring intellectual capital.. (Mezza, 2001) Indicators of intellectual capital in technological foundations. In New Value Patterns for a new economy. Jessica Mezza Jaque.. DINTEl Foundation, Madrid, 2001. Pp. 385 - 395 (OECD, 1993) Proposal for Standards for Conducting Research and Experimental Development Surveys »(PDF format).. http://www.oecd.org (Sánchez, 2001) Sánchez Hernández, David. Knowledge management and the role of the University in the innovative process. In New Value Patterns for a new economy. DINTEl Foundation, Madrid, 2001. Pp. 30 - 53. (Santandreu, 2000). Santandreu Eliseu and Paul Santandreu. Finance Manual. Ediciones Gestion 2000. Barcelona, 2000. 373 p. (Simeón, 2002). Simeon, Rosa Elena.Speech at the opening of IntEmpres'2002 on October 17, 2002. (event compact disc) (Skandia, 2001) Skandia Insurance Company Ltd… (Sveiby, 1998) Sveiby, Karl Eric. The Intangible Assets Monitor. Human Resour and Accounting magazine. Vol. 2, No. 1, pp 73-97 (Vernis, 1998) Vernis, A. The management of non-profit organizations. Bilbao, Harvard Deusto Business Review # 77, pp. 100-103
