Lehner, F., Maier, R.Organizational memory systems1

How Can Organizational Memory Theories Contribute to Organizational Memory Systems?

Franz Lehner, Ronald K. Maier

University of Regensburg, Chair for Business Informatics III

Universitaetsstrasse 31, D-93053 Regensburg, Germany

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Ronald K. Maier

University of Regensburg, Chair for Business Informatics III

Universitaetsstrasse 31, D-93053 Regensburg, Germany

Tel.: ++49-941-943-3203

Fax: ++49-941-943-3211

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Running Title: Organizational memory systems

Abstract:

Organizational memory systems (OMS) support organizations to ensure organizational learning, flexibility and efficiency and the management of change. The paper describes the term organizational memory and reviews a set of theories contributing to this field. As organizational memory is considered interdisciplinary, theories are drawn from research fields as different as organization science, psychology, sociology and artificial intelligence. The consequence is that the design of information systems supporting organizational memory has to be seen in this very specific context which leads to different perspectives contrasting traditional software development. These different perspectives are integrated into our view on organizational memory systems. The paper is concluded by an outlook on the main research questions which we intend to address in our research.

Key Words: Knowledge management, knowledge management system, organizational intelligence, organizational learning, organizational memory, organizational memory system

1.Introduction

1.1.Innovative use of information systems

For some time now under the rubric “organizational memory” (OM), both innovative and familiar concepts as well as highly promising systems have been proposed and tested (cf. e.g. Bannon/Kuuti 1996, Buckingham Shum 1997, Lehner 2000, Morschheuser 1997, Poveschi 1998, Stein/Zwass 1995, Wargitsch 1997). The topic has taken on an intense sense of immediacy given the worldwide processes of restructuring in both economy and society. Relevant projects are already being carried out, especially in large corporations. Environmental dynamics and the pressure of competition that necessitate the development or the activation of new capabilities are paving the way for change. These adaptations occur automatically only in the rarest of cases, but presuppose (learning) processes. Important goals include elevating organizational efficiency and flexibility, overcoming growth limits and integrating organizations after mergers and acquisitions. The concentration on qualitative dimensions of organizational design gains increasing importance. One could look at this as an “expansion inwards”, wherein new or previously unused potential and strengths should be developed.

Example 1: In 1996 the Chase Manhattan Bank installed an intranet-based knowledge management system for approximately 16 million USD. This system enabled the bank’s employees to access the knowledge base of the entire business. Customer-specific data such as credit history, account balance, investment profile, as well as “soft” information such as personal preferences, or characteristics of the borrower could be called up directly from the work place. Already in the first year it was introduced, the system brought in 11 million USD through cost reductions and revenue increases. The system’s profitability results from an increase in employee productivity: the employees can devote more time to speaking directly to the customer because they need not ask for information that had already been obtained at some point in the past. The system was originally developed for the market segment with a turnover per customer between 3 and 500 million USD. Due to its success, the system is now being adapted for other customer segments.

Example 2: Under the direction of a Chief Knowledge Officer, the consulting company Ernst & Young (worldwide app. 40,000 employees) employs 400 full-time employees. They are responsible for documenting the existing knowledge and knowhow in the company, making it accessible for new employees and for protecting it when employees leave the company. The project’s goals are: to introduce knowledge management, to generally improve the exchange of knowledge within the company, and to promote corporate culture in relation to the distribution of knowledge (according to Madey/Muzumdar 1997).

The example of the Chase Manhattan Bank shows that new information systems that aim to improve organizational efficiency in no way necessarily have to mean a break with the past; rather they build upon it. In this case, a customer information system serves as the basis. With Ernst & Young the background and the goals are different. This case deals with supporting a worldwide operation during a phase of extreme growth. The driving force is mostly the need for quick and easy access to data, information and knowledge (often in multimedia form) that are becoming increasingly important for corporations. For a long time, data bases served as the most important means to achieve this task. Given the developments of the last few years, completely new structuring possibilities have arisen which, on the one hand, are leading from isolated data base concepts to company-wide information models and, on the other hand, are leading to a renaissance and evolution of existing business management concepts.

In order to achieve the aforementioned goals it is necessary to develop an understanding of the effected frameworks and management concepts that are already available. In addition, a more comprehensive understanding of the use of conventional database technology has to be developed and integrated within the broader concept of “organizational knowledge”. This paper is meant to take into consideration the framework and content of these goals.

Figure 1: Framework and conditions for organizational memory systems

The development of organizational memory systems (OMS) is substantially more complex than the development of conventional information systems because existing models and planning methods must be developed further, and a relationship to management applications (e.g. business process reengineering, process organization, enterprise modeling) must also be developed. Figure 1 shows how this can be achieved via the convergence of various structural approaches, whereby especially organizational development should be stressed. It should also be emphasized that important developments arise at the juncture where systems and available technologies meet.

Organizational memory systems and knowledge management systems[1] can either be conceived as a special class of information system, or as a characteristic of conventional systems. They are particularly important for innovation and the retention of organizational flexibility. The ways and means in which information technology is actually used for particular corporate goals depend mostly on which concept of “organization” the business has as a model. The systems introduced into a corporation should correspond to the prevailing fundamental views of the time (technology-culture fit). A business that evolves according to the plan of an autopoietic system requires other software-technological solutions than a business that is run in a stable environment according to bureaucratic rules. Differences will also occur depending how the information systems are used, even if it is the same system.

Figure 2: Corporate efficiency through fit between tasks, culture and technology

By using different organizational measures, most modern managers attempt to create a climate in which learning in and about organizations is encouraged. Figure 2 shows the relevant components (cf. Goodhue/Thompson 1995). Most business management applications (see section 3) concentrate for the most part on the relationship represented by arrow 1, i.e. they attempt to create a fit between tasks or, in other words, between labor organization and the (organizational) culture. “Traditional” information management is mainly concerned with trying to bring tasks and the technology that has been introduced into line with each other (arrow 2). With the help of organizational memory systems, the attempt is made to additionally improve the relationship between the technology introduced and organization’s culture (arrow 3) in order to achieve organizational efficiency.

1.2.Changes in economic structures - growing importance of technologies and information

Worldwide changes in economic structures are often attributed to the development or introduction of new technologies. Communication technologies and multi-media information systems currently appear to be playing a key role for the organization and competitive edge of businesses. Bullinger (1995) summarizes the leading technological developments and related periods of growth of certain industries over the last few decades as follows (see also Kock 1999):

  • production industries in the 50s and 60s
  • electronics and microelectronics in the 70s
  • consumer electronics and the computer industry in the 80s
  • telecommunications, information technology, media and entertainment (TIME) in the 90s

Other authors speak of the so-called quaternary-hypothesis (deployment of a fourth economic sector) and point out that, along with the three main economic sectors, a fourth independent sector is beginning to establish itself: the information sector (cf. e.g. Lenk 1989, 24). Above all it includes the production of “information” as well as services that deal with computer technology. Besides that, commerce and the exchange of information or information products are becoming increasingly important. Moreover, telecommunications enables business processes that render geographic proximity irrelevant: electronic business.

In all processes in which the aforementioned economic sectors can be observed, production factors are introduced and combined with each other. These production factors are included in practically all goods, or play a role in their production or extraction. However, their importance and combination varies from product to product. Moreover, the value of a production factor is determined largely by the dynamics of supply and demand. In this process it can be observed that the importance of information along the value chain is growing steadily. Information costs already account for a considerable portion of the total cost of the production process. Already in 1963, information costs accounted for more than 50% of the U.S. gross national product (Wild 1971).

In traditional production enterprises the portion of actual production costs as part of total product costs has fallen to 20% on average (cf. Pulic 1996, 149). This observation has been well supported by a number of recent studies (see e.g. Schüppel 1996, 49, North 1999, Bullinger et al. 1997, 16, ILOI 1997). The main reasons for this development are due to the elimination of product deficiencies and the reduction of productive, routine labor in favor of “intellectual” work. Schneider points out a few examples that powerfully illustrate this trend. At ABB, for example, only 3 percent of the time used for fulfilling a contract is devoted to production; the remaining 97% is used for “other”. Only 6% of IBM employees work in factories, and for a $700 camera, a mere 8.5% results from material costs; the rest is spent on microprocessors and software, i.e. for the “intelligence” of the product. (Peters 1994, 13, quoted from Schneider 1996, 13).

The huge fraction that information and knowledge contribute to production is the main argument for introducing technical support of knowledge management. Additionally, information is the most important prerequisite for decision making and goal-oriented negotiating. According to estimates, despite the increasing importance of knowledge, only about 30% of the actual knowledge available to an organization is really utilized (cf. Zucker/Schmitz 1994). Studies have also shown that due to inaccessible information, expensive but avoidable mistakes occur, and that the danger of losing knowledge is especially great when people leave the company (see e.g. Spek/Hoog 1994). Thus, the volatility of knowledge represents one of the most prevalent problems in the management of an organization’s knowledge base.

In the following the development of information processing is laid out to show the corresponding shift of focus from data via information to knowledge.

1.3.Developmental steps of information processing: from data processing to knowledge management

Over the last few years an evolution has occurred that, among other things, has been defined by continual and very important improvements in information technology. As a direct result of this development, a broad spectrum of variants of this technology are available for implementation for business applications today. Information and communication systems are not only introduced to serve as a more effective and efficient production factor to be used in business processes, but they are also increasingly regarded as a corporate success factor.

Of special interest in this respect is the increasingly important role of the “organization”. It also surfaces in the development of information processing that has occurred in several stages over the last few decades. These stages can be summarized from various standpoints, such as: technological development, corporate applications, importance of data and information, etc. Ortner describes this development from the perspective of the growing importance of data as business resources (Ortner 1991). By considering increasing organizational integration, he differentiates between the following developmental stages (see Figure 3): isolated applications, data base systems, data modeling, data management, and information management. According to him, the formation of business integrated information and communication systems is only feasible economically when based on a corporation-wide, consolidated data architecture or a corporate data model. The decisive contribution to the increasing and necessary integration of corporate processes results accordingly from the data, or rather the function of the data model (cf. Ortner 1991).

Figure 3: Development of information processing with the focus on data (steps 0-4 after Ortner 1991)

A similar system whose focus is corporate application of information technology comes from Hanker (1990). He breaks down the developmental stages of introducing computers into business as follows:

  1. Support of operations
  1. Support of management (e.g. decision support systems)
  1. Support for competitive strategy ( = computer as strategic weapon)
  1. Support for organizational strategy (= comprehensive standpoint, e.g. knowledge management, organizational memory)

The graduated model of Hanker points to a transformation in the way computers are used in business over the course of time. It can be used for diagnosis, i.e. which stage is the business at currently? However, the observation of the new dimension of information processing discussed therein is far more important: knowledge management and organizational memory. Figure 4 summarizes this development from the perspective of data storage and application.

Each individual level supports specific tasks in the corporation and serves to meet corresponding base technologies and methods in the development of concrete systems. The difficulties at the higher levels not only lie in overcoming technical complexity (heterogeneous systems, various norms and standards, differences in languages and interfaces, discretion in system purpose and user groups). More and more, completely new perspectives arise such that conflicts occur between the aims and the underlying levels. At level 4 (knowledge management), matters are compounded because the technology implemented in no way has to be limited to data or data bases; rather this aspect might be relegated completely into the background. Along with the classical modeling of data structures (e.g. a data model in entity-relationship notation), the design and support of dynamic processes (e.g. the process of creating information or the process of changing knowledge) and the support of organizational learning processes are gaining importance in the realm of computer science. Practice clearly shows that it is precisely here where the chances and potentials lie, and that innovative businesses meet this challenge with groundbreaking projects that are already underway.

level/name / type of system/focus
4.knowledge management / organizational memory system
3.information as a resource, information management / Executive information system, management information system, decision support system
2.data management / enterprise-wide data architecture
1.file and data organization / data system, data base system

Figure 4: Developmental levels regarding the handling of data, information and knowledge in businesses

No direct hierarchical relationship exists between the levels shown in figure 4. Rather it represents an idealized conception that results from chronological development. Hence at least partially, most concepts simply build upon each other.

2.Organizational Memory

2.1.What is meant by “organizational memory”? - origin and context of the topic

Today it can be assumed that organizational memories exist – whether as construct or concept. Hence, the question is to what extent is an organizational memory accessible as an active structure and which instrumental results can be achieved with it? Of special interest is what the contribution of information technology means or could mean: Can cultural changes and the mobilization of creative forces be supported by technology? This question can be addressed along with the question of the function and meaning of OMS and will be addressed in more detail in the next section.

The necessity of addressing the question of knowledge, know-how, etc., as well as dealing with the issue of information and knowledge management in business results from the intricate relationship of knowledge and negotiation or, in other words, knowledge and decision making. For the following context, a very broad concept of knowledge is assumed. By applying and developing the existing theories further, the foundation for a system capable of “evolving” into actual practice should be established. Organizational memory systems are put into place to cope with related tasks. They are the (technical) realization or support of those segments of an organization that are labeled “organizational memory”, and are always present in principle, even without technical support.

Talk about the existence of organizational memory has a longer tradition than one might at first suspect. Traces can be found as early as the end of the 19th century. However, at the beginning of the 20th century interest was lost. The topic was almost completely forgotten, despite psychology’s close relationship to organizational memory and the spectacular theories being developed in the fields of cognition, memory, information processing and artificial memory (cf. Wegner 1986, 185). This will be discussed in greater detail later.

Human memory is often used as model and metaphor for the organizational memory. Comparing characteristics of individual and organizational memories the following differences seem to be important:

MetaphorNameFunctions and Examples

MachineStorage-Erasing the contents of memory requires external actuation

-Data can be called up, duplicated, or recovered