Adaptive processes for knowledge creation in complex systems: The ...

Information & Management 43 (2006) 530–540 www.elsevier.com/locate/dsw

Adaptive processes for knowledge creation in complex systems: The case of a global IT consulting firm§ Karma Sherif a,*, Bo Xing b,1 a

Texas Southern University, Jesse H. Jones School of Business, Information System, Houston, TX 77004, United States b Rawls College of Business, Texas Tech University, Lubbock, TX 79409-2101, United States Received 31 January 2005; received in revised form 5 September 2005; accepted 12 December 2005 Available online 20 February 2006

Abstract Knowledge is becoming more important as the foundation of a resource-based theory of the firm but the process of knowledge creation is still neglected. There is no clear understanding of the processes that an organization should adopt to create new knowledge. Drawing on complex adaptive theory, we developed a holistic process to provide a means for knowledge creation; based on the properties of CAS, multiple level processes for knowledge creation were identified. Data collected from a leading multinational IT consulting firm was used to illustrate how the proposed processes were implemented. # 2006 Elsevier B.V. All rights reserved. Keywords: Complex adaptive systems; Knowledge creation; Knowledge management; Processes for knowledge creation

1. Introduction During the last decade, knowledge became the foundation of a new theory: the knowledge-based theory of the firm [11,34]. Unlike the economic and the organizational theories, this asserts that knowledge and its management are the only sources of sustained competitive advantage [2,11,16,22,31]. Advocates of knowledge management (KM) claim the new theory supports organizational learning, organizational innovation, management of business relationships, and adaptation to environmental stimuli [10,13,35,37]. KM is used to develop a systematic set of processes for the creation, organization and dissemination of knowledge, using different technologies and supported by §

This study is funded by a research grant from the Rawls College of Business. * Corresponding author. E-mail addresses: [email protected] (K. Sherif), [email protected] (B. Xing). 1 Tel.: +1 806 742 2397; fax: +1 806 742 2397. 0378-7206/$ – see front matter # 2006 Elsevier B.V. All rights reserved. doi:10.1016/j.im.2005.12.003

a knowledge-creating and a knowledge-sharing culture [14,15]. The dynamic interactions are defining features of a KM program. Today, organizations are reaping huge benefits by aligning KM with business strategy and utilizing it as the mean to improve core business processes [4]. Processes for KM include capturing, sanitizing, packaging, categorizing, storing, disseminating, and sharing knowledge. An organization may focus on one depending on the type of knowledge and the degree of change that renders knowledge assets obsolete [24]. Tacit knowledge (soft knowledge) is best leveraged through social interactions [23,35] whereas explicit knowledge (hard knowledge) can be codified, captured, and disseminated electronically [41]. Organizations that operate in a highly volatile environment tend to attach more importance to experimentation [20] and the synthesis of specialized expertise rather than on knowledge transfer [40]. Different organizational factors are believed to facilitate knowledge creation, some are part of a

K. Sherif, B. Xing / Information & Management 43 (2006) 530–540

systematic approach others more driven by intuition [7,8,39], but organizational learning is an inherent trait of only some organizations. Most prior studies have identified factors without attempting to formulate a holistic model of how organizations can create new knowledge:  Argote et al. [5] offered an integrative framework for KM and identified investment in human capital, rewards and incentives, experimentation, and informal networks as enablers of knowledge creation.  Adler and Clark [1] were among the first to define behavioral processes that gave rise to learning curves. They explored the effect of recursive learning where experience led to induced learning such as changes in engineering design and training, which positively affected innovation and productivity.  Ethiraj and Daniel [18] suggested that modularization of the organizational design paved the way for innovation through parallelism and effective recombination, however no details were given on how organizations could recombine knowledge and no empirical testing of the model was attempted.  Hill and Matusik [25] hypothesized that a moderate use of external technical expertise (contingent work) had a positive effect on the creation of firm-specific and public knowledge. No empirical testing of the model was given.  Sommer and Loch [43] emphasized trial and error learning and ‘‘selectionism’’ of innovation and reported the superiority of trial and error learning when faced with unpredictable uncertainty. While these studies have been useful, we still lack understanding of the detailed processes involved in knowledge creation. The identification of factors has only defined the antecedents of learning, but not the complex process that results in knowledge creation. We are led to believe that knowledge creation is an inherent trait of some organizations [17] but that the majority of organizations fail to achieve it. The majority assume that the process cannot be captured. Nonaka [36] identified four organizational processes that support the creation of new knowledge: socialization, internalization, externalization, and combination. According to this theory, an organization creates new knowledge when individuals share tacit knowledge, reexperience what others did and absorb the tacit knowledge through learning-by-doing or observation (internalization), express the knowledge into a comprehensible explicit form (externalization), and integrate different pieces to create novel ideas. The theory

531

does not, however, describe how to initiate the microlevel processes for individuals or groups to manage the knowledge and be innovative. 2. CAS and the process of knowledge creation The study of complex adaptive systems (CAS) was introduced by the Santa Fe Institute in an attempt to provide a new perspective to the dynamics of complex systems. A CAS is composed of many interacting agents that are diverse in form and ability [12]. The system derives its internal complexity from the diversity of, and the level of interaction between agents. The larger the number of agents and level of interaction between them, the harder it is to predict the system’s behavior. Interacting agents, collectively and non-linearly, determine the characteristics and behavior of the CAS [26]. An example is found in a stock market where investors and traders are reacting to several stimuli (news, market index, and other agents’ behavior) at the same time. Though they act according to their own best interest, they collaboratively cause the market to change in a relatively unpredictable fashion. The environment may be another source of complexity for an adaptive system. It dictates changes and influences the choice of strategies available [6,27]. The degree of change defines the fitness landscape of a CAS and the degree of interdependency between agents in the system. This fitness landscape represents an imaginary grid with points representing possible courses of action. The height of each point denotes the fitness of each course of action. A CAS is always in pursuit of the highest peak [30]. Smooth landscapes are characterized by stability and predictability. The smoothest has one peak that defines the optimum performance, and thus, it is relatively easy for agents of the CAS to locate it. A CAS with a smooth landscape tends to exploit internally formulated rules to adapt to the environment. A rugged landscape, on the other hand, has many peaks. The behavior of a CAS is then highly unpredictable, because the peaks ‘‘buck and heave’’ in response to changes in the environment. The interaction between agents may also change the structure of the landscape. The broad but loosely structured coalition of agents simultaneously explores different points. The process of parallel exploration makes it easier to incorporate new information, which may cause the height of peaks to change relative to one another. Parallel exploration also makes the CAS less susceptible to change in the environment.

532

K. Sherif, B. Xing / Information & Management 43 (2006) 530–540

On both, smooth and rugged landscapes, the agents continuously search for ways to improve the local fitness and never settle on the existing peak, a common attitude described as ‘‘never good enough’’. The cyclical disruption of the landscape is an integral part of the make-up of complex systems that prevents premature lock-in to inferior points. 2.1. The process of knowledge creation in CAS CAS creates new knowledge when it recognizes the relationship between a stimulus and a certain response [21]. The CAS interprets situations in the context of patterns it has previously used in order to adapt to the environment. Even in cases of extreme uncertainty, the CAS will attempt to impose one of its prior patterns to solve and manage a chaotic situation. The process of knowledge creation in CAS is governed by a number of mechanisms. Tagging is one that allows agents to interact with one another. Depending on the tags attached to an agent, others may initiate a request for collaboration to perform complex tasks [3]. In an ant colony, for example, an ant has highly stereotyped behavior and can hardly survive through any dramatic change. The ant colony, on the other hand, is highly adaptive and can survive through a wide range of hazards. In addition to capturing experience, agents establish different relationships between the rules. Agents may link, aggregate, and generalize rules to improve their performance. Rules may be associated with others to respond to complex triggers in an environment. Agents may also aggregate rules that are consecutively applied. Instead of generating new rules for situations that differ only slightly, agents generalize similar rules to be used as rules of thumb in similar situations. Credit assignment is another mechanism whereby agents avoid being trapped in a solution space that outlives its value-generating span. During this process, the rules act as competing hypotheses that undergo test and confirmation. Rules compete on their level of accuracy and specificity. The value of a rule depends on its ability to identify a specific response for a certain stimulus and improve fitness. The exploitation and exploration of rules is another important mechanism for improving fitness. Exploitation depends on the ability of agents to capture past experience and induce rules from recurring patterns. It entails the reuse of intelligent rules that emerged in prior interactions. The rules serve as strategies that define responses for the different stimuli triggered

internally or externally. As agents encounter new situations, rules may be revised or replaced. Agents make long jumps to neighboring settings to explore new rules. These are possible when the agents within the system are loosely coupled and can explore knowledge in neighborhood settings. Through exploration and space probing, the CAS avoids being trapped on a local peak. In scientific research, many breakthroughs were discovered by drawing on disciplines from similar fields. The four mechanisms shed light on how learning and innovation is carried out in complex systems. Applying these to organizational settings takes KM efforts to a new level by supporting organizational learning and emergent innovative behavior [32]. 3. The theoretical model Organizations are pressured to be more responsive to change and are expected to learn to adapt and reconfigure to respond to new demands. They have multiple interdependent units in which information processing and decision-making is decentralized. The different specialized agents operate at different levels and their interaction generates a non-linear behavior that cannot be predicted from the behavior of the individual agent. The agents interact and self-organize in an attempt to achieve higher performance levels and improve organizational effectiveness and competitiveness. 3.1. Knowledge creation in organizations Knowledge creation usually involves three phases: a mechanism of introducing variation to already existing knowledge, a consistent selection process, and a mechanism for preserving and reproducing the selected variations [9]. Like a CAS, a core challenge of organizations is to integrate and synthesize different specialized knowledge in an innovative way. While some argue that the exploitation of already existing knowledge adversely affect innovation, organizational innovations are iterative and build on already existing wellsprings of knowledge [29]. The creation of new knowledge will depend on the processes involved in packaging knowledge assets to facilitate their recombination and cross-fertilization across domains. The knowledge workers who create, make sense of, and use the knowledge assets are agents of the CAS. They capture knowledge gained from the different projects and store it in organizational repositories. When faced with new problems, agents asses their stock

K. Sherif, B. Xing / Information & Management 43 (2006) 530–540

of knowledge and identify assets that are closest to meeting a new requirement. The organizational repository has a fluid structure in which assets are added, deleted, and restructured continuously. The knowledge workers manage different knowledge assets, which differ in specialty and structure. In a software developing company, for example, the knowledge assets can be deliverables of a project, best practices for developing accounting systems, and standards for developing the user interface. Each, obviously, has a different purpose and represents different levels of abstraction. The development of best practices and standards and methods is only possible after the organization has captured several of its experiences in a specific domain. For creation of new knowledge, relationships between the assets must be defined. Knowledge workers need to push knowledge assets outside their domain of origin and challenge the thinking of the professional communities; this is abrasive creativity. The transition of knowledge across boundaries is likely to create friction between the different schools of thought and generate new perspectives and produce new knowledge. The destruction of older ideas should be cyclical rather than anecdotal and motivated by a commitment to create a learning organization. A representation of the theoretical model is shown in Fig. 1. 3.2. Tagging The ability of the organization to exploit its past depends on its ability to recall it. Organizations need to tag knowledge assets to identify the domain of interest, their specific functionality, and level of abstraction. A

533

knowledge asset may be a generalization or a specialization, e.g., a knowledge asset may be absorbed by another, like a description and diagram that are parts of a model. The aggregations can be composite or shared. Thus a knowledge asset may exist as a part in more than one aggregate. By drawing relationships between knowledge assets, organizations can create new knowledge from codified assets in a repository. Building relationships is only possible if the knowledge assets are dynamically tagged. 3.3. Relationships (association, aggregation, generalization and specialization) During its lifetime, an organization accumulates a huge number of knowledge assets. Capturing every experience may not add any value if the knowledge does not result in a change in behavior to improve performance. Thus new knowledge needs to be linked to other knowledge in the repository, possibly becoming part of a hierarchy of knowledge assets, a case of aggregation; or it also may provide more insights into a process by providing more details, an example of specialization; or it may abstract knowledge into an information schema [33,44] to increase the level of reuse across domains, a case of generalization. Without synthesis of knowledge, the creation of value from captured experiences is dubious. Accordingly we propose: Hypothesis 1. Establishing relationships between the knowledge assets will facilitate the creation of new knowledge. Hypothesis 1a. Aggregating knowledge assets for the development of complete solutions will facilitate the creation of new knowledge. Hypothesis 1b. Abstracting knowledge assets into generalized assets will facilitate cross-fertilization of assets across domains and the creation of new knowledge. Hypothesis 1c. Creating multiple versions of the same knowledge assets that differ in specificity will facilitate recombination of assets and the creation of new knowledge. 3.4. Credit assignment

Fig. 1. Processes for knowledge creation in organizations.

The ability of organizations to create new knowledge from existing assets requires a rigorous evaluation of its knowledge base [28]. Feedback should be collected on the knowledge workers’ perception of the strength and

534

K. Sherif, B. Xing / Information & Management 43 (2006) 530–540

specificity of the assets. Only fit knowledge assets should be stored. Fitness depends on the ability of the knowledge asset to support reuse in solving a problem. As time passes, some knowledge assets may become outdated and thus removed or replaced. Rules may not hold in certain conditions, confining their fitness to specific domains. Assigning credits to the various knowledge assets within a repository will motivate knowledge workers to provide feedback to prevent low quality assets from receiving credit. We propose: Hypothesis 2. Assigning credit based on feedback collected on the performance of knowledge assets will facilitate the reuse of assets and the creation of new knowledge. 3.5. Exploitation and exploration Exploitation and exploration are processes that organizations utilize to solve problems. An organization may decide on whether to solve a problem by exploiting knowledge embedded in its prefabricated knowledge assets or by exploring new ideas. organizational researchers and practitioners have favored exploration over exploitation, arguing that knowledge is a flow rather than a stock [38,42]. To a large extent, the process of innovation is incremental and significantly relies on old knowledge. The greater the diversity and scope of the knowledge assets, the higher the possibility of generating new knowledge [19] through aggregation, specialization, generalization, or cross-fertilization across domains. The process of creating new knowledge requires that organizations engage in creative thinking and reflection on past experience. Comparisons of similar assets may result in eliminating redundancies or declaring some as specific to certain conditions. Higher benefits can also be achieved from the cross fertilization of ideas across domains. Like a CAS, an organization needs to conduct scrupulous parallel experiments to ensure the applicability of knowledge borrowed from neighboring domains. A series of experiments are needed to determine a proof of concept. Experts within the application domain should be involved in the evaluation of ideas borrowed from neighboring domains to reduce risk of loss. We thus propose: Hypothesis 3. The exploitation of knowledge assets within domains and the exploration of knowledge assets across domains will facilitate the creation of new knowledge.

4. The research method Given our limited understanding of the knowledge creation processes, we adopted an in-depth case as our methodological premise to help in hypothesis formulation and model building. Our case study approach traded generalizability for the opportunity to observe knowledge creation processes in action. The data was provided by an intensive study of a global IT consulting firm, which, to preserve its anonymity, will be referred to as Global Consult. It operates in more than 30 countries with about $ 8 billion in annual revenues for the year 2002. The company provides technology solutions to six industry sectors: manufacturing, retail, and distribution; energy utilities and chemicals; life sciences; financial services; telecom and media; and public services. Their mission is ‘‘to help clients improve business performance in a volatile environment’’. Each sector is compartmentalized into a number of service lines that encapsulate the different IT divisions. The research site was identified from the KM literature. Global Consult, the recipient of several awards in KM, is recognized for its practices and its System K-NET. The importance of managing knowledge became obvious to them and a KM program was initiated in the early nineties to preserve and capitalize on corporate knowledge. According to the chief knowledge officer of the Americas region the program was perceived as: ‘‘The harnessing of the right processes by the right people using the right technology, to help an organization understand what it does well and what is sub-optimal, and to benchmark those [processes] against other parts of its own organization and the marketplace.’’ The KM program integrates people, processes, technologies and strategies for capturing knowledge and deploying it across the organization. It is believed to save the company millions of dollars and is credited for creating a global culture. As explained by the telecom sector knowledge officer in the Americas: ‘‘It enables us to chase valuable information from the consultants. When they come into the firm, the KNET is the first they see and we tell them we expect them to use it. We also expect when you do a great job and you’ve got an outstanding deliverable that you have given to our client, that you’ll submit it to the repository. . . . I think the K-NET put the responsibility or a big part of it back onto the

K. Sherif, B. Xing / Information & Management 43 (2006) 530–540

consultant and make them accountable. Really getting the word out to them through the K-NET is important.’’ The infrastructure for the K-NET was based on Lotus Notes1. In 1992, Business Week rated it as one of the best tools in the area of KM. A portal for K-NET was developed to provide homogeneity for all the KM systems, allow both passive and interactive communication with the users seeking access to the content, and make it possible for users to navigate, search, and retrieve details that are of interest and relevant. The portal can route users to internal communities or third party information service providers, which can provide information on a subscription basis through contracts with various content aggregators, such as the Gartner Group. Though consultants submit documents once to the repository, the deliverables may appear in different places. Once submitted, the documents appear on the KNET. Another possible location is on the community home spaces, created for special interest groups. After being audited, the document may also be listed as one of the best practices, or lessons learnt, from actual engagements. Some best practices are aggregated and further abstracted into a set of methods and techniques. In addition, electronic communication tools enable a variety of synchronous and asynchronous communication. Users are able to communicate asynchronously using email and discussion boards. Video conferencing, chat rooms, and instant messaging enable synchronous rich communication for complex problem solving. Participants were interviewed and asked about their perceptions and beliefs about the K-NET. This strategy seemed more likely to surface positive as well as negative attitudes. We followed the positivist perspective in developing and then assessing a research model, examining how well it corresponded with the experiences of actors associated with the KM program at Global IT. We restricted our data collection and analysis to our theoretical foundation and the a priori set of constructs in the proposed research model. Thus, the units of analysis were the discrete statements, extracted from interview data, about the different processes that the company adopted to facilitate knowledge creation. We conducted 22 interviews: we sliced vertically through the organization, using knowledge workers at various hierarchical levels. The sample included four top managers; three project managers, and seven consultants within two sectors: oil and gas and telecommunication. From the KM side, we interviewed the chief knowledge officers (CKO) for the company as

535

a whole and for the Americas, the knowledge managers for the telecommunication and the oil and gas sectors, and four librarians who worked at the project level. All interviews were conducted by one of the authors. The questions were open-ended questions to allow the participants to express freely their ideas. The questions were:  Explain your current role within the organization and the type of tasks you are charged with.  How do you proceed doing your work?  What are the tools that you believe contribute the most to your learning of new knowledge?  What does the organization do to facilitate the process of learning new knowledge?  What changes would need to be in place for existing tools to be effective contributor to learning of new knowledge? Interviews lasted from 45 to 90 min and were recorded. The study took 6 months from July of 2001 till January of 2002; we visited the company seven times. The data analysis started with transcription of the recorded interviews. In total, over 200 pages of interview data resulted. Content coding was performed using QSR N5 software, which allows researchers to categorize text to one of four high-level categories (tagging, relationships, credit assignment, and exploitation and exploration). In addition, interviewee comments were searched for statements linking knowledge creation processes to higher productivity and profitability. Organizational barriers to knowledge creation were also identified. The two co-authors individually coded interviews and discussed discrepancies. 4.1. Global consult KM processes Global Consult has designed a structured set of processes around KM. These deal with ways to infuse knowledge gained through experience into all stages of project development in order to streamline the company’s ability to respond to customer requirements. Standards exist at different levels; from the project to the organizational to ensure that knowledge is shared within and across projects, sectors, and regions. An important process that reinforces knowledge sharing is the expectation that all client deliverables must be stored in the knowledge repository. In addition, project members are asked to describe new information they learned on the project: the type of data they used, they way they manipulated the data, and what worked for the

536

K. Sherif, B. Xing / Information & Management 43 (2006) 530–540

client. As such, Global Consult transfers knowledge to the organization as evident from the quote: One person per project is in charge of posting project deliverables onto the repository. They hit that button and it generates an e-mail to Anne where they fill-out the categorization fields and attach the document. On a weekly basis the knowledge manager goes in and makes sure it has been categorized correctly and the document has been zipped. He just makes sure it has been submitted according to all the standards and guidelines. 4.2. The process of tagging The tagging of knowledge assets is considered critical for the reuse and integration of knowledge assets to solve different problems. Assets within the repository are categorized along several dimensions: the author, project, client, and type of asset. This enables the consultants to determine the relevancy of an asset with respect to a particular context as evident in the following quote: We’ve got to put tags on that content in a way that it’s retrievable, in a way that makes sense as to how we do business. When you’ve done a particular type of project, creating particular set of deliverables to a particular type of client, then you want to be able to hand this next person a path or a navigational metaphor or structure so that they can find what they are looking for and its is meaningful to them they can reuse it with a slight change. The knowledge assets take several forms: documents, presentations, demonstrations, and software products. The process of submitting documents to the repository starts by the consultant emailing a deliverable to a knowledge manager after stripping customer proprietary information from the deliverable. The consultant also attaches a form to categorize the asset within the knowledge repository. It is the consultant’s responsibility to define the asset by associating it with one or more keywords. The taxonomy is as dynamic as the repository itself, with keywords added by the knowledge managers. The idea is to facilitate the process of retrieving relevant documents for a consultant working on an engagement in a particular sector for a particular service line. A knowledge manager in the telecom sector explained that: ‘‘You cannot just willy-nilly grab content and throw it into a big pot and then hope that it can be reused. Obviously, you’ve got to put tags on that content in a

way that it is retrievable. You have to be able to provide the knowledge contributor with the analog on the front end, so that they can categorize and catalog their knowledge in a way that makes its meaningful for the person who is now coming and going to repeat it all. As the taxonomy gets more sophisticated, it becomes easier for the knowledge reuser to retrieve but harder for the knowledge contributor to categorize. It is important to balance the ease of search and retrieval with the difficulty of categorization before creating new tags. In addition, tags play an important role in the recombination of assets and the emergence of new ones. Knowledge managers in charge of a service line or sector use them to determine relationships between knowledge assets. These are also forwarded for review to competency leads, who are experts that specialize in a service line and are the knowledge leader in that area. They are the best person to assess the value of a knowledge asset within their subject domain. They use the tags to determine if a new deliverable needs to be integrated or simply associated with other knowledge assets. The relationships are critical given the multitiered nature of developing knowledge. 4.3. Relationships among assets in the repository Global Consult believes that the content of a knowledge asset has great business value, thus the relationships between the assets are important. Several relationships are drawn among assets in the K-Net. The content of the repository is continuously filtered to decide what project deliverables should be promoted as best practices for the whole sector. These are organized in ‘‘launch kits’’ or ‘‘power packs’’ and are considered to be best of breed. A sector knowledge manager who oversees projects within a whole business unit undertakes the process of building a power pack by aggregating deliverables from different projects and picking out the best. Launch kits are also reviewed and approved by competency leads. Consultants are periodically notified of new launch kits that are developed within their industry and service lines. In an effort to recreate its success across sectors, Global Consult organizes its sector-specific best practices into organizational best methods and techniques. The process involves abstracting specific lessons learnt into general standards and guidelines. One of the consultants demonstrated how to locate an abstract knowledge assets (method) and how it was interlinked to specialized examples

K. Sherif, B. Xing / Information & Management 43 (2006) 530–540

‘‘You go to this site that have the method and you click on the phases and read about the phases, you read about stages, and it shows what work products and what deliverables come out of those activities and stages. You can click on that and it will bring up the best examples of those deliverables and work products . . . it is a lot of collaboration of a lot of projects because we put all these together . . .. There is a lot of experience at that table.’’ In addition, there are models that can be used to generate specific values for industry related problems that consultants use when preparing bids. These models are the abstraction of the best functions used to estimate cost. Global Consult also incorporates external knowledge and links it to knowledge created within the organization as follows: Say you have someone on the Exxon Mobile team, and they need to keep up with what’s going on with Exxon Mobile, so we set up a search term for them and we tie it into our Dow Jones service that we use and everyday, Dow Jones uses that search term that we put in there and dumps these articles about Exxon Mobile into a profiling container so the team member can use it. They don’t have to go to Dow Jones, they don’t have to look through 50 different articles, they go right here and they see right here, here’s the 10 articles that came in today about Exxon Mobile. 4.4. Credit assignment Global Consult promotes the sharing and reuse of knowledge assets through a structured process of seeking feedback on the performance of assets. The company interjects communication through routine sessions where knowledge managers seek the direct feedback of consultants on assets reused on projects. The repository automatically tracks and analyzes statistics on its assets. Both qualitative and quantitative data are utilized to plan updates to the assets as well as the structure of the repository. Any changes made to a knowledge asset or to the structure of the repository must be approved by both the knowledge managers and the competency leads to ensure consistency and accuracy. Data on the performance measures of assets are used to credit both the assets and their creators. In addition, competency leads ‘‘review documents, and say whether they think it is considered the best example of this kind of document.’’ The data is also used in the biannual employee review to assess the knowledge sharing behavior and creation of value. Global Consult believes

537

that an assessment of knowledge sharing promotes the receptiveness and readiness of members to contribute to the knowledge pool. Global Consult believes that feedback and credit assignment allow them to learn and continuously improve on the quality of work delivered to the client. As the chief knowledge officer explains: ‘‘We are able to deliver more efficiently and with higher quality. Our margins of profit on engagement are increasing . . .. The consultant gets rewarded for their contribution. So, it’s a win–win situation.’’ 4.5. Exploration and exploitation Global Consult in its development standards insists that consultants start with the repository when preparing for an engagement, identifying appropriate tags that best describe the knowledge required to generate a solution. A knowledge manager may be assigned to the project to help the team identify assets that they can exploit. The knowledge managers perform researchintensive probes to locate the right information. The retrieval of knowledge assets start with the best practices. If searches do not yield any results, the consultants or the project knowledge manager go to a domain-specific repository to find appropriate knowledge assets. Consultants, occasionally, combine resources embedded in several knowledge assets to develop a customized solution for a client. Exploitation of knowledge, however, can never generate 100% of project deliverables but reuse enables Global Consult to evolve their knowledge assets: Every time we reuse these different documents that we collect from our different clients, at the beginning of a new project we have something in place to help facilitate what we do. It accelerates our time to market and nurtures our knowledge bit by bit . . .. Now, we are able to take it and spin it onto a global base. Using a global knowledge repository is also believed to be instrumental in the global exploitation of knowledge I think one of the benefits of the K-Net is you get things far outside your local area. Like if I call Paul, I’m probably just going to get a lot of things from Dallas and from the southern region. Where, if I was to type something into our knowledge base it’s processed nationally. And so I think that’s better. The degree of exploration will depend on the novelty of a client needs or of the technology used to implement the project. When new knowledge is created, the

538

K. Sherif, B. Xing / Information & Management 43 (2006) 530–540

company looks for ways to offset the learning cost and leverage the new knowledge across projects, sectors, and service lines. Their rationale drew on an analogy from the medical field. When we go into the hospital to get brain surgery, even if we have the most brilliant brain surgeon in the world and he or she is using some great new technique that they came up with, still I think we feel a little bit confident in the fact that we are actually now going to benefit from a thousand years of medical development. We are not sitting here with a single Einstein who has developed over in one night, brain surgery, so I think it’s an evolutionary thing and to be able to provide the next step in evolution you take and morph. Likewise, there are enough factors in where the customer is coming from, what their needs are, what their regulatory environment is, what their technology and Legacy systems that you have to work with and deal with, that you never get the same fingerprints and you will have to adapt. You will have to be creative and adapt. The customer is not looking for brilliant creativity; the customer is looking for a quality solution that will work, that has been proven to work. You never see anything original in Hollywood anyway so why should we be creative geniuses in the consulting business. The company has created the researcher role to aid consultants in exploiting existing knowledge and exploring new sources. Researchers assist consultants searching for knowledge assets from the repository and answering vaguely defined problems. Researchers conduct content consultations with their colleagues to make sure that the best path has been pursued. Much knowledge sharing takes place among knowledge managers. Knowledge managers have content leads that evaluate external knowledge resources and establish pointers to the new resources for specific domains. The searches are synthesized to allow higher level of reuse. Knowledge researchers strongly support sharing and reuse of knowledge probes: The first thing I do is go check that database to make sure that no one hasn’t already pulled that information before I go and start a whole new search. A process that supports exploration is monthly meeting where cross fertilization of knowledge assets across domains is discussed Knowledge managers who work for a particular sector or service line meet on a monthly basis, in many cases far more often than that. They meet with

their colleagues and counterparts in other sectors and service lines and explore together the different knowledge assets. The would say, hey, this is something that occurred on this engagement and this is something that if you brought to your sector or service line, you could be equally successful and here’s how it would help you. The balance between exploitation and exploration stems from the company’s belief that they primarily sell solutions and that their most important value is in experience, stability, and track record. 4.6. Organizational barriers to knowledge creation Several problems in Global Consult slowed down the processes of knowledge creation. The biggest, as seen by top officials, was the economy. With the depression and sudden down turn that have occurred, Global Consult focused its efforts on reducing cost per transaction. Resources were taken from programs that were not directly related to sales. As the chief knowledge officer explained: ‘‘When business is not good you try to reserve your cash and you try to reserve as many of your people to make themselves available out in the field.’’ Projects lost support for KM positions because it was difficult to get the client or firm to pay for a full-time knowledge manager. The pressure to move on to new projects also added to the problem. With new engagements, consultants felt pressured and had no time to review deliverables of consigned projects, remove client proprietary information, or deliver knowledge assets to the repository. As a result, KM involuntarily was sidelined. One knowledge manager believed that nurturing consultants to do KM was like ‘‘herding cats’’. All they cared about was their billable hours. They would not work on overhead tasks that did not appear on their time sheets. Formalities imposed by KM were also believed to be a constraint. Some knowledge managers believed that the processes actually turned away consultants, who felt that they should be given more control over the content that they submitted rather than removing all rights. As explained by one knowledge manager: ‘‘Effective KM really takes place at the constituent business groups. The very size of our organization and the number of different communities that have to use the same system has historically caused a certain amount of rigidity that I don’t think we need to suffer with going forward. You know, I think we could handle the diversity and could handle the size of our

K. Sherif, B. Xing / Information & Management 43 (2006) 530–540

company and the shear volume of knowledge, by relaxing some of these procedures.’’

539

when knowledge assets do not exist for new projects, they assert that the repository helps them to put things in perspective and avoid making wrong decisions.

5. Discussion 6. Conclusions The observations of the case study show the importance of defining a systematic process for knowledge creation. Processes used by CAS are mechanisms that organizations can use to facilitate the process of knowledge creation. Qualitative data collected from a global IT consulting firm illustrated how these processes are implemented and their effect on knowledge creation. Through the capturing of expertise, the tagging of assets, and the repeated cycles of knowledge reuse, the organization could find patterns which made it possible it to respond to change. Relationships among the knowledge assets, supported by tagging, allowed the organization to recombine assets in an innovative way and generate multiple solutions for problems. While aggregation increased the granularity of reuse, abstraction increased the level of reuse across the organization. The abstraction of best practices, for example, was a way to increase reuse of lessons learned. Credit assignment was another important mechanism to help avoid being trapped with a stock of knowledge that had outlived its value-generation span. Assigning credit to the different knowledge assets resulted in a productive disruption of the repository’s structure. The exploitation of simple and synergistically combined knowledge assets within a domain helped to speed the process of knowledge creation. Recombination created new knowledge and substantially improved performance through learning reinforcement. All four processes helped Global Consult transfer knowledge created at the individual level to the organization as whole. Consultants were allocated time to submit new knowledge that they gained while working on new engagements. Knowledge managers worked on the explicit knowledge, categorizing it and linking it to already existing documents. By establishing relationships, Global consult was able to create new knowledge. One important finding was the dissipative structure of a KM program. It required continuous work to sustain a pattern of interactions between organizational members so that new knowledge structures emerged. Global Consult has managed to create an all-encompassing, high quality, highly trusted, knowledge repository. Consultants believe the knowledge assets have facilitated the process of knowledge creation. Consultants now strongly believe that they should always capitalize on earlier experiences and systematically add to the collective body of knowledge. Even

We have defined processes for the creation of new knowledge within organizations using CAS as our theoretical framework. The processes focused on identifying attributes of each knowledge assets and drawing relationships between them, allowing their abstraction and recombination to create new knowledge. An important result of our study is that the capture and dissemination of knowledge is not enough in managing knowledge; organizations are constantly battling with change. But having a knowledge repository may actually stifle innovation as users may try to frame new encounters as old experiences and fail to see the need for change. Feedback loops can facilitate the process of updating the memory; getting rid of obsolete assets and shedding light on those with favorable outcomes. Applying assets outside their domain will help diffuse innovations across the organization. References [1] P.S. Adler, K.B. Clark, Behind the learning curve: a sketch of the learning process, Management Science 37(3), 1991, p. 167. [2] M. Alavi, D. Leidner, Review: knowledge management and knowledge management systems: conceptual foundations and research issues, MIS Quarterly 25(1), 2001, pp. 1–37. [3] P. Anderson, A. Meyer, K. Eisenhardt, K. Carley, A. Pettigrew, Introduction to the special issue: applications of complexity theory to organization science, Organization Sciences 10(3), 1999, pp. 233–236. [4] D. Apostolou, G. Mentzas, Managing corporate knowledge: a comparative analysis of experiences in consulting firms, Knowledge and Process Management 1999. [5] L. Argote, B. McEvily, R. Reagans, Managing knowledge in organizations: an integrative framework and review of emerging themes, Management Science 49(4), 2003. [6] M. Boisot, J. Child, Organizations as adaptive systems in complex environments: the case of China, Organization Science 10(3), 1999, p. 3. [7] S.L. Brown, K.M. Eisenhardt, The art of continuous change: linking complexity theory and time-paced evolution in relentlessly shifting organizations, Administrative Science Quarterly 42(1), 1997, pp. 1–34. [8] S.L. Brown, K.M. Eisenhardt, Competing on the Edge: Strategy as Structured Chaos, Harvard Business School Press, Boston, MA, 1998. [9] D.T. Campbell, Blind variation and selective retention in creative thought as in other knowledge process, Psychiatric Review 67, 1960, pp. 380–400. [10] W.M. Cohen, D.A. Levinthal, Absorptive-capacity: a new perspective on learning and innovation, Administrative Science Quarterly 35(1), 1990, pp. 128–152.

540

K. Sherif, B. Xing / Information & Management 43 (2006) 530–540

[11] K.R. Conner, C.K. Prahalad, A resource-based theory of the firm: knowledge versus opportunism, Organization Science (7), 1996, pp. 477–501. [12] G. Cowan, D. Pines, M.D. Complexity, Metaphors, Models, and Reality. Santa Fe Institute Studies in the Sciences of Complexity, Addison-Wesley, New York, NY, 1994. [13] T.H. Davenport, L. Prusak, Working Knowledge: How Organizations Manage What They Know, Harvard Business School Press, Boston, MA, 1998. [14] D.W. De Long, L. Fahey, Diagnosing cultural barriers to knowledge management, Academy of Management Executive 14(4), 2000, pp. 113–127. [15] K.C. Desouza, Facilitating tacit knowledge exchange, Communications of the ACM 46(6), 2003, p. 85. [16] K.M. Eisenhardt, F.M. Santos, Knowledge-based view of the firm: a new theory of strategy? in: A. Pettigrew, H. Thomas, R. Whittington (Eds.), Handbook of Strategy and Management, Sage, 2001. [17] K.M. Eisenhardt, S.L. Brown, Time pacing: competing in markets that won’t stand still, Harvard Business Review 1998, pp. 59–69. [18] S.K. Ethiraj, L. Daniel, Modularity and innovation in complex systems, Management Science 50(2), 2004, p. 159. [19] R.G. Fichman, C.F. Kemerer, The assimilation of software process innovations: an organizational learning perspective, Management Science 43(10), 1997, pp. 1345–1363. [20] A.D. Garvin, Building a learning organization, Harvard Business Review 74(4), 1993, p. 78. [21] M. Gell-Mann, The Quark and the Jaguar: Adventures in the Simple and the Complex, W.H. Freeman, New York, NY, 1994. [22] R.M. Grant, Toward a knowledge-based theory of the firm, Strategic Management Journal 17, 1996, p. 109. [23] M.T. Hansen, Knowledge networks: explaining effective knowledge sharing in multiunit companies, Organization Science 13(3), 2002, p. 232. [24] M.T. Hansen, N. Nohria, T. Tierney, What’s your strategy for managing knowledge? Harvard Business Review 77(2), 1999, p. 106. [25] C.W.L. Hill, S.F. Matusik, The utilization of contingent work, knowledge creation, and competitive advantage, Academy of Management Review 23(4), 1998, p. 680. [26] J.H. Holland, Hidden Order: How Adaptation Builds Complexity, Addison-Wesley, Reading, MA, 1995. [27] J.H. Holland, J.H. Miller, Artificial Adaptive Agents in Economic Theory, 1991. [28] K.C. Lee, S. Lee, I.W. Kang, KMPI: measuring knowledge management performance, Information and Management 42(3), 2005, p. 469. [29] D. Leonard-Barton, Building and Sustaining the Source of .Innovation, Harvard Business School Press, Boston, MA, 1995 [30] D.A. Levinthal, Adaptation on rugged landscapes, Management Science 43(7), 1997, p. 934. [31] A.P. Massey, M.M. Montoya-Weiss, T.M. O’Driscoll, Knowledge management in pursuit of performance: insights from Nortel networks, MIS Quarterly 26(3), 2002, pp. 269– 289. [32] M.W. McElroy, Second-generation KM: a white paper, Emergence 2(3), 2000, p. 90. [33] H. Mintzberg, Rounding out the manager’s job, Sloan Management Review 36(1), 1994, p. 11.

[34] J.A.Z. Nickerson, R. Todd, A knowledge-based theory of the firm—the problem-solving perspective, Organization Science 15(6), 2004, p. 617. [35] I. Nonaka, The knowledge-creating company, Harvard Business Review 69(6), 1991, p. 96. [36] I. Nonaka, A dynamic theory of organizational knowledge creation, Organization Science 5(1), 1994, p. 14. [37] I. Nonaka, The Knowledge-Creating Company: How Japanese Companies Create the Dynamics of Innovation, Oxford University Press, New York, NY, 1995. [38] E. Ofek, M. Sarvary, Leveraging the customer base: creating competitive advantage through knowledge management, Management Science 47(11), 2001, pp. 1441–1456. [39] W.J. Orlikowski, D.J. Hofman, An improvisational model for change management: the case of groupware technologies, Sloan management review 38(2), 1997, pp. 11–22. [40] J.B. Quinn, P. Anderson, S. Finkelstein, Managing Professional Intellect: Making the most of the best, Harvard Business Review, 1996 (March–April). [41] W. Skok, C. Kalmanovitch, Evaluating the role and effectiveness of an intranet in facilitating knowledge management: a case study at surrey county council, Information and Management 42(5), 2005, p. 731. [42] D. Snowden, Complex acts of knowing—paradox and descriptive self-awareness, Journal of Knowledge Management 6(2), 2002, p. 100. [43] S.C. Sommer, C.H. Loch, Selectionism and learning in projects with complexity and unforeseeable uncertainty, Management Science 50(10), 2004. [44] S. Wang, G. Ariguzo, Knowledge management through the development of information schema, Information and Management 41(4), 2004, p. 445. Karma Sherif is an assistant professor at the Rawls College of Business, Texas Tech University. She received her PhD degree in management information systems from Texas A&M University. She also holds an MS degree in MIS from Texas A&M and a BA in business administration from The American University in Cairo. Before pursuing her doctoral studies, Karma worked as an information systems consultant at DATACOMP, a leading IT consulting firm. Karma has articles in journals such as MIS quarterly, decision support systems, journal of the association of information systems, information and management, and journal of knowledge management. She has taught courses on object-oriented programming, electronic commerce, systems design, knowledge management systems, and MIS research methods. Bo Xing is a PhD candidate in area of information systems and quantitative sciences, Jerry S. Rawls College of Business Administration, Texas Tech University. Prior to joining the PhD program in 2002, he worked as an IT consultant and team lead in US, mainland China and Hong Kong for 6 years, concentrating on telecom billing system and e-commerce platform design and implementation. In 2002, Mr. Xing also worked as IT outsourcing manager in The World Bank Group, Beijing, China.