The Maturity Model, Essay Example

The maturity model offers a compelling template for the integration of a KMS with another e-system, in this case an IS. The integration takes place as the organization progresses, or ‘matures’, through a series of four clearly-defined stages of developmental maturity; at every level, five common elements are used to assess the maturity of the organization. Coupled with action research, the maturity model offers a compelling and clearly-defined template for the integration of a KMS with another e-system, one that produces effective organizational cohesion and increased productivity.

Following Schwartz and Tauber (2009), the method I have chosen is a maturity model for integrating a knowledge management system (KMS) with an information system (IS) (p. 59). As Schwartz and Tauber explained, developing information systems faces a major challenge, “when one begins to take into account the need to integrate classic structured information systems with the types of knowledge management systems that deal with unstructured information” (p. 59). Accordingly, the maturity model is designed to reflect “how the development organization matures towards integrated systems development” (p. 59). Maturity models are “closely related to Stages of Growth Models which… can be used to describe organizational phenomenon (sic) including… Information Systems Planning, Organizational Life Cycle, and Product Life Cycle” (p. 59). To date, maturity models for KMS have primarily focused on “understanding the maturity of the organization in terms of specific knowledge areas”, including “knowledge sharing… knowledge engineering… and knowledge capabilities” (p. 60).

Schwartz and Tauber (2009) argue for the existence of “identifiable stages of maturity that an organization goes through in developing its capabilities to produce and field integrated IS/KMS systems” (p. 60). This emphasis on stages is the defining characteristic of maturity models: the stages trace the evolution of the organization from its initial, immature stage, to a final, integrated stage (p. 61). Simply put, a maturity model delineates a number of “distinct, repeatable, and identifiable stages” in this evolution or adoption process, from beginning to end (p. 61). The stages are each defined in terms of specific characteristics, including “the existence of certain procedures, rules, norms, activities and other aspects related to the area being modeled” (p. 61). Maturity models map out these stages, defining each, in order to give an organization metrics for the success of implementation (p. 61).

As Schwartz and Tauber  (2009) explained, in order to understand maturity models one must understand “the difference between an immature and mature organization” (p. 61). Immature organizations feature processes “related to the area of concern” which are “generally improvised by practitioners and their management, using ad hoc procedures leading to only periodic heroic success” (p. 61). In other words, the immature organization is not characterized by an effective knowledge management system, at least in the area under consideration. The organization’s endeavors in the area under consideration are improvised, designed on the proverbial fly as stop-gap measures. The immature organization may have plenty of information, plenty of data, but it does not have effective access to knowledge; it does not manage its knowledge in order to design processes and increase process efficiency. Processes may be specified in the immature organization, but if so they are typically “not… enforced or followed rigorously, and management is reactionary dealing more with fire-fighting than proactive planning and execution” (p. 61).

The contrast with the mature organization could not be the sharper, nor the clearer: in the mature organization, the processes in question are managed effectively (Schwartz & Tauber, 2009, p. 61). What, then, is meant by ‘managed effectively’? Simply that the organization has the organizational capability to effectively manage, guide, and direct the processes, in accordance with established procedures guided by effective working knowledge (p. 61). The mature organization communicates all of this to every single employee in an effective manner (p. 61). The processes that the mature organization employs and makes use of are “repeatable, defined, managed and optimized” (p. 61). When the mature organization follows these principles, it achieves the desired results, meeting its stipulated strategic organizational goals (p. 61). Every employee understands and accepts the “transparent roles and responsibilities related to the processes” in question (p. 61). The roles and responsibilities are transparent because the organization is a learning- and knowledge-based organization: every employee understands not only what they are supposed to do, but why they are supposed to do it. In the words of Schwartz and Tauber (2009), “such mature processes are followed because all of the participants understand the value of doing so, and the necessary supporting infrastructure exists” (p. 61).

What, then, is the path from the immature to the mature organization? Different maturity models delineate different steps; however, Schwartz and Tauber (2009) presented from Ferguson et al. (1996) “five common features that can be used to assess the capabilities at a given level of maturity”: the first is “commitment to perform”; the second, “ability to perform”, the third, “activities performed”; the fourth, “measurement and analysis”, and the fifth, “verifying implementation” (p. 61). The methodology used for the model is that of action research, which uses “the results from a cycle of interaction with the organization… as a basis for modifying certain actions, and then re-engaging with that organization” (p. 63). By contrast, the Case Study approach generally entails studies which “view an organization at a specific point in time and do not, in an interactive manner, influence the actions taken at the organization” (p. 63). The goal of action research, in contrast, is to modify the actions taken by the organization or other subject of interest; the result of “a number of action research cycles” is a more refined methodology (p. 63). Schwartz and Tauber (2009) applied the action research methodology “to a large military organization over an extended period in order to distill a new systems analysis methodology” (p. 63). In the process, they documented the “evolution of the organization through [its] stages of maturity” (pp. 63-64).

Regarding action research, Anderson, Bider, and Perjons (2004) explained that this methodology utilizes a combination of both “theoretical studies” and “an experimental work where the experimental part plays a decisive role” (p. 227). As a result, the theoretical findings are tested in practice. Anderson et al. explained that for knowledge management to be useful in an organization, “it should be seamlessly incorporated in everyday business activities” (p. 227). The challenge, then, is to create an integrated system, one that “supports both daily operations and knowledge management” (p. 227).

The organization chosen was the CIO Offices of the Israeli Navy, which “can be characterized as an early adopter of new technologies and methodologies” (Schwartz & Tauber, 2009, p. 64). The Israeli Navy functions as “the naval arm of the Israel Defense Forces, operating primarily in the Mediterranean Sea in the west and in the Gulf of Eilat, Red Sea, in the south” (p. 64). Schwartz and Tauber conducted a 5-year action research program, tracking “the maturity stages of the organization as it moved from the independent design and development of IS and KMS systems towards a fully integrated design and development process” (p. 64).

The Knowledge Management Systems Integration Maturity Model or KMSI-MM consists of “four maturity levels, each one of which carries a set of organizational capabilities” (Schwartz & Tauber, 2009, p. 67). In total, the four levels are: firstly, “Independent design and development” of the systems; secondly, “Post-development integration”; thirdly, “Independent design, coordinated development”, and fourthly, “Integrated design and development” (p. 67). Each of these levels entails particular roles, roles “that are identified or filled in the organization and key processes that are implemented” (p. 67). In the first level, Independent Design and Development, the IS and the KMS are designed and developed on “separate system analysis tracks” (p. 67). The tracks run in parallel, with “separate systems analysis teams working with different methodologies” (p. 67). In other words, the IS and the KMS are not integrated at all.

As Anderson et al. (2004) argued, operational knowledge “is structured around business processes, such as processing an order, insurance claim, or [dealing with a] bug in a software system” (p. 228). It therefore follows that both systems, the KMS and the e-system with which it is to be integrated, “should be process-oriented” (p. 228). If the organization is not process-oriented, it will be harder to practically introduce a KMS (p. 228). Moreover, for a KMS to function effectively and efficiently in practice, “a majority of the organization[‘s] staff [must] actually use the system in a major part of their daily work” (p. 228).

What Schwartz and Tauber (2009) found was that generally speaking, the IS track “worked according to classic IS development approaches that closely followed the structured information systems analysis methodology… or the object analysis methodology” (p. 67). Which methodology was utilized “depended primarily on the development history of the unit in question” (p. 67). According to Schwartz and Tauber, “a classic system analysis process” consists of six separate phases: firstly, “Initial problem/opportunity identification (including feasibility testing)”; secondly, “Study of the current system”; thirdly, “requirements discovery and analysis”; fourthly, “data modeling”; fifthly, “information modeling”, and sixthly, “process modeling” (p. 67). Both the IS and the KMS followed these specific phases on their respective, parallel development streams and systems tracks.

Anderson et al. (2004) explained that business processes can be modeled in a number of different ways (p. 229). First of all, any given business process “engages a number of participants, which can be divided into two categories: ‘passive’ and ‘active’ participants” (p. 229). Passive participants are affected by the process, but do not participate in it directly, actively: “for example, a document being written, an organization being reorganized, or a patient [being] treated in a hospital” (p. 229). By contrast, active participants, also known as agents, “are those participants that perform activities aimed at the passive participants” (p. 229). Moreover, both human beings and artifacts can fill these roles (p. 229).

All of this is important for an organization seeking the integration of a KMS and another e-system to be mindful of. The integration will necessarily affect many business processes, and the organization must be mindful concerning the effect that these changes will have on the various participants, both passive and active. There are four basic, common categories of business process modeling that touch on these concepts. Firstly, business processes may be modeled in terms of input/output flows: here, the focus “is on passive participants that are being consumed, produced, or changed by the activities” (Anderson et al., 2004, p. 229). Secondly, business processes may be modeled in terms of workflows: here, the focus “is on time ordering of activities performed by active participants” (p. 229).

Thirdly, business processes may be modeled in terms of agent-related workflows, placing emphasis on “agent cooperation, i.e., order in which active participants get and perform their part of work” (Anderson et al., 2004, p. 229). The difference between this and the previous method is simply the added presence of the agent (p. 229). Fourthly, business processes may be modeled in terms of state-flows: here, emphasis is placed on “changes produced by activities executed in the frame of a given process instance” (p. 229). These changes may involve changes in state for passive participants, “e.g., their form, shape, or physical location” (p. 229). On the other hand, certain other changes “may concern the state of active participants, e.g., a state of the mind of a human agent trying to find a solution for a complex problem” (p. 229). Anderson et al. (2004) explained that “the first three views are in essence type-oriented,” concerned as they are with the description of “normative behavior of business processes” (p. 230). On the other hand, the fourth approach “is instance-oriented and requires tracing the changes in the part of reality that concerns a particular process instance” (p. 230).

On the scale of the KMSI-MM, Schwartz and Tauber (2009) found that under the first element, “Commitment to perform”, neither team was committed “to creating an integrated system” (p. 67). There was commitment, to be sure, but it was “bounded within each team and system” (p. 67). Under the second element, “Ability to perform”, both groups did well: each “was competent and experienced in their own performance tasks” (p. 67). Under the third element, Activities performed, “each group conducted independent analysis and development cycles” (p. 67). Under the fourth element, Measurement and analysis, “each group independently measured and monitored its progress with no cross-checking or coordination with the other groups” (p. 67).

Under the fifth element, Verifying implementation, “each system was tested and verified independently” (Schwartz & Tauber, 2009, p. 67). In other words, the organization was immature in terms of its integration of its KMS with its IS: the two functioned as separate, parallel entities, rather than enhancing and informing each other, in accordance and alignment with the strategic aims of the organization. Indeed, Schwartz and Tauber characterized the two entities as “two separate systems, the KMS and the MIS” (p. 69). At this stage of the organization’s development, it lacked any “significant capabilities… that relate[d] to the desired integrated development” (p. 69). The only capabilities of importance were “the individual capabilities of each team in their own analysis domain” (p. 69). The lead roles included “systems analysts and top/expert users for the IS development track, and systems analysts and the CKO [Chief Knowledge Officer] for the KMS development track” (p. 69).

Level 2 of the model is Post-development Integration: as Schwartz and Tauber (2009) explained, “this level is characterized by integrating the two systems after they have been individually specified, designed, and developed” (p. 69). The main technique employed was that of coordination: “the human-computer interface (HCI) of the two systems” was coordinated, producing a kind of integration (p. 69). However, the authors were quick to note that in practice, “this integration is superficial and limited in its abilities to create a fusion system” for the simple reason that both systems, the KMS and the IS, “are already fully designed and developed” (p. 69). Integration has been achieved, but only in the most shallow and superficial sense: the two systems have been veritably cobbled together at this stage of the model. In fact, the systems analysis techniques employed at this phase “are the same as in the previous phase with no awareness to (sic) the post-development integration goals or needs” (p. 70). Lead roles are largely unchanged; the only difference of note is “the addition of required HCI expertise” (p. 70). Thus, at this stage the two systems are still precisely this: two separate systems (p. 70).

Level 3 is Independent Design, Coordinated Development (Schwartz & Tauber, 2009, p. 70). At this level, participants recognize that although “there are distinct design goals and methodologies,” the organization as a whole desires “an integrated fusion system… at an organizational level” (p. 70). Here, for the first time, there is a meeting of “narrow development and broad organizational goals” (p. 70). The organization is still growing, but it has attained some maturity. Accordingly, it undertakes an effort “to coordinate the different system designs in creating an integrated system” (p. 70). Integration is desired, integration is being sought, integration is undertaken. Here, at last, under the element of Commitment to perform, there is a “pre-design and pre-development commitment to the organizational need for an integrated system” (p. 70). The members of the different systems are at last actively trying to fuse, trying to integrate the two into one.

Under the element of Ability to perform, not only is “each team… skilled in its distinct analysis and design methodologies”, but “additional expertise in mapping distinct designs to a joint development process is apparent” (Schwartz & Tauber, 2009, p. 70). The organization as a whole is clearly evolving integrated organizational capabilities: it is beginning to fuse the two systems into an integrated system, and the signs are quite evident. Under the third element, Activities performed, both teams still do analysis in parallel; however, the distinct design documents that each team produces “are then analyzed to determine the required points of integration” (p. 70). From here, development is “planned so that the points of integration are created and dealt with as an inherent part of the development process” (p. 70). Now the organization begins to take an eye towards joint, integrated development as never before.

Under the fourth element, Measurement and analysis, each of the groups still independently measures and monitors “its design progress”; as a result, “upon completion of the designs another analysis cycle is required to produce the integration development plan” (Schwartz & Tauber, 2009, p. 70). The organization has become a hybrid between its former, immature self, and the more mature, integrated form into which it is evolving. Under the fifth element, Verifying implementation, “verification and testing is performed on a single integrated system” (p. 70). Although lead roles “remain the same as in previous stages,” there is a new and important development: “the teams are now integrated and work as if on a single project”, producing “an integrated system, the KM/MIS” (p. 70).

The fourth stage or level of the model is Integrated Design and Development (Schwartz & Tauber, 2009, p. 70). At this level, KM and IS are fully synchronized in both “design and development” (p. 70). System analysis phases at this stage “include integrating the knowledge items as part of the system analysis process, and adding the knowledge items into the… annotated charts” (p. 70). The organization is characterized by one common goal, namely “to achieve tight coupling between KMS and MIS by integrating knowledge items (or knowledge artifacts) into the organizational procedures that were handled by the information system” (p. 70). At this stage the organization has become vastly more cohesive and tremendously more efficient: it is no longer two separate organizations, but rather one single united, integrated organization (p. 70). All team members are “made aware that a ‘new’ type of analysis procedure is being followed and that addition[al] steps of divergence and convergence for the two system designs will be followed” (pp. 70-71). For the first time, the organization as a whole achieves “’just-in-time delivery’” (p. 71). Another key change that the modifications have produced is “the bifurcation of classic system analysis process into two tracks”: the tracks still run in parallel, but now there are “clearly defined points of intersection” (p. 71). At this stage, careful planning and synchronization will pay off, as “the work in the two tracks will be able to be done independently applying different tools and techniques,” yet still synchronously (p. 71).

Divergence is seminal to this model: as Schwartz and Tauber (2009) explained, “each phase begins by planning the KMS and the IS activities to be accomplished within this phase,” and then each track “is allowed to diverge and proceed according to its distinct IS or KMS methodologies” (p. 71). This is the ‘best of both worlds’ approach: the two are synchronized, but each has specific capabilities for the fulfillment of its specific responsibilities. Synchronization between the two “focuses the KMS on serving the IS,” precipitating “a situation in which knowledge serves the organizational procedures by nourishing those procedures with the knowledge items at the appropriate IS stages” (p. 71). Thus, the KMS methodological tool of the knowledge map or conceptual stage is harnessed in this level-four organization “to serve the organizational procedural processes” of the IS track as well (p. 71). What this means is that every knowledge item matched will have a corresponding process notification, which will be able “to address the organizational procedures it serves” (p. 71).

After divergence, there is convergence: at the close of each analysis step, “there is a convergence of the KMS and IS tracks” (Schwartz & Tauber, 2009, p. 71). If the synchronization is done properly, it will ensure that the process as a whole is a success (p. 71). To achieve this, there must be a very clear definition “of the activities in each track so full cooperation avoids unnecessary overlap,” precipitating a fusion of the two groups (p. 71). This process of convergence uses data and information modeling, to be sure, but it also uses knowledge modeling (p. 71). What this means is that the system analyst must not only define “the organizational procedure[,] but also the knowledge items that serve each event of these procedures” (p. 71). This in turn allows the system model to integrate the knowledge management functions into the organizational procedures (p. 71). The CKO must continue to maintain this integration “into the next stage of the KMS life cycle, the maintenance phase” (p. 71). Clearly, convergence produces remarkable results: the KMS enhances the IS, and the functions of the two are integrated.

Finally, we must consider full system modeling. With full system modeling, “two groups of system analysts conduct the system analysis phases” to ensure proper implementation and maintenance of the system (Schwartz & Tauber, 2009, p. 71). The KM group is led by its CKO, and “the IS group is accompanied by the User Representative who operates the organizational procedures” (p. 71). By working together, both groups plan the activities for each phase in a united, integrated format (pp. 71-72). This produces, at last, “an integrated system from a single design process, the KM/MIS” (p. 72).

This, then, is the model for the integration of a KMS with another e-system, in this case an IS. The action research methodology affords the advantages of multiple interactions with the organization at different stages of its development, coupled with an emphasis on using the research for knowledge building, refining the methodology in the process. It also makes use of the findings from one stage to inform and guide the organization in the implementation of the next stage, another key difference with the Case Study methodology (Schwartz & Tauber, 2009, p. 63). The advantages of this maturity model are also considerable, inasmuch as it examines the organization at different stages of its development and can serve as a template for organizations in their own implementation efforts.

As Schwartz and Tauber (2009) explained, the four stages delineated in their research “present a seemingly viable migration path for organizations seeking to move proactively from independent to integrated development of IS/KMS” (p. 74). However, a key finding of the research was that “even a proactive move can be fraught with difficulties and adjustments ranging from incompatible analysis[,] tools and data representation methods, to lack of teamwork and coordination due to improper team composition and balance” (p. 27). Overall, the model unquestionably provides a solid template for organizations seeking integration of a KMS with another e-system. The four levels offer a series of “distinct characteristics that can be sought out, identified, managed and modified” (p.74). An important point is that the progress between the stages, though of course planned, was allowed to develop “over an extended period of time” rather than pigeonholing the progress of the two teams (pp. 74-75).

A number of problems commonly afflict organizations attempting to implement an integration between a KMS and another e-system. Organizational difficulties that can hinder and derail such an effort include bad planning, “unwillingness on the part of the management to press their staff to use the system”, assigning people “not part of the analysis project to test the system”, and “insufficient quality of training programs” (Anderson et al., 2004, p. 233). User expectations can also be an issue, if the employees lack the requisite experience with using computers to begin with; employee unfamiliarity with business processes is another factor that can derail an implementation and prevent full, effective integration of the KMS with the other e-system in question (p. 233).

Fortunately, the solutions to the aforementioned problems are rather obvious: for an implementation to be successful, every employee must clearly understand their role in the company, in the business processes, and in the implementation. This is the importance of transparency, learning, and a properly-supportive, effectively governed organizational environment. Anderson et al. (2004) also recommended reducing complexity to increase ease of use, easing planning and registering requirements at need “so that the system does not force the end-users to introduce new activities in the project plan,” and making the user interface in line “with the other systems used in the office” (p. 234). The lessons from Schwartz and Tauber (2009) are also clear: organizations must grow into their implementations. Integrating a KMS with another e-system is a process that requires time, effort, and patience. In order for an integration to be successful, the members of both teams must work effectively in their respective teams and, over time, with each other. Gradually, the two systems become integrated.

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