Describing Knowledge Maturing: The Knowledge Maturing Phase Model

In a nutshell

Knowledge maturing describes the development of knowledge from a team, community, or organisational perspective. It can be divided into distinct phases along which the characteristics of learning and dealing with knowledge change significantly. The Knowledge Maturing Phase Model can be used to analyse and understand real-world knowledge maturing practices and helps to distinguish between different problem areas and suitable solutions. 

Parent section

Concept of Knowledge Maturing

Further information

Knowledge Maturing Whitepaper

Kaschig, A., Maier, R., Sandow, A., Schmidt, A., Thalmann, S. (Eds.): D1.1 Results of the Ethnographic Study and Conceptual Knowledge Maturing Model, Deliverable 1.1 of the FP7 IP MATURE, Section 5,

Kaschig, A., Maier, R., Sandow, A. & Schmidt, A. (Eds.) (2010). D1.2 - Results Of The Representative Study And Refined Conceptual Knowledge Maturing Model. Deliverable of the FP7 IP MATURE, Section 5,

Kaschig, A., Maier, R., Sandow, A. & Schmidt, A. (Eds.) (2011). D1.3  Results of In-depth Case Studies, Recommendations and Final Knowledge Maturing Model. Deliverable of the FP7 IP MATURE, Section 5,

Schmidt, Andreas (2005). Knowledge Maturing and the Continuity of Context as a Unifying Concept for Knowledge Management and E-Learning. In: Proceedings of I-KNOW 05, Graz, Austria.

Maier, Ronald, Schmidt, Andreas (2007). Characterizing Knowledge Maturing: A Conceptual Process Model for Integrating E-Learning and Knowledge Management. In: Gronau, Norbert (eds.): 4th Conference Professional Knowledge Management - Experiences and Visions (WM '07), Potsdam, GITO, pp. 325-334

Key publication to cite


Ronald {Maier, Andreas} Schmidt
{Explaining organizational knowledge creation with a knowledge maturing model}
{Knowledge Management Research & Practice}, vol. 2014, no. 1, 2014, pp. {1--20}

Abstract {Social media challenge knowledge management because of encouraging conversations, networking and participation in more distributed, diverse and dynamic ways of knowledge development and increasingly important individuals’ interests driving them. Hence, we need to understand the complex relationships between different qualities of knowledge developed in informal and formal processes as well as for overcoming misalignments in routines, tools and infrastructures supporting organizational knowledge creation. This paper contributes a maturation perspective towards explaining organizational knowledge creation and presents a knowledge maturing model, which is grounded in organizational practice and validated with qualitative and quantitative empirical and design studies. The results describe how characteristics of knowledge and support by IT change between phases of knowledge maturing. Our findings confirm theories of organizational knowledge creation with respect to expanding scopes from individuals through communities to organizations moving from interest-driven knowledge exploration in informal contexts to goal-driven knowledge exploitation in formal contexts. The maturation perspective adds to our understanding that organizational knowledge creation is not simply a continuous process. Phases that emphasize changeability alternate with phases concerned with stability. Knowledge develops in contexts that need to switch multiple times between opening up for new knowledge and filtering relevant knowledge and between de- and re-contextualization. }


Andreas P. Schmidt

Knowledge maturing is based on the assumption that learning is an inherently social and collaborative activity in which individual learning processes are interdependent and dynamically interlinked with each other: the output of one learning process is input to the next. If we have a look at this phenomenon from a distance, we can observe a knowledge flow across different interlinked individual learning processes. Knowledge becomes less contextualized, more explicitly linked, easier to communicate, in short: it matures.

We define knowledge maturing as the goal-oriented development of collective knowledge, or better as goal-oriented learning on a collective level where

  • goal-oriented describes knowledge maturing as a process with a direction. The goal can be an individual goal (e.g., deepen understanding in an area out of curiosity), a team goal (e.g., grasp known errors with respect to a product that the team works on), or an organisational goal (e.g., refine an organisations core competency). Goals typically change over time and get aligned in social processes, resulting in a direction as a (mostly a posteriori) interpretation.
  • collective level can refer to different levels of granularity, e.g., a team, an organisation or a community. Knowledge maturing is not the result of an individual‘s activity, but of an interconnected series of activities of interacting individuals, frequently also within different collectives.
  • knowledge is understood as both cognitive structures bound to individuals‘ minds (becoming manifest in their behaviour) and as an abstraction of the knowledge of individuals in a collective.

Knowledge Maturing Phase Model



  • I. Emergence. Individuals create personal knowledge by pursuing their interests in browsing abundant knowledge spaces inside and beyond the organisation, opening up for new knowledge and the changes it might bring about. Based on the findings of our studies, we revised this phase to include two subphases, exploration and appropriation.
    • Ia. Exploration: New knowledge is developed by individuals either in highly informal discussions or by browsing the knowledge spaces available inside the organisation and beyond. Extensive search and retrieval activities often result in loads of material influencing creative processes of idea generation. Knowledge is subjective, deeply embedded in the originator’s context and the vocabulary used for communication might be vague and restricted to the originator.
    • Ib. Appropriation: New knowledge or results found in the investigation phase that have been enriched, refined or otherwise contextualized with respect to their use are now appropriated by the individual, i.e. personalised and contributions are marked so that an individual can benefit from its future (re-)use. While many initiatives for knowledge management have focused on sharing knowledge or even detaching knowledge from humans as “media”, at least in a more individualistic culture, individuals also require support for appropriation.
  • II. Distribution (community interaction): The first phase on the level of communities describes interactions between individuals driven by social motives and the benefits that individuals typically attribute to sharing knowledge. These are, among others, belonging to a preferred social group, thus increasing the probability of getting back knowledge from the community when one needs it. Distribution is not meant in the sense of a one way street of individuals contributing new knowledge that they have committed to. The phase includes discussing the new knowledge, negotiating its meaning and impact, co-developing knowledge, convincing others and agreeing plus committing to the knowledge as collective. From the perspective of semantics, a common terminology is developed and shared among community members.
  • III. Transformation: Artefacts created in the preceding phases are often inherently unstructured and still highly subjective and embedded in the community context which means they are only comprehensible for people in this community due to shared knowledge needed to interpret them. Transformation means that knowledge is restructured and put into a form appropriate for moving it across the community’s boundaries. Structured documents are created in which knowledge is de-subjectified, sometimes formalized using established containers and context is made explicit to ease the transfer to collectives other than the originating community.
  • IV. Introduction: Knowledge is prepared with a specific focus on enhancing understandability, handed on and applied in an ad-hoc manner in trainings in which a selected group of users is instructed using didactically prepared material. We found two primary interpretations of introduction, (1) an instructional setting called ad-hoc training and (2) an experimental setting called piloting.
    • IV1. Ad-hoc training: Documents produced in the preceding phase are typically not well suited as learning materials because no didactical considerations were taken into account. Now the topic is refined to improve comprehensibility in order to ease its consumption or re-use. Individual learning objects are arranged to cover a broader subject area. Tests allow to determine the knowledge level and to select learning objects or learning paths.
    • IV2. Piloting: Typically, not every implementation detail can be foreseen in the preceding phase. Knowledge is arranged in a way so that it can be applied in a dedicated, specific experiment involving not only the creators of knowledge, but other stakeholders. Experiences are collected with a test case before a larger roll-out of a product, a service to an external user community, e.g., customers or stakeholders, or new organisational rules, procedures or processes to an organisational-internal target community such as project teams, work groups, subsidiaries or other organisational units.
  • V. Standardization: The knowledge is further solidified and formally established in the organization to be used in repeatable formal trainings, work practices, processes, products or services. As in phase IV, we distinguish an instructional setting with standardised training activities, called formal training, and an experimental setting turning pilots into standard organizational infrastructure, processes and practices, called institutionalisation. The term standard, finally, also evoked the connotation of external standardisation initiatives which are similar for both settings, transcend the organizational boundaries and move knowledge maturing to the level of societies.
    • V1a. Formal training: In an instructional setting, the subject area becomes teachable to novices. A curriculum integrates learning content into a sequence using sophisticated didactical concepts in order to guide learners in their learning journeys to capture a subject area thus increasing the probability of successful knowledge transfer. Learning objects are arranged into courses covering a broader subject area. Learning modules and courses can be further combined into programs used for preparing for taking on a new role or for career development.
    • V2a. Institutionalisation: In the organisation-internal case, formalised documents that have been learned by knowledge workers are solidified and implemented into the organisational infrastructure in the form of processes, business rules and/or standard operating procedures. In the organisation-external case, products or services are launched on the market. They are institutionalised into the portfolio of products and services offered by the organisation.
    • Vb. External standardisation: The ultimate maturity sub-phase is very similar for both paths, the instructional and the experimental path, and covers some form of standardisation or certification. On an individual level, certificates confirm that participants of formal trainings achieved a certain degree of proficiency. On an organisational level, certificates allow organisations to prove compliance with a set of rules that they have agreed to fulfil, e.g., with service level agreements or regulations such as Basel II or SOX. Concerning products and services, certificates show compliance to laws, regulations or recommendations that can, should or must be fulfilled before a product or service can be offered in a certain market.

This model describes characteristic phases of knowledge maturing, but does not imply a linear development that is the same in each and every case. Therefore, this model should not be misunderstood as a process model in the business process modelling sense. Rather we can observe complex patterns like the combination of knowledge assets, backward steps and cycles as well as improvement patterns.

Implications and practical relevance

The Knowledge Maturing Phase Model allows for analysing concrete families of knowledge processes in companies, diagnose its problems and propose possible solutions. This can be illustrated by examples that we have collected in researching and applying the model in practical projects:

An interview of the study we conducted in MATURE related the knowledge maturing phase model to his company’s experience and found that the “distribution in communities” (phase II) was not required because within his company, this does not play a role. Within the course of the interview, it was found that the company has implemented a continuous improvement programme. Employees are asked to put new ideas into an idea management system in a structured description format. These ideas (mostly from individuals) are then assessed by an expert panel. “Good” ideas get rewards. The interviewee expressed his experience that they do not have a problem with idea generation because way too many ideas are generated, which are frequently of little use to the company because they are too trivial. n terms of the knowledge maturing phase model, the company expected employees to jump directly from appropriation to formalization. This omits the crucial phase of discussing ideas in a group of people with a shared context. Typically, within this phase individual contributions are amalgamated to larger ideas that are better understood and more developed. Such a discussion is not just a simple selection process (like the expert panel, which would be the filtering function between phase III and IV), but also a co-creation phase in which team members build upon the results of others.

In a consulting project for a large German financial services company, the company was dealing with the question which software product to select for their “collaboration” needs inside their IT services unit. They asked for external advice whether a collaboration platform such as Microsoft Sharepoint or a wiki-based solution would be more appropriate. At the beginning of the consulting process, the knowledge maturing phase model was introduced to clarify the collaboration problems that needed to be addressed. As a result of a reflection process, they have found out that they actually have two different collaboration “problems”, each of them located in different maturity phases. On the one side, they collaborate with external partners to co-create new solutions, on the other side, they need to systematically manage their subcontractors so that everyone has access to the latest contract version and to contractually relevant deliverables. While the first situation is located in phase II (distribution in communities), the second is located in phase V2a (institutionalization) and Vb (external standardization), mostly referring to company standards for contract management, but some of this is also relevant for external compliance aspects). While both problems are related to the same activities (communicate with people, co-develop artifacts), it is important to realize that the characteristics are different. The first situation needs quick and easy collaboration (changeability) where structure can easily get into the way, the second situation needs traceability, clearly defined access rights, among others, i.e., stability with respect to rules and structure.

While it is generally desirable to aim at a balanced distribution of knowledge maturing processes, companies are not free to choose where they operate. There are external regulations, particularly in the medical sectors, that require a high degree of standardization when it comes to the production of medical equipment. The production processes need to be certified in an expensive procedure, and compliance to the certified processes need to be documented. This can lead to situations in which a company still needs to manufacture according to processes which are known to be less efficient than newer production processes so that employees can see their idea come to practical applications only after a considerable time period (usually at least three, but up to ten years). This creates motivational issues to stay innovative, which is needed to retain the competitive advantage.  A company that has been interviewed as part of LBS has realized the problems that are associated with such conditions and introduced (a) a highly attractive incentive system with considerable benefits, and (b) an experimentation environment as part of a “rapid response team” that is very well equipped with new technology and is responsible for rapid prototyping for new customer requests. This makes sure that employees are motivated to develop new ideas and they can experience them getting applied at least at prototyping stage early on without interfering with external compliance requirements.

Related publications


Andreas Schmidt
MATURE: Den Wissensreifungsprozess in Unternehmen verbessern
In: Ockenfeld, Marlies (eds.): Verfügbarkeit von Informationen - 30. Online-Tagung der DGI / 60. Jahrestagung der DGI. Frankfurt am Main, 15. - 17. Oktober 2008, Proceedings, 2008


Ronald Maier, Andreas Schmidt
Characterizing Knowledge Maturing: A Conceptual Process Model for Integrating E-Learning and Knowledge Management
In: Gronau, Norbert (eds.): 4th Conference Professional Knowledge Management - Experiences and Visions (WM '07), Potsdam, GITO, 2007, pp. 325-334

Abstract Knowledge management and e-learning both attempt to support learning and knowledge transfer in organizations. However, they aim at knowledge of different degrees of maturity. Central hypothesis of this paper is that the approaches can be integrated on the basis of a process that explicitly aims at designing the transitions of knowledge along varying degrees of maturity. The knowledge maturing process is presented as a conceptual model for explaining and analyzing disruptions in the inter-individual flow of knowledge within organizations. These disruptions can be attributed to a fragmented systems landscape and separated organizational units that foster knowledge of different degrees of maturity. The paper presents criteria for a characterization of this process model and discusses its implications for the design of learning support systems.


Andreas Schmidt
Knowledge Maturing and the Continuity of Context as a Unifying Concept for Knowledge Management and E-Learning
In: Proceedings of I-KNOW 05, Graz, Austria, 2005

Abstract Although both e-learning and knowledge management are about facilitating learning in organization, the major obstacle to bring both of them together can be traced back to different paradigms of learning, resulting from the different nature of the knowledge they are dealing with. In this paper, a knowledge maturing process is presented to illustrate the change of nature and the discontinuities. This lays the foundation for a better understanding. In order to overcome the discontinuities, the consideration of context is proposed, which offers the required continuity.