Contributing to Knowledge Maturing: Knowledge Maturing Activities

In a nutshell

Knowledge Maturing Activities describe activities of individuals and teams that are key for knowledge maturing. Their identification helps to analyse and prioritise which need more or other forms of support.

Parent section

Concept of Knowledge Maturing

Further information

MATURE Deliverable 1.1 contains a discussion of the concept of knowledge maturing activities and a first version based on ethnographically informed studies.

MATURE Deliverable 1.2 contains results of a large-scale interview study in which activities where rated according to importance, support, and success.

Flyer on the large-scale interview study

Key publication to cite

2010

Andreas Kaschig, Ronald Maier, Alexander Sandow, Mariangela Lazoi, Sally-Anne Barnes, Jenny Bimrose, Claire Bradley, Alan Brown, Christine Kunzmann, Athanasios Mazarakis, Andreas Schmidt
Knowledge Maturing Activities and Practices Fostering Organisational Learning: Results of an Empirical Study
In: Sustaining TEL: From Innovation to Learning and Practice 5th European Conference on Technology Enhanced Learning, EC-TEL 2010, Barcelona, Spain, September 28 - October 1, 2010. Proceedings, Lecture Notes in Computer Science vol. 6383, Springer, 2010, pp. 151-166

Abstract Knowledge work is performed in all occupations and across all industries. The level of similarity of knowledge work allows for designing supporting tools that can be widely used. In this paper an activity-based perspective towards knowledge work is taken. Based on findings from a previous ethnographically-informed study, we identified valuable activities to be supported in order to increase knowledge maturing inside companies. The goal of this paper is to contribute to which knowledge maturing activities are deemed important, so that they can be supported by IT services. Quantitative and qualitative data have been collected in 126 organisations of different size, sector and knowledge intensity. Important feedback and issues emerged and need to be managed in order to support success in the knowledge maturing activities that allow improvement of organisational learning through the dissemination and application of the most appropriate knowledge.

The attempt to pack and articulate organizational Knowledge Maturing Activities (KMA) in context of creating learning rich workplaces led to a study crossing theoretical definition as well as practical validation. The performance of activities identified contribute to the development of knowledge on a collective level, where usually the goal-oriented learning of individuals involved goes way beyond in its effects.

The concept of activity proves to be beneficial to analyse knowledge maturing where the perspective of practice finds its roots in knowledge work in different professions, positions and industries. Practices formed by individuals or teams are characterised by knowledge work comprising activities of acquisition, creation, collection, organization, maintenance, systemization, communication and application of knowledge. Primarily, the exploration and joint creation of knowledge is operationalized as strategic focus and applied to all business processes. It is for KMAs to facilitate communication, function as mediation or as cognitive support, making use of artefacts, cognifacts and sociofacts (see section 2) as well as producing such for business progress.

In preparation to the empirical study on deriving an agreed list of KMA occurring across the whole of knowledge maturing processes, the profound theoretical investigation was supplemented by an ethnographically-informed study to match elaborated KMA to real-world maturing practices and activities. The scope of organisations investigated widened the picture of perception by underlying companies of different size, sector and knowledge intensity. What resulted was a comprehensive and practically corresponding list of twelve KMAs, discussed and formulated on grounds of deep understanding of activities performed by knowledge workers and used as interview guideline to the empirical study.

1

Find relevant digital resources

Search for information, e.g. documents, web pages or images.

2

Embed information at individual or organisational level

Include the information into one’s own knowledge base, which could be a (personal or shared) file system, a (personal/team/corporate) wiki, or similar.

3

Keep up-to-date with organisation-related knowledge

making sure that oneself or another person stays up-to-date regarding a certain topic

4

Familiarise oneself with new information

Making oneself familiar with e.g. a topic or a community or processes

5

Reorganise information at individual or organisational level

Restructure collections (file systems, wikis, …), consolidate different approaches to collective structuring, removing outdated items, improving findability through assigning metadata, “gardening” of wikis, vocabularies etc., rearrange contents or files, clean-up work spaces and assure quality of a collection of digital resources

6

Reflect on and refine work practices or processes                      

This reflects process maturing from discovery of task or process patterns, the analysis thereof to improving practices and/or processes. The knowledge maturing activity thus comprises practices (i.e. not formally specified), procedures (informal or endorsed) as well as processes (specified, defined)

7

Create and co-develop digital resources

Generate new or update existing contents by oneself or together with others.
Note: co-development is a form of collaboration.

8

Share and release digital resources

Share denotes the informal, release the formal or official part of granting access to contents for a specified or unspecified group of people.

9

Restrict access and protect digital resources

Restricting access to contents.

10

Find people with particular knowledge or expertise

identify a contact person, e.g. by skills

11

Communicate with people

interact with others, e.g. face-to-face, by phone, by mail

12

Assess, verify and rate information

Evaluate contents with respect to certain quality criteria like accurateness, up-to-dateness, usefulness or people with respect to their capacities or behaviour

Empirical results

As part of a large-scale interview study, the listed KMAs were investigated with respect to three concepts: “perceived importance”, “perceived support” and “perceived success”. 139 interviewees were asked to reflect on how important they think that the KMAs were for increasing maturity of knowledge in the organisation they represent, how far organisational or ICT instruments contribute to these knowledge maturing activities and finally, the interviewees were asked to state on how successfully they believe these KMAs are performed in their organisation. Besides rating on each proposed KMA, the respondents were asked to provide further KMAs performed in their organisation (see section  REF _Ref326586411 \r \h 3.3 08D0C9EA79F9BACE118C8200AA004BA90B02000000080000000E0000005F005200650066003300320036003500380036003400310031000000 ).

The results brought up relatively high mean values to all three concepts, having the interviewees predominantly agree with the worked out KMAs under the presented aspects.

Considering the design of software and services to support KM, the most interesting KM activities are those which are viewed as important for increasing knowledge maturity, but for which interviewees have the impression that they are not well supported. According to the portfolio, the following activities are most interesting to KM by interviewees:

  • reflect on and refine work practices or processes
  • find people with particular knowledge or expertise
  • assess, verify and rate information

Related publications

2010

Andreas Kaschig, Ronald Maier, Alexander Sandow, Mariangela Lazoi, Sally-Anne Barnes, Jenny Bimrose, Claire Bradley, Alan Brown, Christine Kunzmann, Athanasios Mazarakis, Andreas Schmidt
Knowledge Maturing Activities and Practices Fostering Organisational Learning: Results of an Empirical Study
In: Sustaining TEL: From Innovation to Learning and Practice 5th European Conference on Technology Enhanced Learning, EC-TEL 2010, Barcelona, Spain, September 28 - October 1, 2010. Proceedings, Lecture Notes in Computer Science vol. 6383, Springer, 2010, pp. 151-166

Abstract Knowledge work is performed in all occupations and across all industries. The level of similarity of knowledge work allows for designing supporting tools that can be widely used. In this paper an activity-based perspective towards knowledge work is taken. Based on findings from a previous ethnographically-informed study, we identified valuable activities to be supported in order to increase knowledge maturing inside companies. The goal of this paper is to contribute to which knowledge maturing activities are deemed important, so that they can be supported by IT services. Quantitative and qualitative data have been collected in 126 organisations of different size, sector and knowledge intensity. Important feedback and issues emerged and need to be managed in order to support success in the knowledge maturing activities that allow improvement of organisational learning through the dissemination and application of the most appropriate knowledge.

2009

Sally-Anne Barnes, Jenny Bimrose, Alan Brown, Daniela Feldkamp, Andreas Kaschig, Christine Kunzmann, Ronald Maier, Tobias Nelkner, Alexander Sandow, Stefan Thalmann
Knowledge Maturing at Workplaces of Knowledge Workers: Results of an Ethnographically Informed Study
In: 9th International Conference on Knowledge Management (I-KNOW '09), Graz, Austria, 2009, pp. 51-61

Abstract Maturity models are popular instruments used, e.g., to rate capabilities of maturing elements and select appropriate actions to take the elements to a higher level of maturity. Their application areas are wide spread and range from cognitive science to business applications and engineering. Although there are many maturity models reported in scientific and non-scientific literature, the act of how to develop a maturity model is for the most part unexplored. Many maturity models simply – and vaguely – build on their, often well-known, predecessors without critical discourse about how appropriate the assumptions are that form the basis of these models. This research sheds some light on the construction of maturity models by analysing 16 representative maturity models with the help of a structured content analysis. The results are transformed into a set of questions which can be used for the (re-)creation of maturity models and are answered with the help of the case example of a knowledge maturity model. Furthermore, a definition of the term maturity model is developed from the study’s results.