Archive for the ‘Knowledge Management’ Category

Decision Making Within Distributed Project Teams (Bourgault et al., 2008)

Montag, November 3rd, 2008

ecision Making Within Distributed Project Teams (Bourgault et al., 2008)

Bourgault, Mario; Drouin, Nathalie; Hamel, Émilie: Decision Making Within Distributed Project Teams – An Exploration of Formalization and Autonomy as Determinants of Success; in: Project Management Journal, Vol. 39 (2008), Supplement, pp. S97–S110.
DOI: 10.1002/pmj.20063

Bourgault et al. analyse group decision making in virtual teams. Their article is based on the principles of limited rationality, i.e. deciding is choosing from different alternatives, and responsible choice, i.e. deciding is anticipating outcomes of the decision.

Existing literature controversially discusses the effects of virtualising teams. Some authors argue that virtual teams lack social pressure and thus smaler likelihood of showing escalation of committment behaviour, whilst making more objective and faster decisions. Other authors find no difference in working style between virtual and non-virtual teams. Generally literature explains that decision-errors are mostly attributed to break-downs in rationality, which are caused by power and group dynamics. Social pressure in groups also prevents efficiency. In any team with distributed knowledge the leader must coordinate and channel the information flow.

Bourgault et al. conceptualise that Formalisation and Autonomy impact the quality of decision-making, which then influences the team work effectiveness. All this is moderated by the geographic dispersion of the team.
They argue that formalisation, which structures and controls the decision making activities, helps distributed teams to share information. Autonomy is a source of conflict, for example with higher management due to a lack of understanding and trust, ultimately it weakesn a project decision-making because it diverts horizontal information flow within the team to vertical information flow between project and management.
Quality of decision-making process – the authors argue that groups have more information resources and therefore can make better decisions, but this comes at an increased cost for decision-making. Geographical distributed teams lack signals and have difficulties in sharing information. Thus high quality teamwork benefits from more dispersed knowledge but low quality teamwork suffers from a lack of hands-on leadership.
Teamwork effectiveness – this construct has mostly been measured using satisfaction measurements and student samples. Other measures are the degree of taks completion, goal achievement, self-efficacy (intent to stay on the team, ability to cope, percieved individual performance, perceived team performance, satisfaction with the team). Bourgault et al. measure teamwork effectiveness asking for the perceived performance on taks completion, goal achievement, information sharing, conflict resolution, problem solving, and creating a prefereable and sustainable environment.

The authors‘ quantitative analysis shows that in moderated teams all direct and indirect effects can be substantiated, with exception of the autonomy influencing the quality of decision-making. Similarily in highly dispersed teams all direct and indirect effects, but the direct influence of formalisation on teamwork effectiveness, could be proven.

Bourgault et al. conclude with three points of recommendation for the praxis – (1) Distribution of a team contributes to high quality of decisions, although it seems to come at a high cost. (2) Autonomous teams achieve better decisions – „despite the fear of an out of sight out of control syndrome“. (3) Formalisation adds value to teamwork especially the more distributed the team is.

Learning and acting in project situations through a meta-method (MAP) a case study: Contextual and situational approach for project management governance in management education (Bredillet, 2008)

Dienstag, Oktober 28th, 2008

 Bredillet

Bredillet, Christophe N.: Learning and acting in project situations through a meta-method (MAP) a case study – Contextual and situational approach for project management governance in management education; in: International Journal of Project Management, Vol. 26 (2008), No. 3, pp. 238-250.
http://dx.doi.org/10.1016/j.ijproman.2008.01.002

[This is a relatively complex post that follows – the article goes into epistemology quite deep (What is knowledge? How do we acquire it?) without much explanation given by the author. I tried to put together some explanatory background to make the rationale for the article more accessible. If you are just interested in the curriculum Bredillet proposes for learning project management on the job, skip these parts and jump right to the end of the post.]

In this article Bredillet outlines his meta-method used to teach project management. This method’s goal is to provide a framework in terms of processes and structure for learning in situ, namely on projects, programmes and alike. Bredillet argues that this method is best in accounting for complex, uncertain and ambiguous environments.

[Skip this part if you’re only interested in the actual application of the method.]

The authors starts with reviewing the three dominant project perspectives. a) Instrumental Perspective, which defines a project as a temporary endeavour to create something. b) Cognitive Perspective, which defines projects as exploitation of constraints and human/monetary capital in order to achieve an outcome. c) Political Perspective, which define projects as spatial actions which are temporarily limited, thus interacting with their environment. Bredillet argues that project management education does not reflect these perspectives according to their importance in the real world.

Bredillet argues that project management, knowledge creation and production (epistemology) have to integrate classical scientific aspects (Positivism) as well as fuzzy symbolisms (Constructivism). He says: „that the ‚demiurgic‘ characteristic of project management involves seeing this field as an open space, without ‚having‘ (Have) but rather with a raison d’être (Be), because of the construction of Real by the projects“ (p. 240).
Without any prior indulgence into epistemology (‚What is knowledge?‘ E. v. Glaserfeldt, Simon, Le Moigne etc.) this sentence is rather cryptic. What Bredillet wants to achieve is to unify the Positivist and Constructivist epistemology. Positivist epistemology can shortly be summarised to be our approach to understand the world quantitatively (= have = materialism, with only few degrees of freedom, e.g., best practices, OR, statistical methods). On the other hand Constructivist epistemology tries to understand the world with a qualitative focus (=be = immateriality, with many degrees of freedom, e.g., learning, knowledge management, change management). Bredillet summarises the constructivist epistemology citing Comte as „from Science comes Prevision, from Prevision comes Action“, and the positivist epistemology according to Le Moigne’s two hypothesis of reference – phenomenological („an existing and knowledgeable reality may be constructed by its observers who are then its constructors“) and teleological („knowledge is what gets us somewhere and that knowledge is constructed with an aim“).

Bredillet then argues that most research follows the positivist approach, valuing explicit over tacit knowledge, individual knowledge over team/organisational knowledge. To practically span the gap between Constructivism and Positivism Bredillet suggests to acknowledge tacit, explicit, team and individual knowledge as „distinct forms – inseparable and mutually enabling“ (p. 240).

How to unify Constructivsm and Postivitsm in Learning of Project Management?
Practically he explores common concepts always from both views, from the positivist and the constructivist standpoint, for instance, Bredillet describes concepts of organisational learning using the single-loop model (Postivism) vs. double-loop model, and system dynamics theory (Constructivsm).  Secondly, Bredillet stresses that learning and praxis are integrated, which is what the MAP method is all about:

„The MAP method provides structure and process for analysing, solving and governance of macro, meso, and micro projects. It is founded on the interaction between decision-makers, project team, and various stakeholders.“ (p. 240)

The three theoretical roots for the map method are (1) Praxeological epistemology, (2) N-Learning vs. S-Learning, (3) Theory of Convention. Thus the map method novelty is that it

  • Recognises the co-evolution of actor and his/her environment,
  • Enables integrated learning,
  • Aims at generating a convention (rules of decision) to cope with the uncertainty and complexity in projects.

Ad (1): The basic premises of Praxeological epistemology [in Economics] taken from Block (1973):

  • Human action can only be undertaken by individual actors
  • Action necessarily requires a desired end and a technological plan
  • Human action necessarily aims at improving the future
  • Human action necessarily involves a choice among competing ends
  • All means are necessarily scarce
  • The actor must rank his alternative ends
  • Choices continually change, both because of changed ends as well as means
  • Labour power and nature logically predate, and were used to form, capital
  • Technological knowledge is a factor of production

Ad (2): I don’t know whether n-Learning in this context stands for nano-Learning (constantly feeding mini chunks of learning on the job) or networked learning (network over the internet to learn from each other – blogs, wikis, mail etc.). Neither could I find a proper definition of S-Learning. Generally it seem to stand for supervised learning. Which can take place most commonly when training Neural Networks, and sometimes on the job.
Sorry – later on in the article Bredillet clarifies the lingo: N-Learning = Neoclassical Learning = Knowledge is cumulative; and S-Learning = Schumpeterian Learning = creative gales of destruction.

Ad (3): Convention Theory (as explained in this paper) debunks the notion that price is the best coordination mechanism in the economy. It states that there are collective coordination mechanisms and not only bilateral contracts, whose contingencies can be foreseen and written down.
Furthermore Convention Theory assumes Substantive Rationality of actors, radical uncertainty (no one knows the probability of future events), reflexive reasoning (‚I know that you know, that I know‘). Thus Convention Theory assumes Procedural Rationality of actors – actors judge by rational decision processes & rules and not by rational outcome of decisions.
These rules or convention for decision-making are sought by actors in the market. Moreover the theory states that

  • Through conventions knowledge can be economised (e.g., mimicking the behaviour of other market participants);
  • Conventions are a self-organising tools, relying on confidence in the convention
  • Four types of coordination exist – market, industry, domestic, civic

[Start reading again if you’re just interested in the application of the method.]

In the article Bredillet then continues to discuss the elements of the MAP meta model:

  • Project situations (entrepreneurial = generating a new position, advantage) vs. operations situations (= exploiting existing position, advantage)
  • Organisational ecosystem [as depicted on the right of my drawing]
  • Learning dynamics and praxis, with the three cornerstones of knowledge management, organisational learning, and learning organisation

Thus learning in this complex, dynamic ecosystem with its different foci of learning should have three goals – (1) individual learning, e.g., acquire Prince 2/PMP methodology; (2) Team learning, e.g., acquire team conventions; and (3) organisational learning, e.g., acquire new competitive position.

The MAP model itself consists of the several project management theories and concepts [theories are depicted on the left side of my drawing], the concepts included are

  • Strategic Management
  • Risk Management
  • Programme Management
  • Prospective Analysis
  • Projects vs. Operations
  • Ecosystem project/context
  • Trajectory of projects/lifecycles
  • Knowledge Management – processes & objects; and individual & organisational level
  • Systems thinking, dynamics
  • Organisational design
  • Systems engineering
  • Modelling, object language, systems man model
  • Applied sciences
  • Organisational Learning (single loop vs. double loop, contingency theory, psychology, information theory, systems dynamics)
  • Individual learning – dimensions (knowledge, attitudes, aptitudes) and processes (practical, emotional, cognitive)
  • Group and team learning, communities of practice
  • Leadership, competences, interpersonal aspects
  • Performance management – BSC, intellectual capital, intangible assets, performance assessments, TQM, standardisation

The praxeology of these can be broken down into three steps, each with its own set of tools:

  1. System design – social system design (stakeholder analysis, interactions matrices), technical system design (logical framework, e.g., WBS matrix, and logical system tree)
  2. System analysis – risk analysis (technical/social risk analysis/mapping), scenario analysis (stakeholder variables & zones)
  3. System management – scheduling, organisation & planning, strategic control

As such, Bredillet describes the MAP method trajectory as

  1. Strategic choice with a) conception, b) formulation
  2. Tactical alternatives with a) alternatives analysis and evaluation, b) decision
  3. Realisation with a) implementation, b) reports and feedback, c) transition into operations, c) post-audit review

In praxis the learning takes part in form of simulations, where real life complex situations have to be solved using the various concepts, methods, tools, and techniques (quantitative and psycho-sociological) which are included in the MAP-method. To close the reflective learning loop at the end two meta-reports have to be written – use of methods and team work, and how learning is transferred to the workplace. Bredillet says that with this method his students developed case studies, scenario analysis, corporate strategy evaluation, and tools for strategic control.

Building knowledge in projects – A practical application of social constructivism to information systems development (Jackson & Klobas, 2008)

Donnerstag, Oktober 23rd, 2008

Building knowledge in projects - A practical application of social constructivism to information systems development (Jackson & Klobas, 2008)

Jackson, Paul; Klobas, Jane: Building knowledge in projects – A practical application of social constructivism to information systems development; in: International Journal of Project Management, Vol. 26 (2008), No. 4, pp. 329-337.
http://dx.doi.org/10.1016/j.ijproman.2007.05.011

Jackson & Klobas describe the constructivist model of knowledge sharing and thus organisational learning. This classical model describes knowledge sharing in organisations as a constant cylcle of

  • Creating personal knowledge
  • Sharing newly created personal knowledge = Externalisation
  • Communication knowledge = Internalisation
  • Acquiring other peoples‘ knowledge = Learning

This cylcle includes the facilitating steps of Objectivation (=creating organisational knowledge), Legitimation (=authorising knowledge), and reification (=hardening knowledge) between externalisation and internalisation.

Jackson & Klobas argue that IT project failure can be explained using this model. The authors outline and discuss three failure factors – (1) lack of personal knowledge, (2) inability to externalise knowledge, and (3) lack of communication.

Integrating diverse knowledge through boundary spanning processes – The case of multidisciplinary project teams (Ratcheva, in press)

Freitag, Oktober 3rd, 2008

Integrating diverse knowledge through boundary spanning processes – The case of multidisciplinary project teams (Ratcheva, in press)

Ratcheva, Violina: Integrating diverse knowledge through boundary spanning processes – The case of multidisciplinary project teams; in: International Journal of Project Management, in press, corrected proof.
http://dx.doi.org/10.1016/j.ijproman.2008.02.008

The author argues that diverse, multi-disciplinary teams have knowledge boundaries which make information sharing difficult. An issue even more difficult if the team is geographically separated.

Ratcheva conceptualises the diverse project team as being embedded in the macro environment and organisational environment. The team itself is characterised at its starting point by three factors – (1) interpersonal, interactions & relational capital, (2) knowledge diversity, and (3) establishing workpractice. These three factors influence each other. Starting with this diverse team context or setting the team goes on to integrate it’s knowledge which ultimately leads to a project outcome.

Which knowledge boundaries exist in such a project team? Ratcheva identifies three different knowledge domains and at the edge of these knowledge boundaries. First of all there is the project team, surrounded by it’s projectation boundary, outside this boundary lies the occupational knowledge. Which simply means that each project team member is rooted in a broader knowledge of his profession which goes beyond the boundaries of the current project.
Secondly, the team has contextual knowledge which is confined by the project knowledge boundary. Thirdly, the broader project relevant knowledge lies inside the project’s social boundary.

How does the concept look like in motion? Which boundary spanning activities does the team perform? Ratcheva describes a four step process which combines all knowledge related and boundary spanning activities.

  1. The project core team works on the project, solves problems and issues = understanding occupational knowledge, and realising and spanning the projectation boundary
  2. The team understands the context knowledge, e.g., customer needs, stakeholder requirements = realising and spanning the project knowledge boundary
  3. The team understands  it’s personal diversity, thus understanding which personal knowledge is project relevant knowledge = realising and spanning the project social boundary
  4. The team integrates all knowledge, a knowledge which then feeds back into the first step

Post-project reviews as a key project management competence (Anbari et al., 2008)

Mittwoch, September 17th, 2008

 Post-project reviews as a key project management competence

Anbari, Frank T.; Carayannis, Elias G.; Voetsch, Robert J.: Post-project reviews as a key project management competence; in: Technovation, Vol. 28 (2008), No. 10, pp. 633-643.
http://dx.doi.org/10.1016/j.technovation.2007.12.001

George Santayana was the wise guy who said: „Those who cannot remember the past are condemned to repeat it.“ At university I learned that 2 strategies exist to make an organisation remember it’s past – Internalisation and Codification. While internalisation usually happens anyway and an organisation only needs to keep track on who did which projects in the past, so that he can be interviewed, the codification bit is tricky.

Anbari et al. describe which interest are held by which stakeholder group and how that is going to impact any knowledge management or lack thereof. The authors also outline useful techniques and critical aspects, plus when project reviews are most usefully held during the project lifecycle.

Furthermore, the paper discusses where post-project reviews fit into the project life cycle and project management processes. It assesses how such reviews can assist an organization in improving the manner in which its projects are conceived, planned, implemented, reported, and evaluated.

Finally Anbari et al. outline a 3-fold growth model for organisations
(1) Vicious circle = no real reviews
(2) Functional circle = reviews which no one knows about
(3) Virtuous circle = reviews everybody knows.

Managing Knowledge and Learning in IT Projects: A Conceptual Framework and Guidelines for Practice (Reich, 2007)

Dienstag, Juli 15th, 2008

Knowledge gaps and risks

Reich, Blaize Horner: Managing Knowledge and Learning in IT Projects – A Conceptual Framework and Guidelines for Practice; in: Project Management Journal, Vol. 38 (2007), No. 2, pp. 5-17.

This paper won the PMI award for the best paper in 2007. She identifies 10 risks on the projects which arise due to knowledge gaps. Reich structures the risks from a systems and process perspective. Risks 1&2 are project inputs, Risks 3&4 are linked to the project governance, Risks 5-8 are operational risks, Risk 10 is an output risk.

  1. Previous lessons are not learned
  2. Team selection is flawed
  3. Volatility in the governance team
  4. Lack of role knowledge
  5. Inadequate knowledge integration
  6. Incomplete knowledge transfer
  7. Exit of team members
  8. Lack of knowledge map
  9. Loss between phases
  10. Failure to learn

Since learning the way to bridge knowledge gaps, Reich concludes that the best way to address the risks is 4-fold (1) establish a learning climate, (2) establish and maintain knowledge levels, (3) create channels for knowledge flow, and (4) develop a team memory.

A set of frameworks to aid the project manager in conceptualizing and implementing knowledge management initiatives (Liebowitz & Megbolugbe, 2003)

Montag, Juli 14th, 2008

KM

Liebowitz, Jay; Megbolugbe, Isaac: A set of frameworks to aid the project manager in conceptualizing and implementing knowledge management initiatives; in: International Journal of Project Management, Vol. 21 (2003), No. 3, pp. 189-198.
http://dx.doi.org/10.1016/S0263-7863(02)00093-5

Liebowitz & Megbolugbe describe three frameworks which can be used by practitioners to think about Knowledge Management (KM) approaches. Firstly the outline Wiig’s framework which describes the knowledge activities cycle (Conceptualise –> Reflect –> Act –> Review –> Conceptualise…) and the connected workplace structure (Business processes, [used in] Knowlege items, [bound to] organisational roles).

Secondly they present the Knowledge Management Pyramid and thirdly they derive a new implementation framework. Liebowitz & Megbolugbe’s framework connects the KM Intentions and Needs with the KM Solution via 4 knowledge objects/critical factors. (1) Knowledge taxonomies, (2) organizational culture, (3) user feedback on usability and functionalities, and (4) alignment with business strategy and senior management committment.

Managing incomplete Knowledge (Pender, Steven 2001)

Mittwoch, Juli 2nd, 2008

ICK (thumb)

Pender, Steven: Managing incomplete knowledge – Why risk management is not sufficient, in: International Journal of Project Management, Vol. 19 (2001), pp. 79-87.

Pender basically looks into the question if project risks is better described by the term ‚incomplete knowledge‘ and therefore be linked to probability theory. (Kudos to everyone who did the PMP and still knows which contingency reserve accounts for ‚known unknowns‘ and which for ‚unknown unknowns‘.)

He looks into the question of randomness (probability vs. non-probability), repeatability, human limitations to understand such a complex thing as a project, uncertainty & ignorance, flow of knowledge, and fuzziness of parameters.