Eight to Late

Introduction

Over the last two decades or so, it has been recognized that creativity and innovation tend to thrive in organisations  where employees have a say in decisions that affect their work.  This has lead to the notion of a post-bureaucratic organisation –  an organisation in which decisions are made collectively through dialogue and consensus, and where  the hierarchy is flat.  Although a number of workgroups within large organizations function this way (and with some success too),  a post-bureaucratic organisation is generally seen as a utopian and academic ideal; one that is  unlikely to work in the real world. Those who manage  organizations, departments or workgroups  are generally uncomfortable with employees working autonomously,  even though this might lead to the generation of novel ideas and products.  This is understandable: it is ultimately the responsibility of managers to ensure that  organisational or departmental goals are achieved. How else to do this but through the time-tested command and control approach to management?

In response to the question posed above, project management is often touted as a means to manage creative and innovative efforts in organisations (see some of the articles in this issue of PM Network, for example).  The claim seems a reasonable one: project management (by definition) provides a means to manage  collective, goal oriented endeavours. Further, many projects – especially those involving  new product or software development – have a creative/innovative component. In practice, though, project management tends to be a bureaucratic affair;  involving plans that must be followed, schedules that must be adhered to and regular progress reports that must be made. Even so (or perhaps, because this is so) many organizations see project management as a means to manage all creative work in a post-bureaucratic setting.  Implicit in this view is the assumption that the implementation of project management processes will  enable managers to control and direct creative work without any adverse side-effects.  An article by Damian Hodgson entitled Project Work: The Legacy of Bureaucratic Control in the Post-Bureaucratic Organisation, explores the tensions and contradictions presented by this notion. Although the article was written a while ago (in 2003), I believe the ideas explored in it are ever more relevant today, particularly in view of the increasing projectisation of organisations and the work carried out within them.  Hence my motivation to  summarise and review  the paper.

Background – setting the stage

To be fair, many organizations recognise that a “light hand on the rudder” is needed in order to encourage creativity and innovation.  In these organisations, project management is often seen as a means to achieve this.  But  how well does it work in practice? Hodgson’s paper aims to provide some insight into this question via a case study of an organization in which a project-based form of management was implemented as a means to balance the  requirements of creativity and control. In his words:

In response to the challenges of the post-bureaucratic form, project management has  been put forward by many as a ‘tried-and-tested’ package of techniques able to cope with discontinuous work, expert labour and continuous and unpredictable change while delivering the levels of reliability and control of the traditional bureaucracy. In this article I explore some of the contradictions and tensions within a department where such a ‘hybrid’ mode of control is implemented, embodying both bureaucratic and post-bureaucratic logics. In particular, I focus upon the discursive tactics employed to sell ‘rebureaucratization’ as ‘debureaucratization’, and the complex employee responses to this initiative. I argue that the tensions evident here cast significant doubt on the feasibility of a seamless integration of bureaucracy and the post-bureaucratic [organization].

The “discursive tactics” that Hodgson mentions to are (seemingly reasonable and rational) arguments that an organization might use to “sell” the idea that the methods and approaches of project management are consistent with the ideals of a post-bureaucratic organization. An example of such an argument goes as follows: project management is routinely used to manage new product development projects, so it is eminently suited to managing creative work (Incidentally,  this isn’t quite right – see this paper review for more on why)

Post bureaucracy vs. bureaucracy

Before moving on, it is worth comparing the characteristics of bureaucratic and post-bureaucratic organizations. Hodgson provides the following comparison, drawn from Hekscher’s work:

Bureacracy	Post-bureaucracy
Consensus through Acquiescence to Authority	Consensus through Institutionalized Dialogue
Influence based on Formal Position	Influence through Persuasion/PersonalQualities
Internal Trust Immaterial	High Need for Internal Trust
Emphasis on Rules and Regulations	Emphasis on Organizational Mission
Information Monopolised at Top of Hierarchy	Strategic Information shared in Organization
Focus on Rules for Conduct	Focus on Principles Guiding Action
Fixed (and Clear) Decision Making Processes	Fluid/Flexible Decision Making Processes
Network of Specialized FunctionalRelationships	Communal Spirit/Friendship Groupings
Hierarchical Appraisal	Open and Visible Peer Review Processes
Definite and Impermeable Boundaries	Open and Permeable Boundaries
Objective Rules to ensure Equity of Treatment	Broad Public Standards of Performance
Expectation of Constancy	Expectation of Change

The aim of the case study is to highlight some of the inconsistencies and contradictions that result from applying a bureaucratic mechanism (project management) to manage the work of a group that was very good at doing creative work, but was used to a more free-wheeling, hands-off management style (i.e. a group which approximates the idealised post-bureaucratic environment described above).

Why project management?

Project management has its roots in classical management (ala Taylor and Fayol), so it is perhaps  surprising that it is considered as a means to manage work in a post-bureaucratic setting. In Hodgson’s words:

I would argue that what distinguishes project management as of particular relevance to 21stcentury organizations is its rediscovery of a very 19th-century preoccupation with comprehensive planning, linked to a belief in the necessity of tight managerial discipline.

Project management tools and techniques support managerial discipline by providing means to decompose the project into manageable bits – by using a WBS say – and then assigning these bits to individuals (or small teams). The work assigned can then be tracked and controlled tightly – which is a good thing.  If the matter rested there it wouldn’t be too bad, but very often management also prescibes how the work should be done. This level of control results in a loss of autonomy (and motivation)  for team members whose job it is to do the work. The loss of motivation can have negative effects, especially in projects with a large creative component.  To counter this criticism, in recent years project management has started to focus on the creative aspects of projects – what’s needed to motivate teams, how to foster creativity (in new product development work, say) etc. As Hodgson puts it,

The linking of project management and change management has increased project management’s influence across industries, such that now the largest professional organization in project management includes special interest groups in areas as diverse as healthcare, retail, media, marketing, and hospitality. As a consequence the last decade has been a time of particularly rapid expansion for project management, as issues of change, knowledge management, and constant innovation emerged as central themes in popular management discourse.

So, project management offers two (seemingly contradictory) benefits: the ability to maintain tight control of work and the ability to foster innovation and creativity:

…project management can be seen as an essentially bureaucratic system of control, based on the principles of visibility, predictability and accountability, and operationalized through the adherence to formalized procedure and constant written reporting mechanisms. At the same time, however, project management draws upon the rhetoric of empowerment, autonomy and self-reliance central… In principle, then, project management offers a system which attempts to integrate bureaucratic control and a form of responsible autonomy more in keeping with the interdisciplinary, knowledge-intensive nature of much project work in teams.

Seen in this light, it is perhaps not so surprising that project management is viewed as a means to manage creative work.

The case study

With the above background done, I now move on to a discussion of the case study.  In Hodgson’s words, the study:

…focused upon  a telephone bank in northern England which I have referred to under the pseudonym Buzzbank. In the late 1980s, Buzzbank had been set up by a major UK bank, which I will call TN Banking, and represented one of several success stories in the retail banking sector over this period. Through reduced overheads and the extensive use of new technology in the form of sophisticated marketing techniques and call-centre technology, Buzzbank had expanded rapidly in terms of market share and turnover, developing into a key component of TN Banking’s global operations. My interest in particular centred on Buzzbank senior management’s identification of project management as the prime ‘critical success factor’ for the organization; the development of project management expertise throughout the organization was seen as a key priority to maintain performance into the next decade. To an extent, the project teams researched could scarcely be more ‘cutting edge’, representing highly-trained ‘knowledge workers’ developing innovative high technology applications and solutions in a new sector of an enormously profitable industry

Hodgson conducted interviews and observed operations within the IT department of Buzzbank over a period of two years. During this period, the organization was implementing a “strategic plan” aimed at formalizing innovation and creative work using project management processes. The idea, in the words of a couple of senior IT managers was to “bring a level of discipline” and “bring an idea of professional structuring” to the work of the highly successful unit. The structuring and discipline was to be achieved by implementing project management processes.

The main rationale used to sell project management to the Buzzbank IT team is a familiar one: the need to ensure predictability and repeatability of work done whilst ensuring that innovation and creativity would not be impeded. Another justification offered by management was that the size of the organization (which had grown considerably in the years prior to the implementation of the strategic plan) meant that  the existing “ad-hoc” work culture would no longer be successful. That is,  the size of the organization necessitated a degree of formalization,  ergo bureaucratic procedures had to be put in place. This was rationalised  (by senior management) as a natural and inevitable consequence of growth:

…The organization was therefore portrayed by senior management in IT as approaching its ‘next stage of evolution’. The immediate benefit of such a metaphor for those members of senior management charged with rebureaucratizing the organization is that it carries a very strong sense of inevitability. As such, it casts opposition to such changes as irrational and futile, standing in the way of natural ‘evolution’.

Further, managers in the organization dubbed any employee resistance as “natural growing pains” – like those of an adolescent, say. Cast in this light, dissenting viewpoints were portrayed as natural and unavoidable – and possibly even necessary – but ultimately without any validity.

Another interesting aspect that Hodgson highlights is the way in which old practices (the successful but “bad” ones) were subsumed in the new (formal) framework. For example, in the old world, employees were given the freedom to experiment, and many considered this as a strength not a weakness. In the new world, however, such a practice was seen as a threat; it was considered more important to capture how to do things correctly so that things became repeatable (ala best practice) and experimentation would not be necessary. As one manager put it:

If we capture how we do things right, at least it makes things repeatable, and we can record the improvement required when things don’t go right, which doesn’t happen in a rapidly-expanding, gung-ho environment.

Hodgson notes that the terms rapidly-expanding and gung-ho, which are used in a negative sense, could just as well be cast in positive terms such as  flexible, proactive etc. The point being that management framed the existing situation in terms that made the implementation of the new procedures seem like a logical and reasonable next step. The processes were touted as a means to achieve change (i.e. be flexible), but in a controlled way. So, management went to great lengths to avoid use of terms that would be perceived as being negative – for example, the term “structure” was used instead of “bureaucracy” or “formalization.” In this way, management attempted to assimilate the existing values of Buzzbank into the strategic plan.

So, how well did it work? Here’s what Hodgson says about the end result:

The impression given [by senior management] was that of an organizational change which was inevitable, which gave rise to some understandable but irrational resistance, and which had now been effectively completed, for the good of the organization as a whole.

On the other hand, the impression Hodgson got from speaking to lower level employees was very different:

However, in the time spent by myself in the organization, the tone and target of much of the humour, as well as much stronger reactions, appeared to throw doubt on the extent to which this discourse had permeated among the general employees, particularly within the IT department. Humour was commonplace in the everyday banter both within teams and between teams in the IT division at Buzzbank, and the increasing levels of bureaucratization was the butt of most of the humour, particularly at the lower levels of the hierarchy. The main experience of project management as reported by many  Buzzbank employees was one of intensified bureaucratic surveillance…

A key example is the reaction of employees to managerial jargon that was used in company circulars and literature intended to promote the strategic plan.

Typically, comments were provoked by the circulation of literature on the strategic plan, and again, excerpts of the document were read out by members of staff, adding ironic comments to underline the gap between the document and their experience of life and work in the department.

Hodgson notes that employees often appeared to comply with the new regulations, but not in the way intended by management:

At other times, the employees appeared to comply with the formal requirements of the new system, in terms of filling in the necessary forms, reporting in at given times, completing the necessary work-logs and so on. Even here, despite the relative sophistication of senior management’s re-articulation of key discourses, compliance on the part of Buzzbank employees in many cases bore all the hallmarks of instrumental behaviour, accompanied by insubordinate statements and humour ranging from the cynical to the confrontational. At other times, assurances were given to senior management and immediately contravened, fictionalized accounts of project activities were submitted late, or else procedures were observed meticulously to the detriment of deadlines and other constraints. The emergent organizational order was a precarious negotiation between alienated compliance and an autonomous disregard for bureaucratic demands…

In short: there was a clear gap between the perceptions of management and employees as to the success of the newly implemented processes.

It is clear that Buzzbank managers saw  project management as  a means to control and direct creative / innovative work in a way that would have no negative effect on employee morale and motivation.   The challenge, of course, lay in achieving employee buy-in.  Management used many creative (!) tactics to “sell” project management to staff. These included:

1. References to a “natural process of evolution” and the consequent “growing pains” that the organization would experience. This made the pain of the change natural and inevitable, but necessary in the interest of future gain.
2. Manipulation of terminology to make the changes seem more palatable – e.g. using the word “structure” instead of “formalization” or “bureaucracy”.
3. Co-opting terminology of post-bureaucratic organizations into literature designed to promote the new structure. For example, claiming that project management processes would enable the organization to be even more responsive to change (i.e. flexible), through change management processes.

From employees’ perspective, such techniques were plainly seen for what they were: methods to “sell the unsellable”. The negative reactions of employees were manifested through sarcastic humour and (often minor) acts of insubordination. The case study thus highlights the difficulties in using project management as a means to control work in a post-bureaucratic work environment.

Wrapping-up: reflections and summary

Hodgson sees the case study as exemplifying the problem of control vs. autonomy in emerging post-bureaucratic organizations:  managers view project management as a means to address the risks inherent in post-bureaucratic work, whereas employees view it as a unnecessary and unjustified imposition. Management was looking for the “best of both worlds”, a hybrid model that incorporated the best elements of a post bureaucratic model and a traditional command and control approach. The case study casts doubt on whether such a hybrid is possible solely through the implementation standard project management techniques and processes. It does so by exposing some of the tensions and differences in perceptions that can occur when such a model is implemented.

So where does this leave managers? Is there a way to manage creative work without destroying employee morale and motivation?

Looking over the complaints of the Buzzbank employees, it is clear that most of the problems arose from the loss of autonomy that they had enjoyed prior to the implementation of the new processes. This being the case, any measure to increase autonomy should improve the situation. A couple of possibilities come to mind – both of which I have discussed in earlier pieces. These are:

1. Empower employees to make decisions that affect their work. This means allowing them the freedom to decide the best approach to solving problems (within limits specified by organisational and resource constraints).
2. In situations where (1) isn’t possible, one could use collaborative techniques such as dialogue mapping to achieve employee buy-in. Of course, management has to be prepared to engage in true dialogue, and be willing to act upon (reasonable) suggestions made by employees.

The key message is simple and obvious: the more of say employees have in making work-related decisions, the more engaged and motivated they’ll be. This is not just a warm and fuzzy notion, but one that is backed up by research on motivation (see this paper review, for example). Yes, this does mean letting go of the “reins of control” to an extent but it is clear, as highlighted by Hodgson’s work, that holding the reins tightly might cause more problems that it solves. What’s called for, above all, is a degree of flexibility:  use project management processes by all means, but be open to employee input as to what’s working well and what’s not.

To sum up:  Hodgson’s case study suggests that inflexible project management based approaches to managing creative work  may not work as well as advertised by purveyors of frameworks and methodologies. As an alternative,  it might be worth taking a step towards the utopian ideal of a post-bureaucratic organisation  by using techniques that encourage employee input in organisational decision making.

Introduction 

Conventional approaches to knowledge management on projects focus on  the cognitive (or thought-related) and mechanical  aspects of knowledge creation and capture. There is alternate view, one which considers knowledge as being created through interactions between people who –  through their interactions -  develop mutually acceptable interpretations of theories and facts in ways that suit their particular needs. That is, project knowledge is socially constructed. If this is true, then project managers need to pay attention to the environmental and social factors that influence knowledge construction.  This is the position taken by Paul Jackson and Jane Klobas in their paper entitled, Building knowledge in projects: A practical application of social constructivism to information systems development, which presents a  knowledge creation / sharing process model based social constructivist theory. This article is a summary and review of the paper.

 A social constructivist view of knowledge

Jackson and Klobas begin with the observation that engineering disciplines are founded on the belief that knowledge can be expressed in propositions that correspond to a reality which  is independent of human perception.  However, there is an alternate view that knowledge is not absolute, but relative – i.e.  it depends on the mental models and beliefs used to interpret facts, objects and events. A  relevant example is how a software product is viewed by business users and software developers. The former group may see an application in terms of its utility whereas the latter may see it as an instance of a particular technology. Such perception gaps can also occur within seemingly homogenous groups – such as teams comprised of software developers, for example. This can happen for a variety of reasons such as the differences in the experience and cultural backgrounds of those who make up the group. Social constructivism looks at how such gaps can be bridged.

The authors’ discussion relies on the work of Berger and Luckmann, who described how the gap between perceptions of different individuals can be overcome to create a socially constructed, shared reality. The phrase “socially constructed” implies that reality (as it pertains to a project, for example) is created via a common understanding of issues, followed by mutual agreement between all the players as to what comprises that reality. For me this view strikes a particular chord because of it is akin to the stated aims of dialogue mapping, a technique that I have described in several earlier posts (see this article for an example relevant to projects).

 Knowledge in information systems development as a social construct

 First up, the authors make the point that information systems development (ISD) projects are:

 …intensive exercises in constructing social reality through process and data modeling. These models are informed with the particular world-view of systems designers and their use of particular formal representations. In ISD projects, this operational reality is new and explicitly constructed and becomes understood and accepted through negotiated agreement between participants from the two cultures of business and IT

 Essentially, knowledge emerges  through interaction and discussion   as the project proceeds.  However, the methodologies used in design are typically founded on an engineering approach, which takes a positivist view rather than a social one. As the authors suggest,

Perhaps the social constructivist paradigm offers an insight into continuing failure, namely that what is happening in an ISD project is far more complex than the simple translation of a description of an external reality into instructions for a computer. It is the emergence and articulation of multiple, indeterminate, sometimes unconscious, sometimes ineffable realities and the negotiated achievement of a consensus of a new, agreed reality in an explicit form, such as a business or data model, which is amenable to computerization.

With this in mind, the authors aim to develop a model that addresses the shortcomings of the traditional, positivist view of knowledge in ISD projects. They do this by representing Berger and Luckmann’s theory of social constructivism in terms of a knowledge process model. They then identify management principles that map on to these processes. These principles form the basis of a survey which is used as an operational version of the process model. The operational model is then assessed by experts and tested by a project manager in a real-life project.

The knowledge creation/sharing process model

The process model that Jackson and Klobas describe is based on Berger and Luckmann’s work.

The model  describes how personal knowledge is created – personal knowledge being what an individual knows. Personal knowledge is built up using mental models of the world – these models are frameworks that individuals use to make sense of the world.

According to the Jackson-Klobas process model, personal knowledge is built up through a number of process including:

 Internalisation: The absorption of knowledge by an individual

 Knowledge creation: The construction of new knowledge through repetitive performance of tasks (learning skills) or becoming aware of new ideas, ways of thinking or frameworks. The latter corresponds to learning concepts and theories, or even new ways of perceiving the world. These correspond to a change in subjective reality for the individual.

 Externalisation: The representation and description of knowledge using speech or symbols so that it can be perceived and internalized by others. Think of this as explaining ideas or procedures to other individuals.

 Objectivation: The creation of a shared constructs that represent a group’s understanding of the world. At this point, knowledge is objectified – and is perceived as having an existence independent of individuals.

 Legitimation: The authorization of objectified knowledge as being “correct” or “standard.”

 Reification: The process by which objective knowledge assumes a status that makes it difficult to change or challenge. A familiar example of reified knowledge is any procedure or process that is “hardened” into a system – “That’s just the way things are done around here,” is a common response when such processes are challenged.

  The links depicted in the figure show the relationships between these processes.

 Jackson and Klobas suggest that knowledge creation in ISD projects is a social process, which occurs through continual communication between the business and IT. Sure, there are other elements of knowledge creation – design, prototyping, development, learning new skills etc. – but these amount to nought unless they are discussed, argued, agreed on and communicated through social interactions. These interactions occur in the wider context of the organization, so it is reasonable to claim that the resulting knowledge takes on a form that mirrors the social environment of the organization.

 Clearly, this model of knowledge creation is very different from the usual interpretation of knowledge having an independent reality, regardless of whether it is known to the group or not.

 An operational model

 The above is good theory, which makes for interesting, but academic, discussions. What about practice? Can the model be operationalised?  Jackson and Klobas describe an approach to creating to testing the utility (rather than the validity) of the model.  I discuss this in the following sections.

 Knowledge sharing heuristics

 To begin with, they surveyed the literature on knowledge management to identify knowledge sharing heuristics (i.e. experience-based techniques to enable knowledge sharing).  As an example, some of the heuristics associated with the externalization process were:

• We have standard documentation and modelling tools which make business requirements easy to understand
• Stakeholders and IS staff communicate regularly through direct face-to-face contact
• We use prototypes

 The authors identified more than 130 heuristics. Each of these was matched with a process in the model. According to the authors, this matching process was simple: in most cases there was no doubt as to which process a heuristic should be attached to. This suggests that the model provides a natural way to organize the voluminous and complex body of research in knowledge creation and sharing. Why is this important? Well, because it suggests that the conceptual model (as illustrated in Fig. 1) can form the basis for a simple means to assess knowledge creation / sharing capabilities in their work environments, with the assurance that they have all relevant variables covered.

 Validating the mapping

 The validity of the matching was checked using twenty historical case studies of ISD projects. This worked as follows: explanations for what worked well and what didn’t were mapped against the model process areas (using the heuristics identified in the prior step). The aim was to answer the question:   “is there a relationship between project failure and problems in the respective knowledge processes or, conversely, between project success and the presence of positive indicators?” 

 One of the case studies the authors use is the well-known (and possibly over-analysed) failure of the automated dispatch system for the London Ambulance Service.  The paper has a succinct summary of the case study, which I reproduce below: 

The London Ambulance Service (LAS) is the largest ambulance service in the world and provides accident and emergency and patient transport services to a resident population of nearly seven million people. Their ISD project was intended to produce an automated system for the dispatch of ambulances to emergencies. The existing manual system was poor, cumbersome, inefficient and relatively unreliable. The goal of the new system was to provide an efficient command and control process to overcome these deficiencies. Furthermore, the system was seen by management as an opportunity to resolve perceived issues in poor industrial relations, outmoded work practices and low resource utilization. A tender was let for development of system components including computer aided dispatch, automatic vehicle location, radio interfacing and mobile data terminals to update the status of any call-out. The tender was let to a company inexperienced in large systems delivery. Whilst the project had profound implications for work practices, personnel were hardly involved in the design of the system. Upon implementation, there were many errors in the software and infrastructure, which led to critical operational shortcomings such as the failure of calls to reach ambulances. The system lasted only a week before it was necessary to revert to the manual system.

 Jackson and Klobas show how their conceptual model maps to knowledge-related factors that may have played a role in the failure project. For example, under the heading of personal knowledge, one can identify at least two potential factors: lack of involvement of end-users in design and selection of an inexperienced vendor. Further, the disconnect between management and employees suggests a couple of factors relating to reification: mutual negative perceptions and outmoded (but unchallenged) work practices.

 From their validation, the authors suggest that the model provides a comprehensive framework that explains why these projects failed. That may be overstating the case – what’s cause and what’s effect is hard to tell, especially after the fact. Nonetheless, the model does seem to be able to capture many, if not all, knowledge-related gaps that could have played a role in these failures. Further, by looking at the heuristics mapped to each process, one might be able to suggest ways in which these deficiencies could have been addressed. For example, if externalization is a problem area one might suggest the use of prototypes or encourage face to face communication between IS and business personnel.

 Survey-based tool

 Encouraged by the above, the authors created a survey tool which was intended to evaluate knowledge creation/sharing effectiveness in project environments. In the tool, academic terms used in the model were translated into everyday language (for example, the term externalization was translated to knowledge sharing – see Fig 1 for translated terms). The tool asked project managers to evaluate their project environments against each knowledge creation process (or capability) on a scale of 1 to 10.   Based on inputs, it could recommend specific improvement strategies for capabilities that were scored low. The tool was evaluated by four project managers, who used it in their work environment over a period of 4-6 weeks. At the end of the period, they were interviewed and their responses were analysed using content analysis to match their experiences and requirements against the designed intent of the tool.  Unfortunately, the paper does not provide any details about the tool, so it’s difficult to say much more than paraphrase the authors comments.

 Based on their evaluation, the authors conclude that the tool provides:

1. A common framework for project managers to discuss issues pertaining to knowledge creation and sharing.
2. A means to identify potential problems and what might be done to address them.

 Field testing 

One of the evaluators of the model tested the tool in the field. The tester was a project manager who wanted to identify knowledge creation/sharing deficiencies in his work environment, and ways in which these could be addressed.  He answered questions based on his own evaluation of knowledge sharing capabilities in his environment and then developed an improvement plan based on strategies suggested by the tool along with some of his own ideas.  The completed survey and plan were returned to the researchers.

 Use of the tool revealed the following knowledge creation/sharing deficiencies in the project manager’s environment:

1. Inadequate personal knowledge.
2. Ineffective externalization
3. Inadequate standardization (objectivation)

Strategies suggested by the tool include:

1. An internet portal to promote knowledge capture and sharing. This included discussion forums, areas to capture and discuss best practices etc.
2. Role playing workshops to reveal how processes worked in practice (i.e. surface tacit knowledge).

Based on the above, the authors suggest that:

1. Technology can be used to promote support knowledge sharing and standardization, not just storage.
2. Interventions that make tacit knowledge explicit can be helpful.
3. As a side benefit, they note that the survey has raised consciousness about knowledge creation/sharing within the team.

Reflections and Conclusions

In my opinion, the value of the paper lies not in the model or the survey tool, but the conceptual framework that underpins them – namely, the idea knowledge depends on, and is shaped by, the social environment in which it evolves. Perhaps an example might help clarify what this means. Consider an organisation that decides to implement project management “best practices” as described by <fill in any of the popular methodologies here>. The wrong way to do this would be to implement practices wholesale, without regard to organizational culture, norms and pre-existing practices. Such an approach is unlikely to lead to the imposed practices taking root in the organisation. On the other hand, an approach that picks the practices that are useful and tailors these to organizational needs, constraints and culture is likely to meet with more success. The second approach works because it attempts to bridge gap between the “ideal best practice” and social reality in the organisation. It encourages employees to adapt practices in ways that make sense in the context of the organization. This invariably involves modifying practices, sometimes substantially, creating new (socially constructed!) knowledge in the bargain. 

Another interesting point the authors make is that several knowledge sharing heuristics (130, I think the number was) could be classified unambiguously under one of the processes in the model. This suggests that the model is a reasonable view of the knowledge creation/sharing process. If one accepts this conclusion, then the model does indeed provide a common framework for discussing issues relating knowledge creation in project environments. Further, the associated heuristics can help identify processes that don’t work well.

  I’m unable to judge the usefulness of the survey-based tool developed by the authors because they do not provide much detail about it in the paper. However, that isn’t really an issue;  the field of project management has too many “tools and techniques” anyway.  The key message of the paper, in my opinion, is the that every project has a unique context, and that the techniques used by others have to be interpreted and applied in ways that are meaningful in the context of the particular project. The paper is an excellent counterpoint to the methodology-oriented practice of knowledge management in projects; it should be required reading for methodologists and  project managers who believe that things need to be done by The Book, regardless of social or organizational context.

Over the last few months I’ve written a number of posts on IBIS (short for Issue Based Information System), an argument visualisation technique invented in the early 1970s by Horst Rittel and Werner Kunz.  IBIS is best known for its use in dialogue mapping – a collaborative approach to tackling wicked problems – but it has a range of other applications as well (capturing project knowledge is a good example).    All my prior posts on IBIS focused on its use in specific applications.   Hence the present piece,  in which I discuss the “what” and “whence”  of IBIS:  its practical aspects – notation, grammar etc. –   along with  its origins, advantages and limitations

I’ll begin with a brief introduction to the technique (in its present form) and then move on to its origins and other aspects.

 A brief introduction to IBIS 

 IBIS  consists of three main elements: 

1. Issues (or questions): these are issues that need to be addressed.
2. Positions (or ideas): these are responses to questions. Typically the set of ideas that respond to an issue represents the spectrum of perspectives on the issue.
3. Arguments: these can be Pros (arguments supporting) or Cons (arguments against) an issue. The complete  set of arguments that respond to an idea represents the multiplicity of viewpoints on it.

The best IBIS mapping tool is Compendium – it can be downloaded here.  In Compendium, the IBIS elements described above are represented as nodes as shown in Figure 1: issues are represented by green question nodes; positions by yellow light bulbs; pros by green + signs and cons by red – signs.  Compendium supports a few other node types,  but these are not part of the core IBIS notation. Nodes can be linked only in ways specified by the IBIS grammar as I discuss next.

The IBIS grammar can can be summarized in a few simple rules: 

1. Issues can be raised anew or can arise from other issues, positions or arguments. In other words, any IBIS element can be questioned.  In Compendium notation:  a question node can connect to any other IBIS node.
2. Ideas can only respond to questions – i.e.  in Compendium “light bulb” nodes  can only link to question nodes. The arrow pointing from the idea to the question depicts the “responds to” relationship.
3. Arguments  can only be associated with ideas -  i.e in Compendium + and –  nodes can only link to “light bulb” nodes (with arrows pointing to the latter)

 The legal links are summarized in Figure 2 below.

The rules are best illustrated by example-   follow the links below to see some illustrations of IBIS in action:

1. See this post for a simple example of dialogue mapping.
2. See this post or this one for examples of argument visualisation .
3. See this post for the use IBIS  in capturing project knowledge.

Now that we know how IBIS works and have seen a few examples of it in action, it’s time to trace its history from its origins to the present day. 

Wicked origins

A good place to start is where it all started. IBIS was first described in a paper entitled, Issues as elements of Information Systems; written by Horst Rittel (who coined the term “wicked problem”) and Werner Kunz in July 1970. They state the intent behind IBIS in the very first line of the abstract of their paper:

Issue-Based Information Systems (IBIS) are meant to support coordination and planning of political decision processes. IBIS guides the identification, structuring, and settling of issues raised by problem-solving groups, and provides information pertinent to the discourse.

Rittel’s preoccupation was the area of public policy and planning – which is also the context in which he defined wicked problems originally.  He defined the term in his landmark paper of 1973 entitled, Dilemmas in  a General Theory of Planning. A footnote to the paper states that it  is based on an article that he   presented at an AAAS meeting in 1969. So it is clear that he had already formulated his ideas on wickedness when he wrote his paper on IBIS in 1970.

 Given the above background it is no surprise that Rittel and Kunz foresaw IBIS to be the:

…type of information system meant to support the work of cooperatives like governmental or administrative agencies or committees, planning groups, etc., that are confronted with a problem complex in order to arrive at a plan for decision…

The problems tackled by such  cooperatives are paradigm-defining examples of wicked problems. From the start, then, IBIS was intended as a tool to facilitate a collaborative approach to solving such problems.

 Operation of early systems

 When Rittel and Kunz wrote their paper, there were three IBIS-type systems in operation: two in governmental agencies (in the US, one presumes) and one in a university environment (possibly, Berkeley, where Rittel worked). Although it seems quaint and old-fashioned now, it is no surprise that they were all manual, paper-based systems- the effort and expense involved in computerizing such systems in the early 70s would have been prohibitive, and the pay-off questionable.

 The paper also offers a short description of how these early IBIS systems operated:

An initially unstructured problem area or topic denotes the task named by a “trigger phrase” (“Urban Renewal in Baltimore,” “The War,” “Tax Reform”). About this topic and its subtopics a discourse develops. Issues are brought up and disputed because different positions (Rittel’s word for ideas or responses) are assumed. Arguments are constructed in defense of or against the different positions until the issue is settled by convincing the opponents or decided by a formal decision procedure. Frequently questions of fact are directed to experts or fed into a documentation system. Answers obtained can be questioned and turned into issues. Through this counterplay of questioning and arguing, the participants form and exert their judgments incessantly, developing more structured pictures of the problem and its solutions. It is not possible to separate “understanding the problem” as a phase from “information” or “solution” since every formulation of the problem is also a statement about a potential solution.

 Even today, forty years later, this is an excellent description of how IBIS is used to facilitate a common understanding of complex (or wicked) problems. The paper contains an overview of the structure and operation of manual IBIS-type systems. However, I’ll omit these because they are of little relevance in the present-day world.

As an aside, there’s a  term that’s conspicuous by its absence in the Rittel-Kunz paper: design rationale. Rittel must have been aware of the utility of IBIS in capturing design rationale: he was a professor of design science at Berkley and design reasoning was one of his main interests. So it is somewhat odd that  he does not mention this term – even once –  in his IBIS  paper.   

Fast forward a couple decades (and more!)

 In a paper published in 1988 entitled, gIBIS: A hypertext tool for exploratory policy discussion, Conklin and Begeman describe a prototype of a graphical, hypertext-based  IBIS-type system (called gIBIS) and its use in capturing design rationale (yes, despite the title of the paper, it is more about capturing design rationale than policy discussions). The development of  gIBIS represents a key step between the original Rittel-Kunz version of IBIS and its  present-day version as implemented  in Compendium.  Amongst other things, IBIS was finally off paper and on to disk, opening up a new world of possibilities.

gIBIS aimed to offer users:

1. The ability to capture design rationale – the options discussed (including the ones rejected) and the discussion around the pros and cons of each.
2. A platform for promoting computer-mediated collaborative design work  – ideally in situations where participants were located at sites remote from each other.
3. The ability to store a large amount of information and to be able to navigate through it in an intuitive way.

 Before moving on, one point needs to be emphasized: gIBIS was intended to be used in collaborative settings; to help groups achieve a shared understanding of central issues, by mapping out dialogues in real time. In present-day terms – one could say that it was intended as a tool for sense making.

 The gIBIS prototype proved successful enough to catalyse the development of Questmap, a commercially available software tool that supported IBIS. However, although there were some notable early successes in the real-time use of IBIS in industry environments (see this paper, for example), these were not accompanied by widespread adoption of the technique. Other graphical, IBIS-like methods to capture design rationale were proposed (an example is Questions, Options and Criteria (QOC) proposed by MacLean et. al. in 1991), but these too met with a general reluctance in adoption.

 Making sense through IBIS

 The reasons for the lack of traction of IBIS-type techniques in industry are discussed in an excellent paper by Shum et. al. entitled, Hypermedia Support for Argumentation-Based Rationale: 15 Years on from gIBIS and QOC.  The reasons they give are: 

1. For acceptance, any system must offer immediate value to the person who is using it. Quoting from the paper, “No designer can be expected to altruistically enter quality design rationale solely for the possible benefit of a possibly unknown person at an unknown point in the future for an unknown task. There must be immediate value.” Such immediate value is not obvious to novice users of IBIS-type systems.
2. There is some effort involved in gaining fluency in the use of IBIS-based software tools. It is only after this that users can gain an appreciation of the value of such tools in overcoming the limitations of mapping design arguments on paper, whiteboards etc.

 The intellectual effort – or cognitive overhead, as it is called in academese – in using IBIS in real time involves: 

1. Teasing out issues, ideas and arguments from the dialogue.
2. Classifying points raised into issues, ideas and arguments.
3. Naming (or describing) the point succinctly.
4. Relating (or linking) the point to an existing node.

This is a fair bit of work, so it is no surprise that beginners might find it hard to use IBIS to map dialogues. However, once learnt, a skilled practitioner can add value to design (and more generally, sense making) discussions in several ways including: 

1. Keeping the map (and discussion) coherent and focused on pertinent issues.
2. Ensuring that all participants are engaged in contributing to the map (and hence the discussion).
3. Facilitating useful maps (and dialogues) – usefulness being measured by the extent to which the objectives of the session are achieved. 

See this paper by Selvin and Shum for more on these criteria. These criteria are a qualitative measure of how well a group achieves a shared understanding of the problem under discussion. 

Clearly, there is a good deal of effort involved in learning and becoming proficient at using IBIS-type systems, but the payoff is an ability to facilitate  a shared understanding of wicked problems – whether in public planning or in technical design.

 Why IBIS is better than conventional modes of documentation

 IBIS has several advantages over conventional documentation systems. Rittel and Kunz recognized these; their 1970  paper contains a nice summary of these, which I paraphrase below: 

1. IBIS can bridge the gap between discussions and records of discussions (minutes, audio/video transcriptions etc,). IBIS sits between the two, acting as a short term memory. The paper thus foreshadows the use of issue-based systems as an aid to organizational or project memory.
2. Many elements (issue, ideas or arguments) that come up in a discussion have contextual meanings that are different from any pre-existing definitions. In discussions, contextual meaning is more than formal meaning. IBIS  captures the former in a very clear way – for example a response to a question “What do we mean by X? elicits the meaning of X in the context of the discussion, which is then subsequently captured as an idea (position)”.
3.  Related to the above, the commonality of an issue with other, similar issues might be more important than its precise meaning. To quote from the paper, “…the description of the subject matter in terms of librarians or documentalists (sic) may be less significant than the similarity of an issue with issues dealt with previously and the information used in their treatment…”  With search technologies available, this is less of an issue now. However, search technologies are still limited in terms of finding matches between “similar” items (How is “similar” defined? Ans: it depends on context). A properly structured, context-searchable IBIS-based project archive may still be more useful than a conventional document archive based on a document management system.
4. The reasoning used in discussions is made transparent, as is the supporting (or opposing) evidence. (see my post on visualizing argumentation for example)
5. The state of the argument (discussion) at any time can be inferred at a glance (unlike the case in written records). See this post for more on the advantages of visual documentation over prose.  

Issues with issue-based information systems

 Lest I leave readers with the impression that IBIS is a panacea, I should state that it isn’t. According to Conklin, IBIS maps have the following limitations:

1. They atomize streams of thought into unnaturally small chunks of information thereby breaking up any smooth rhetorical flow that creates larger, more meaningful chunks of narrative.
2. They disperse rhetorically connected chunks throughout a large structure.
3. They are not is not chronological in structure (the chronological sequence is normally factored out);
4. Contributions are not attributed (who said what is normally factored out).
5. They do not convey the maturity of the map – one cannot distinguish, from the map alone, whether one map is more “sound” than another.
6. They do not offer a systematic way to decide if two questions are the same, or how the maps of two related questions relate.

Some of these issues (points 3, 4) can be addressed by annotating nodes;  others are not so easy to solve.

Concluding remarks

My aim in this post has been to introduce readers to the IBIS notation, and also discuss its origins, development and limitations.  On one hand, a knowledge of the origins and development  is valuable because it  gives  insight into the rationale behind the technique, which leads to a better understanding of the different ways in which it can be used. On the other hand, it is also important to know a technique’s limitations,  if for no other reason than to be aware of these so that one can work around them.  

Before signing off, I’d like to mention an observation from my experience with IBIS. The real surprise for me has been that the technique can capture most written arguments and discussions,  despite having only three distinct elements and a very simple grammar. Yes, it does require some thought to do this, particularly when mapping discussions in real time. However,  this cognitive “overhead”  is good because  it forces the mapper to think  about what’s being said  instead of just writing it down blind. Thoughtful transcription is the aim of the game. When done right, this results in a map that truly reflects a  shared understanding of the complex  (and possibly wicked) problem under discussion.

There’s no better coda to this post on IBIS than the following quote from  this paper by Conklin:

…Despite concerns over the years that IBIS is too simple and limited on the one hand or too hard to use on the other, there is a growing international community who are fluent enough in IBIS to facilitate and capture highly contentious debates using dialogue mapping, primarily in corporate and educational environments…

For me that’s reason enough to improve my understanding of IBIS and its applications,  and to look for opportunities to use it in ever more challenging situations.

Introduction

One of the standard ways of characterising risk on projects is to use matrices which categorise risks by impact and probability of occurrence.  These matrices provide a qualitative risk ranking in categories such as high, medium and low (or colour: red, yellow and green). Such rankings are often used to prioritise and allocate resources to manage risks. There is a widespread belief that the qualitative ranking provided by matrices reflects an underlying quantitative ranking.  In a paper entitled, What’s wrong with risk matrices?, Tony Cox shows that the qualitative risk ranking provided by a risk matrix will agree with the quantitative risk ranking only if the matrix is constructed according to certain general principles. This post is devoted to an exposition of these principles and their consequences. 

Since the content of this post may seem overly academic to some of my readers, I think it is worth clarifying why I believe an understanding of Cox’s principles is important for project managers. First, 3×3 and 4×4 risk matrices are widely used in managing project risk.  Typically these matrices are constructed in an intuitive (but arbitrary) manner. Cox shows – using very general assumptions – that there is only one sensible colouring scheme (or form) of these matrices. This conclusion was surprising to me, and I think that many readers may also find it so. Second, and possibly more important, is that the arguments presented in the paper show that it is impossible to maintain perfect congruence between qualitative (matrix) and quantitative rankings. As I discuss later, this is essentially due to the impossibility of representing quantitative rankings accurately on a rectangular grid. Developing an understanding of these points will enable project managers to use risk matrices in a more logically sound manner. 

 Background and preliminaries

 Let’s begin with some terminology that’s well known to most project managers:

 Probability: This is the likelihood that a risk will occur. It is quantified as a number between 0 (will definitely not occur) and 1 (will definitely occur).

 Impact (termed “consequence” in the paper): This is the severity of the risk should it occur. It can also be quantified as a number between 0 (lowest severity) and 1(highest severity).

 Note that the above scales for probability and impact are arbitrary – other common choices are percentages or a scale of 0 to 10.

 Risk:  In many project risk management frameworks, risk is characterised by the formula: Risk = probability x impact.  This formula looks reasonable, but is typically specified a priori, without any justification.

A risk can be plotted on a two dimensional graph depicting impact (on the x-axis) and probability (on the y-axis). This is typically where the problems start: for most risks, neither the probability nor the impact can be accurately quantified. The standard solution is to use a qualitative scale, where instead of numbers one uses descriptive text – for example, the probability, impact and risk can take on one of three values: high, medium and low (as shown in Figure 1 below).  In doing this,  analysts make the implicit assumption that the categorisation provided by the qualitative assessment ranks the risks in correct quantitative order. Problem is, this isn’t true.

Let’s look at the simple case of two risks A and B ranked on a 2×2 risk matrix shown in Figure 2 below.  Let’s assume that the probability and impact of each of the two risks are independent and uniformly distributed between 0 and 1. Clearly, if the two risks have the same qualitative ranking (high, say), there is no way to rank them correctly unless one has quantitative knowledge of probability and impact – which is usually not the case. In the absence of this information, there’s a 50% chance (all other factors being equal) of ranking them correctly - i.e.  one is effectively “flipping a coin” to choose which one has the higher (or lower) rank. This situation highlights a shortcoming of risk matrices: poor resolution. It is not possible to rank risks that have the same qualitative ranking.

“That’s obvious,” I hear  you say – and you’re right. But there’s more:  if one of the ratings is medium and the other one is not (i.e. the other one is high or low), then there is a non-zero chance of making an incorrect ranking because some points in the cell with the higher qualitative rating have a lower quantitative value of risk than some points in the cell with the lower qualitative ranking. Look at that statement again: it implies that risk matrices can incorrectly assign higher qualitative rankings to quantitatively smaller risks – i.e. there is the possibility of making ranking errors.  This point is seriously counter-intuitive (to me anyway) and merits a proof, which Cox provides and I  discuss below.  Before doing so, I should also point out that the discussion of this paragraph assumes that the probabilities and impacts of the two risks are independent and uniformly distributed. Cox also points out that the chance of making the wrong ranking can be even higher if the joint distribution of the two are correlated. In particular, if the correlation is negative (i.e. probability decreases as impact increases), a random ranking is actually better than that provided by the risk matrix. In this situation the information provided by risk matrices is “worse than useless” (a random choice is better!).  Negative correlations between probability and impact are actually quite common – many situations involve a mix of high probability-low impact and low probability-high impact risks. See the paper for more on this.

 Weak consistency and its implications

 With the issues of poor resolution and ranking errors established, Cox asks the question: What can be salvaged?  The underlying problem is that the joint distribution of probability and impact is unknown. The standard approach to improving the utility of risk matrices is to attempt to characterise this distribution. This can be done using artificial intelligence tools – and Cox provides references to papers that use some of these techniques to characterise distributions. These techniques typically need plentiful data as they attempt to infer characteristics of the joint distribution from data points. Cox, instead, proposes an approach that is based on general properties of risk matrices – i.e. an approach that prescribes a set of rules that ensure consistency. This has the advantage of being general,  and not depending on the availability of data points to characterise the probability distribution.

 So what might a consistency criterion look like? Cox suggests that, at the very least, a risk matrix should be able to distinguish reliably between very high and very low risks. He formalises this requirement in his definition of weak consistency, which I quote from the paper:

 A risk matrix with more than one “colour” (level of risk priority) for its cells satisfies weak consistency with a quantitative risk interpretation if points in its top risk category (red) represent higher quantitative risks than points in its bottom category (green)

 The notion of weak consistency formalises the intuitive expectation that a risk matrix must, at the very least, distinguish  between the lowest and highest (quantitative) risks.  If it can’t, it is indeed “worse than useless”.  Note that weak consistency doesn’t say anything about distinguishing between medium and lowest/highest risks – merely between the lowest and highest.

 Having defined weak consistency, Cox derives some of its surprising consequences, which I describe next.

 Cox’s First Lemma:  If a risk matrix satisfies weak consistency, then no red cell (highest risk category) can share an edge with a green cell (lowest risk category).

 Proof:  To see how this is plausible, consider the different ways in which a red cell can adjoin a green one. Basically there are only two ways in which this can happen, which I’ve illustrated in Figure 3. Now assume that the quantitative risk of the midpoint of the common edge is a number n (n between 0 and 1). Then if x and y and are the impact and probability, we have

  xy=n or y=n/x

 So, the locus of all points having the same risk (often called the iso-risk contour) as the midpoint is a rectangular hyperbola with negative slope (i.e.  y decreases as x increases). The negative slope (see Figure 3) implies that the points above the iso-risk contour in the green cell have a higher quantitative risk than points below the contour in the red cell. This contradicts weak consistency. Hence - by reductio ad absurdum –  it isn’t possible to have a green cell and a red cell with a common edge. 

Cox’s Second Lemma: if a risk matrix satisfies weak consistency and has at least two colours (green in lower left and red in upper right, if axes are oriented to depict increasing probability and impact), then no red cell can occur in the bottom row or left column of the matrix.

 Proof:  Assume it is possible to have a red cell in the bottom row or left column. Now consider an iso-risk contour for a sufficiently small risk (i.e. a contour that passes through the lower left-most green cell). By the properties of rectangular hyperbolas, this contour must pass through all cells in the bottom row and the left-most column, as shown in Figure 4. Thus, by an argument similar to the one of the previous lemma, all points below the iso-risk contour in either of the red cells have a smaller quantitative risk than point above it in the green cell. This violates weak consistency, and hence the assumption is incorrect.

 An implication that follows directly from the above lemmas is that any risk matrix that satisfies weak consistency must have at least three colours!  

Surprised? I certainly was when I first read this.

Between-ness and its implications

If a risk matrix provides a qualitative representation of the actual qualitative risks, then small changes in the probability or impact should not cause discontinuous jumps in risk categorisation from lowest to highest category without going through the intermediate category. (Recall, from the previous section, that a weakly consistent matrix must have at least three colours). 

This expectation is formalised in the axiom of between-ness:

 A risk matrix satisfies the axiom of between-ness if every positively sloped line segment that lies in a green cell at its lower end and a red cell at its upper end must pass through at least one intermediate cell (i.e. one that is neither red nor green).

By definition, no 2×2 cell can satisfy between-ness. Further, amongst 3×3 matrices, only one colour scheme satisfies both weak consistency and between-ness. This is the matrix shown in Figure 1: green in the lower left-most cell, red in upper right-most cell and yellow in all other cells. This, to me, is a truly amazing consequence of a couple of simple,  intuitive axioms.

 Consistent colouring and its implications

 The basic idea behind consistent colouring is that risks that have the identical quantitative values should have the same qualitative ratings. This is impossible to achieve in a discrete risk matrix because iso-risk contours cannot coincide with cell boundaries (Why? Because  iso-risk contours have negative slopes whereas cell boundaries have zero or infinite slope  – i.e. they are horizontal or vertical lines).  So, Cox suggests the following: enforce consistent colouring for extreme categories only – red and green – allowing violations for intermediate categories.  What this means is that cells that contain iso-risk contours which pass through other red cells (“red contours”) must be red and cells that contain iso-risk contours which pass through other green cells (“green contours”) must be green. Hence the following definition of consistent colouring: 

A cell is red if it contains points with quantitative risks at least as high as those in other red cells, and does not contain points with quantitative risks as small as those on any green cell.

A cell is green if it contains points with risks at least as small as those in other green cells, and does not contain points with quantitative risks as high as those in any red cell.

A cell has an intermediate colour only if it a) lies between a red cell and a green cell or b) it contains points with quantitative risks higher than those in some red cells and also points with quantitative risks lower than those in some green cells.

 An iso-risk contour is green if it passes through one or more green cells but no red cells and a red contour is one which passes through one or more red cells but no green cells. Consistent colouring then implies that cells with red contours and no green contours are red; and cells with green contours and no red contours are green (and, obviously, cells with contours of both colours are intermediate)

 Implications of the three axioms – Cox’s Risk Matrix Theorem

 So, after a longish journey, we have three axioms: weak consistency, between-ness and consistent colouring. With that done, Cox rolls out his theorem – which I dub Cox’s Risk Matrix Theorem (not to be confused with Cox’s Theorem from statistics!), which can be stated as follows:

 In a risk matrix satisfying weak consistency, between-ness and consistent colouring: 

a)      All cells in the leftmost column and in the bottom row are green.

b)      All cells in the second column from the left and the second row from the bottom are non-red. 

The proof is a bit long, so I’ll omit it, making a couple of plausibility arguments instead: 

1. The lower leftmost cell is green (by definition), and consistent colouring implies that all contours that lie below the one passing through the upper right corner of this cell must also be green because a) they pass through the lower leftmost cell which is green and b) none of the other cells they pass through are red (by Cox’s second lemma). The other cells on the lowest or leftmost edge of the matrix can only be intermediate or green. That they cannot be intermediate is a consequence of  between-ness.
2. That the second row and second column must be non-red is also easy to see: assume any of these cells to be red. We then have a red cell adjoining a green cell, which violates between-ness.

 I’ll leave it at that, referring the interested reader to the paper for a complete proof.

 Cox’s theorem has an immediate corollary which is particularly interesting for project managers who use 3×3 and 4×4 risk matrices: 

A tricoloured 3×3 or 4×4 matrix that satisfies weak consistency, between-ness and consistent colouring can have only the following (single!) colour scheme:

a)      Leftmost column and bottom row coloured green.

b)      Top right cell (for 3×3) or four top right cells (for 4×4) coloured red.

c)      All other cells coloured yellow.

 
Proof:  Cox’s theorem implies that the leftmost column and bottom row are green. The top right cell must be red (since it is a tricoloured matrix). Consistent colouring implies that the two cells adjoining this cell (in a 4×4 matrix) and the one diagonally adjacent must also be red (this cannot be so for a 3×3 matrix because these cells would adjoin a green cell which violates Cox’s first lemma). All other cells must be yellow by between-ness.

This result is quite amazing. From three very intuitive axioms Cox derives essentially the only possible colouring scheme for 3×3 and 4×4 risk matrices.

Conclusion

This brings me to the end of this post on the Cox’s axiomatic approach to building logically consistent risk matrices.  I highly recommend reading the original paper for more. Although it presents some fairly involved arguments, it is very well written. The arguments are presented with clarity and logical surefootedness,  and the assumptions underlying each argument are clearly laid out.  The three principles (or axioms) proposed are intuitively appealing – even obvious – but their consequences are quite unexpected (witness the unique colouring scheme for 3×3 and 4×4 matrices). Further, the arguments leading up to the lemmas and theorems bring up points that are worth bearing in mind when using risk matrices in practical situations.

 In closing I should mention that the paper also discusses some other limitations of risk matrices that flow from these principles: in particular, spurious risk resolution and inappropriate resource allocation based on qualitative risk categorisation.   For reasons of space, and the very high likelihood that I’ve already tested my readers’ patience to near (if not beyond) breaking point,  I’ll defer a discussion of these to a future post.

Introduction

One consequence of the increasing awareness of knowledge as an organisational asset is that many organisations have launched projects aimed at managing knowledge.  Unfortunately, a large number of these efforts focus entirely on technical solutions, neglecting the need for employee participation. The latter is important; as  stated in this paper, published a decade ago, “Knowledge transfer is about connection not collection, and that connection ultimately depends on choice made by individuals…”  This suggests that participant motivation is a key success factor for knowledge management initiatives. A recent paper entitled, Considering Participant Motivation in Knowledge Management Projects, by Allen Whittom and Marie-Christine Roy looks at theories of motivation from the context of knowledge management projects. This post is a summary and annotated review of the paper.

Many researchers claim that the failure rate of knowledge management projects is high, but there seems to be some confusion as to just how high the figure is (see this paper, for example). In the introduction to their paper, Whittom and Roy claim that the failure rate may be higher than 80% – but they offer no proof. Still, with many independent researchers quoting figures ranging from 50 to 80%, one can take it as established that it is a matter that merits investigation. Accordingly, many researchers have looked at causes of failure of knowledge management projects (see this paper or this one).  Some specifically identify lack of participant motivation as a cause of failure (see this paper or this one). Whittom and Roy claim that despite the work done thus far, knowledge management research does not provide any suggestions as to how motivation is to be managed in such projects. Their aim, therefore, is to:

1. Present concepts from theories of  motivation that are relevant to knowledge management projects.
2. Propose ways in which project managers can foster participant motivation in a way that is consistent with business objectives.

These points are covered in the next two sections. The final section presents some concluding remarks.

 Theoretical Overview                                    

 Motivation and Knowledge Transfer

The authors define motivation as the underlying reason(s) for a person’s actions. Motivation is usually classified as extrinsic or intrinsic depending on whether its source is external or internal to the individual. People who are extrinsically motivated are driven by rewards such as bonuses or promotions. Typically such individuals work for rewards. On the other hand intrinsically motivated individuals are self-driven, and need little supervision. Their enthusiasm, however, depends on whether or not their personal goals are congruent with the task at hand. This is important: their aims and objectives may not always be aligned with business goals. Further, intrinsically motivated individuals perform creative or complex tasks better than others, but this type of motivation varies greatly from one person to another and cannot be controlled by management. See my post on motivation in project management for a comprehensive discussion on extrinsic and intrinsic motivation.

The authors then discuss the link between motivation and the willingness to share knowledge. Knowledge falls into two categories: tacit and explicit. Tacit knowledge is hard to codify and communicate (e.g. a skill, such as riding a bicycle) whereas explicit knowledge can be formalised and transmitted (e.g. how to open a bank account). Tacit knowledge is in “people’s heads” and is consequently harder to capture. More often than not, though, it turns out to be more valuable than explicit knowledge. In their paper entitled, Motivation, Knowledge Transfer and Organisational Forms,  Osterloh and Frey state that, “…Intrinsic motivation is crucial when tacit knowledge in and between teams must be transferred…” Following this work, Gartner researchers Morello and Caldwell proposed a model in which intrinsic motivation drives the creation and sharing of tacit knowledge which in turn drives the dissemination and use of tacit knowledge in the organisation (I couldn’t find a publicly available copy of their work – but there is an illustration of the model in  Figure 1 Whittom and Roy’s paper).  

The message from motivation research is clear: intrinsic motivation is critical to the success of knowledge management projects.

Rewards and Recognition

Rewards and recognition are “levers of motivation”: they can be used to enhance and direct employee motivation towards achieving organisational goals. Reward systems are aimed at aligning individual efforts with organisational objectives. Recognition systems, on the other hand,  are designed to express public appreciation for high standards of achievement or competence. These may be set  according to criteria that diverge from preset objectives (as an example – a public thanks for a job well done can be made irrespective of whether the job is in line with company objectives)

Rewards can be extrinsic (not related to the task) or intrinsic (related to the task) and material or non-material.  Extrinsic rewards are typically material – i.e. they involve giving the recipient something tangible. Financial incentives are the most common form of extrinsic rewards because they are easily administered through the pay system.  Extrinsic rewards can also be non-financial (gift certificates or a meal at a nice restaurant, for example). For the same investment, non-financial rewards are found to have a more lasting effect than financial ones. This makes sense: people are more likely to remember a memorable meal than a few hundred dollar raise; the latter is sometimes forgotten as soon as it comes into effect. A downside of financial rewards is that they are easily forgotten and may actually decrease intrinsic motivation (see this paper by David Beswick). Another is that they may encourage sub-standard work, particularly in cases where benchmarks are based on volume rather than quality of output.

Extrinsic rewards can also be non-material – promotions and training opportunities, for example (see this paper by Wolfgang Semar for more on non-material, extrinsic rewards).

Intrinsic rewards generally pertain to the satisfaction derived from performing a task. The moral satisfaction arising from a job done well is also a form of intrinsic reward. It should be clear that these rewards work only for intrinsically motivated individuals. Intrinsic rewards are invariably non-material and they cannot be controlled by management.  However, awareness of factors influencing intrinsic motivation  can help managers create the right environment for intrinsically motivated individuals.  Kenneth Thomas, in his book entitled, Intrinsic Motivation at Work – Building Energy and Commitment, identifies four psychological factors that can influence intrinsic motivation. They are:

1. Feelings of accomplishment: These can be enhanced by devising interesting work tasks and aligning them with employee interests.
2. Feelings of autonomy: These can be enhanced by empowering employees with responsibility and authority to do their work.
3. Feelings of competence: These can be enhanced by offering employees opportunities to demonstrate and enhance their expertise.
4. Feelings of progress: These can be enhanced by fostering a collaborative atmosphere in which project successes are celebrated.

 These factors are (to an extent) under management control. If nothing else, it is worth being aware of them so that one can avoid doing things that might reduce intrinsic motivation.

Motivation crowding and psychological contracts

 The authors then examine the effects of rewards on intrinsic motivation in the context of knowledge management projects (Recall that intrinsic motivation was seen to be a key success factor in knowledge management projects).  They use motivation crowding theory to frame their discussion. Crowding theory suggests that intrinsic motivation can be enhanced (“crowded-in”) or undermined (or “crowded-out”) by external rewards.

To understand motivation crowding, one has to look at how extrinsic (or external) rewards work. Basically there are two ways in which an extrinsic reward can be perceived. To quote from the paper,

External interventions, such as rewards, may influence this perception either through information or control. If people see a reward as being related to their competence (information), intrinsic motivation for the task will be encouraged or maintained. On the other hand, if they see a reward as a way to control their performance or autonomy, intrinsic motivation would be decreased.

Extrinsic rewards can have a positive or negative effect on information and control. This is best understood through an example: consider a company that announces cash incentives for the top three contributors to a knowledge database. This reward has a positive control aspect (i.e. encourages participation) but a negative information aspect (i.e. no check on quality of contributions). Consequently, the reward encourages high volume of contributions with no regard to quality. This situation typically undermines or “crowds-out” intrinsic motivation. Note that motivation “crowding out” is sometimes referred to as motivation eviction in the literature.

Crowding-out is also seen in recurring tasks. For example, if a monetary incentive is offered for a task, there will be an expectation that the incentive be offered the next time around. On the other hand, non-monetary interventions such as increased employee involvement and autonomy in project decision making can “crowd-in” or enhance intrinsic motivation.

These effects are intuitively quite obvious, but it’s interesting to see them from a social science / economics point of view. If you’d like to find out more, I highly recommend the paper, Motivation crowding theory: A survey of empirical evidence, by Bruno Frey and Reto Jegen.

The take home lesson from the above is that intrinsic motivation can sometimes be negatively affected by external rewards. Manager, beware.

Whittom and Roy also discuss the notion of psychological contracts between the employer and employee. These contracts, distinct from formal employment contracts, refer to the unstated (but implied) informal, mutual obligations pertaining to respect, autonomy, work ethic, fairness etc. An employee’s intrinsic motivation can be greatly reduced if he or she perceives that the contract has been breached. For example, if an employee’s regarding improvements to a knowledge database are ignored, she might feel undervalued. In her eyes, management (and hence the organisation) has lost credibility, and the psychological contract has been violated. In psychological contract theory, personal relationships are seen to be  an important driver of intrinsic motivation: people are more likely to enjoy working in teams in which they have good relations with team members.

Discussion

Practices to foster intrinsic motivation

One conclusion from the aforementioned theories is that intrinsic motivation is essential for the transfer of tacit knowledge. Accordingly, the authors suggest the following practices to maintain and enhance intrinsic motivation of employees involved in knowledge management projects: 

1. Avoid the use of monetary rewards. Instead, use non-monetary rewards that recognize competence. Monetary rewards may also encourage the transfer of unimportant knowledge.
2. Involve employees in the formulation of project objectives.
3. Encourage team work and team bonding. A good team dynamic encourages the sharing of tacit knowledge. The technique of dialogue mapping facilitates the sharing and capture of knowledge in a team environment.
4. Emphasise how the employee might benefit from the project – this is the old WIIFM factor. This needs to be done in a way that shows how the benefit is integrated into the organisation’s culture – i.e. the benefit must be a realistic and believable one, else the employee will see right through it.
5. Good communication between management and employees. This one is a “usual suspect” that comes up in virtually all best practice recommendations. Unfortunately it is seldom done right.

Contextual recommendations based on knowledge and motivation types 

Theories of motivation indicate that, as far as motivation for knowledge sharing is concerned, one size does not fit all. The particular strategy used depends on the nature of the knowledge that is being captured (tacit or explicit), participants’ motivational drivers (intrinsic or extrinsic) and organizational resources. Based on this, the authors discuss the following contexts

1.  Tacit knowledge management / intrinsic motivation: This is an ideal situation. Here the manager’s role is to support participants in achieving project objectives rather than to influence their behaviour through rewards. Extrinsic rewards should be avoided because participants are intrinsically motivated.
2. Tacit knowledge management / extrinsic motivation: From the preceding discussion of motivation theories, it is clear that this is not a good situation. However, all is not lost. A manager can develop knowledge management strategies based on structured training, discussion groups etc. to help codify and transfer tacit knowledge. These strategies should highlight the project benefits (for the employee and the organisation). Further, extrinsic rewards can be offered, but their “crowding-out” effect over time should be kept in mind.
3. Explicit knowledge / intrinsic motivation:  Here the knowledge management aspect is easier because the knowledge is explicit. Typically, once the objectives are identified, it is clear how knowledge should be captured and organized. Obviously, structured training and tools such as Wikis and databases can help facilitate knowledge transfer. Further, these will be more effective than case (2) above, because the participants are intrinsically motivated.. Recommendations, as far as rewards are concerned are the same as in the first case.
4. Explicit knowledge / extrinsic motivation: For knowledge management the same considerations apply as in case (3). However, these strategies will be less effective because employees are extrinsically motivated. For rewards management, the considerations of case (2) apply.

As discussed above, the motivation strategy should be determined by whether the team members are intrinsically or extrinsically motivated. Unfortunately, though, the strategy often dictated by the culture of the organization – the manager may have little say in determining it. The authors do not discuss what a manager might do in such a situation.

Conclusion

 The paper presents no new data or analysis of existing data. As such it must be evaluated on the basis of new concepts and theoretical constructs that it presents. From this perspective  there’s little that’s new in this paper.   That said, project managers leading knowledge management projects might find the paper a worthwhile read because of  its coverage of motivation theories (crowding theory and psychological contracts, in particular). 

Let me end with an extrapolation of the above discussion to software projects. The holy grail of knowledge management initiatives is to capture tacit knowledge. By definition, this knowledge is difficult to codify.  One sees something similar in requirements gathering for application software. The analyst needs to capture all the explicit and tacit process knowledge that’s in users’ heads. The former is easy to capture; the latter isn’t. As a result requirements usually do not capture tacit process knowledge. This is one aspect of what Brooks referred to as the essential problem of software design – figuring out what the software really needs to do (see this post for more on Brooks’ argument). Well designed software embodies both kinds of knowledge, so software projects are knowledge management projects in a sense.  As far as motivation is concerned, therefore,  the theories and conclusions sketched above should apply to software projects.  An intrinsically motivated development team will  improve the chances of success greatly;  a trite statement perhaps, but one that may resonate with those who have had the privilege of working with such teams.