Tuesday, 30 January 2018

Portfolio knowledge: models of learning and knowledge sharing in project based organisations


Written by Bryan Fenech, Director - PPM Intelligence.

Note: This article is summary of a paper I delivered at a PMI Asia-Pacific Conference. The original conference paper is available from PMI here.

Introduction

A knowledge management dimension to, and perspective upon, project management has become increasingly prevalent in the project management literature in recent years. Increasingly, it has been recognised that projects, comprising “…teams of individuals from diverse organisations with different specialist knowledge … [working] together under time and budget constraints to produce a new product, process or service” (Reich, 2007), involve significant knowledge processing and are “rich with significant personal learning opportunities” (Sense, 2003). Sense (2003) presents a conception of project teams as “learning generators” where the members of different communities of practice interact to achieve a common objective. It is reasoned that team members, individually and collectively, must learn new knowledge, create new shared understandings, and transfer their knowledge to others “at the right times and for the right cost” (Reich, 2007).

A Quick Explanation of Key Knowledge Management Concepts


Positivist and Constructivist Epistemologies

Hold on: what the hell is an epistemology?

What is Epistemology?

Epistemology, or the theory of knowledge, is concerned about issues having to do with the nature, creation, dissemination and limits of knowledge. Assumptions and beliefs (worldviews) strongly influence approaches to personal and organisational learning and knowledge management.

Positivism

Positivism is just one kind of world view. It assumes that knowledge exists in the real world just like everyday objects such as houses and cars; knowledge is “out there”, residing in books, independent of thinking beings. This knowledge is a reflection of a correspondence to reality. Knowledge represents a real world that is thought of as existing, separate and independent from acts of knowing and “knowers”, and knowledge should be considered as true only if it correctly reflects the independent world. Positivism well and truly pervades the project management profession.

Constructivism

Over the last century, however, philosophers, cultural anthropologists, sociologists and knowledge management researchers have influenced our thinking to appreciate that knowledge is not absolute, but relative to cultures and contexts (Jackson & Klobas, 2007). A constructivist epistemology (or world view) sees knowledge as something that is constructed by people rather than as something that has some objective reality; knowledge and reality do not have an objective or absolute value or, at the least, we have no way of knowing this reality, as the only tools available to a “knower” are the senses. It is only through seeing, hearing, touching, smelling, and tasting that individuals build (or construct) a picture of the world.

To illustrate this, a systems development project can be seen as a process of social construction by the project team: “the knowledge embodied in information systems emerges as we proceed in the analysis and design of a business system … 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 new business or data model, which is amenable to computerisation.” (Jackson and Klobas, 2007). However, most contemporary design methodologies use the language of engineering, a discipline that “builds lasting structures of steel and concrete from pre-existing elements”, which may explain the high rate of failure in such projects.

Cognitive and Situated Learning Approaches


Cognitive Learning Approaches

The predominant approach to learning, underpinned by a positivist epistemology, focuses upon the cognitive dimensions of learning – i.e., the internal processes of the mind. This focus “includes those fabled items of "mental models" (Senge, 1990), single and double-loop learning and Model I and Model 2 type people (Argyris & Schon, 1978), and experiential-learning cycles (Kolb, 1984; Lewin, 1951)” (Sense, 2003). The emphasis of this approach is upon the psychological dimension of learning and it assumes that knowledge can be transferred between people independently of any particular social context, experience or practice. Learners are encouraged to view objects, events and phenomena with an “objective” mind. The meaning that is produced through thought processes is external and determined by the structure of the real world.

Situated Learning Approaches

On the other hand, informed by a constructivist epistemology, a focus on “the situated aspects of learning is concerned with the practical and social aspects of learning, assuming that most learning occurs on the job in culturally embedded ways within a community of practice … Situated learning evolves from the participation of people and the negotiated construction of their identities and common meanings within this community of practice” (Sense, 2003, p 6). Learners are encouraged to make sense of what is taught by trying to fit it with their previous experience.

Belline and Conico (2007, p 2) state that the “creation, diffusion and application of knowledge is situated and thus heavily influenced by the context of practice …the concept of doing is not only the element that characterises knowledge, but it becomes the way through which knowledge is manifested, converted and transferred”.

Communities of Practice


What is a Community of Practice?

Communities of practice have been defined as “groups of people who share a concern, a set of problems, or a passion about a topic, and who deepen their knowledge and expertise in this area by interacting on an ongoing basis” (Wenger et al, 2002, pp 4-5). Three interacting elements define a community of practice – a domain of knowledge, a community of people who care about this domain and the shared practice that they develop over time to be effective in their domain (Wenger et al, 2002, p 27). A domain sets the common ground and creates a sense of common identity for all community of practice participants. A community consists of a group of people who interact, build relationships, learn together, and in the process develop competence, a sense of belonging and mutual commitment and accountability. A practice embodies the history of the community and the knowledge it has developed over time, including historical or social resources and frameworks, ideas, tools, information, styles, language, stories, routines, and documents that the community develops, shares and maintains. Thus a community of practice represents a shared knowledge and a shared discourse that reflects a particular perspective on the world (Sense, 2003).

Project Teams and Communities of Practice

The PMBOK Guide™ defines a project as “[a] temporary endeavour undertaken to create a unique product or service”. Projects are non-routine processes and are ad hoc in nature. This combination of temporality, uniqueness (or specificity around predefined tasks and objectives) and non-routine processes contrasts a project team with a community of practice, where the emphasis is upon an ongoing domain and a shared practice. Additionally, the identities of project team members are forged externally to the project team. Garrety et al (2004, p 352) note that “projects are more clearly instrumental than communities of practice”.

On the other hand, while a project team is a very different creature to a community of practice, it is usually the case that project teams develop a common perspective on the world and negotiate shared meanings over time. It also follows that some of the social processes that lead to new knowledge in communities of practice are bound to exist in project teams, but will rarely if ever have the time dimension required to develop into a practice. This has lead Sense (2003) to posit that project teams should be considered as a type of “embryonic community of practice”.

Social and Morale Capital


The processes of learning and knowing depend heavily upon the availability of intangible forms of capital that are generated and leveraged 'in community' – in particular, social and morale capital (Dovey & Fenech, 2007). Social capital is a form of capital that is collectively owned by members of a 'network' characterized by strong relationship bonds and multiplex connections to other 'networks', and involves resources such as trust and voluntary cooperation between all those who hold a stake in the mission of the organization (Nahapiet & Ghoshal, 1998). Morale capital refers to resources such as passionate identification with, and commitment to, the purpose of the organization (Dovey & Singhota, 2005).

The most critical of these social capital resources is trust, as it underpins the capacity to leverage many of the other resources potentially available to a network either through its members or through its partner networks (connections) (Dovey & Fenech, 2007).

However, while trust is such an important resource in a knowledge economy, it is for many reasons rarely available in abundance in organizations (Putnam, 1993; 1995).

Applied Knowledge Management Problems in Project Management


Barriers to Learning within Projects


As observed earlier projects have been described as learning generators and are widely seen as the powerhouse of learning within organisations. However, the very characteristics that underpin this learning potential also create barriers to harnessing it. As Garrety et al (2004, p 353) state: “The problem for project managers is to overcome barriers to communication created by the existence of groups with quite different skills, languages, expectations and assumptions”, and they are under time and budget constraints to do so.

One of the key processes by which project teams integrate their divergent knowledge is through a process of “brokering”. Garrety (2004, pp 353-357) – citing Wenger (1991) – describes the process of “brokering” as “the use of multi-membership to transfer some element of one practice to another …it involves processes of translation, coordination, and alignment between perspectives. It requires enough legitimacy to influence the development of a practice, mobilise attention and address conflicting interests”. Such integration of knowledge between different communities requires a great deal of work in creating and maintaining social relationships. Projects need persons to act as brokers, transferring and translating knowledge and aligning and productively organising different interests and perspectives as projects move through phases of differentiation and integration.

Knowledge Sharing between Projects and from Project to Organisation


Ayas and Zeniuk (2007, p 61) ask the question: “Can projects enable or facilitate the creation and diffusion of knowledge and innovative practices beyond individuals, specific teams or projects?” Schindler & Eppler (2003, p 219) have recently reported that while “projects are especially suited to learning …our research with various project teams (in product development, controlling, consulting and financial services) over the course of three years shows that knowledge and experiences gathered in different projects are not being systematically integrated into the organisational knowledge base”. Similarly, Scarborough et al (2004, p 492) state that “despite increasingly systematic efforts to capture learning from projects and make it available to other parts of the organisation, the evidence to date suggests limited success for such initiatives (Chaston, 1998; Sahlin-Andersson, 2002) suggesting a sharp contrast between the abundant generation of learning within projects and the more limited prospects for the diffusion of such learning across the wider organisational context (Ayas & Zeniuk, 2001).”

Challenges stem from the relatively self contained, idiosyncratic and finite nature of project tasks – inevitable discontinuities occur in the flow of resources (especially personnel and information) from one project to the next (Bresnen et al, 2003). Kasvri et al (2003) observe that “ …projects are temporally limited, and the people involved and the lessons learned are dispersed when the project ends. Often people change even during a project”.

Bresnen et al (2003) argue that in addition to the problem of the fragmentation of knowledge, the ability to develop shared meaning and understandings is also undermined in a project setting. Groups are temporally, spatially and culturally differentiated in ways that militate against the diffusion of knowledge via the development of well established communities of practice. The immediacy of project objectives and the finite lifespan of project activity may act as a focus for innovative activity, but they also militate against the emergence of networks of actors who are able to construct a community based upon shared understandings. Attempts to develop informal networks for the spread of knowledge and learning inevitably cut across strong institutional, professional and contractual boundaries and demarcations.

Scarborough et al (2002, p 492) describe how the “absorptive capacity” of an organisation – i.e., the ability to recognise the value of new information, assimilate it and then apply it to commercial ends – is determined in large measure by the prior distribution of knowledge and the extent to which there is a shared common stock of knowledge, both technical and organisational.

A particularly interesting idea in this context is the concept that in a multi-project environment, which characterises most organisations where change and innovation are imperative (Fenech and Dovey, 2005), a community may develop around the “practice” of serial and ongoing participation in tightly knit project teams. The domain in this case is the “multi-project environment”, in which “most of the work of businesses is organized as projects, formalised project management is the predominant business process for managing change, and multiple projects are executed simultaneously” (Fenech and Dovey, 2005). The community comprises those people who work and thrive in this dynamic business context, regardless of their disciplinary background, including project managers, business analysts, solutions architects, test managers, deployment managers, and so on. The shared practice involves that combination of skills and knowledge required to collaboratively solve problems and autonomously make decisions framed by agreed objectives by diverse participants, under time and budgetary constraints. On this last point, Gee et al (1996, p 58) state that “in the new capitalism it is not really important what individuals know on their own, but rather what they can do with others in a collaborative way to effectively add ‘value’ to the enterprise”.

There is some support for such a conception in the literature. For example, Sense (2003, p 8) states that “a project-based or matrix organisation may have people constantly moving between and interacting frequently on different projects, and a focus on learning across all those projects may constitute a type of mobile COP” (2003, p 8). Through this Sense posits the “development of a mobile practice that can constitute learning between projects” (2003, p 9). Similarly, Ayes and Zeniuk (2007, p 71-72) note that:

It is not only the nature of single projects that supports learning but also the web of relationships that are created in organisations that manage by projects …Project-based organisations may grow into constellations of interrelated communities of practice, offering a web of mutual support for cultivating reflective practices. When projects share members, they are bound together and become embedded in the same social network (Grantovetter, 1973). The recursive interaction among projects creates social networks of mutual assistance.

Such a mechanism would need to be supported by appropriate organisational structures and power management practices. Project Portfolio Management offers some promise in this respect, providing the basis of an organisational configuration, and formal and informal practices, in which such project knowledge can become embedded. As well as that it provides a structure of legitimacy that promises to limit inappropriate management intrusions and power management practices by providing project teams with autonomy through formal project selection and the approval of charters and budgets. Consequently, this may assist to facilitate the development of social capital resources such as trust that are sensitive to power management practices.

Responsibility for Knowledge Management in Project Based Organisations


Project Managers’ Responsibilities

Reich (2007, p 13) expresses the view that it is the responsibility of project managers “to establish a climate of trust, where it is safe to make mistakes (Grant, 2006), where sharing knowledge is the norm and helping others is promoted (Adenfelt & Lagerstr├Âm, 2006). This nurturing and safe climate is essential for implementing even simple activities such as collecting accurate and meaningful lessons learned”. Project managers can implement 5 practices to build a climate for learning:
Engage the team when building the risk register
Communicate that mistakes are a natural part of the team’s growth and understanding
Reward behaviour that supports a learning climate
Practice using desired team behaviours on minor issues
Speak the truth

Similarly, Jackon & Klobas (2007) state that “if knowledge is socially constructed then managers of projects need to attend to the elements of an environment which influence the construction of the knowledge required to get things done in projects”.

Senior Management and Leadership Responsibilities

However, while there is no doubt that project managers have an important role to play, particularly with respect to learning within projects, there are obvious limits to their power. There is little that a project manager can do to address organisational factors that inhibit both project learning and organisational learning from projects. Cultural and political factors often lead to inappropriate power management practices that can destroy the nascent culture of trust established by a project manager within (or through) some project initiative, which makes it essential that organisational leaders not only support the efforts of project managers but drive the transformation and structural change necessary to ensure the success of learning and knowledge management initiatives (see Dovey & Fenech, 2007). Eskerod & Skriver (2007, p 118) note that their findings from a detailed case study “suggests that to promote knowledge transfer, top management must focus on basic assumptions embedded in the organisational culture at hand and not solely on direct knowledge transfer between project managers”.

Dovey & Fenech (2007) argue for leaders to develop “a new form of enterprise logic – one characterized by emergent structures, shared ownership, and broadly distributed ‘non-authoritarian’ power bases – through which the creativity and learning capabilities of all staff can be built and leveraged”. The key implication of their findings is the need to broaden the concept of leadership in organisations to incorporate the role of 'structural architect'. They go on to argue that:

With suitable frames of reference regarding the relationship between structure and mission accomplishment, leaders need to explore the range of organizational forms that are emerging as appropriate alternatives to the functional hierarchy. Such forms include cellular (Miles et al, 1997); federal (Handy, 1994); hypertext (Nonaka & Takeuchi, 1995); communities of practice (Wenger, 1999) and network (Lipnack et al, 1994) structures (Fenech & Dovey, 2007, p 587).

This argument is supported by a case study at Fokker Aircraft described by Ayus and Zeniuk (2007, 68-70) in which project learning was facilitated by the implementation of a project network structure – “an organic network of self managing teams …a dynamic approach to [organisational] design derived from the principles of organisational learning …constituted by teams within teams” – and changes to reward systems. Their findings support the need for organisational leaders to establish conditions of “psychological safety” and a “learning infrastructure”.

Conclusion


In this paper we have attempted to provide project managers with the benefit of practical access to concepts from knowledge management literature in order to assist their practice as project managers. For example, Garrety et al (2004, p 351) state that “[a] comunities of practice perspective can help project managers to maximise the fruitfulness of the relationships that are crucial to knowledge exchange in complex projects … [drawing] attention to the social processes that produce differentiation, as well as the processes that facilitate productive integration … [and recognising that while] it is important to specify and pursue technical goals, complex projects are also social enterprises”. It is hoped that this assistance extends to helping project managers to influence organisational leaders more effectively. We have also sought to highlight some of the areas where organisational leaders need to drive transformation in order to support learning cultures within their organisations. It is not all up to project managers.

References


Ayus, K. & Zeniuk, N. (2001) Project-based learning: building communities of reflective practitioners Management Learning32(1), 65-76
Bellin, E. & Canonico (2007, In Print) Knowing communities in project driven organisations: analysing the strategic impact of socially constructed HRM practices International Journal of Project Management
Bresnen, M, Edelman, L., Newell, S. Scarborough, H. & Swan, J. (2003) Social practices and the management of knowledge in project environments International Journal of Project Management 21, 157-166
Dovey, K. A. & Fenech, B. J. (2007, November) The role of enterprise logic in the failure of organisations to learn and transform Management Learning 38(5), 573-590
Eskerod, P. & Skriver, H.J. (2007, March) Organisational culture restraining in-house knowledge transfer between project managers – a case study Project Management Journal 38(1), 110-122
Faraj, S. & Sproull, L. (2000) Coordinating expertise in software development teams Management Science 46(12), 1554-1568
Fenech, B. & Dovey, K. (2005) Evaluating project management maturity models: an analysis of business needs 2005 PMI Global Conference – Asia Pacific, Singapore.
Garrety, K., Robertson, P.L. & Badham, R. (2004) Integrating communities of practice in technology development projects International Journal of Project Management 22, 351-358
Gee, J., Hull, G., & Lankshear, C. (1996) The new work order: behind the language of the new capitalism. Sydney: Allen & Unwin.
Jackson, P. & Klobas, J. (2007, In Print) Building knowledge in projects: A practical application of social constructivism to information systems development International Journal of Project Management
Kasvi, J.J.J., Vartiainen, M & Hailikari (2003) Managing knowledge and knowledge competencies in projects and project organisations International Journal of Project Management 21, 571-582
Reich, B. H. (2007, June) Managing knowledge and learning in IT projects: a conceptual framework and guidelines for practice Project Management Journal 38(2), 5-17
Schindler, M. & Eppler, M.J. (2003) Harvesting project knowledge: a review of project learning methods and success factors International Journal of Project Management 21, 219-228
Sense, A. (2003) Learning generators: project teams reconceptualised Project Management Journal 34(3), 4-12
Tiwana, A., Bharadwaj, A. & Sambamurhty, V. (2003) The antecedents of IS development capability: a knowledge integration perspective Proceedings of the 24th International Conference on Information Systems Seattle, USA
Yoo, Y. & Kanawattanachai, P. (2001) Developments of transactive memory systems and collective mind in virtual teams The International Journal of Organisational Analysis 9(2), 187-208
Wenger, E., McDermott, R. & Snyder, W. (2002) Communities of practice: learning, meaning and identity, Cambridge, UK: Cambridge University Press



Monday, 29 January 2018

AI, robotics and automation, IoT, block chain, big data: why portfolio management is mission critical in an age of disruption and innovation?

Written by Bryan Fenech, Director - PPM Intelligence.


Disruptive digital technologies, including IoT, AI, robotic automation, block chain, crypto currencies and big data, are impacting all industries and no organisation is immune.

Business and government leaders face increasing demand to respond effectively to the threats and opportunities presented by these developments. This response requires innovation in products, services, internal processes and systems as well as, in many cases, whole-of-organisation transformation.

The more disruption there is in the marketplace the greater the demand for change in organisations, both in terms of volume and complexity.

Finding and articulating these opportunities and threats, and formulating a well considered response, isn’t the hard part. Most leaders understand how:

  • AI can be used to tame complex organisational problems cost effectively
  • Robotics can be used to automate the supply chain to make it more secure, less prone to defects and cheaper to run
  • Product designs can be enhanced through the incorporation of internet connectivity into all of our buildings and infrastructure, automobiles, appliances and gadgets
  • Block chain can be used to digitally automate smart contracts in a way that is secure and reliable,
  • Big data can be used to identify what customers want and how much they are willing to pay for it, and
  • Information security is under increasing threat.

The possibilities are not understood just on a theoretical level. There are working examples of all manner of application, often developed by startups with limited funding, and business and government leaders know that they will get left behind if they don’t act quickly. One revealing example is how Fintech startups are hastening the arrival of open banking, one of the more significant disruptions to the industry ever.

Most organisations have a digital strategy or at the very least a long wish list of initiatives that they would like to pursue.

The greater difficulty lies in executing all of these initiatives successfully. The main challenge is that there are so many change initiatives being put forward, each of which is seen as in some way mission critical, but undertaking them all is well beyond the available human and financial resources of the organisation.

Choices need to be made regarding the prioritisation, sequencing and risk-appropriateness of change initiatives. Organisations that can marshal and deploy their people and assets most effectively to prioritise and execute multiple change initiatives simultaneously have a distinct competitive advantage and are more likely to succeed.

This requires “portfolio thinking”. Portfolio management techniques were originally purpose-developed to help investment fund managers make sense of multiple value drivers, realisable over different timeframes and subject to complex and changing assumptions, constraints, dependencies and opportunity costs, for different classes of financial instrument. Such portfolio management techniques, used by the managers of investment and superannuation funds for selecting and managing portfolios of stocks, options, futures and derivatives for decades, have been found to be highly applicable to selecting and managing portfolios of projects and programs.

Portfolio management provides evidence-based decision-making techniques for making prioritisation, sequencing and risk versus reward choices. The following examples illustrate this point:

  • Financial return models such as NPV and Payback Period can be used to identify what subset of initiatives is the most financially rewarding long term or best supports short term cashflow.
  • Multi-attribute scoring models can be used to identify which initiatives best align with the organisation’s strategy.
  • Critical Chain Method can be used to sequence the execution of initiatives optimally around resource bottlenecks.
  • Monte Carlo Simulation can be used to identify “efficient frontiers” in order to optimally balance risk versus reward.
  • Dependency analysis can reveal the true impact and significance of risks by identifying "domino effects" on downstream dependent change initiatives.
  • Benefits projections can help identify what needs to be done to ensure benefits are realised.


Leaders need to be knowledgeable of and be able to apply portfolio management techniques within a structured process. It is therefore an increasingly critical leadership competency and organisational capability in an age of disruption and innovation.

Just as an investment manager understands the language of stocks, options and futures so too 21st century business and government leaders need to understand the language of portfolio analytics, decision-making and governance in order to ensure that their digital strategies don't end up in the too hard basket or, worse still, use up a significant amount of investment without result.

Saturday, 27 January 2018

Visualising portfolio risk and performance reviews - presentation delivered at the AIPM 2017 National Conference

Written by Bryan Fenech, Director - PPM Intelligence.

Note: This article is a summary of a presentation that I gave at the recent AIPM 2017 Conference in Melbourne. A link to the full presentation is provided at the end.

Traditional approaches to portfolio risk and performance review

More often than not the implementations of portfolio management that I come across do not deliver on their promised benefits. The reason for this is almost always the same: portfolio governance boards and portfolio management offices (PMOs) do not make sufficient use of the plethora of data available to them to support decision making about portfolio selection, monitoring and controlling.





Organisations are particularly weak in the areas of portfolio performance, risk and benefits management. The most common approach followed when portfolio governance boards review their inflight portfolio is to run through a list of projects and programs with health ratings for a set of simple performance metrics along with some basic commentary. The health ratings are usually represented as traffic lights – red, amber, green. The performance metrics usually include overall, budget, schedule, resources, risk, benefits and overall health.If you are doing this you are wasting your time!

Firstly, it is duplication of the governance practices that occur at project and program Steering Committee level and adds little if any value. If something is going wrong with one of the projects or programs in the list the best that the portfolio governance board can do is authorise actions to be taken with respect to the project or program concerned. The portfolio governance board is doing little more than delegating back (with interest) what the Sponsor has escalated up to them and is already doing their best to deal with.

Secondly, and worse still, it is ineffective as it does not make it easy to identify and resolve systemic issues that impact across the portfolio, for eg resource bottlenecks in certain skill categories causing delays in multiple projects, or common risk types and estimation errors. This misses the opportunity for creating learning and facilitating evidence-based decision making that improves structural and systemic problems and inefficiencies regarding the organisation’s portfolio management capability and capacity. This situation is not a good use of anyone’s time and energy.




Portfolio data analytics

An alternative approach is to give your portfolio data to a data analyst with project management knowledge and ask them to turn it into valuable information that tells you something about portfolio performance, risk profile and benefits position as a whole, rather than project by project.




Here are a few examples of what you might ask them to provide you:
  1. What types of risk are the most common across the portfolio? Is there a particular type of resource bottleneck that presents regularly? Is vendor management a recurring problem? Is there evidence that project managers are consistently demonstrating forms of cognitive bias in their estimation, such as being overly optimistic?
  2. Are there particular “break points” in the portfolio (ie, projects or programs upon which there is a high degree of dependency by other projects and programs)? What is the health of the most significant break points? What is the combined value of 'at risk' investment dollars or benefits dependent on these break points?
  3. How does the health of tier 1 projects and programs compare with less critical projects and programs? Is there a point of increasing complexity at which portfolio performance and throughput tends to 'fall off a cliff'? Is the organisation allowing sufficient schedule and budget contingency in its tier 1 projects for these realities?
  4. What is the combined value of investment dollars or benefits by overall traffic light rating? Is the position improving over time?



The information derived can be a snapshot at a point in time or represent historical trends.


Portfolio data visualisation

However, it is critical that portfolio analytics are presented in a way that decision makers can make immediate sense of them. Data visualisation techniques can help to present an incredibly rich picture of your project portfolio. Bringing together graphical representations of portfolio information in a portfolio info-graphic facilitates immediate practical application by senior decision makers. This approach delivers vastly superior outcomes in terms of the quality of learning and decision making.





Charles Minard’s famous graphical depiction of Napoleon’s campaign against Russia helps us to think about how we might represent portfolio information graphically. The Minard diagram shows the losses suffered by Napoleon's army in the 1812–1813 period. Six variables are plotted: the size of the army, its location on a two-dimensional surface (x and y), time, direction of movement, and temperature. The line width illustrates a comparison (size of the army at points in time) while the temperature axis suggests a cause of the change in army size. This multivariate display on a two dimensional surface tells a story that can be grasped immediately while identifying the source data to build credibility.




Types of visualisation

Author Stephen Few described eight types of quantitative messages that users may attempt to understand or communicate from a set of data and the associated graphs used to help communicate the message. I’ve adapted his typology so that it applies to portfolio analytics:



  1. Time-series: A single variable is captured over a period of time, such variances in planned portfolio spend or benefits over a 3-year period. A line chart may be used to demonstrate the trend.
  2. Ranking: Categorical subdivisions are ranked in ascending or descending order, such as a ranking of cost/benefit or contribution to strategy (the measure) by projects in the portfolio (the category, with each sales person a categorical subdivision) during a single period. A bar chart may be used to show the comparison across the projects.
  3. Part-to-whole: Categorical subdivisions are measured as a ratio to the whole (i.e., a percentage out of 100%). A pie chart or bar chart can show the comparison of ratios, such as the incidence of risk types across the portfolio, or the total portfolio spend or expected benefits by overall health indicator.
  4. Deviation: Categorical subdivisions are compared against a reference, such as a comparison of actual vs. budget expenses for enterprise, divisional or department portfolios for a given time period. A bar chart can show comparison of the actual versus the baseline amount.
  5. Frequency distribution: Shows the number of observations of a particular variable for given interval, such as the number of years in which the stock market return is between intervals such as 0-10%, 11-20%, etc. A histogram, a type of bar chart, may be used for this analysis. A boxplot helps visualize key statistics about the distribution, such as median, quartiles, outliers, etc.
  6. Correlation: Comparison between observations represented by two variables (X,Y) to determine if they tend to move in the same or opposite directions. For example, plotting project size (X) and the incidence of cost and schedule overruns (Y) for a sample of months. A scatter plot is typically used for this message.
  7. Nominal comparison: Comparing categorical subdivisions in no particular order, such as project performance by type, size or business division. A bar chart may be used for this comparison.
  8. Geographic or geospatial: Comparison of a variable across a map or layout, such as the portfolio performance by office location. A cartogram is a typical graphic used.




Using portfolio infographics

Portfolio infographics can demonstrate critical insights in an instant that are otherwise buried in the data:


  • What types of risk are the most common across the portfolio?
  • Is there a particular type of resource bottleneck that presents regularly? 
  • Is vendor management a recurring problem?
  • Is there evidence that project managers are consistently demonstrating forms of cognitive bias in their estimation, such as being overly optimistic?
  • Are there particular “break points” in the portfolio (ie, projects or programs upon which there is a high degree of dependency by other projects and programs)? What is the health of the most significant break points? What is the combined value of 'at risk' investment dollars or benefits dependent on these break points? 
  • How does the health of tier 1 projects and programs compare with less critical projects and programs?
  • Is there a point of increasing complexity at which portfolio performance and throughput tends to 'fall off a cliff'? Is the organisation allowing sufficient schedule and budget contingency in its tier 1 projects for these realities? 
  • What is the combined value of investment dollars or benefits by overall traffic light rating? Is the position improving over time? 





Benefits of portfolio intelligence

This information is far more valuable than a list of projects and programs with health indicators. It facilitates evidence-based decision making for steering the portfolio and resolving problems relating to capability and capacity, and provides the business case for action to address systemic problems. This is a more appropriate focus for portfolio governance boards.


The power of this information in the hands of senior management is significant. It can be applied to everything from which risk categories to address first, to where to focus recruitment efforts, to how to tailor project management training needs to get the most value for the organisation.

Roles

This has implications for PMOs. In particular, the role of the portfolio analyst needs to become more analytical and versed in data visualisation techniques to be able to surface key messages and trends out of the detail of portfolio data. In most cases, PMO personnel come from a delivery background, and adopting portfolio analysis and visualisation techniques and approaches requires a significant degree of upskilling.


This in turn highlights the importance of the role of independent portfolio assurance. Assurance, through health checks and other reviews, of your most important projects and programs remains essential. However, a portfolio intelligence expert can give you immediate access to the relevant analytics and visualisation skills needed to bring your portfolio information to life. Such services are a highly cost effective use of your assurance investment, resulting in improved portfolio performance and knowledge transfer.

You can get the full presentation here.


Sunday, 5 November 2017

Investing for good: saving the world one project at a time - presentation delivered at the AIPM 2017 National Conference

Written by Bryan Fenech, Director - PPM Intelligence.

Note: This article is a summary of a presentation that I gave at the recent AIPM 2017 Conference in Melbourne. A link to the full presentation is provided at the end.

Legal limits on office holders to pursue philanthropic ends


In Dodge v. Ford Motor Company, 170 NW 668 (Mich 1919) a US superior Court held that pioneer car maker Henry Ford owed a duty to profit his shareholders, rather than to benefit the community as a whole or employees. Ford was prevented by the Court from investing a $60M capital surplus “to spread the benefits of this industrial system to the greatest possible number, to help them build up their lives and their homes”, and was required to pay special dividends to shareholders.

This decision was recently clarified in eBay v Newmark (2010). eBay acquired shares in Craigslist when it became a public corporation. The owners of Craigslist sought to continue to be of service to communities rather than focusing on stockholder wealth maximisation. This was challenged by eBay and it was held that having chosen a for profit corporate form the Craigslist directors were bound by the fiduciary standards that accompany that form, including the duty to act in the interests of shareholders.

The legal position is that while most companies can engage in modest philanthropy, if it a company starts putting its money where its mouth is on philanthropy they’ll get eBay’d just like Craigslist did.

Practical limits on officeholders to pursue philanthropic ends


While the Corporations Law in Australia, and similar legislation in other countries, has over time broadened the duties owed by Directors, the primacy of shareholder return nevertheless remains the chief lens through which company decisions get made.

This was very strongly borne out in interviews I conducted recently with 7 CEOs (2 of whom are also Chairpersons), 3 CIOs and 1 CFO. All of the leaders I spoke to work for large organisations ranging in size up to $87B by market capitalisation and 40,000 employees. One of the practical constraints on the power of these leaders to implement change is risk aversion in the broader industry context, particularly amongst large institutional shareholders and creditors such as banks and superannuation funds, to anything that might potentially impact steady returns. As one CEO put it
“The shareholders will revolt. Being a listed company is another difficulty …if you’ve got massive shareholders, you know, some of the banks or superannuation funds or pension funds …you’re a new CEO and you want to make changes and they don’t get it, they’ll take their money, all your shareholders get pissed off and you’re out of your job.” 
“In the world’s business model today that’s a major thing for any chief executive, you get up in the morning saying you want to change the organisation you probably won’t have a job in a couple of weeks … you’re not going to deviate from my risk versus return thanks very much”. 

Competing for priority with financial objectives


It is no wonder that corporate social responsibility and environmental sustainability objectives struggle for priority with initiatives that bring a financial return. Unfortunately, stories about companies engaged in environmental damage, sweatshops and anti-competitive practices in the pursuit of profit are all too common.

The B corporation movement – a new kind of organisation



The B Corporation Declaration of Independence states:

We envision a global economy that uses business as a force for good. 
This economy is comprised of a new kind of corporation – the B corporation – which is purpose driven and creates benefit for all stakeholders, not just shareholders. 
As B corporations and leaders of this emerging economy we believe:
  • That we must be the change that we seek in the world
  • That all businesses ought to be conducted as if people and place mattered
  • That through their products, practices and profits, businesses should aspire to do no harm and benefit all
  • To do so requires that we act with the understanding that we are each dependent on one another and responsible for each other and future generations.
In the US 31 of 50 states have passed laws allowing companies to choose whether they will be a traditional company or the equivalent of a B corporation.

In Australia there are over 80 B corporations at the time of writing but no legal framework in place to protect officeholders seeking to undertaken philanthropic ends. It remains the legal position that a Director's decision must advantage the company.

Responses from traditional corporations

Within their limited remit to pursue philanthropic ends traditional companies endeavour to do their bit but tend to be limited to declarations of values, some small scale funding social programs, pro bono work and voluntary participating in events such as hackathons.

Defining value in a more flexible manner


If this is to change, businesses need a broader conception and longer term view of “value” built into their DNA. Putting this into practice also requires businesses to adopt entirely new valuation techniques that are aligned to this more developed notion of value. Today’s most popular techniques, such as Net Present Value and Payback period, are designed to select for short term financial return. The challenge is to be able to measure value in a more flexible, nuanced and multifaceted way that strikes a better balance between profits and other objectives.

How portfolio management and assurance can help

Project Portfolio Management (PPM) has an important and emerging role to play here. There are 3 PPM techniques, in particular, that can help business strike this balance between their corporate social responsibility and environmental sustainability objectives and the need to be profitable:
  • Portfolio segmentation
  • Multi attribute scoring models, and
  • Portfolio balancing.
I have also identified a number of approaches to program assurance that can help business strike this balance between their corporate social responsibility and environmental sustainability objectives and the need to be profitable.

Portfolio segmentation


Portfolio segmentation refers to splitting the funding available for undertaking projects and other initiatives into segments that reflect high level strategic choices. Projects are prioritised within each category rather than all of them competing for the same investment dollar. This ensures that there is a guaranteed level of investment in each strategic category.

These categories can be defined to reflect an intelligent balance between profitability and other objectives. For example, a business might segment its capital budget as follows:
  • Customer satisfaction (25%)
  • Employee engagement (10%)
  • New revenue (20%)
  • Cost savings or avoidance (20%)
  • Carbon neutral (5%)
  • Indigenous communities programs (10%).
In this example, projects that contribute toward carbon neutrality do not need to compete directly for funding with projects that grow revenue or reduce costs.

Multi-attribute scoring models


Multi attribute scoring models measure the relative potential contribution of projects and other initiatives against a set of strategic objectives or parameters. Parameters are created for criteria that are important to an organization – e.g., improving customer service, productivity improvement, new product development and growth, cost savings or avoidance, strategic market positioning, and so on. Scoring against these parameters may involve a numerical scale or use natural language that is mapped back to a numerical scale.

Parameters can be defined that reflect corporate social responsibility and environmental objectives alongside profitability objectives. Models can be refined over time and objectives weighted to reflect the relative importance that the organisation places on them. A high degree of sophistication can be achieved with such models, bringing greater precision to the way organisations go about determining which projects and other initiatives they invest in.

Portfolio balancing


Finally, portfolio balancing refers to assessing whether a portfolio is optimal taking into account timing, spread of strategic objectives served, business impact, risk versus reward, and resource availability. This often involves undertaking “what if” analysis and comparing the results.

This “helicopter view” of the overall portfolio affords opportunities to adjust and improve the portfolio and here is also an important opportunity for an organisation to assess its role as a responsible corporate citizen. It can ensure, in effect, that its money is where its mouth is.

Portfolio assurance

Independent portfolio assurance can be structured in a way that assurance providers, in addition to assessing the fitness for purpose of an organisation's project and program management approaches, assess the levels of commitment and investment in employee, community and environmental sustainability. Independent reports on investment in these areas provides office holders with the information they need to justify an expanded commitment to their stakeholders.

You can get the full presentation here.

Tuesday, 5 September 2017

Wednesday, 9 August 2017

Portfolio intelligence: analytics and visualisation

Written by Bryan Fenech, Director - PPM Intelligence.

Charles Minard's Visualisation of Napoleon's Retreat from Moscow
More often than not the implementations of portfolio management that I come across do not deliver on their promised benefits. The reason for this is almost always the same: portfolio governance boards and portfolio management offices (PMOs) do not make sufficient use of the plethora of data available to them to support decision making about portfolio selection, monitoring and controlling.

Organisations are particularly weak in the areas of portfolio performance, risk and benefits management. The most common approach followed when portfolio governance boards review their inflight portfolio is to run through a list of projects and programs with health ratings (eg traffic lights – red, amber, green) for a variety of performance indicators (eg overall, budget, schedule, resources, risk, and benefits), and some basic commentary. If you are doing this you are wasting your time.

Firstly, it is ineffective. This approach is incapable of creating learning and facilitating decision making that improves structural and systemic problems and inefficiencies regarding the organisation’s portfolio management capability and capacity. If something is going wrong with one of the projects or programs in the list the best that the portfolio governance board can do is authorise actions to be taken by, or with respect to, the project or program concerned. But, secondly and worse still, this is merely duplicating effort that has already taken place at Steering Committee level; the portfolio governance board is doing little more than delegating back (with interest) what the Sponsor has escalated up to them and is already doing their best to deal with. This is not a good use of anyone’s time and energy.

Portfolio Analysis

An alternative approach is to give your portfolio data to a data analyst with project management knowledge and ask them to turn it into valuable information that tells you something about portfolio performance, risk profile and benefits position as a whole, rather than project by project. Here are a few examples of what you might ask them to provide you:
  • What types of risk are the most common across the portfolio? Is there a particular type of resource bottleneck that presents regularly? Is vendor management a recurring problem? Is there evidence that project managers are consistently demonstrating forms of cognitive bias in their estimation, such as being overly optimistic?
  • Are there particular “break points” in the portfolio (ie, projects or programs upon which there is a high degree of dependency by other projects and programs)? What is the health of the most significant break points? What is the combined value of 'at risk' investment dollars or benefits dependent on these break points?
  • How does the health of tier 1 projects and programs compare with less critical projects and programs? Is there a point of increasing complexity at which portfolio performance and throughput tends to 'fall off a cliff'? Is the organisation allowing sufficient schedule and budget contingency in its tier 1 projects for these realities?
  • What is the combined value of investment dollars or benefits by overall traffic light rating? Is the position improving over time?
The information derived can be a snapshot at a point in time or historical.

Portfolio Visualisation

This information is far more valuable than a list of projects and programs with health indicators. It facilitates evidence-based decision making for steering the portfolio and resolving problems relating to capability and capacity, and provides the business case for action to address systemic problems.

This is a more appropriate focus for portfolio governance boards.

However, it is critical that portfolio analytics are presented in a way that decision makers can make immediate sense of them. Data visualisation techniques can help to present an incredibly rich picture of your project portfolio. Bringing together graphical representations of portfolio information in a portfolio info-graphic facilitates immediate practical application by senior decision makers. This approach delivers vastly superior outcomes in terms of the quality of learning and decision making.


The power of this information in the hands of senior management is significant. It can be applied to everything from which risk categories to address first, to where to focus recruitment efforts, to how to tailor project management training needs to get the most value for the organisation.


Roles

This has implications for PMOs. In particular, the role of the portfolio analyst needs to become more analytical and versed in data visualisation techniques to be able to surface key messages and trends out of the detail of portfolio data. In most cases, PMO personnel come from a delivery background, and adopting portfolio analysis and visualisation techniques and approaches requires a significant degree of upskilling.

This in turn highlights the importance of the role of independent portfolio assurance. Assurance, through health checks and other reviews, of your most important projects and programs remains essential. However, a portfolio intelligence expert can give you immediate access to the relevant analytics and visualisation skills needed to bring your portfolio information to life. Such services are a highly cost effective use of your assurance investment, resulting in improved portfolio performance and knowledge transfer.

For the purposes of this article I have created some simple visualisations of risk and benefits data using a basic tool. But there isn’t one size fits all for this and there are very powerful tools available to help you explore your data with greater precision and expressiveness. While there are common techniques, it is worth developing your own rich visual representations of your portfolio data. This information is what is unique to your business and it can be enriched so that it becomes one of your most valuable information assets and a source of competitive advantage.


Monday, 13 October 2014

To kill a project ...

Written by Bryan Fenech, Director - PPM Intelligence.
"Action expresses priorities" - Mahatma Gandhi


When to kill off a project, and the decision criteria for doing so, has been a prominent discussion topic among my colleagues lately. It seems that it doesn't happen nearly as often as one would expect. And, perhaps surprisingly, there is not a lot of science that goes into such decisions.

What the theory says

The theory says that you should kill a project when its business case no longer makes sense. There are 2 reasons why this may be the case. Either:

  1. Costs are higher than expected because of delay, poor estimation of effort, error and rework, or resources have become more expensive than planned, or
  2. Benefits have been compromised due to delay, overly optimistic estimation of new revenue or cost savings, competitors getting to market first, downturn in market conditions, or disruption of the market due to external conditions.

The availability of other projects that represent a better return on the investment of organisational resources should be a determining factor also. Why persist with a project that is no longer expected to deliver valuable outcomes when there are other more attractive options?

What happens in practice

In practice these principles are a good basis on which to make a case to wind up a failed project. More often than not, however, I find its much simpler than that and if there is a major project failure - usually a significant delay or cost blow out - no one will want to be associated with it.

However, statistical studies such as the CHAOS Report suggest that, while about 25% of projects are failures that are killed off at some point, about 50% continue on through to completion even though they are on average around 200% over budget or late. The latter figure suggests its harder than expected to kill a project, and not always a rational decision.

Human factors

This accords with feedback from some of my colleagues from the MBITM Program at the University of Technology, Sydney who work in the field. Consider the following 2 quotes which I think put the matter succinctly:
"It seems to me that many projects don't refer back to the Business Case often enough. And that human trait of wanting to salvage something (anything!) from the investment in the projects leads to a reluctance to kill it off." 
"I've not seen any project 'killed' in my experience. What I've experienced is that when a project fails to deliver, rather than killing it then and there, more resources (money, labour etc.) are thrown at it to 'make it work' - nobody wants to be seen or associated with a failed project. Or it is re-scoped to such an extent that it really bears no resemblance to what was originally envisaged or sign(ed) off on. Successful projects have many parents, while a failed project is an orphan."

Killing a healthy project

I have heard it sometimes said that the maturity of an organisation's portfolio management capability can be measured by its ability to kill projects that are not troubled.

The reasoning is that an organisation with a high portfolio management maturity level will be so in tune with its resource-supply/project-demand equation that it will be able to respond to new opportunities and make space for them by stopping or deferring less valuable in-flight projects.

But is it really that easy? In my experience, not only do organisations not have the tools to do this with any level of rigor, but there is no agreement on the critical issues involved.

For example, when comparing the value of a new opportunity with an in-flight project should we take into account the sunk cost expended to date in the latter? If we do a straight NPV comparison at the time of decision the in-flight project has already expended some of its costs so its NPV at that point will be hard to beat? Alternatively, should we include this sunk cost in the NPV equation? But if we do that then it is no longer an NPV that we are measuring but a present value of both past and future cashflows.

Another problem is that the estimates for in-flight projects are likely to be more accurate than those for a new idea. Should we discount estimates, or apply a risk factor, to account for the different levels of confidence?

What does best practice say?

There are no hard and fast rules here. Both of the key industry standards - Management of Portfolios (Axelos) and The Standard for Portfolio Management (PMI) - are silent on these questions. This is curious given that killing off projects when appropriate is often cited as one of the key objectives of portfolio management.

This area is ripe for field research to survey and gather data on how organisations are approaching these issues.