Averaging the Power of Portfolios

July 8, 2012

The interaction between dependent or connected risk and independent risk is interesting and will significantly change the overall probability of success or failure of an endeavour or organisation.

As discussed in my last post on ‘The Flaw of Averages’ using a single average value for an uncertainty is a recipe for disaster. But there is a difference between averaging, connecting and combining uncertainties (or risk).

Adding risk

Where risk events are connected, the ability to model and appreciate the effect of the risk events interacting with each other is difficult. In ‘The Flaw of Averages’ Sam Shaw uses the simile of wobbling a step ladder to determine the uncertainty of how safe the ladder is to climb. You can test the stability of one ladder by giving it a good ‘wobble’. However, if you are trying to determine the stability of a plank between two stepladders doubling the information from wobbling just one is not a lot of help. Far more sophisticated modelling is needed and even then you cannot be certain the full set of potential interactions is correctly combined in the model. The more complex the interactions between uncertainties, the less accurate the predictive model.

However, when the risks or uncertainties are independent, combining the risks through the creation of a portfolio of uncertainties reduces the overall uncertainty quite dramatically.

The effect of portfolios

Consider a totally unbiased dice, any one throw can end up anywhere and every value between 1 & 6 has an equal probability of being achieved. The more throws, the more even the results for each possibility and consequently there is no possibility of determining the outcome!

The distribution after 10, 100 and 1000 throws.

As the number of throws increase, the early distortions apparent after 10 throws smooth out and after 1000 throws the probabilities are almost equal.

However, combine two dice and total the score results in a very different outcome. Whilst it is possible to throw any value between 2 & 12, the probability of achieving a number nearer the middle of the range is much higher than the probability of achieving a 2 or a 12. The potential range of outcomes starts to approximate a ‘normal distribution curve’ (or a bell curve). The reason for this is there is only one combination of numbers that will produce a 2 or a 12; there are significantly more combinations that can make 7.

The more dice you add to the ‘throw’, the closer the curve becomes to a ‘normal distribution’ (or bell curve), which is normally what you expect/get, which is the origin of the name!

The consequence of this phenomenon is to demonstrate that the creation of a portfolio of projects will have the effect of generating a normal distribution curve for the outcome of the overall portfolio, which makes the process of portfolio management a more certain undertaking than the management of the individual projects within the portfolio. The overall uncertainty is less than the individual uncertainties……

Each project carries its level of uncertainty and has a probability of succeeding off-set by a probability of failing (see Stakeholder Risk Tolerance) but as more projects are added the probability of the overall portfolio performing more or less as expected increases, provided each of the uncertainties are independent! This effect is known as the Central Limit Theorem.

One important effect of the Central Limit Theorem is the size if the contingency needed to achieve a desired level of safety for a portfolio of projects is much smaller than the sum of the contingencies needed to achieve the same level of ‘safety’ in each of the individual projects. Risk management is a project centric process; contingency management is better managed at the portfolio level. Not only is the overall uncertainty reduced, but the portfolio manager can offset losses in one project against gains in another.

Whist this theorem is statistically valuable, the nature of most organisations constrain the potential benefits. From a statistical perspective diversity is the key; this is why most conservative investment portfolios are diversified. However, project portfolios tend to be concentrated in the area of expertise of the organisation which removes some of the randomness needed for the Central Limit Theorem to have its full effect.

It is also important to remember that whilst creating a portfolio will reduce uncertainty, no portfolio can remove all uncertainty.

In addition to the residual risk of failure inherent in every project, there is always the possibility of a ‘black swan’ lurking in the future. Originally conceptualized by philosopher Karl Popper and refined by N. N. Taleb, a ‘black swan’ is a risk event that has never occurred before, if it did occur would have and extreme impact and is easy to explain after the event, but is culturally impossible to predict in advance (ie, the event could be foreseen if someone is asked to think about it but it is nearly impossible to think the thought for a compelling reason). For more on black swans see: http://mosaicprojects.wordpress.com/2011/02/11/black-swan-risks/ 

The Law of Averages

The Central Limit Theorem is closely aligned to The Law of Averages. The Law of Averages states that if you repeatedly take the average of the same type of uncertain number the average of the samples will converge to a single result, the true average of the uncertain number. However, as the ‘flaw of averages’ has demonstrated, this does not mean you can replace every uncertainty with an average and some uncertain numbers never converge.

Summary

Both the Law of Averages and Central Limit Theorem are useful concepts; they are the statistical equivalent of the adage “don’t put all your eggs in one basket”. When you create a portfolio of projects, the average probability of any one project succeeding or failing remains the same as if the project was excluded from the portfolio, but the risk of portfolio suffering an overall failure becomes less as the number of projects included in the portfolio increases.

However, unlike physical laws such as gravity, these laws are not immutable – drop an apple within the earths gravitational pull and it will fall; create a portfolio and there is always a low probability that the results will not conform to normal expectations!

Certainly the probability of a portfolio of projects ‘failing’ is lower then the average probability of each project failing but a reduced level of risk still leaves a residual level of risk.


Key roles within Project, Program and Portfolio Management

April 16, 2011

Project, Program and Portfolio management is frequently seen as a seamless part of a business. However, distinctly different skill sets, personal attributes and capabilities are needed in the different roles.  This post suggests a framework that can be used to understand the differences.

Role 1 – Technical

Most people start on a project management career as a team member focused on technical work. Aspects of the role include:

  • Developing the skills to do the work
  • Solving technical problems
  • Supporting and engaging with fellow team members
  • Planning the work to be accomplished in the next day or two

The team leader is a skilled and experienced technician with additional responsibilities to ensure the others in the team can be successful. The team leader’s additional roles include:

  • Leading the team, leads by doing
  • Skills transfer to new team members
  • Resolving technical problems that are beyond individual team member’s skill sets
  • Planning the work for the team for the next week or two
  • Clearing road blocks and keeping project management informed.

Role 2 – Project Management

The step from team leader to project manager role is a career change.  The project manager manages technicians by providing appropriate direction and leadership. Whilst technical understanding is important, the PM does not need to be a technician.  For example, in many countries it is illegal for a construction project manager to install electrical wiring; this is a job for qualified electricians.  Success for the PM lays in planning and managing the overall project he or she is responsible for and negotiating it through to a successful conclusion. Aspects of the role include:

  • Designing the project to efficiently deliver stakeholder requirements within acceptable time, cost, quality and risk parameters
  • Providing clear achievable and effective direction, leadership and motivation to the project teams through the team leaders
  • Helping team leaders develop their skills and their team members skills
  • Resolving stakeholder issues and problems across the spectrum of the project, usually through negotiation and communication
  • Planning the project work through to completion and then transitioning the plan into action
  • Acting as a buffer to protect the project team from undesirable external influence

Role 3 – Program Management / Project Director

Moving up the career ladder, the next career change is to the role of program manager or project director. The difference between these roles is the program manager will typically manage a range of projects across functions to achieve an organisational objective aligned with the organisations strategy. Whereas the Project Director has responsibility for the performance of project managers within a functional area; eg, the IT Department.

These are junior executive roles focused on achieving organisational objectives and creating value through the work of other managers. These managers, manage project managers. Success for a program manager is delivering organisational change and benefits. Aspects of the role include:

  • Defining strategies to achieve the organisation’s objectives
  • Initiating projects to deliver the required outputs
  • Providing clear achievable and effective direction, leadership and motivation to the project managers
  • Helping project managers develop their skills
  • Negotiating stakeholder issues and resolving problems at the organisational level
  • Planning the organisation’s work through to the achievement of the objective (minimum 1 to 2 years)
  • Helping other organisation executives appreciate the value of the program and ensuring the work is aligned with the evolving organisational objectives

Role 4 – Organisational Governance

Slightly to one side of the ‘doing’ of projects and programs the organisational governance structures are supported by portfolio management and PMOs.  These management roles are focused on providing strategic advice to the executive. The portfolio manager assesses current and planned projects and programs on a routine basis to recommend the optimum mix for future resourcing.  The PMO manager should be operating at the strategic level,  providing input to the portfolio management process based on the performance of current projects and additionally providing input to the organisations overall governance structure. Whilst the PMO staff are frequently technical, the PMO manager needs to operate effectively at the executive levels of the organisation.

Success in these roles is being a ‘trusted advisor’ to the organisations executives. Aspects of the role include:

  • Defining appropriate governance processes to support the achievement of the organisation’s strategy
  • Selecting projects and programs to deliver the required outcomes
  • Negotiating resource and capacity issues and resolving problems at the organisational level
  • Planning the organisation’s work on an on-going basis (minimum 2 to 5 years)
  • Helping other organisation executives appreciate the value of the project and program portfolio and ensuring the work is aligned with the evolving organisational objectives

Whilst these four very different roles are frequently lumped under the one umbrella of project management, as this post has demonstrated, very different skill sets are required for each and transitioning from one role to another, needs to be treated as a career change.

For more information see: