Extreme Risk Taking is Genetic……

December 20, 2014

A recent 2014 scientific study, Going to Extremes – The Darwin Awards: sex differences in idiotic behaviour  highlights the need for gender diversity.  The class of risk studied in this report is the idiotic risk, one that is defined as senseless risks, where the apparent payoff is negligible or non-existent, and the outcome is often extremely negative and often final. The results suggest that having an ‘all male’ or male dominated decision making group may be a source of risk in itself.

Darwin1Sex differences in risk seeking behaviour, emergency hospital admissions, and mortality are well documented and confirm that males are more at risk than females. Whilst some of these differences may be attributable to cultural and socioeconomic factors (eg, males may be more likely to engage in contact and high risk sports, and are more likely to be employed in higher risk occupations), sex differences in risk seeking behaviour have been reported from an early age, raising questions about the extent to which these behaviours can be attributed purely to social and cultural differences. This study extends on these studies to look at ‘male idiot theory’ (MIT) based on the archives of the ‘Darwin Awards’. Its hypothesis derived from Women are from Venus, men are idiots (Andrews McMeel, 2011) is that many of the differences in risk seeking behaviour may be explained by the observation that men are idiots and idiots do stupid things…… but little is known about sex differences in idiotic risk taking behaviour.

Darwin2The Darwin Awards are named in honour of Charles Darwin, and commemorate those who have improved the human gene pool by removing themselves from it in an idiotic way (note the photographs are both of unsuccessful attempts to win an award).  Whilst usually awarded posthumously, (the idiot normally has to kill themselves) the 2014 The Thing Ring award shows there are other options.  Based on this invaluable record of idiotic human behaviour, the study considered the gender of the award recipients over a 20 year period (1995-2014) and found a marked sex difference in Darwin Award winners: males are significantly more likely to receive the award than females.

Darwin3Of the 413 Darwin Award nominations in the study period, 332 were independently verified and confirmed by the Darwin Awards Committee. Of these, 14 were shared by male and female nominees (usually overly adventurous couples in compromising positions – see: La Petite Mort) leaving 318 valid cases for statistical testing. Of these 318 cases, 282 Darwin Awards were awarded to males and just 36 awards given to females. Meaning 88.7% of the idiots accepted as Darwin Award winners were male!

Gender diversity on decision making bodies may help to reduce this potential risk factor in two ways.  First, by reducing the percentage of people potentially susceptible to MIT. Second, by modifying the social and cultural environment within decision making body, reducing the body’s tendency to take ‘extreme risk decisions’.

One well documented example is the current Federal Government. Given the extremely limited representation of women in the make-up of the current Abbott government, and some of the self-destructive decisions they have made, I’m wondering if there is a correlation. A softer, less aggressive, lower risk approach to implementing many of the policies they have failed to enact may have resulted in a very different outcome for the government.

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Stakeholders and Risk

December 12, 2012

Probably the biggest single challenge in stakeholder communication is dealing with risk – I have touched on this subject a few times recently because it is so important at all levels of communication.

Projects are by definition uncertain – you are trying to predict a future outcome and as the failure of economic forecasts and doomsday prophets routinely demonstrate (and bookmakers have always known), making predictions is easy; getting the prediction correct is very difficult.

Most future outcomes will become a definite fact; only one horse wins a race, the activity will only take one precise duration to complete. What is uncertain is what we know about the ‘winner’ or the duration in advance of the event. The future once it happens will be a precise set of historical facts, until that point there is always a degree of uncertainty, and this is where the communication challenge starts to get interesting……

The major anomaly is the way people deal with uncertainty. As Douglas Hubbard points out in his book the Failure of Risk Management: “He saw no fundamental irony in his position: Because he believed he did not have enough data to estimate a range, he had to estimate a point”. If someone asks you what a meal costs in your favourite restaurant, do you answer precisely $83.56 or do you say something like “usually between $70 and $100 depending on what you select”? An alternative answer would be ‘around $85’ but this is less useful than the range answer because your friend still needs to understand how much cash to take for the meal and this requires an appreciation of the range of uncertainties.

In social conversations most people are happy to provide useful information with range estimates and uncertainty included to make the conversation helpful to the person needing to plan their actions. In business the tendency is to expect the precisely wrong single value. Your estimate of $83.56 has a 1 in 3000 chance of actually occurring (assuming a uniform distribution of outcomes in a $30 range). The problem of precisely wrong data is discussed in Is what you heard what I meant?.

The next problem is in understanding how much you can reasonably expect to know about the future.

  • Some future outcomes such as the roll of a ‘true dice’ have a defined range ( 1 to 6) but previous rolls have absolutely no influence on subsequent rolls, any number can occur on any roll.
  • Some future outcomes can be understood better if you invest in appropriate research, the uncertainty cannot be removed, but the ‘range’ can be refined.

This ‘know-ability’ interacts with the type of uncertainty. Some future events (risks) simply will or won’t happen (eg, when you drop your china coffee mug onto the floor it will either break or not break – if it’s broken you bin the rubbish, if it’s not broken you wash the mug and in both situations you clean up the mess). Other uncertainties have a range of potential outcomes and the range may be capable of being influenced if you take appropriate measures.

The interaction of these two factors is demonstrated in the chart below, although it is important to recognise there are not absolute values most uncertainties tend towards one option or the other but apart from artificial events such as the roll of a dice, most natural uncertainties occur within the overall continuum.

Stakeholders and Risk - Risk Matrix

Putting the two together, to communicate risk effectively to stakeholders (typically clients or senior managers) your first challenge is to allow uncertainty into the discussion – this may require a significant effort if your manager wants the illusion of certainty so he/she can pretend the future is completely controllable and defined. This type of self-delusion is dangerous and it’s you who will be blamed when the illusion unravels so its worth making the effort to open up the discussion around uncertainty.

Then the second challenge is to recognise the type of uncertainty you are dealing with based on the matrix above and focus your efforts to reduce uncertainty on the factors where you can learn more and can have a beneficial effect on future outcomes. The options for managing the four quadrants above are quite different:

  • Aleatoric Incidents have to be avoided (ie, don’t drop the mug!)
  • Epistemic Incidents need allowances in your planning – you cannot control the weather but you can make appropriate allowances – determining what’s appropriate needs research.
  • Aleatoric Variables are best avoided but the cost of avoidance needs to be balanced against the cost of the event, the range of outcomes and your ability to vary the severity. You can avoid a car accident by not driving; most people accept the risk and buy insurance.
  • Epistemic Variables are usually the best options for understanding and improvement. Tools such as Monte Carlo analysis can help focus your efforts on the items within the overall project where you can get the best returns on your investments in improvement.

Based on this framework your communication with management can be used to help focus your efforts to reduce uncertainty within the project appropriately. You do not need to waste time studying the breakability of mugs when dropped; you need to focus on avoiding the accident in the first place. Conversely, understanding the interaction of variability and criticality on schedule activities to proactively managing those with the highest risk is likely to be valuable.

Now all you have to do is convince your senior stakeholders that this is a good idea; always assuming you have any stakeholders after the 21st December!*

____________________

*The current ‘doomsday’ prophecy is based on the Mayan Calendar ending on 21st December 2012 but there may be other reasons for this:

Stakeholders and Risk Myan Prediction


The value of stakeholder management

August 13, 2012

One of the questions I’m regularly asked is to outline the business case for using stakeholder management in a business or project. This is a difficult question to answer accurately because no-one measures the cost of problems that don’t occur and very few organisations measure the cost of failure.

The problem is not unique; it is very difficult to value the benefits of an effective PMO, of improving project delivery methods (eg, improving the skills of your schedulers), of investing in effective communication (the focus of my September column in PMI’s PM Network magazine) or of better managing risk. The costs of investing in the improvement are easily defined, but the pay-back is far more difficult to measure.

There are two reasons why investing in effective stakeholder analytics is likely to deliver a valuable return on investment (ROI).

  • The first is by knowing who the important stakeholders are at any point in time, the expenditure on other processes such as communication can be focused where it is needed most, generating efficiencies and a ‘bigger bang for your buck’.
  • The second is stakeholders are a major factor in the risk profile of the work, their attitudes and actions can have significant positive or negative consequences and understanding the overall community provides valuable input to a range of processes including risk identification, requirements definition and schedule management.

At the most fundamental level, improving the management of stakeholders is directly linked to improving the quality of the organisation’s interaction with the stakeholders and as a consequence, the quality of the goods or services delivered to the end users or client (ie, stakeholders) as a result of being better informed whilst undertaking the work.

Quality was defined by Joseph Juran as fit for purpose, this elegant definition applies equally to the quality of your management processes as it does to your production processes and to the deliverables produced. And the three elements are interlinked; you need good management systems and information to allow an effective production system to create quality outputs for delivery to the client. A failure at any point in the chain will result in a quality failure and the production on deliverables that do not meet client requirements.

Placing stakeholder management within the context of quality allows access to some reasonably well researched data that can be interpolated to provide a reasonable basis for assessing the ‘return’ likely to be generated from an investment in stakeholder management.

Philip B. Crosby invented the concept of the ‘cost of quality’ and his book, Quality Is Free set out four major principles:

  1. the definition of quality is conformance to requirements (requirements meaning both the product and the customer’s requirements)
  2. the system of quality is prevention
  3. the performance standard is zero defects (relative to requirements)
  4. the measurement of quality is the price of nonconformance

His belief was that an organization that established a quality program will see savings returns that more than pay off the cost of the quality program: “quality is free”. The challenge is knowing you fully understand who the ‘customers’ actually are, and precisely what their various requirements and expectations are, and having ways to manage mutually exclusive or conflicting expectations. Knowing ‘who’s who and who’s important’ is a critical first step.

Feigenbaum’s categorization of the cost of quality has two main components; the cost of conformance (to achieve ‘good’ quality) and the cost of poor quality (or the cost of non-conformance).

Derived from: Feigenbaum, Armand V. (1991), Total Quality Control (3 ed.), New York, New York: McGraw-Hill, p. 109, ISBN 978-0-07-112612-0.

The cost of achieving the required level of quality is the investment made in the prevention of non-conformance to requirements plus the cost of testing and inspections to be comfortable the required quality levels have been achieved.

The cost of poor quality resulting from failing to meet requirements has both internal and external components. The internal costs are associated with defects, rework and lost opportunities caused by tying people up on rectification work. External failure costs can be much higher with major damage to an organisation’s brand and image as well as the direct costs associated with fixing the quality failure.

The management challenge is balancing the investment in quality against the cost of quality failure to hit the ‘sweet spot’ where your investment is sufficient to achieve the required quality level to be fit for purpose; overkill is wasted $$$$. But first you and ‘right stakeholders’ need to agree on precisely what fit for purpose actually means.

Also, the level of investment needed to achieve the optimum cost of quality is not fixed. The better the organisation’s quality systems, the lower the net cost. Six sigma proponents have assessed the total cost of quality as a percentage of sales based on the organisations sigma rating.

This table demonstrates that as the quality capability of the organisation improves, the overall cost of quality reduces offering a major competitive advantage to higher rating organisations. Most organisations are rated at 3 Sigma so the opportunity for improvement is significant.

Within this overall framework, the costs and risks associated with poor stakeholder engagement are significant and follow the typical pattern where most of the costs of poor quality are hidden. Using the quality ‘iceberg metaphor’ some of the consequences of poor stakeholder engagement and communication are set out below:

 

Effective stakeholder analysis and management directly contributes to achieving the required quality levels for the organisation’s outputs to be fit for purpose whilst at the same time reducing the overall expenditure on the cost of quality needed to achieve this objective. The key components are:

  • Effective analysis of the stakeholder community will help you identify and understand all of the key stakeholders that need to be consulted to determine the relevant aspects of fit for purpose.
  • Understanding the structure of your stakeholder community facilitates the implementation of an effective two-way communication strategy to fully understand and manage the expectations of key stakeholders.
  • Effective communication builds trust and understanding within a robust relationship.
    o Trust reduces the cost of doing business.
    o Understanding the full set of requirements needed for the work to be successful reduces the risk of failure.
    o Robust relationships with key stakeholders also contribute to more effective problem solving and issue management.
  • Maintaining the stakeholder engagement effort generates enhanced information that will mitigate risks and issues across all aspects of the work.

Calculating the Return on Investment:

Effective stakeholder management is a facilitating process that reduces the cost, and increases the efficiency of an organisations quality and risk management processes. Based on observations of similar process improvement initiatives such as CMMI, the reduction in the cost of quality facilitated by improved stakeholder engagement and management is likely to be in the order of 10% to 20%.

Based on the typical ‘Level 3’ organisation outlined above, a conservative estimate of the efficiency dividend per $1million in sales is likely to be:

     Total cost of quality = $1,000,000 x 25% = $250,000
     Efficiency dividend = $250,000 x 10% = $25,000 per $1 million in sales.

Given the basic costs of establishing an effective stakeholder management system for a $5million business, using the Stakeholder Circle®, (See: http://www.stakeholder-management.com) including software and training will be between $30,000 and $50,000 the efficiency dividend will be:

      ($25,000 x 5) – 50,000 = $75,000
      (or more depending on the actual costs and savings).

The element not included above is the staff costs associated firstly with maintaining the ‘culture change’ associated with introducing an effective stakeholder engagement process and secondly with actually performing the stakeholder analysis and engagement. These costs are embedded in the cost of quality already being outlaid by the organisation and are inversely proportional to the effectiveness of the current situation:

  • If current expenditures on stakeholder engagement are relatively low, the additional costs of engagement will be relatively high, but the payback in reduced failures and unexpected risk events will be greater. The overall ROI is likely to be significant.
  • If the current expenditures on stakeholder engagement are relatively high, the additional costs will be minimal (implementing a systemic approach may even save costs), however, the payback in reduced failure costs will be lower because many of the more obvious issues and opportunities are likely to have been identified under the current processes. The directly measurable ROI will be lower, offset by the other benefits of moving towards a higher ‘Sigma level’.

Conclusion:

The introduction of an effective stakeholder management system is likely to generate a significant ROI for most organisations. The larger part of the ‘return’ being a reduction in the hidden costs associated with poor stakeholder engagement. These costs affect reputation and future business opportunities to a far greater extent than their direct costs on current work. For this reason, we feel implementing a system such as the Stakeholder Circle is best undertaken as a strategic organisational initiative rather than on an ad hoc project or individual workplace basis.

The path to organisational Stakeholder Relationship Management Maturity (SRMM®) is discussed at: http://www.stakeholdermapping.com/srmm-maturity-model


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.


Managing risk

April 9, 2012

One of the most overlooked processes for effectively managing the day-to-day uncertainty that is the reality for every single project, everywhere, all of the time, is an effective performance surveillance process. This involves more than simply reporting progress on a weekly or monthly basis.

An effective surveillance system includes regular in-depth reviews by an independent team focused on supporting and helping the project team identify and resolve emerging problems. Our latest White Paper, Proactive Project Surveillance defines this valuable concept that is central to providing effective assurance to the organisation’s key stakeholders in management, the executive and the governance bodies that the project’s likely outcomes are optimised to the needs of the organisation.


Stakeholder Risk Tolerance

April 3, 2012

Managing the inherent risk associated with undertaking any project, anywhere, in any industry is a critical organisational capability. Within the organisations overall Project Delivery Capability (PDC) the maturity of its risk management approaches is central to the organisation’s ability to generate value (see more on PDC Maturity).

Only very immature or deluded organisations seek or expect to run ‘risk free’ projects. To quote Suzanne Finnamore: “Delusion detests focus and romance provides the veil.” Any sensible analysis of any business activity will indicate levels of risk; effective organisations understand and manage those risks better then ineffective organisation.

The skills that a mature organisation brings to the art of ‘risk management’ is to focus effort on managing risks that can be managed, providing adequate contingencies for those risks that cannot be controlled and deciding how much residual risk is sensible. The balance that has to be struck is between the cost and time needed to reduce the risk exposure further (the pay-back diminishes rapidly), the impact of the risk if it occurs and the profit to be made or value created as a result of the total expenditure on a project.

The sums are superficially simple; adding another $100,000 to the cost of a project to reduce its risk exposure by $10,000 reduces the value of the project by $90,000. In competitive bids, increase your bid price too much and the value drops to $Zero because the organisation fails to win the work! However, the situation is more complex; the nature of the risk may require the expenditure regardless of the potential saving (particularly in areas of safety and quality) and whilst expenditures are reasonably quantifiable, the actual cost of a risk event and the probability of it occurring are variable and cannot be precisely defined for a unique project. Our paper The Meaning of Risk in an Uncertain World discusses these issues in more depth.

To develop a mature approach to risk management, each layer of management has a role to play:

  • The organisation’s governing body (typically a Board of Directors) is responsible for developing an appropriate risk taking policy and defining the organisations ‘risk appetite’.
     
  • The Executive are responsible for creating the culture and framework that approached the management of risk within the parameters set by the Board in a capable and effective way.
     
  • Senior management are responsible for implementing the risk management system.

The mark of a mature organisation is the recognition at all levels of management that having implemented these systems, the organisation still has to expect failure! Every single project has an associated risk and properly managed, these risks are at an acceptable level for the organisation. But if there is a probability for success, there has to be a corresponding probability of failure!

Assuming the organisation is very conservative and requires budgets to be set with appropriate contingencies to offer a 90% certainty of being achieved, and this setting is applied to all projects consistently, the direct consequence is an expectation that 1 in 10 projects will overrun cost. Certainly 9 out of 10 projects will equal or underrun cost but there is always the remaining 10%. Mature organisations expect the profits and un-spent contingencies on the ‘9 underruns’ to more then offset the ‘1 overrun’. However, these ‘expected failures’ tend to be totally ignored by immature executives who want to pretend there is ‘no risk’ and then blame the PM for the failure.

There are two aspects of dealing with the ‘expected failures’ implicit in any realistic risk assessment. The first is setting the boundaries of accepted risk at an appropriate level of the organisation. Aggressive ‘risk seeking’ organisations will set a lower threshold for acceptability and experience more failures that conservative organisations. But the conservative organisations will achieve far less.

Source: Full Monte Risk Analysis

Looking at the cost aspect of risk for the project above, the most likely cost for this project is $17,500 but this is optimistic with a less then 50% chance of being achieved. The range of sensible options are to set the budget at:

  • The Mean (50% probability of being achieved) is $17,770.
     
  • Add one standard deviation to the Mean increases the probability of achieving the project to 84%, but the budget is now $18,520.
     
  • Add two standard deviations to the Mean and the probability of achieving the budget increases to 97% but the budget is now up to $19,270.

From this point, the pay-back diminishes rapidly, to move from 97% to 99.99% (six sigma), an additional $3,000 would be required in contingencies making a total contingency of $4,770 to effectively guaranteed there will be no cost overruns. Because of this very high cost for a very limited change in the probability of achieving the objective most projects focus on either the 80% or the 90% probabilities.

However, even within these relatively sensible ranges, making a sensible allowance for risk has consequences. Assuming all projects have a similar cost distribution and the organisations total budget for all projects is $10 million the consequences are:

  • To achieve a 50%/50% probability of projects achieving budget, approximately 1.6% of the budget will need to be allocated to contingencies: $160,000
     
  • To achieve an 84% probability of projects meeting the allocated budget, approximately 5.8% of the budget will need to be allocated to contingencies: $580,000
     
  • To achieve a 97% probability of projects meeting the allocated budget, approximately 10.1% of the budget will need to be allocated to contingencies: $1,010,000

Whilst the mathematics used above are highly simplified, the consequences of risk decisions are demonstrated sufficiently for the purpose of this post (for more on probability see: WP1037 – Probability). To be 97% sure there will be no cost overruns, more than 10% of the available budget to undertake projects will be tied up in contingencies that may or may not be needed, the consequence is less than 90% of the possible project work will be undertaken by the organisation in a year. The projects ‘not done’ are opportunities foregone to be ‘safe’.

In a competitive bidding market, adding 10% to your estimate to be 90% sure there will be no cost overruns is likely to have a more dramatic effect and price the organisation out of the market resulting in no work. In either situation a careful balance has to be struck between accepted risk and work accomplished, this is a governance decision that needs input from the executive and a decision by the Board.

The governance challenge is getting the balance ‘right’:

  • The higher the safety margin the more likely most projects will underrun and the greater the probability some of the contingent reserves will not be used and therefore opportunities to use the funds elsewhere are foregone.
     
  • However, reducing the reserves increases the probability that more projects will overrun (ie, ‘fail’) and this increases the probability that in aggregate the whole project budget will be exceeded.

The challenge for the rest of management is making sure the data being used is as reliable as possible.

The second key feature of mature organisations is the existence of efficient scanning systems to see problems emerging backed up with effective support systems to proactively help the project team achieve the best outcome. The key words here are ‘proactive’ and ‘help’. The future is not set in concrete and timely interventions to help overcome emerging problems can pay dividends. This requires a culture of openness and supportiveness within the organisation so that the root cause of the emerging issue can be quickly defined and appropriate support provided, promptly and effectively. This approach is the antithesis of the approach adopted by immature organisations where the ‘blame game’ is played out and the project team ‘blamed’ for every project failure.

In summary, the organisation’s directors and executive managers need to determine the appropriate risk tolerance levels for their organisation and then set up systems that have the capability of keeping most projects within these accepted boundaries. Understanding and managing risk is a key element of PDC. But having done all of this, mature risk organisations know there are still Black Swans lurking in the environment and remain vigilant and responsive to unexpected and unforeseen events.


Project and Organisational Governance

December 28, 2011

One of the themes running through several of my recent posts is the importance of effective Governance. Both organisational governance and its sub-set project governance.

Good governance is a synonym for ‘good business’, structuring the organisation to deliver high levels of achievement on an ethical and sustainable basis. This requires the optimum strategy and the right approach to risk taking supported by sufficient processes to be reasonably confident the organisations limited resources are being used to achieve the best short, medium and long term outcomes.

Project governance focuses on the portfolios of programs and projects used by the organisation to deliver many of the strategic objectives. This process focuses first on doing the right projects and programs constrained by the organisations capacity to undertake the work – Portfolio Management; secondly, creating the environment to do the selected projects and programs right- developing and maintaining an effective capability; and lastly systems to validate the usefulness and efficiency of the ongoing work which feeds back into the selection and capability aspects of governance.

Within this framework, portfolio management is the key. Strategic Portfolio Management focuses on developing the best mix of programs and projects to deliver the organisations future within its capacity to deliver. This means taking the right risk and having sufficiently robust system in place to identify as early as possible the ‘wrong projects’, so they can be either be reframed or closed down and the resources re-deployed to other work.

It is impossible to develop an innovative future for an organisation without taking risks and not every risk will pay off. Remember Apple developed the ‘Apple Lisa’ as its first GUI computer which flopped in the market, before going on to develop the Apple Macintosh which re-framed the way we interact with machines.

Apple Lisa circa. 1983

Obviously no organisation wants to have too many failures but good governance requires ‘good risk taking’. Apple had no guarantees the i-Pod and its i-Tunes shop would succeed when it started on the journey of innovation that has lead to the i-Phone, i-Pad and Apple becoming one of the largest companies in the world based on capitalisation. As Richard Branson says – ‘you don’t bet the company on a new innovation’ but if you don’t innovate consistently, obsolescence will be the inevitable result.

The balance of project governance focuses around creating the environment that generates the capability to deliver projects and programs effectively, effective sponsorship, effective staff development, effective and flexible processes and procedures, simple but accurate reporting and good early warning systems to identify issues, problems and projects no longer creating value (a pharmaceutical industry saying is that if a project is going to fail it is best to fail early and cheap!).

Good questions outrank easy answers! Every hour and dollar spent on governance processes is not being spent on developing the organisation. The challenge of good governance is to have just enough reporting processes embedded in an effective culture of openness and accountability to provide an appropriate level of assurance the organisations resources are being used effectively; whilst at the same time allowing innovation and development. Restrictive and burdensome governance processes are simply bad governance – they restrict the organisation’s ability to achieve excellence.

To help organisations understand these key governance processes we have updated our two White Papers on the subject:
Corporate Governance: http://www.mosaicprojects.com.au/WhitePapers/WP1033_Governance.pdf
Project Governance: http://www.mosaicprojects.com.au/WhitePapers/WP1073_Project_Governance.pdf

For more discussion around the subject of governance see the previous posts on this blog.