Variation: Project Enemy Number One

There are some things that you know to be true, and others that you know to be false; yet, despite this extensive knowledge that you have, there remain many things whose truth or falsity is not known to you. We say that you are uncertain about them. You are uncertain, to varying degrees, about everything in the future; much of the past is hidden from you; and there is a lot of the present about which you do not have full information. Uncertainty is everywhere, and you cannot escape from it.

Dennis Lindley, Understanding Uncertainty

Quantitative risk assessments are commonly used to determine time and cost contingencies for engineering and construction projects. Eager software jockeys often do these “black-box” assessments using one of the many available software packages that provide a large variety of probability distributions. But project teams often don’t grasp the underlying principles that drive successful quantitative risk assessments when selecting distributions or assigning ranges. One of the fundamental principles of risk quantification is differentiating between uncertainty and variation.

Imagine developing the perfect project plan. All the project team members and contractors agree with it and it gets baselined. When the project is implemented, there are no changes; every task is completed exactly as estimated, the durations and effort are exactly as planned, the quantities and rates don’t change, there are no over- or underruns, and there are no scope changes. The project is completed exactly on time and to the budget, and it achieves all its business objectives.

But we know this never happens. Project plans are never perfect, and things change during project implementation. The difference between the perfect project and reality is variation and our uncertainty about the variation.

Predicting future events is an essential part of human existence and we are constantly faced with situations that require us to estimate uncertain outcomes. These estimates range from simple scenarios such as the time it will take to get to work, to complex predictions of how long it will take to complete a project with thousands of tasks. A consistent observation about our ability to estimate future events is that we often get it wrong and there are countless examples of failed human endeavors to support this. A second, equally prevalent, observation is that we do not learn from our past estimation mistakes, and often repeat those mistakes.

To counter our inability to estimate accurately, we add contingencies to our estimates. These contingencies are often based on expert judgment or “gut feel”, or they may be the result of carefully crafted statistical models.

Uncertainty has been studied extensively in many fields, including economics, statistics, metrology, insurance, philosophy and physics. The definition of uncertainty often depends on the perspective and needs of the user. To some, uncertainty is closely associated with risk, while others may see it simply as the choice between preferences.

In projects, our interest in uncertainly is specific to the estimation of cost and time. But project teams frequently suffer from planning fallacy, which leads them to underestimate the quantity of work and the time required to perform activities, or the cost of performing the activities. Kahneman and Lovallo describe two views of estimators. The inside view considers the specific estimating problem on its own merits of time, effort and skills required. The outside view ignores the factors that could affect the specific problem and focuses on similar historical cases in the estimating process. In estimation, we have an intuitive preference for our own inside views, and we tend to treat each estimate as a unique situation that is different from previous projects. This approach leads to inconsistencies in our estimation attempts.

A person who travels to work every day has little control over the time it takes to complete the journey. There are numerous factors that affect this journey, such as traffic lights, slow traffic, queues at intersections, roadworks and the weather. The time of the journey will vary from day-to-day and the traveler has limited influence over this variation. This is the natural variation of the event and it has some underlying probability distribution. For instance, the probability that the journey will take 5 minutes may be very low, but the probability that it will take 90 minutes is also very low. If we record the actual journey times over many days, we may find that the journey has a distinct probability distribution, like the one shown below.

However, when a person is asked to estimate how long it will take to travel to work on an average day, she will not have the luxury of a carefully developed probability density function or graph and will assess her travel time under uncertainty. This means that she will construct an assessment of the variation in her head, based on her past experiences, and decide what the most likely travel time is. Her assessed travel time could be more, less or the same as the measured most probable time.

The table and graphs below show the results of an actual experiment in which five participants had to give an initial three-point estimate of their travel time to work. They then recorded their actual travel time over 25 days. The estimated journey times are shown as PERT-distributions and the actual times as normal distributions.

These graphs illustrate the difference between uncertainty and variation. Four of the five participants were more pessimistic about their estimated journey times and the ranges (the difference between the highest and lowest durations) of the actual journey times are also smaller than the estimate. The estimated journey duration is an estimate under uncertainty and the actual time is the real variation in the travel time over 25 days. This experiment illustrates the dilemma with any estimate, the uncertainty of knowing what the true distribution of the variation will be or, in the case of a single value, what the actual value will be when the future event occurs.

Uncertainty is present whenever a human observes some real event that exhibits variation. The variation may follow a predictable pattern or may be completely random. A human observer of the event may notice that the event has variation and may attempt to predict the pattern or quantity of variation. The observer will make assumptions about the behavior of the variation pattern. These assumptions may lead the observer to believe that there is less, more, or the same variation than the actual case. We say that the human assessment of the variation is uncertain.

Excessive over- or underestimation of variation always leads to problems since the observer’s uncertainty pattern does not match the variation of real-world events, and business decisions are based on the observer’s assessment of the variation and not the actual variation. But one cannot blame the observer for not knowing the actual distribution since it will be known only after the event has occurred. It is for this reason that quantitative risk assessments are important. They are the best tools we have available to predict variation and to highlight the extent of our uncertainty, provided that we understand how to use these tools correctly.

When risks are assessed on a project, the project team should take note of the following:

  1. Risk registers and risk heat maps do very little to guide our understanding of uncertainty, variation and responses to risk – quantitative risk assessments are essential for project decision making.
  2. Successful quantitative risk assessments require analysts to clearly separate uncertainty from variation.
  3. Uncertainty is a human condition, but variation is independent and is not affected by the presence of a human observer. Range estimation of time and cost reflects the uncertainty of a specific observer about the underlying variation.
  4. Project variation can be reduced through better project definition, for instance requirements definition, engineering and design, and planning.
  5. Project uncertainty can be reduced if team members understand the underlying factors that drive variation. It can also be reduced by comparing project estimates to similar previous projects through benchmarking, independent project reviews, and reference class forecasting.


Kahneman, D., & Lovallo, D. (1993). Timid choices and bold forecasts: A cognitive perspective on risk taking. Management Science, 39(1), 17-31.

Lindley, D. V. (2006). Understanding uncertainty. Hoboken, New Jersey: John Wiley & Sons.

Project Success Relies On More Than Just Certifications And Technical Expertise

There is nothing more frustrating than appointing a project manager to manage a project and then they can’t deliver. You appoint someone under the premise that they’re fully competent based on their impressive CV, citing the right experience and knowledge. Then, after a few months, you find out the project manager couldn’t successfully execute what was required and the project is derailed. You are now facing three problems; the project is late, you don’t have a competent person to take control of it, and you are overspent and behind schedule.

For over 22 years we have been assisting organizations achieve repeatable project success by providing them with competent project personnel. Finding qualified and effective project personnel that can deliver projects successfully is a frequent problem that many of our clients experience. Although there are many project professionals out there, not all of them have the required set of skills to effectively deliver projects.

Two common cases that we observe in the industry are; ‘over-certified’ project managers and ‘accidental’ project managers. The ‘over-certified’ project manager have a string of certifications. They look good on paper but don’t necessarily have the “soft skills” or the ability to practically implement the knowledge they have gained. This results in impressive CV’s and high asking-salaries but once appointed the reality is an inability to lead project teams and to deliver projects successfully.

The ‘accidental’ project manager is a person who finds themselves managing a project without any formal project management training. They might have strong technical skills but are unable to consider the big picture and lack the experience to formally manage a project. This often results in cost and time overruns or incomplete requirements and project rework due to unsatisfied project sponsors (Hunsberger 2011).

The consequence with both these project managers is that the project suffers. We see and hear it all too often, how clients battle to find competent project managers that can effectively deliver projects from execution through to closeout and realize the intended business benefits. Managing a project from start to finish requires more than just the technical skills and tools that project managers traditionally focus on (PMI 2020). Research by Millhollan & Kaarst-Brown (2016: p.90) found that “Earning a certification may provide evidence of experience and knowledge; however, holding a certification does not always provide evidence of an IT project manager’s skill or his or her efficacy.”

We don’t disagree that being the holder of a project management certification is an indication of some level of baseline knowledge; however, this doesn’t mean that the project manager has the necessary ‘soft skills’ to deliver a project successfully (Millhollan & Kaarst-Brown, 2016, p.90). The PMI’s Pulse of the Profession® (2018: p.17), found that “four in five respondents reported that soft skills, such as communications, leadership, and negotiation, are more important today than they were just five years ago.”

We can therefore infer that certifications and technical skills aren’t the only things that make you a successful project manager, you must also possess the ‘soft skills’, the right experience in managing projects, and the ability to mobilize people. Project management is a soft science, and although many understand the theory, they don’t know how to apply it. With our extensive experience in projects, we know what to look for in competent project professionals. We conduct psychometric assessments, ask critical questions in our interviews, and have designed our own competency assessments that our candidate consultants must successfully complete.

We promote life-long learning through internal training and team knowledge sharing sessions, ensuring that our consultants constantly exemplify the key set of competencies of a successful project manager. Through our managed service we empower our project professionals to deliver projects from execution through to closeout.

Executives don’t have the time to constantly check up on their project managers. We ensure quality performance through regular internal consultant reviews. When you hire a project professional, you expect that person to have the required knowledge and skills to hit the ground running.

Contact us for peace of mind, let us restore your faith in project managers by providing you with the repeatable project success that you seek.


Hunsberger, K. (2011). The accidental project manager. PM Network, 25(8), 28–33.

Millhollan, C., & Kaarst-Brown, M. (2016). Lessons for IT project manager efficacy: A review of the literature associated with project success. Project Management Journal, 47(5), 89-106.

PMI, 2018. Pulse of the Profession. Success in Disruptive Times | Expanding the Value Delivery Landscape to Address the High Cost of Low Performance. Available at: [Accessed 06 October 2020].

PMI, 2020. Pulse of the Profession. Ahead of the Curve | Forging a Future-Focused Culture. Available at: [Accessed 02 November 2020].

Project Systemic Risk

ProjectLink has, over the past few years, performed a substantial amount of primary research on the matter of systemic risk in projects. The research involved real projects for which ProjectLink performed services such as Project Reviews and Quantitative Risk Assessments (QRA).

In projects, which are a type of system, systemic risks differ from “ordinary” risks because they cannot be addressed using conventional processes, such as identifying the individual risk, giving it a probability and impact score, determining a suitable risk response strategy, assigning an owner, monitoring the risk, and so forth. Instead, systemic risks are system-wide and, therefore, have the potential to overwhelm the entire system.

In considering probable project variance for schedule and time objectives, ProjectLink has found that, for a project for which systemic risks are not properly mitigated, the chance of time and cost overruns or even outright failure is often unacceptably high. To address the matter purposely, the observations lead to the formulation of several Systemic Risk Mitigation Areas (SRMA). Examples of such SRMA are project team history working together, the speed at which critical decisions are made, and the effectiveness of communication structures. These, and several more, are explored in the paper titled Managing Systemic Risk in Mining Capital Projects. Although the paper uses mining projects as case studies, in principle the key learnings are relevant to all types and sizes of projects. A few examples of lessons from the study that have universal application are as follows.

  1. All projects involve inputs, processes, and outputs; therefore, they are systems. Any system is subject to systemic risk, i.e. a type of risk that, if not identified and addressed pre-emptively, is likely to cause significant harm to the project.
  2. A project need not be earmarked for a QRA for it to benefit from systemic risk management, as it will also benefit qualitatively from doing so. For example, putting measures in place to effectively manage project communication will be beneficial to the project, regardless of whether the resulting successes can be measured in quantifiable terms.
  3. The causes of systemic risk are relatively easy to identify, as they are usually underpinned by good project management practice. For example, no-one who has ever worked with contracting in projects would need any convincing regarding the importance of proper contract clauses.
  4. Systemic risk mitigation takes a bit of effort but is relatively simple to implement; all it needs is some commitment.

Project Management Consultancy

With the current COVID-19 pandemic hitting South Africa, there are many companies that will be required to assist with the supply of various products and services to aid in the fight against the coronavirus. With a National State of Disaster having been declared in our country, numerous emergency projects will need to be executed successfully, with limited time and budget available. Effective project management will ensure that these products and services that are so desperately needed will be delivered as quickly and efficiently as possible, at a suitable standard to combat the effects of this virus.

In this regard, ProjectLink is offering Project Management, Project Administration and Project Planning and Scheduling services at cost to any companies that need assistance with their COVID-19 relief projects. We can provide you with a Project Manager, Project Administrator or Project Planner to assist you in delivering your project successfully. Whether you are in the healthcare, manufacturing, government, pharmaceutical, construction or engineering industry we have experience in all of them and we would like to help you make a difference.

This is a time for us all to stand together and help in any way that we can. We hope that our small contribution will aid our country in overcoming this devastating pandemic.  If you would like ProjectLink’s assistance with your COVID-19 relief project, please contact Sianne Carter at

Kind Regards,

Hannes van den Berg
Managing Director
Mobile Tel: +27 (0) 83 308 7051

Event: The Science of De-Risking Projects

Projects are uncertain endeavours with many unknowns during the Front-End Loading (FEL) phases leading up to the execution of the project.  Reducing the risk of choosing a sub-optimal solution is the main focus of these phases. When these phases are rushed or based on biased assumptions, the result is a project that has little chance of meeting its business objectives.

ProjectLink’s multi-faceted approach to project de-risking focusses on the work leading up to project execution to ensure that organisations perform projects optimally.

A complimentary breakfast will be served while our Professional Services team give an overview of the following De-Risking Solutions:

  • Decision Science
  • Project Reviews
  • Risk Quantification
  • Risk Management
  • Simulations

Let us show you how to navigate through a world full of risk, how we can shed some light and give you peace of mind! DATE: 18th October 2019
VENUE: Houghton Golf Course
TIME: 07:00 – 10:30 AM
RSVP: Kindly RSVP to

5 Steps For De-Risking A Project Schedule

Schedule risk in project management is the possibility that an activity or an entire project takes longer than initially planned. This often results in late completion and increased project cost. Schedule risk is frequently ignored during project planning and is only considered just before the project is presented for approval, leaving the project with little time to plan for risk mitigation actions or schedule contingency.

This article discusses the shortcomings of schedule risk identification in early planning phases, specifically in mining capital projects. Basic planning principles and schedule development methods for including risk during planning are discussed, as well as setting up the schedule for a Quantitative Risk Assessment (QRA) to determine schedule and cost contingencies.

Why is it important to provide for schedule risk?

The early stages of Front-end Planning (FEP) are performed to define a project and to reduce a project’s risk exposure. Optimal use of FEP will improve the predictability of the project and increase the likelihood of success. The primary focus of FEP for some project teams is to reduce project cost, while less emphasis is placed on de-risking the project schedule. This is shortsighted, as time overruns almost always lead to cost overruns.

Following are five methods I have found useful to increase schedule risk awareness during FEP phases and to prepare a realistic project schedule.

Method 1: Document risk drivers when developing your schedule

When developing a schedule during FEP, planners are often pressed for time to complete the schedule. Planners should guard against creating low integrity schedules just to meet deadlines. Identifying risk drivers while developing the schedule enables the team to plan for those risks and mitigate, or even eliminate them, before they can occur. Make use of columns in your scheduling software (risk cause, risk description, risk effect, probability, frequency of occurrence, impact, and response actions) to indicate the risks applicable to each line item. This information will be invaluable when conducting a QRA as the risks are already highlighted.

Method 2: Avoid overly optimistic durations

Scheduling unrealistically optimistic durations during FEP have no benefit during execution, neither to the project nor to the business. It reduces the likelihood of delivering the project within the communicated time and budget and degrades the confidence stakeholders have in the project team. Be realistic when estimating durations and make use of actual durations from similar previous projects and experience of team members.

Method 3: Conduct an independent schedule review

Independent project schedule reviews can be performed on both the project management and technical deliverables during FEP. Schedule reviews do, however, require review of all the planning information such as the scope of work and basis of schedule. Although this will not eliminate risks entirely, it will reduce uncertainty and improve the overall risk profile of the project.

Method 4: Apply the theory of constraints and critical chain scheduling

After determining the critical path of the project, evaluate the resource availability for activities in the schedule. This may result in a resource constrained project schedule and critical path which may require some alterations.

The alterations can then be done by applying the critical chain method when scheduling a single project. When resources work on multiple concurrent projects, consider theory of constraints (TOC). In an article `Project management applications of the theory of constraints beyond critical chain scheduling` by Herman Steyn he lists 5 steps to approach TOC:

  1. Identify the constraint(s) of the system;
  2. Decide how to exploit the constraint(s);
  3. Subordinate non-constraints to the decision(s) on exploiting the constraint(s);
  4. Elevate the constraint(s) (in other words: take steps to “widen the bottleneck”); and
  5. By returning to Step 1 above, determine whether the new constraint has been uncovered, rendering the constraint under consideration a non-constrain or less critical.

Method 5: Conduct quantitative risk assessment (QRA)

To conduct a schedule QRA, the impact of risk on the project is expressed numerically in terms of additional or reduced durations. Schedule contingency is calculated for both the entire project and the individual networks in the schedule. This assists with managing schedule contingency for the project and for individual contracts in the schedule. To calculate contingency through probability distribution methods or any other reputable method, contingency can be justified, which increases the probability of delivering the project in the expected time.

Werner G Meyer, author of ‘Quantifying risk, measuring the invisible’, writes more about Quantitative Risk Assessments.

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