Project Estimation: Bench activities

Project Estimation: Bench activities

by | 16 Jul, 2024 | Blog

Project Estimation

One of the biggest misconceptions in project management is the idea that project cost is a sum of the cost of individual activities. It is not.

Projects always have unavoidable idle time and cost. The idle cost must be included in the project’s overall cost.

The challenge is to develop a DYNAMIC delivery model that can accurately calculate:

  • Resource critical path (that defines overall duration) and
  • Overall project cost (including idle cost).

It is relatively easy to develop a model that can calculate one or another, but not both at the same time.

Resource Demand

A project requires various skill sets and needs people and equipment to be hired with such skills.

Ideally, it would be great to hire resources only for a period of time when they are actually needed, but practically, it may not be possible as:

  • It is impossible to predict demand precisely. Delay or acceleration in one part of the project changes demand in another part;
  • Demand for specialised skills may not be flat. Some days, projects may need more resources with specialised skills than others.
  • If the resource is not secured, it may not be available straight away

To secure access to critical skill sets, project resources are paid for the TIME of engagement, not work performed.

Projects usually have idle time for specialised resources. If the project does not pay for idle time, the project may need to wait until the resource is available. However, if the risk is mitigated by securing resources, the project has idle cost that must be included in the overall project cost.

Idle cost belongs to the project but doesn’t belong to any activity.

It creates an assignment dilemma:

  • If resources are assigned to related activities, we can calculate the resource critical path but not the overall cost;
  • If resources are assigned to hammock activities instead, we can calculate overall cost but not resource critical path;
  • If resources are assigned to related activities and hammocks, it doubles resource quantity.

Bench Activity 

The solution to this dilemma is Bench Activities.

Bench activities work like hammock activities, with one critical difference. In Hammock activities, resources are assigned with FIXED assignment. It works well for project support resources.

Bench activity is a dummy activity that should not drive the resource-critical path. It may or may not have a fixed duration (based on an arrangement agreement) and has a VARIABLE resource assignment.

When a resource does not perform any activity, it is AUTOMATICALLY moved to the bench activity. The cost of all bench activities is the project idle cost.

In that case, a dynamic delivery model can calculate resource critical path and overall cost correctly.

It also opens an opportunity for two valuable project control metrics: ‘idle time’ and ‘idle cost’. These metrics could be applied to the whole project, a work package or skillset.

In this example, six activities require the same skill (Specialist). Demand for this skill is not 100%. There are periods when fewer specialists are needed. The bench activity calculates the cost of resources when they are not assigned to any activity.

If the duration of any activity and/or resource supply changes, idle and overall costs are automatically recalculated.

Alex Lyaschenko

PMO | Portfolio Planning & Delivery | PMP | P3O Practitioner | AgilePM Practitioner | Six Sigma

Monte Carlo Simulation Challenges: Third Probability Axiom.

Monte Carlo Simulation Challenges: Third Probability Axiom.

by | 7 Jul, 2024 | Blog

The standard probability axioms are the foundations of probability theory introduced by Soviet Union mathematician Andrey Kolmogorov almost a century ago. These axioms remain central and have direct contributions to mathematics, the physical sciences, and real-world probability cases, except project management.

How does it happen that some of the fundamental principles of risk analysis are ignored in project management, and how does it impact the result of the Monte Carlo Simulation analysis?

Probability axioms

We assign a probability measure P(A) to an event A. This is a value between 0 and 1 that shows how likely the event is. If P(A) is close to 0, it is very unlikely that the event A occurs. On the other hand, if P(A) is close to 1, A is very likely to occur. The main subject of probability theory is to develop tools and techniques to calculate probabilities of different events. Probability theory is based on probability axioms that act as the foundation for the theory.

Axiom 1: For any event A, P(A)≥0.
Axiom 2: Probability of the sample space S is P(S)=1.
Axiom 3: If A1,A2,A3,⋯ are disjoint events, then P(A1∪A2∪A3⋯)=P(A1)+P(A2)+P(A3)+⋯

Translating Kolmogorov’s probability axioms in plain language we can say that:
• Probability of risk event is nonnegative.
• Probability of all possible risk outcomes is 100%.
• For every collection of mutually exclusive risk outcomes, the probability of their union is the sum of the individual probabilities.

Project risk management practices and popular risk simulation tools ignore the third probability axiom, making the Monte Carlo Simulation results unreliable.

There are two main reasons:
• the way project delivery models are created;
• the way risk events are analysed, probability and consequences are estimated.

Risk Analysis Challenge

According to the third axiom, a risk event may have multiple mutually exclusive outcomes. Each has a probability of occurring, and together, they have 100% likelihood. 

Traditionally, in project management, risk events are analysed with only two outcomes: the planned scenario vs all other possibilities. If a risk event has multiple scenarios, the impact of one of them (usually the worst case) is analysed. However, the probability of the analysed scenario is not sum of all ‘other scenarios’.

Example:
You can win or lose by throwing a dice. If it is 1 or 2, you win 100$. If it is 6, you lose 150$. Otherwise, draw.

In project management, such a risk event is likely to be estimated with 67% probability with a consequence minus 150$ (as the worst scenario).

Instead, it has to be:
• 33% +100$
• 50% no impact
• 16% -150$

Widely applied two-dimensional risk registers don’t allow to store of multiple probabilities outcomes in the one risk record. Such thinking creates problems with Risk Matrix and other risk management methods, not just Monte Carlo Simulation analysis.

Critical Path Method (CPM) challenge

Even if a project can evaluate probabilities correctly and find a way to store risk data, they may not be able to apply it to Monte Carlo Simulation Analysis.

The uniqueness of project risk management as it exists today is in the typical approach of creating a deterministic project delivery model and using it as the base for planning, analysis, and control. It simplifies (or oversimplifies?) project complexity and opens an opportunity to calculate planning and delivery metrics. A few to mention: Total Float, Earned Value, Team velocity, etc.

Implementing the third axiom requires ‘AND’ & ‘OR’ conditions, but applied deterministic models are based on ‘AND’ logic only. There is no way to implement ‘it depends on’ scenarios in CPM, CCPM or Scrum delivery models.

Why is this a problem?
Let’s review the following use case:

A project requires testing. It is impossible accurately predict how many testing cycles are needed. It could be one, two or three test cycles with the following probabilities:

One testing cycle: 30%
Two testing cycles: 60%
Three testing cycles: 10%

In deterministic CPM-based modelling, one of the scenarios must be used as the base, and other options are considered to be a risk event. Depending on which scenario is chosen as the base, the risk could be a threat, opportunity, or both:

• If the base scenario is ‘one testing cycle,’ it can only get worse. So, the risk event is a THREAT.

• If ‘three testing cycles’ is the base, it can only be better. The event is an OPPORTUNITY.

• However, if ‘two testing cycles’ is the base, it can be better or worse, so the event is threat and opportunity. It is a THROPPOTUNITY.

It is quite possible that the project team chose ‘two testing cycles’ be the base scenario for the CPM modelling. In that case, correct risk modelling may not be possible, as risk modelling tools only classify risk events as threats or opportunities.

I believe such tools don’t comply with ISO 31073:2022 Risk Management. ISO 31073:2022 does not recommend a term to describe a risk with positive and negative outcomes, but it states that such an event is possible.

Risk – effect of uncertainty on objectives.

Note 1 to entry: An effect is a deviation from the expected. It can be positive, negative or both, and can address, create or result opportunities and threats.

The result of the Monte Carlo Simulation analysis should not depend on which scenario is chosen as the base.

However, the fact that a base is required impacts how a dynamic delivery model is developed.

Let’s review possible options.

Option 1: ‘One testing cycle’ is the base.

In this case, the risk event has 70% (60% + 10%) probability with two possible outcomes:
2 cycles: 86%
3 cycles: 14%

Scenario probabilities:
1 cycle = 30%
2 cycles = 86% * 70% = 60%
3 cycles = 14% * 70% = 10%

Option 2: ‘Two testing cycles’ is the base.

In this case, the risk event has 40% probability with two possible outcomes:
1 cycle: 75%
3 cycles: 25%

Scenario probabilities:
1 cycle = 75% * 40% = 30%
2 cycles = 60%
3 cycles = 25% * 40% = 10%

Option 3: ‘Three testing cycles’ is the base.

In this case, the risk event has 90% probability with two possible outcomes:
1 cycle: 33%
2 cycles: 67%

Scenario probabilities:
1 cycle = 33% * 90% = 30%
2 cycles = 67% * 90% = 60%
3 cycles = 10%

Theoretically, if a project delivery model is developed correctly, the Monte Carlo Simulation analysis result will be the same regardless of which scenario was chosen as the base. Practically, such analysis is impossible as popular planning and risk management tools have two gaps:
• Planning tools don’t support ‘OR’ logic.
• Risk events have ONE outcome only.

Solutions

To be able to fully extend probability analysis to project management changes in project management methods, trainings and delivery tools are essential.

People: Theory of probability analysis need to be included in project risk management standards and trainings.

Processes: GERT (Graphical Evaluation and Review Technique) model based on conditional scheduling has to replace CPM models.

Tools: It is essential that project risks are fully embedded in project delivery model. For that risk registers and Monte Carlo Simulation Analysis must part of planning and delivery tools, not to be performed in standalone risk management systems.

Let’s back to the above use case and review possible solution.

There are multiple ways how dynamic delivery model  can be developed. This is one of them: delivery schedule includes all three scenarios and depending of team preference any of them could be the base. It may impact CPM metrics but it would not impact result of Monte Carlo Simulation.

One Test Cycle

Two Test Cycles

Three Test Cycles

Alex Lyaschenko

PMO | Portfolio Planning & Delivery | PMP | P3O Practitioner | AgilePM Practitioner | Six Sigma

Earned Schedule Metrics Challenge

Earned Schedule Metrics Challenge

by | 15 May, 2024 | Blog

It sounds like EVM is the topic of the week on LinkedIn 😊 It prompts me to
raise awareness of one popular myth that pops up whenever EVM challenges are discussed.

👺 Myth: “Earned Schedule addresses EVM methodological time management problems”.

One of LI’s comments: “A good alternative to SPI is the Earned Schedule created by Walter Lipke, while SPI makes measurements the schedule deadline in money, earned schedule makes in time (i.e. days) much more reliable and understandable.”

No, it doesn’t! Earned Schedule addresses one problem, but others are so big that time forecast is still unreliable.

🔮 Addressed challenge:
The original EVM method is based on the assumption that the remaining part of the project will be performed as it was planned on time of baseline. Walter pointed out that current progress is a better proxy and offered a set of metrics to apply the new ‘TPI – Time Performance Index ‘ proxy.

It is the right idea that the performance factor has to be considered, so Earned Schedule is an excellent addition to EVM and is a better alternative to SPI. However, it does make forecasts reliable! It doesn’t show when the project is likely to be delivered!

There are other challenges that should not be ignored.

💣 Critical path.
We can’t apply the same principle to forecasting cost and time!

A dollar spent on a project will be added to the overall cost regardless of where it was spent. However, a day of delay may or may not impact the delivery date, depending on whether the delay was on a critical path.

The completion date depends on critical path activities, not all activities.
Both EVM and ES ignore this fact.

💣 Risk profile.
Let’s assume a project progressed ideally; all works performed as per the original plan but the probability of one risk is changed from low to high. It means that if the risk impacts activities that are likely to be on a critical path, the expected completion date is changed, but both SPI and TPI can’t show that.

💣 Project stages
Projects progress through different stages, meaning different activity types drive critical paths. Each stage has its unique uncertainties, challenges, and opportunities.

💡 There are no reasons to assume that previously materialised risks will materialise again for the same project!

Even worse, a project may accelerate delivery, pushing risks to later stages of the project. Rush (to initiate/design/develop/etc.) compromising maturity & quality may help with good performance but will likely cause delays during testing.

Due to the unique nature of projects, it is impossible to predict completion dates just by analysing past performance. It must be done by analysing the remaining work and risks. Performance is a complementary factor, not the base for such analysis.

Alex Lyaschenko

PMO | Portfolio Planning & Delivery | PMP | P3O Practitioner | AgilePM Practitioner | Six Sigma

Project Resource Levelling and Risk Analysis

Project Resource Levelling and Risk Analysis

by | 29 Apr, 2024 | Blog

The results of Project Risk Analysis performed without considering resource limitations are not reliable.

Project practitioners are usually aware that a risk may impact cost, completion date, and resource demand. However, that there is an opposite correlation between resources and risks.

Resource limitations may impact risk consequences.

Let’s review the following scheduling quiz:

Project with resource constraints and a risk

A project has two streams of work: A->B and C->D and will be completed when both streams are completed.
The project has activity uncertainties, resource uncertainty and one risk.
Activity uncertainties
The duration of each activity is estimated as a range. Let’s consider 2-point estimations to keep it simple.
Resource uncertainty
Activities A and C require the same skill. So, two resources are needed to perform these activities in parallel. However, it is unclear if the second resource is going to be available or not.
Risk
The project has a risk associated with Activity D. Activity D will take one day longer if the risk materialises. There is an opportunity to fully mitigate the risk, but it requires additional expenses.
Project priorities and goal

The goal is to complete the project as soon as possible with the fewest expenses.
The project team needs to determine the overall duration (as a range) and decide whether it is worth mitigating the risk.

Optimistic project plan

Let’s review an optimistic scenario: each activity takes the least possible time, there are two resources ‘Resoucre 1’, and the risk is mitigated. This project takes 12 days.

Optimistic plan with the resource constraint

How could the plan be optimised if only one resource is available (to perform Activities A and C)? There are only two possible options: to either delay Activity A or Activity C.

Option 1a: delay Activity A

Option 1b: delay Activity C

It seems obvious to choose Option 1a, mitigate the risk, and complete the project in 12 days.

Pessimistic project plan

The project plan without resoucre constraints based on pessimistic durations doesn’t look dramatically different.
The critical path is the same as it was in the optimistic scenario. It still makes sense to mitigate the risk and complete the project in 14 days.

Pessimistic plan with the resource constraints

Let’s add the resource constraint to the pessimistic scenarion. There are still only two possible options: delay Activity A or Activity C:

Option 2a: Delay Activity A

Option 2b: Delay Activity C

It still makes sense to complete Activity C before Activity A. However, please pay attention to Activity D. This activity is no longer on the resource critical path, so incurring extra expenses for risk mitigation doesn’t make sense. If Activity D takes one day longer, it will not delay the project completion date. The consequence of the risk has changed!

Conclusion N1: A change in resource allocation in one part of the schedule may change risk consequences in another part.

This is a very simple example, and we can track the impact of each uncertainty on all project attributes and the overall result. Real-life projects are more complex. Even small projects have uncertainties, resource limitations and risk events. As a result, the Resource Critical Path is volatile. Without a dynamic delivery model, it is usually impossible to understand how a change in one project parameter impacts other project parameters and project objectives. 

If the consequences of evaluated risks may change after resource levelling, risk evaluation needs to be repeated after each levelling cycle. However, risk re-evaluation is a time-consuming task, and it would be beneficial if a project delivery system could automatically identify changes in the risk profile after re-levelling is performed. 

 

Quiz answers

How long does it take to deliver this project?

If the delivery plan is optimised and used to drive project decisions, it takes 12-16 days, depending on uncertainties. However, wrong decisions can extend the project to 20 days (25%).

Should the risk be mitigated?

This question is not as simple as it may sound and has no YES/NO answer.

Depending on uncertainties, the risk may impact the overall project duration and need to be mitigated, or in some circumstances, the mitigation would not bring any benefits but rather would cause extra expenses.

We found two answers based on edge-case scenarios:

– The optimistic scenario: definitely mitigate risk.

– The pessimistic scenario: definitely not mitigate risk.

These two extremes give an an opposite answer. Optimistic and Pessimistic scenarios have a nearly zero chance of occurring. The actual progress will be somewhere in between these two extremes.

Additional information is required to enable a data-driven decision .

Risk Period

The quiz specified that if the risk is materialised, it takes one day longer to complete Activity D but it doesn’t explain the risk period. A potential period could be:

  • Before Activity D start date;
  • Any time during Activity D period;
  • Specific day during Activity D.

Mitigation decision date

When is the latest date to decide on a risk mitigation strategy? It would be good if we could postpone our decision as we may be better informed by that time.

For example, the above analysis shows that if two resources are available, the risk has to be mitigated regardless of other uncertainties. So, when project commenced we may have some addional information that is not directly related to the project risk but couls help us to choose the best mitigation strategy.

Conclusion N2: Risk mitigation strategy is a variable parameter, not a stable risk characteristic.

Probabilistic approach
An alternative approach is to make a probabilistic decision. The project can calculate the chance the risk impacts the completion date by clarifying risk probabilities and building a probabilistic project delivery model. This approach can provide some vital information for project decisions. However, projects need to be extremely careful with this approach, as a low-quality model may show measling results and drive wrong project decisions.

Data-driven decisions require development of Dynamic Deliery Model that correctly shows how primary uncertenites and risks may impact project objectives (time, cost and benefits).

Could different project teams be using exactly the same initial information to develop a model that gives accurate and consistent outcomes? Could it be an another quiz?

Alex Lyaschenko

PMO | Portfolio Planning & Delivery | PMP | P3O Practitioner | AgilePM Practitioner | Six Sigma

Schedule Logic Check Metrics

Schedule Logic Check Metrics

by | 12 May, 2022 | Blog

One of the fundamental questions for any schedule health assessment is “Is the schedule logically driven?” There are some scheduling metrics that could help planners and schedulers to find the answer to this question. In this post, we will review some of them, that are related to missing dependencies.  

Missing Dependencies Metrics

Missing logic metrics is a group of metrics known as:

 

  • missing dependencies,
  • missing predecessors and successors,
  • open start & finish,
  • dangling activities.

This check is not as simple as many project managers and schedulers might think. In fact, it is actually very hard to answer the question: Are there any missing or incorrect dependencies in the schedule?

A very popular DCMA-14 Points schedule assessment includes a check of logic (metric N1). Schedulers who are familiar with a scheduling tool (usually Primavera or Microsoft Project) but lacking scheduling knowledge very often apply DCMA-14 “blindly”. Their schedule may have critical logical issues but is reported as a schedule with sufficient quality. I have seen this issue in small business projects and also in large construction programs. So, let’s review what needs to be considered for a comprehensive schedule logic analysis.

Missing Dependencies?

There is no metric that could confirm that a schedule has no dependencies missing.

The fact that each activity (except first and last) has a predecessor and successor doesn’t mean that another successor from/to this activity is not missing. The only way to guarantee that a schedule has correct logic is to implement correct schedule development and maintenance processes and apply control to ensure these processes are followed.

Each reporting period logic changes have to be analysed, documented and explained.

While scheduling metrics can’t guarantee that dependencies are not missing, some of them are good indicators that logic has to be checked and, if required, fixed. There are four primary schedule quality metrics used to indicate that a schedule may have a missing dependency:

♣   Missing Predecessor

All ‘Not Completed’ activities except 1st activity and external incoming activities must have a predecessor(s).

♣   Missing Successor

All ‘In Progress’ or ‘Not Started’ activities except the last activity and external outcoming activities must-have a successor(s).

♣   Open Start

Activities where only the predecessor(s) are either ‘Finish-to-Finish’ or Start-to-Finish resulting in an open start to the activity. All ‘Not Completed’ activities except 1st activity and external incoming activities must have at least one ‘Finish-to Start’ or ‘Start-to-Start’ predecessor.

♣   Open Finish

Activities where the only successor(s) are either ‘Start-to-Finish’ or ‘Start-to-Start’ resulting in an open finish to the activity. All ‘In Progress’ or ‘Not Started’ activities except the last activity and external outcoming activities must have at least one ‘Finish-to-Start’ or ‘Finish-to-Finish’ successor.

There is a number of points that have to be taken into consideration when these metrics are applied:

  • A project may have external dependencies and it is not always possible, and in some cases, not recommended to link schedules from different projects. Milestones representing such dependencies do not have predecessors or successors.
  • A Project may have Level of Effort (LoE), Hammock and WBS activities. Different scheduling tools implement these types of activities differently and this impacts the “missing logic” analysis. 

–   Hummocks in MS Project are shown without a predecessor and a successor but there is no way to identify “Hammock” type of activities in the system.

–   “WBS summary” activities in Primavera don’t need a predecessor or a successor. So they have to be excluded from the analysis. Another metric is required to check that “WBS summary” activities don’t have logic as Primavera permits linking activity to “WBS summary” activity.

–  In Primavera, if all activity successors are linked to LoE or “WBS summary” activities, the activity is actually missing a valid successor. Otherwise, based on the logic, there are no requirements to complete this activity. The same is applicable to predecessors. Such cases could only be identified via a specially developed project report, not via filters.

  • If a milestone has “Open Start” or “Open Finish” it actually doesn’t create any issues with logic. Milestones could be excluded from these metrics.
  • Microsoft Project has a unique feature to link activities with summary tasks. If this technique is applied it is very hard to analyse logic, as some of the activities are driven by logic from activities and some from summary tasks, so it is not recommended. An additional metric is required to identify summary tasks with processors and successors.

Filters

Missing logic metrics could be developed via filters in Primavera and Microsoft Project but, as described above, specifics of each tool have to be taken into account. Spider Project already has all these metrics build-in and also allows developing comprehensive additional filters as required.

Primavera filters to identify activities with missing logic:

♣  No Predecessors

♣  No Successors

♣  Open Finish

♣  Open Start

External Schedule Analysis Tools

When an external schedule analysis tool is used each metric has to be configured to address explained challenges. For example, Acumen Fuse has a pre-developed “Missing predecessors” metric. However, the metric includes ALL activities with missing predecessors. If an activity already started (or completed) it doesn’t matter if it has a predecessor or not. It is recommended to configure this metric to exclude these activities. Otherwise, the Acumen Fuse Report creates “noise” and may incorrectly show that the schedule has predecessors issues when it actually doesn’t.

Alex Lyaschenko

PMO | Portfolio Planning & Delivery | PMP | P3O Practitioner | AgilePM Practitioner | Six Sigma