Mastering Project Management: A Deep Dive into the Estimate Activity Duration Process

Introduction

Accurately estimating the duration of activities is a critical process in project management. The time it takes to complete project tasks directly impacts the overall project schedule and completion date. Underestimating activity durations can lead to schedule overruns, resource constraints, and cost escalations. Overestimating can build in unnecessary schedule slack and may lead to perceptions that the team is not working efficiently. Therefore, effective techniques for estimating realistic but aggressive activity durations are essential for project success.

This article provides an overview of activity duration estimation in project management. It covers key concepts and definitions, reasons for accurate estimates, commonly used estimation techniques with examples, and best practices for developing quality estimates.

Defining Activity Duration Estimates

Activity Duration Definition

An activity duration estimate defines the number of work periods required to complete a project activity. Activities are the individual tasks that must be performed to create project deliverables. Activity duration measures the elapsed time from start to finish of each task. Common units for measuring duration include hours, days, weeks or months.

The duration estimate attempts to quantify how long the work effort for an activity should take. Estimating activity duration is often described as predicting “how long something will take”. Duration estimates should consider the scope of work involved and the resources assigned. Accurate estimates require an understanding of the work effort needed as well as factoring in risks and unknowns.

Purpose of Duration Estimating

There are several key reasons why accurately estimating activity durations is important in project management:

• Develop Reliable Project Schedules: Duration estimates are required as inputs when generating the project schedule. Realistic estimates make schedules achievable.
• Assign Resources Appropriately: The duration of an activity helps determine resource needs and availability dates when scheduling resources.
• Monitor Progress Efficiently: Comparing actual progress against duration estimates helps identify schedule variances requiring corrective action.
• Maintain Management Credibility: Consistently meeting activity duration targets builds confidence in management’s ability to plan and execute projects.

Reasonable but Aggressive Estimates

Project managers should seek “reasonable but aggressive” activity duration estimates from teams. This means realistic appraisals of the work effort involved without excessive contingency padding. Activity duration targets should promptly communicate expectations while being achievable for workers assigned.

Padding estimates builds in unnecessary slack whereas overly idealistic targets cause teams to miss key dates. Well-crafted duration estimates balance attainability and a sense of urgency to support project success.

Types of Duration Estimating Methods

Project managers have several techniques available for predicting task durations. Each approach has advantages and drawbacks. Applying multiple estimations methods helps improve accuracy. Common techniques include:

• Expert Judgment: Leverage stakeholders’ specialized knowledge who have previously completed similar work. However, experts can still provide biased guesses rather than data-driven forecasts.
• Historical Data: Analyze actual durations from prior comparable projects. But every project still has unique attributes that can invalidate historical extrapolations.
• Published Estimating Data: Utilize reference tables, books, and digital tools that compile typical activity duration timeframes. Published data offers general guidelines but activities still vary widely in practice.
• Analogous Estimation: Compare the current activity’s scope against a similarly completed past activity and extrapolate the past actual duration. This method is fast and easy but still only estimates.
• Parametric Estimation: Use quantifiable activity parameters such as task effort hours or lines of code to calculate estimates via standardized formulas. Formulas provide objectivity but developing them can be complex.
• Three-Point Estimates: Have team members provide an optimistic, pessimistic, and most likely duration estimate then statistically analyze the results to trim bias and extremes. The three-point approach taps collective wisdom but applying statistics adds subjectivity.
• Reserve Analysis: Add contingency reserves onto an initial duration estimate to account for known-unknowns and unknown-unknowns that could impact the activity. Determining appropriate reserves levels is itself challenging.

Commonly Used Techniques

Expert Judgment

Expert judgment techniques leverage inputs from seasoned resources with deep knowledge and prior exposure with the type of work involved in an activity. Subject matter experts can draw on their specialized experience performing similar tasks to predict upcoming effort and duration.

The project manager should document the credentials and background that qualify identified experts. This helps establish their credibility and why their projections warrant validity. Expert judgment works best when experts have executed highly comparable activities within the recent past. Estimates derived longer ago under materially different circumstances become less relevant.

To apply an expert judgment approach:

• Identify enterprise personnel who match needed skillsets and possess extensive domain project experience
• Interview experts to detail their projections for the specific assignment based on prior efforts
• Consider blending inputs from multiple topic authorities to balance out biases
• Validate final estimates against other methods to check for reasonability

Example:

A project manager is estimating how long it will take two architects to create preliminary drawings for a 40-story downtown office tower residential conversion. An expert judgment technique would have the PM interview senior architects within the firm who have led similar residential conversion designs in the past. Their prior experience with comparable projects helps estimate the effort and duration for the new endeavor.

Analogous Estimating

With analogous estimation, durations are predicted by comparing the current activity to a similar past activity in terms of size, scope, complexity, or effort. The key to analogous estimating is identifying a past baseline project where detailed actual durations were recorded. This baseline project serves as a proxy benchmark for mapping out estimates on the current work.

The advantage of this technique is its simplicity. By benchmarking against historical precedence, analogous estimating provides a straightforward way to quickly quantifying estimates. It also provides a built-in data-driven analysis based on prior achievements. However, finding perfectly comparable precedents can be challenging. Apply judgment in determining how closely aligned the baseline example truly is.

To utilize analogous estimating:

• Thoroughly define key traits of the current activity requiring estimation
• Search historical project records to identify a completed activity with highly similar attributes & scope
• Gather detailed data on the actual effort hours, duration, and resources expended to complete the historical baseline activity
• Determine appropriate scaling factors to apply to baseline metrics to match the size of current activity
• Calculate a duration estimate for current work by adjusting baseline actuals

Example:

If a prior software enhancement involved 4 developers taking 6 weeks to add 5 new user interface screens, this analogous data could estimate how long it would take 3 developers to add 7 new screens now. Scaled proportionally, 9 weeks would be a plausible resulting estimate.

Parametric Estimating

Parametric estimating leverages quantifiable parameters about an activity to calculate its duration. This technique utilizes established parametric models tied to measurable activity attributes. Variables such as work effort hours, development team size, lines of code, or function points are fed into standardized formulaic models. The models output corresponding duration estimates based on proven correlations. A simple example would be

Duration = Effort Hours / Team Size.

The advantages of parametric models are their analytical objectivity versus subjective guesses. However, developing useful parametric models requires abundant relevant historical data. Parameters interacting in models must demonstrate stable causal relationships across projects for reliable extrapolations. Models need periodic auditing to confirm outputs match actual subsequent results. If underlying project work substantially changes over time then the model grows stale.

To implement parametric estimating techniques:

• Gather extensive quantitative data on pertinent completed project activities to serve as baseline cases
• Determine measurable activity parameters with strongest correlation to actual durations
• Build duration calculation models using those high-impact parameters through statistical analysis of baselines
• Define ranges where the parametric model provide reasonable outputs given the data variations
• As new projects execute, measure target activity parameters to input into models producing estimates
• Compare subsequent actual durations to parametric estimates to validate and enhance model continuing viability

Example:

A basic parametric estimation model uses work effort hours divided by team size to estimate software project task durations. Extensive analysis of prior projects shows tasks involving 350 – 550 programming hours by teams of 4 – 6 developers take 6 - 10 weeks. Using regression analysis a formula is created enabling new task inputs for effort and team size to produce projected durations.

Three-Point Estimating

Three-point estimating leverages inputs from multiple experts stating their optimistic, pessimistic, and most likely duration estimations. Statistical techniques are then applied to the 3 data points to approximate a final blended analysis that helps offset inherent human biases. This aims to capture a realistic range informed by practical implementation experience.

The advantages of three-point estimates are tapping multiple perspectives to frame the duration possibilities, identifying outlier positions, while ultimately landing on an objective data-driven duration. Challenges can come from influencing experts to provide candid projections during data collection. The final statistical analysis also introduces further interpretation subjectivity if not applied carefully.

To construct three-point estimates:

• Select at least 3 qualified experts familiar with the type of activity to independently generate estimates
• Have them each provide their assessment of the optimistic, pessimistic, and most realistic durations
• For each expert data set, apply a PERT (Program Evaluation Review Technique) calculation: (Optimistic + 4 x Most Likely + Pessimistic) / 6 determines one blended duration estimate per expert
• Average the blended PERT duration estimates across all experts to create a final activity duration

Example:

An engineer provides estimates of 4 weeks (optimistic), 12 weeks (pessimistic), and 8 weeks (most likely) for a technical design activity. Applying PERT analysis yields: (4 + 4x8 + 12) / 6 = 34/6 = 6 weeks blended estimate for that expert.

After gathering 3+ such mixed sets of estimates and running PERT calculations, average the resulting blended durations.

Reserve Analysis

Reserve analysis aims to buffer activity duration estimates by applying contingency reserves amounts. Reserves help account for known activity threats and risks as well as unplanned events that often delay tasks. Reserve determination methods size contingencies as a percentage of initial predictions or use historical delay data to quantify typical overruns for analysis.

Building reserve buffers directly into estimates helps mitigate against variability concerns not addressed otherwise. By acknowledging risks and unknowns upfront duration targets become attainable. If no delays materialize the resulting schedule slack also provides flexibility to absorb emerging issues later on. However, excessive contingency padding also builds inefficiency into project plans and reduces urgency to perform. Finding data-driven optimal reserve sizing is crucial for balancing these tradeoffs.

To properly incorporate reserve buffers:

• Develop initial activity duration estimate using another technique first
• Document known or likely risks that could impact the task duration
• Assess reserve levels needed to cover risks plus typical unplanned delays
• Apply quantitative data from past projects to derive statistically valid reserve ranges by activity type
• Establish reserve buffer policies capping total padding allowed (e.g. 10-20% of estimate)
• Add reserve duration amounts to initial estimate to create risk-adjusted final duration targets

Example:

Initial bottom-up estimates show testing a module will require 4 weeks. Past data indicates on average testing slips 2 weeks typically and up to 4 for more complex elements. After evaluating module complexity a 3 week testing contingency is added to the estimate. The final duration target thus builds in buffer by stating testing should take 4 weeks + 3 week reserve = 7 week estimate.

Best Practices for Quality Duration Estimates

Project managers overseeing activity duration estimate creation should enforce best practices to help achieve reasonable and achievable targets including:

• Base estimates on scope decomposition and effort quantification - Avoid guessing without tying projections to the work breakdown structure and resource assignments.
• Document estimate rationale and source data to enable critique - Estimate development should not be black boxes. Capture inputs, analyses, and supporting materials to inspect estimate quality.
• Gather multiple inputs beyond one person’s opinion - Blend insights from relevant experts, key team members, and data analysis for estimate consensus.
• Use multiple estimation methods to pressure test projections - Cross check estimates against different techniques to identify inconsistencies needing reconciliation towards balanced durations.
• Use past performance data to ground estimates in precedent - Availability of directly comparable historical durations should set an anchor point to calibrate around. Variances require justification.
• Define risks and issues then assess duration reserves needed - Account for activity uncertainties when setting duration targets so time buffers mitigate surprises.
• Avoid padding duration targets beyond reason or need - Build efficiency expectations into estimates so slack does not enable unfocused execution.
• Treat estimates as commitments not aspirations - Set activity durations aggressively but attainably so teams have degree of stretch to perform against.
• Continuously refine estimating approach via lessons learned - Learn from gaps between estimates and actuals to expand organizational estimating capacity over time.

Conclusion

Estimating realistic and reliable activity durations is pivotal for project schedule development, resource planning, execution monitoring, and overall management credibility. Underestimating durations leads to missed milestones whereas overestimating causes inefficiencies. A variety of estimating techniques are available. Applying multiple methods helps pressure test estimates converged on through an analytical data-driven approach. Duration targets should additionally include carefully derived contingency reserves sized reasonably to tasks’ risk exposures. Institutional use of top activity duration estimating practices ensures projects have a sound foundation for on-time successful delivery.