Strategies For Estimating Unfamiliar Tasks In Project Management

The Challenge of Estimating New Tasks

Project managers often face the challenge of estimating unfamiliar tasks that have never been done before in a project. Without previous experience or benchmarks, creating accurate estimates can be very difficult.

Some examples of unfamiliar tasks include:
– Developing a new software feature using an unfamiliar technology

– Creating a new manufacturing process for an innovative product
– Implementing a business process that the company has never done before

When dealing with unfamiliar tasks, project managers lack two key inputs that are needed for estimating:
1. Knowledge and understanding of exactly what work needs to be done
2. Historical data from similar past tasks that can serve as a baseline

Without these inputs, estimates may be based more on guesswork than solid logic. This often leads to underestimating the time, effort, and resources truly required to complete the task.

Inaccurate estimates cause problems down the line, including:
– Inefficient allocation of project resources

– Missed deadlines
– Budget overruns

– Compromised quality

All projects have uncertainties, but unfamiliar tasks multiply those uncertainties. By following structured estimation strategies, project managers can minimize guesswork and develop estimates grounded in logic and empirical data as much as possible.

Gathering Information to Understand the Task

The first step in estimating an unfamiliar task is information gathering to thoroughly understand what the task entails.

Project managers should:

– Identify the goals and objectives behind the task—what business value will it create?
– Define the scope and requirements needed to meet those goals

– Break down all the sub-tasks and steps involved from start to finish

This upfront learning is crucial. Estimating will suffer if there are gaps in understanding exactly what work needs to be delivered.

Useful techniques for gathering info include:
– Brainstorming sessions with the project team
– Interviews with subject matter experts (SMEs)

– Process mapping exercises

– Design charrettes (focused sessions to produce solutions to design problems)

– Research on similar tasks outside the organization

– Listing out key questions, decisions, and unknowns

Document the information gathered so there is a common reference point for creating estimates.

Breaking Down the Task into Smaller Components

With an understanding of the overall task, the next step is decomposing it into smaller, more manageable pieces. Breaking down complexity makes it easier to estimate accurately.

Ways to break down an unfamiliar task include:

– Divide by roles—what work does each project role need to do?

– Order chronologically—what are the timestamps from start to end?
– Separate by sub-system—what components comprise the whole system to deliver?

– Isolate major deliverables—what tangible/measurable outputs get created?
– Think inputs required—what info, resources, technology is needed?

Document the breakdown structure so stakeholders can validate if it’s comprehensive enough or if anything major has been missed.

At the end of decomposition, you should have a list of smaller, tightly defined work items that add roll up to completing the one larger unfamiliar task.

Researching Similar Tasks for Comparison

Even if the exact task is entirely new for the organization, chances are that similar tasks have been done either internally (on other projects) or externally (at other companies).

Identifying analogues tasks to use as benchmarks during estimation is hugely valuable for unfamiliar work. Useful comparison points typically include:

  • How long did it take?
  • How much effort was involved for how many people?
  • How complex was it on a relative scale?
  • What risks, impediments, and uncertainties arose?

Places to research similarities include:
– Your organization’s project history
– Public case studies from industry sources

– Subject matter experts with relevant past experiences

The most reliable comparisons come from projects within your own organization. But even if all you have are external proxy tasks, identifying analogy points is still far better than completely blind guessing.

Building Time Estimates for Each Component

With the task decomposed and benchmark data on analogous tasks collected, project managers can build time estimates for each component.

Estimation techniques that leverage benchmarks include:

Bottom-up estimation: Estimate duration of lower-level items first, then aggregate upwards

Analogous estimation: Use actual time from previous comparable tasks
Parametric estimation: Plug component details into model to automatically generate estimate

When estimating lower-level components:

  • Identify items involving unfamiliar work or high uncertainty to flag as risk factors
  • Add notes explaining the logic behind each estimate
  • Label estimates based on low, likely, and high case scenarios

Estimates derived throughBottom-up estimationdecomposition and benchmarks have higher accuracy. But uncertainty does still exist, requiring the next step…

Adding Buffer Time for Unexpected Issues

Project managers should add buffer time to estimates for unfamiliar work to account for unexpected issues arising.

Forms of buffer time include:
Contingency time: Reserve for known risks that may happen

Management reserve: Extra cushion for general uncertainties

To determine the appropriate buffer size:

– Revisit identified risk factors and uncertainties

– Reference history from past projects to inform percentages
– Have subject matter experts review estimates

Buffers should not be arbitrary “fudge factors.” Customize them based on the task’s novelty, complexity, prerequisites, and other dynamics affecting certainty.

As execution begins and uncertainty decreases, adjust buffer sizes downward. Right-size buffers to balance project cost and risk.

Reviewing Estimates with Team Members

Before finalizing estimates for unfamiliar work, reviews with team members are extremely constructive.

Reviews help in several ways:

– Fills knowledge gaps about the work specifics
– Incorporates different perspectives on approach and duration
– Builds consensus among those doing the work
– Tests logic underpinning each estimate

Tips for effective reviews include:
– Ask open ended questions about each item’s estimates, not just yes/no on the numbers

– Probe on “what could go wrong” with each task
– Capture feedback individually first before group discussion

– Have reviewers annotate the estimates documentation directly with comments

Estimate reviews take some time upfront but repay that investment many times over through higher accuracy. And collaborative reviews boost team commitment to meeting the targets.

Adjusting Estimates as Work Begins

Estimating unfamiliar items has inherent uncertainty. Even with rigorous estimation processes, the true task effort only reveals itself as work begins.

Project managers should plan to track progress closely, monitor variances to estimates, and adjust estimates as necessary in response.

Useful techniques for estimate adjustment include:
Earned value management (EVM): Compare work completed versus estimates

– Percent complete assessments: Check milestones achieved

– Buffer draw-down tracking: Follow rate contingency/reserve used
– Variance drilling: Analyze causes behind estimate inaccuracies

Integrate estimate updating into regular project status processes. Frequent estimate-to-actual checks minimize delivery risk and keep timelines realistic.

Adjustments of course impact downstream scheduling. But methodically updating unfamiliar work estimates with empirical data is far better than blindly sticking to original guesses.

Learning from Experience to Improve Future Estimates

The final step of the estimation process for unfamiliar work isharvesting lessons learned once the project completes each item.

Retrospectively compare initial estimates versus actuals to reveal misestimations. Understanding causes behind poor estimates leads to better estimates next time.

Areas to examine when estimate differences emerge:
– Poor understanding of work scope

– Gaps in required knowledge/skills
– Cognitive biases distorting estimates

– Weak estimating practices
– Bad assumptions on risks or dependencies

Capture findings in historical estimate databases and project documentation to inform future teams facing similar unfamiliar work.

Unfamiliar tasks always hold uncertainty. But deliberately learning from experience builds organizational estimating capabilities over time.

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