What Is a Time Study?

A time study is a structured work measurement technique used to determine the time required for a trained operator to perform a specific task under standard conditions. In engineering service processes—such as design reviews, prototype testing, or maintenance dispatch—time studies provide an objective baseline for evaluating productivity, balancing workloads, and identifying waste. By breaking down complex service workflows into discrete, measurable elements, organizations can replace guesswork with data-driven decisions.

Time studies are not limited to manufacturing. Engineering services present unique challenges: tasks are often cognitive, non‑repetitive, and influenced by variable inputs. Nonetheless, the core principle remains the same: observe, record, and analyze the time each step consumes under typical conditions. The resulting data empowers engineers and managers to simulate “what‑if” scenarios, set realistic delivery timelines, and justify resource investments.

Why Conduct a Time Study in Engineering Services?

Quantify Productivity and Baseline Performance

Without objective time data, teams can only estimate how long projects take. A time study reveals the actual duration of recurring tasks—say, a code review cycle or a system integration test—and highlights deviations from expected norms. This baseline is essential for continuous improvement programs such as Lean or Six Sigma.

Identify Bottlenecks and Waste

Engineering service processes often hide non‑value‑added activities: waiting for approvals, rework due to incomplete specifications, or excessive handoffs. A time study makes these wastes visible. For example, if an engineer spends 30 % of the day navigating an outdated permissions system, the study will surface that inefficiency with concrete numbers.

Balance Workloads Across Teams

Disparities in task duration can lead to burnout or underutilization. By comparing the time required for similar assignments across different engineers, managers can redistribute work more evenly and design cross‑training plans to reduce single‑points‑of‑failure.

Support Cost Estimation and Pricing

In consultant or contract engineering firms, accurate time data underpins bids and hourly rates. A time study provides defensible evidence for the labor content of each deliverable, reducing the risk of underbidding or overcharging.

Preparing for a Time Study

Proper preparation ensures the study yields reliable, actionable data. Skipping this phase often leads to biased results or wasted effort.

Define Clear Objectives

Start with a precise question: Do you want to reduce the average cycle time for a change order approval? Identify the key performance indicators (KPIs) that matter—throughput, cycle time, on‑time delivery, etc. The objectives will determine which tasks to time and which data to collect. Document the purpose in a brief charter that stakeholders approve before observation begins.

Select Tasks and Resources

Not every process element needs to be studied. Use a process map or value stream map to identify high‑impact, repetitive tasks. Examples in engineering services include:

  • Responding to a service ticket (triage, resolution, closure).
  • Reviewing and merging a code pull request.
  • Performing a finite element analysis simulation.
  • Generating a project status report.

Select tasks that are representative of the overall process and have clear start/stop points. Also secure the necessary tools: a reliable timing device (stopwatch or software), a structured data collection sheet (digital or paper), and access to the work environment without disrupting the operator.

Choose the Right Methodology

There are several established time study approaches:

  • Continuous timing – The observer records cumulative times without resetting the stopwatch between elements. This yields a continuous record of the entire observation session and captures waiting or idle periods.
  • Snapback timing – The stopwatch is reset to zero at the start of each element. This method is faster for recording but omits non‑cyclic delays unless noted separately.
  • Work sampling – Instead of continuous observation, the observer takes instantaneous snapshots at random intervals. This is less intrusive, but provides statistical estimates rather than exact times. It is useful for low‑frequency or very long tasks.
  • Predetermined motion time systems (PMTS) – In engineering contexts, these are less common because tasks are cognitive rather than purely physical. However, standard elements like “turn on equipment” or “open software dialog” can be estimated using methods‑time measurement (MTM).

For most engineering service processes, continuous or snapback timing with a moderate sample size (10–15 observations per element) offers a good balance of accuracy and effort.

Conducting the Observation

Observation is the heart of the time study. How you conduct it directly affects data quality.

Observer Role and Neutrality

The observer must remain as unobtrusive as possible. Announce the purpose of the study to all participants, emphasizing that the goal is to improve the process—not to evaluate individual performance. Position yourself where you can clearly see the task start and end points without hovering. If the operator feels watched, they may alter their pace (the Hawthorne effect). To mitigate this, allow a short adaptation period before recording.

Recording Data Consistently

Use a standardized data sheet with columns for:

  • Task element number and description
  • Start and end time (or duration)
  • Observation number
  • Remarks (interruptions, unusual conditions, operator questions)

If using a digital tool or spreadsheet on a tablet, ensure the interface is simple enough to operate without losing focus on the operator. Record every element cycle in the order they occur. When an interruption happens—such as a phone call or another colleague asking for help—flag that cycle and briefly note the cause. These data points are valuable for calculating “net” work time versus “gross” elapsed time.

Handling Interruptions and Irregularities

Interruptions are normal in engineering services. Do not force the operator to ignore them; that would produce unrealistic times. Instead, record the interruption as a separate element (e.g., “wait – unscheduled question”) and later decide whether to include it in the standard time. For a reliable standard, you may average only “normal” cycles and treat interruptions separately as allowances.

Analyzing Time Study Data

Once you have a set of observations, the raw times need to be processed into meaningful metrics.

Calculate Average Times and Variance

For each task element, compute the mean (average) time across all valid observations. Also calculate the standard deviation and range. High variance indicates inconsistency that may stem from operator skill, tool performance, or ambiguity in the task definition. A good rule of thumb: if the coefficient of variation (standard deviation / mean) exceeds 30 %, investigate the cause before using the average as a standard.

Apply Performance Rating (If Needed)

In traditional time studies, the observer assigns a performance rating factor to adjust the operator’s pace to a “normal” level. For engineering services, this is controversial because cognitive work is difficult to rate objectively. Instead, focus on using a sufficient sample size and operating under typical conditions. If you choose to apply a rating, use a validated scale (e.g., 100 % = normal pace) and ensure the same observer rates all data to maintain consistency.

Identify Bottlenecks and Non‑Value‑Added Time

Plot the cumulative time distribution or create a process chart. Elements with disproportionately high average times or frequent interruptions are prime candidates for optimization. For example, if “approval sign‑off” takes 4 hours but actual work is only 10 minutes, that indicates a queue and waiting time. Distinguish between value‑added (work that transforms the service output) and non‑value‑added (inspection, movement, waiting) activities.

Use Statistical Software for Large Datasets

For studies spanning dozens of elements and hundreds of cycles, manual calculation becomes error‑prone. Use spreadsheet tools (Excel, Google Sheets) or dedicated time study software (e.g., ProModel or QualaTime). These tools can automatically generate histograms, control charts, and summary reports.

Implementing Improvements

Data without action is just numbers. The final objective of a time study is to drive process improvement.

Develop Improvement Hypotheses

Based on your analysis, list the top three to five opportunities. For each, propose a change that targets the root cause. If excessive waiting time is caused by a sequential approval chain, consider parallel reviews or delegating approval authority. If a manual data entry step consumes 15 minutes every morning, explore automation or pre‑filled templates.

Test Changes with a Pilot

Implement the proposed change on a small scale—one team, one project, or one day. Conduct a follow‑up time study on the same tasks to compare before‑and‑after times. Ensure that the measurement conditions (operator, tools, time of day) are as similar as possible to isolate the effect of the change.

Roll Out and Monitor

Once the pilot confirms improvement, standardize the new process through updated procedures, training, and tool modifications. Monitor the key metrics over the next several weeks to ensure the gains are sustained. Time studies can be repeated periodically (e.g., quarterly) to maintain a culture of continuous improvement.

Best Practices for Effective Time Studies

  • Communicate the purpose – Explain to operators that the study aims to help everyone work smarter, not to cut jobs or micromanage. Transparency builds trust and reduces anxiety.
  • Use a standardized data sheet – Pre‑define the elements and their boundaries before you start. This reduces ambiguity and makes data comparison across observations easier.
  • Conduct enough observations – A single observation can be misleading. For engineering tasks, a sample of 10 to 15 cycles per element often provides a reasonable confidence interval. For tasks with high variability, increase the sample size.
  • Record context – Note the time of day, day of week, operator experience level, and any atypical conditions. These factors can explain outliers and help you decide whether to exclude them from the standard.
  • Stay neutral – Do not coach the operator or suggest changes during the observation period. The goal is to capture current reality, not an idealized vision.
  • Use technology wisely – Smartphone apps like TimeCulator or dedicated time study apps can simplify recording and automatically compute statistics. However, ensure that the tool does not introduce more complexity than it solves.
  • Pilot the data collection method – Test your data sheet on a short run before the main study. This catches misunderstandings and missing elements early.
  • Get feedback from operators – After the study, share preliminary findings with the people who performed the work. They often have valuable insights into why certain steps take longer and what improvements would actually work.

Common Pitfalls to Avoid

  • Timing the wrong tasks – Focusing on tasks that are already efficient while ignoring high‑impact bottlenecks wastes energy. Always use process mapping to prioritize.
  • Ignoring the human factor – Observers who stand too close, make notes loudly, or fail to build rapport will distort natural behavior. Train observers to be invisible and respectful.
  • Averaging all data without scrutiny – Outliers caused by genuine interruptions should be treated separately. Blindly averaging them can produce a standard that is impossible to meet consistently.
  • Neglecting to update standards – Once processes change (new software, new tooling, new team members), old time standards become obsolete. Schedule periodic reviews to keep time data relevant.
  • Over‑engineering the study – It is tempting to time every single micro‑motion. For engineering services, breaking the task into small cognitive steps (e.g., “open email,” “read requirement”) often yields little actionable insight. Focus on logical work blocks of 5 to 15 minutes.
  • Using time studies for individual performance evaluation – This is a sure way to destroy trust. Time studies are meant for process analysis, not employee ranking. If used for performance, operators will inevitably game the system.

Tools for Time Study in Engineering Services

You can conduct a time study with nothing more than a stopwatch and paper, but digital tools streamline the process. Here are several categories:

  • Spreadsheets – Pre‑built templates with formulas for mean, stdev, and histograms. Microsoft Excel and Google Sheets are the most flexible.
  • Specialized time study apps – Mobile apps such as T² Solutions Time Study or Kommand Work Sampling allow real‑time data entry, photo attachments, and automated calculation. These are especially useful for field engineers.
  • Industrial engineering software – Tools like ProModel or Arena Simulation are heavy‑duty but ideal for modeling complex service processes with multiple resources and probabilistic durations.
  • Work sampling boards or apps – For quick, less precise estimates, work sampling tools can provide a statistical approximation of time allocation without continuous observation.

Conclusion

A well‑executed time study transforms subjective hunches about engineering service process efficiency into hard data. By following a structured preparation phase, conducting neutral observations, and applying rigorous analysis, teams can pinpoint waste, balance workloads, and implement changes that yield measurable improvements. The investment in time study effort pays back quickly—often in the first pilot project where cycle time drops by 20 % or more. Moreover, the practice builds a culture of evidence‑based decision‑making that will serve your engineering organization long after the study itself is complete.

For further reading on work measurement fundamentals, consult the International Labour Organization’s Introduction to Work Study or the American Society of Mechanical Engineers’ standards for time study practices. Pair these guidelines with the steps above, and you will be well on your way to mastering time study in the engineering services domain.