Instructions to conduct a work sampling study in groups

Instructions to conduct a work sampling study in groups

Important: When conducting a work sampling study, the researcher and the stakeholders share the mission of the study with the people being studied.

A. Decide on a mission of the project – the objective of the study is being detailed in this stage. This can be done by answering a set of questions, like: Why is the study performed? What are the results the researcher is after? Is the target activity a grouped one (like indirect work) or a detailed activity (like waiting time)? Will the study be performed through outside consultantsinside people or self-reported? The list of questions differs from one study to another. The main idea is to capture the scope of the project, detailing the expectations and needs.

Even if this step can be easily overlooked or minimized, it is critical to conduct a thorough analysis about the mission of the project at this point. Not doing this can cause issues on data reliability and validity that can only be corrected with losses both on financial and personnel levels.

The baseline parameters that are chosen include;

  • Study start date, length or finish date;
  • The population under study: individuals or groups, detailing the specificity for each of them and concluding with a certain number of people or equipments that will be under observation;
  • The structure of the working hours/days of week: for example working from Monday until Friday during 9 a.m. and 5 p.m.;
  • Type of study: outside consultant, inside consultant or self-reported;
  • If the study is being done with older technology or manually then it is important to estimate the proportion of the activity (you are interested in) with all the activities performed during working hours. For example, if the targeted activity is the waiting time area, the researcher will estimate how much time is consumed performing this task during working hours. This information is critical when calculating the needed number of observations for obtaining the desired accuracy.

B. Again if you are working manually or with old technology you must do some calculations and make some decisions:

The calculation of the total number of observations needed to obtain the desired accuracy. As a consequence, the number of observations can be adjusted to meet certain levels of precision that are considered acceptable by the researcher.

For an automated nomograph to calculate the number of observations go to Choose the right number of observations (Nomograph) 
The formula used to calculate the total number of observation is explained in more depth on the Mathematics tab.

n = (t2 * p(1-p))/m2


 n = number of observations needed

 t = confidence level (standard value) – the confidence level consists of the probability that the results obtained are included in a specified range.Usually researchers use a 95% probability for which t=1.96.

 m = margin of error – for example +/-2% accepted variation from final results.

 p = estimated prevalence of targeted activity declared at the beginning of the project.


For group level studies, after the total number of observations is calculated, the individual number of observations can be determined using the following formula:

nindividual = n/number of individuals


The scheduling of randomly chosen time points for observations. At this stage, the researcher has available inputs about: start date of study, total/individual number of observations, and structure of working schedule (working hours and working days taken into consideration). If the end date of the study is already established, the mean time between observations can be calculated and used for randomization of observations.

The formula used for calculating mean time between observations (MTBO – expressed in minutes) is:

MTBOtotal = Total number of working minutes from start date until end date/n
MTBOindividual = Total number of working minutes from start date until end date for each individual/nindividual

When randomizing the time points for observations based on the formulas described above, there are specific guidelines that can be considered:

  • to set minimum and maximum number of minutes permitted between each two consecutive observations;
  • to move the end date of the study, if the MTBO is too small compared to an acceptable value and is expected to influence work efficiency;
  • to make sure that an equal number of sub-cycles are taken into consideration while establishing the end date (day vs. night; week day vs. week-end day, etc.);
  • to choose a normal load period by avoiding holidays and vacations period or special activities (annual conferences, seminars etc). Normally a work sampling study can range from one week to six weeks or even longer.

C. To define the list of activities The challenge of defining work categories is to be detailed enough to comprise all the anticipated work activities and to give also the possibility to the individual to detail manually an activity if no category contains it. To reduce the number of manual interventions and to ensure data consistency, the definitions of the work activities and categories must be clear and concise.

D. To design all necessary forms and templates for data collection that will contain details about the study parameters (routes, observation points etc).

E. To select and train individuals that will have responsibilities in the survey. This stage is essential for obtaining accurate and reliable data. The motivation and implication of all members involved is a key attribute of a successful work sampling study.

F. Conduct data collection (Make the observations). Once the above calculations have been completed, the observations begin and activities are recorded at the agreed time intervals. When they have been completed, a reverse calculation can be used to determine the margin of error, as follows:

In this case, n is the actual number of observations registered in field for all individuals or equipments (sum of all nindividual values).

A pilot study can also be undertaken. During this period, the definitions of the work categories are tested and adjusted, if needed. Also, valuable information about a preliminary structure of activities is calculated and used for measuring more efficiently the actual study parameters. It is also important to have a supervisor that continuously monitors that the collection phase is going according to schedule.

G. To analyze results and prepare reports with recommendations. The information obtained from each observation is centralized and used for analysis. If bias is thought to have appeared during the first hours or days of the survey, it is recommended to exclude the suspicious data from the analysis. In this case, the remaining observations are assessed for accuracy and reliability based on the formulas presented in the previous sections.

Work sampling provides baseline information for change and improvement. The reports that can be built after the analysis has been finalized relate to:

  • The structure of activities during working hours at study level - the ratio of the number of observations per activity to the total number of observations yields also an estimation of the time spent in each activity;
  • The hourly evolution, visually represented, based on the working schedule - line graphs can be used to spot peak periods of direct/indirect work or of a targeted activity. The hourly evolution results come to support or deny perceptions that are not yet backed up by data (e.g. thatthe employees start the day performing administrative activities). They can also provide new insights that help managers decide based on validated information.
  • The comparative approach - each observation has attached to it information regarding the department, team, group where it was declared, but also regarding the hour, day, shift collected based on the time of registration. The collection process of all these inputs is managed easily by performing a technology based work sampling study ( iPhone App like ISAmpler, etc.). Once these inputs are collected, cross-sectional analysis can be performed that illustrate trend information, as well as improvement opportunities for the unit under observation.