An efficient schedule is one in which the number of rostered agents consistently matches the staffing requirement that was calculated from the forecast workload and shrinkage assumptions. In other words, the number of periods of over-staffing and under-staffing is minimised. The planner’s ability to perfectly match staffing with requirements is constrained by the limitations that he or she inherits: Where there are few or no part-time staff and there are rigid rules about scheduling (e.g. start times and finish times are fixed, days off must be consecutive, breaks must take place during a certain time window, etc.), it is difficult to build shifts that match the peaks and troughs in demand. Nevertheless, a good WFM team will apply creativity in finding and leveraging whatever flexibility exists. For example, even if start and finish times cannot be varied, optimum placement of breaks and meetings can work wonders for schedule efficiency.
Keeping the mismatch between ‘supply and demand’ as low as possible ensures the best utilisation of the personnel resource, more consistent service level for customers, more consistent occupancy levels for staff and reduced cost. Knowing where the mismatches are occurring not only helps the WFM team to build better schedules within the rules that are in place, it also encourages the entire operation to identify new shift types to consider, hiring options to be offered, etc. If the forecast is reasonably accurate and the schedules match up to that forecast reasonably well, the intraday chaos of constant adjustments can be minimised. The calculation requires the following elements:
1. Shrinkage adjustment
You must choose the shrinkage adjustment wisely. Bear in mind that shrinkage may or may not be a constant. It might vary over time. For example, shrinkage is often higher during the summer holiday season. It can also vary by day and week. And make sure you use the correct calculation formula. If the shrinkage percentage is s%, you should inflate the number of scheduled staff by dividing by (1-s%), not multiplying by (1+s%).
Example: In an interval where 70 employees must be on duty in order that the Service Level goal is met, and shrinkage is 30%, you should schedule 70 / (1-0.3) = 100 people. If you add 30% to 70, the result is 91. The shrinkage percentage assumption can be added in each interval to raise the bodies in chairs requirement to the number that is actually needed on the schedule so that absenteeism and other factors can occur without impacting the service delivery.
2. Total required ‘bums in seats’
This is based on the forecast – see section 1 above – inflated by the shrinkage adjustment. Where a skill-based routing configuration is in place, a sophisticated algorithm is needed to take into account the pooling efficiencies offered by multi-skilled agents when calculating required staffing. In a traditional single-skilled environment, basic Erlang C will be acceptable for inbound calls – but bear in mind that other channels such as webchat, email and social media will need a different approach.
3. Total scheduled staff in each period
This is the staff scheduled, including the shrinkage assumption not yet covered by the schedule elements. For example, looking at a schedule for next week, the expectations for vacations and training might already be in the schedules, but daily absenteeism would still need to be a shrinkage assumption. In a single-skilled environment this will be relatively easy to determine, but it is more complex in skill-based configurations where a single agent may be capable of serving more than one type of call at any moment in time. (If preferred, the shrinkage can be deducted from the scheduled staff rather than added to the ‘bums on seats’ calculation).
4. Total variation of scheduled staff compared to required staff
This is a measure of mismatch between ‘supply and demand’ across a period. When the ‘overs’ and ‘unders’ are added together, the total for the period is divided by the total requirements for that period. The result is the percent of variation staffing v. requirements. (A standard deviation analysis of the variances can be done if the over- and under-staffing numbers are converted to percentages of variation by period. When the staffing requirements by period vary significantly by day or week or time of day, the raw numbers of staff variance will provide an inaccurate result).
5. Analysis period
This should generally be analysed at the day or week level, although analysis of the patterns of intraday variations can be effective in determining trends of mismatch.
With thanks to Chris Dealy at injixo