Plain-language definitions, units and examples for workforce planning. The same definitions appear beside key metrics throughout LoughPoint.
38 definitions found
Staffing
Available FTE minus required roster FTE. Positive means surplus capacity; negative means a shortfall. Compare the same scope and paid-hours basis. A net surplus does not guarantee interval or skill coverage.
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Additional roster FTE needed: maximum of zero and required FTE minus available FTE. Zero means no net hiring need. See Staffing balance for surplus or shortfall.
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Staffing expressed as full-time paid hours, rather than the number of people. Two people working 20 hours each equal 1 FTE when a full-time week is 40 hours.
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The paid FTE capacity you enter for the shared setup or a location. It is compared with demand-side requirements and constrains schedule recommendations. Leave blank if unknown; zero means no staff. Dated changes can alter future supply.
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The full-time-equivalent staffing calculated to cover demand, service requirements and shrinkage, using paid hours per FTE. It is a requirement estimate, not a fitted shift schedule.
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Available FTE minus required FTE. If 120 are required and 100 available, the signed gap is −20 FTE (a shortfall). If 90 are required, the gap is +10 FTE (a surplus). Hiring shortfall is the positive amount needed to close a negative gap.
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The number of individual people, regardless of contracted hours. Headcount and FTE are equal only when each person works one full-time equivalent.
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Agents needed to be available for service before adding shrinkage. Depending on channel, this includes the service target or workload-clearance requirement.
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The agent requirement after allowing for shrinkage. This is not proof that saved shifts provide that coverage in every interval.
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The share of paid time unavailable for handling work, such as leave, absence, training and meetings. A 70-agent net need at 30% shrinkage requires 70 ÷ 0.70 = 100 scheduled agents.
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Contracted weekly hours represented by one full-time equivalent. Use a consistent basis for the team; shrinkage is handled separately.
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Average time spent handling a contact, including relevant talk, hold and after-contact work. Check whether imported values use seconds or minutes.
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Total handling time represented by demand: contacts × AHT seconds ÷ 3,600. Effective concurrency can reduce occupied agent time for chat. Workload alone is not roster FTE.
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Contacts arriving in the selected queue and period. These can differ from answered or completed contacts; cost per offered contact uses arrivals.
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The share of available service time occupied by handling work. It excludes shrinkage from the available-time denominator. A calculated load above 100% signals overload or inconsistent inputs, not a sustainable operating occupancy.
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Productive time as a share of a stated time base, often total paid time. Check the denominator: it may differ from occupancy, so the two should not be used interchangeably.
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The average number of contacts handled simultaneously. Use achievable overlap, rather than the maximum number of chats the system allows.
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The agreed service commitment. For synchronous work it may specify a percentage answered within seconds; for back-office work it may specify completion within hours or days. A model estimate is not a guarantee.
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The percentage of eligible contacts answered within the chosen threshold. State the threshold and denominator, including any short-abandon exclusions.
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Average waiting time before an answered contact reaches an agent, usually in seconds. It is different from handling time and depends on the reporting policy for abandoned contacts.
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The percentage of offered contacts that leave before answer. Short-abandon policies affect the reported percentage. Erlang C does not predict abandonment.
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Unfinished work carried into or out of a period. New arrivals and completion capacity both affect whether it grows or clears.
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A queueing model for waiting and staffing estimates. It assumes steady-state arrivals, identical agents and no abandonment; use appropriate interval data and review its assumptions.
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Scheduled agents compared with required agents in each interval. Percentage of intervals covered counts intervals meeting the requirement; it is not a customer service-level percentage.
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Work delivered by your own operation or staff, rather than an outsourced supplier.
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Work delivered by an external supplier. The charging basis can be per FTE, productive hour or offered contact.
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Monthly cost for one FTE, using the salary, employer costs and overheads you choose to include. Example assumptions need replacing with your own costs.
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Estimated cost of the calculated requirement using the selected charging basis, subject to any minimum monthly charge. It is not automatically the payroll cost of available FTE.
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Cost divided by offered contacts for the same period. This is not necessarily cost per completed or answered contact.
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The time represented by one data point: for example 15 minutes, an hour or a month. Uploaded grain and the level used for forecasting can differ.
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How many future periods the forecast covers. The duration depends on the selected model grain: 12 monthly periods means 12 months.
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Total absolute forecast error divided by total actual demand, expressed as a percentage. Lower is better on comparable holdouts; it is unavailable when total actual demand is zero.
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Average absolute difference between forecast and actual values, expressed in the original units, such as contacts.
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Square root of average squared forecast error. It uses the original units and gives large misses greater weight than MAE.
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Signed forecast error indicating persistent over- or under-forecasting. In the calculation library, positive means forecast exceeds actual.
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A historical test that forecasts withheld observations using only earlier data. It estimates past forecasting performance, not guaranteed future accuracy.
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The reference case against which a scenario is compared. Keep its assumptions unchanged to interpret the effect of a scenario. A percentage change from a zero baseline is unavailable.
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A measure of association between two metrics, ranging from −1 to +1 for Pearson correlation. It does not establish causation; missing data and sample size matter.
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