Professional & Industry calculators

Work out the hourly rate to charge a client so that target margin is met after overhead and non-billable time.

Find the true hourly cost of an employee once benefits, payroll cost and overhead are included.

Size a software application from its data and transaction functions before estimating effort or cost.

Estimate development effort, schedule and average team size for a software project of a known size.

Express cloud spend as a cost per customer, per transaction or per other business unit.

Set the rate used to apply manufacturing overhead to jobs for the coming period.

Find the pace of production needed to meet customer demand.

Measure how much of planned production time is truly productive.

Express a defect rate on a scale that can be compared across processes of different complexity.

Judge whether a process fits inside its specification limits and whether it is centred.

Size a pump and estimate the electrical power it will draw at a given duty point.

Measure how much value the project has earned for each unit of cost spent.

Measure how much of the planned work the project has actually completed.

Forecast the total cost of the project from performance so far.

Find the sales volume at which total revenue covers total cost.

See how much each sale contributes towards fixed costs and profit.

Price a monthly retainer and the rate for hours beyond it.

Price a per-device or per-user service from its cost to serve.

Work out the monthly cost of running a managed service, per unit served.

Price a support contract from ticket volume and handling time.

Cost the coverage a service level agreement promises.

Find the blended hourly cost of a junior, mid and senior delivery mix.

Work out what each customer, order or account costs to serve.

Measure how many hours each delivered function point actually took.

Express what a delivery cost in money per unit of functional size.

Turn a function point count into effort using your own delivery rate.

Cost a COCOMO II effort estimate at your own person-month cost.

Estimate calendar time with the published COCOMO II schedule equation.

Size software in thousands of source lines, counted or converted.

Find the average team size an effort and schedule imply.

Cost a build including tools, overhead and a contingency reserve.

Turn effort into a schedule, by the published model or by your staffing.

Estimate a year of maintenance from how much of the system changes.

Work out what fixing a set of defects costs to fix, retest and release.

Value technical debt as remediation cost and annual carrying cost.

Build a total project cost from labour, materials, travel, overhead and contingency.

Cost virtual machine hours at the price on your own bill.

Cost stored data, retrieval and other storage charges you enter.

Cost egress at your own price per GB, less any allowance you hold.

Cost API or object requests from your own price per million.

Cost function invocations and GB-seconds at your own prices.

Cost container tasks charged per vCPU-hour and per GB-hour.

Cost cluster nodes, the control plane, storage and networking.

Cost managed database instances, storage, backup and I/O.

Total a cloud platform's recurring and one-off cost over a period.

Project spend to period end and compare it with the budget.

Project future cloud spend with a growth model you choose.

Split shared cloud cost by a driver you choose.

Total a workload from the cost components you enter.

Express infrastructure cost as cost per request served.

Express infrastructure cost as cost per gigabyte and per terabyte.

Compare reserved capacity with on-demand at the usage you expect.

Value a spend commitment, counting commitment you do not use.

Compare today's resource cost with a proposed smaller size.

Total a job from its materials, labour and the overhead your own rate applies.

Divide manufacturing cost by good units to get the cost of one unit.

Cost a batch from per-unit costs plus the costs the batch carries once.

Cost material from quantity, your own price and any waste allowance.

Cost labour hours at your own rate, with any overtime premium separate.

Total the indirect production costs you enter, and show them per base unit.

Work out what one hour on a machine costs to run.

Build a standard cost card from your own standards, never a benchmark.

Total the costs actually recorded against production.

Split the gap from standard into price, quantity, rate and efficiency variances.

Cost units written off, less anything recovered, plus disposal.

Cost the extra labour, material and overhead spent making units good.

Show what yield loss does to the cost of each unit that survives.

Cost a changeover in setup labour, lost production and start-up scrap.

Price a quote from cost on a margin or a mark-up, chosen explicitly.

Build a bid from quantity, tooling, freight, contingency and profit.

Compare making a part with buying it, and find the cross-over volume.

Work out how much your machines can produce in a period.

See how much of your capacity the period's output actually used.

Measure units per hour of elapsed time, stops included.

Measure how long one unit actually takes on the line.

Find output per running hour, and per shift and week if you want.

See how evenly the work is spread across the stations on a line.

Find the station that limits the line and what the line can produce.

Count and value the units still on the floor at the end of a period.

Add up how long an order takes from receipt to despatch.

Measure how much of the period a machine spent operating.

Measure availability from a shift's records, or from MTBF and MTTR.

Relate work in process, throughput and lead time in a stable system.

Work out defects per unit from your own defect and unit counts.

Find the share of units that passed with no rework of any kind.

Multiply step yields to find the chance a unit passes every step.

Work out the share of units started that had to be discarded.

Work out the share of units that needed rework before they could pass.

Compare specification width with short-term process spread.

Compare specification width with long-term process spread.

Long-term process performance against the nearer specification limit.

Convert a defect rate or yield into a sigma level, with and without the 1.5 shift.

Total prevention, appraisal, internal and external failure costs.

Total the failure costs of work that was not right first time.

Rank up to ten categories by count with shares and cumulative share.

Work out availability from your own MTBF and MTTR.

Turn measured downtime into an uptime percentage for the period.

See how much downtime the availability target you set allows.

See how much of your objective's error budget is left, by events or by time.

Work out the mean time to repair from your own incident data.

Work out the mean time between failures from observed operating time.

Mean time to restore service after a change that failed.

Turn a count of production deployments into a rate per day and week.

Work out the share of production changes that caused a failure.

Compare the service level achieved with the objective you set.

Check measured availability against a commitment and its credit terms.

Add up an incident's cost from components you can evidence.

Direct cost plus a share of shared platform cost, by your own driver.

Divide the period's delivery cost by the deployments made.

Project how large a data store becomes under a growth model you choose.

Turn measured sizes before and after compression into a ratio and the space saved.

Cost keeping data across storage tiers, at the prices you are charged.

Divide a cost you already know by the volume it covered.

Add up what a pipeline cost in a period, component by component.

Cost an extract-transform-load job stage by stage.

Cost an extract-load-transform job, with the transform inside the warehouse.

Cost warehouse compute, storage and any fixed fee at your own prices.

Cost a scanned-data query over a period, from the volume it reads.

Spread a pipeline cost over the records it processed.

Turn a run's record count and elapsed time into a processing rate.

Measure how old your data is when it is used, against your own target.

Cost the tokens a model used, pricing input and output separately at your own rates.

Cost live model traffic from your request volume, token counts and prices.

Spread AI cost across the customers who used the feature.

Cost a batch job over a known number of items at the batch prices you were quoted.

Cost embedding a corpus once, plus any rebuilds, at your own per-million-token price.

Cost a vector search service from your query volume, index size and prices.

Cost the accelerators a piece of work occupied, at your own per-GPU-hour price.

Cost the compute of one training run, and of every restart you paid for.

Add up what training a model cost in compute, data work, storage and engineering time.

Cost a serving endpoint, with the idle hours shown separately.

Divide an AI cost you already know by the requests it covered.

Compare what a customer pays with the AI and variable cost they cause.

One hourly rate for a mixed team, weighted by hours.

Total annual employer cost of an employee, and the cost per paid hour.

Work back from a client bill rate to the pay rate, with margin and markup kept apart.

Scheduled hours less leave, holidays and non-billable work.

Billable hours as a share of available hours.

How much of the standard value of work was actually billed.

Revenue per hour worked, not just per hour billed.

Premium rate and cost for work outside standard hours.

Cost of a standby rota and the call-outs that come with it.

Turn a loaded hourly cost into a published rate, and see the margin after discount.

Add up what the people on a project cost, role by role.

See what share of a project's revenue survives its delivery cost.

See what a project leaves after direct, overhead and administrative cost.

Turn an estimated project cost into a fixed fee at your margin or markup.

Quote an hourly engagement with expenses and materials shown separately.