Construction labor productivity tracking field guide

What labor productivity tracking is, and why labor is the last cost you can change

Labor productivity tracking is the practice of measuring how much work your crew puts in place per labor hour and setting it against the rate the bid assumed, by cost code, while the job is still running. Form 200 ft of footing in 8 hours and that is 25 lf per labor hour. The estimate priced it at 30. The gap is the whole point, and the reason to look every week is that the gap is fixable now and frozen later.

Labor is the cost you can still move after buyout. Material and equipment are mostly locked once the orders are placed and the subcontracts are signed. The price of rebar is what you negotiated, the pump rental is what the invoice says, and neither one cares how the job runs. Labor runs every day, it is the largest variable cost on most self-perform work, and a small slip in the rate compounds across thousands of hours into a loss nobody bid for.

This guide is the productivity half of running a job. What the time and material actually cost as they land belongs in the job-costing guide. Removing the constraints that let the crew hit the rate belongs in the scheduling guide. Productivity tracking is the bridge between them: it is the early number that tells you a job is heading for an overrun before the cost report confirms it and before the schedule shows the slip.

Why productivity tracking is the early warning that matters

The bid is a bet on a production rate. The estimator priced the formwork at so many square feet per hour, the rebar at so many hours per ton, the slab placement at so many cubic yards per hour, and the whole margin sits on the crew hitting those rates. Material gets bought at a price you can defend with an invoice. Labor gets spent at a rate you only find out at the end unless you track it.

Small slips compound, and that is what makes labor dangerous. A crew running at 90 percent of the budgeted rate does not feel slow. The forms go up, the work looks fine, and nobody is alarmed. But 10 percent off across a 4,000-hour concrete package is 400 hours gone, and at a burdened rate that is real money out of a margin you already promised away at the bid. The slip is quiet, it is daily, and it does not announce itself.

Catch it early and you have moves: change the crew mix, stage the material better, fix the sequence, re-train the green hands on that operation. Catch it at closeout and the only move left is the write-off. The reason to track productivity weekly is that it is the soonest honest signal you get, earlier than the cost report and earlier than the schedule update, and earlier is the only thing that lets you act.

The production rate: units of work per labor hour

Productivity comes down to one ratio expressed two ways. The production rate is units of work per labor hour, like 25 lf of footing formed per hour or 0.5 ton of rebar set per hour. The inverse is hours per unit, like 0.04 hours per square foot of wall form or 2 hours per ton of rebar. Estimators usually carry the hours-per-unit form because it is what builds the labor budget; the field usually thinks in units per hour because it is what you watch the crew do.

They are the same number flipped, so pick the one that reads cleaner for the work and stay consistent. Place 180 cy with a crew that burns 30 hours and you placed 6 cy per labor hour, or 0.17 hours per cy. Either way you can set it next to the rate the estimate used and see immediately whether the crew is ahead or behind.

The rate is per labor hour, not per clock hour, because a six-person crew working eight hours spends 48 labor hours, not eight. That distinction is where rookies get the math wrong. Productivity is always work in place divided by the total hours every person on that operation charged to it.

The labor budget is the rate you have to beat

The labor budget is the baseline, and it is not a pile of money. It is the budgeted hours by cost code, and underneath those hours is the production rate the estimate assumed. The estimator took the takeoff quantity, applied an hours-per-unit rate, and the hours fell out. Form 8,000 SF of wall at 0.04 hours per SF and the budget is 320 hours. That 320 is the number the field is racing, and the 0.04 is the rate that has to hold for the bid to make money.

Pull the budget apart before the work starts so you know what rate you are chasing on each operation. The total package hours are useless for steering. The hours behind each cost code, formwork here, rebar there, placement and finishing each on their own line, are what tell a foreman whether today was a good day. Without the budgeted rate in front of you, you are measuring production against nothing, which is the same as not measuring it.

Get the budget from the estimate, not from a feeling. The estimating discipline that sets these rates lives in the job-costing and bidding work; productivity tracking starts the moment those budgeted hours become the target the crew has to hit. If the estimate never broke the hours down by cost code, that is the first thing to fix, because you cannot track a rate you never set.

Track by cost code, not by one lump number

A cost code is the operation the hours and the quantities both land against, and tracking productivity by code instead of by one job total is what makes the number usable. On a concrete package the codes might be footing formwork, wall formwork, rebar, embeds, placement, and finishing. One lump labor number tells you the package is over. The codes tell you that formwork is fine and rebar is bleeding hours, which is the only version you can act on.

The reason is diagnostic, the same reason job costing splits cost into categories. A package over budget on labor could be a forming crew that is slow, a rebar detail that is harder than the takeoff assumed, or a finishing operation that keeps waiting on the pour. One total cannot tell those apart. Productivity by cost code can, because each operation has its own budgeted rate and its own actual rate, and the gap shows up on the line where the problem lives.

Keep the code list short enough that the field will actually charge to it correctly. A scheme with forty codes gets guessed at, and guessed-at codes are worse than coarse ones because the data looks precise and is not. Six to ten codes that match how the crew actually phases the work, used every time, beat an elaborate system that nobody charges right. Granular enough to act on, coarse enough to keep clean.

Earned units: the installed quantity behind the hours

Hours alone tell you nothing about productivity. A crew that burned 200 hours might be a hero or a disaster depending on what got built, and the only way to know is to measure the installed quantity against those hours. The quantity is the earned work: square feet of form actually set, tons of rebar actually placed, cubic yards actually poured. Hours are the input. Quantity in place is the output. Productivity is the second divided by the first.

This is the data that goes missing, because hours come off the timecard automatically and quantities do not. Somebody has to count what got installed and charge it to the same cost code the hours went to. Form 1,200 SF of wall this week, set 6 tons of rebar, place 90 cy: those numbers, captured against the codes, are what turn a timecard into a productivity reading. Skip the quantity and you have payroll, not productivity.

Measure the quantity the same way the estimate measured it, or the comparison breaks. If the takeoff counted wall form by the contact square foot of one side, count it the same way in the field. A production rate that compares field square feet measured one way against budget square feet measured another is a number that will lie to you, and it usually lies in the direction that hides the problem.

What is a productivity factor?

A productivity factor is the crew's actual output against the budgeted output, written as one number you can read at a glance. The common form is earned hours divided by actual hours. Earned hours are the installed quantity times the budgeted hours per unit, which is the credit the estimate gives you for the work in place. Divide that by the hours actually burned and a factor above 1.0 means the crew is beating the budget, below 1.0 means it is losing.

Run it on a real week. The crew forms 4,000 SF at a budgeted 0.04 hours per SF, so it earned 160 hours. It actually charged 200 hours to that code. The productivity factor is 160 divided by 200, or 0.80, meaning the crew is spending 25 percent more time than the bid allowed. The equivalent units-per-hour read is 20 SF per labor hour against a 25 SF budget, the same story told the other way.

Conventions vary, so confirm which way your report runs before you argue about a number. Some shops invert the ratio and call it a performance factor where below 1.0 is good, and some compare actual rate to budget rate as a percentage instead. None of them is wrong, but they point opposite directions, and a foreman reading 0.80 as a win when it is a loss is a real failure. Know your own definition and hold it across every job.

The earned-value view of labor

Earned value is the same idea formalized, and it is worth knowing because it is the language a lot of owners and schedulers already speak. Earned hours are percent complete times the budgeted hours for the cost code: if a 320-hour formwork code is 50 percent done by quantity, you have earned 160 hours regardless of how many you spent. The percent complete is measured by installed quantity, not by calendar time and not by gut feel.

The labor productivity factor maps onto the cost performance index, CPI, from earned-value management. CPI is earned value divided by actual cost, and above 1.0 is favorable while below 1.0 is an overrun, which is exactly how the productivity factor reads when you run it in hours. Construction work commonly lives in a tight band around 1.0, so a CPI that drifts to 0.90 on a major cost code is a real signal, not noise.

Treat the earned-value math as a tool, not a religion. Full earned-value management with schedule and cost variance has its place on large, owner-mandated projects, and it is overkill on a small slab job where earned hours versus actual hours on five cost codes tells you everything you need. Use the level of formality the job and the contract actually call for, and confirm how percent complete is supposed to be measured before the numbers turn into a dispute.

Track weekly, because a monthly look is an autopsy

Productivity tracking only works as a feedback loop, and a feedback loop that fires once a month is too slow to steer a job. Weekly is the working cycle for most crews, daily on a fast or troubled operation. Each cycle you pull the actual hours from the timecards and the installed quantities from the field, compute the rate by cost code, and set it against the budget. The faster that loop turns, the more of the job you can still influence.

A monthly read is an autopsy. By the time a four-week-old number lands, the crew has run the same way for a month, the hours are spent, and whatever was dragging the rate down has been dragging it down the whole time. The slip you could have caught in week one and fixed in week two instead compounds for thirty days before anyone sees it. Monthly productivity tracking is a slightly faster way to confirm you already lost.

This is where a field tool earns its place. With FieldOS the foreman logs the day's hours by cost code and the quantities installed from the phone on site, so the rate computes itself against the budget before the crew leaves. The week's productivity is a report the super reads Monday morning, not a spreadsheet somebody rebuilds three weeks late. The loop turns fast because the capture happens where the work happens.

Garbage in: the field data is the whole game

Productivity tracking is only as honest as two field numbers: the hours charged to the right cost code and the quantity installed against that same code. Get either one wrong and the rate is fiction. The most common corruption is hours that all land on one code because charging them correctly was a hassle, which smears a real problem across operations that were running fine and hides the one that was not.

The quantity side is harder because nobody is forced to report it the way payroll forces hours. The foreman knows what the crew built, but unless capturing it is easy, the count gets skipped, rounded, or reconstructed Friday from memory, and reconstructed quantities flatter the job the same way reconstructed timecards do. The fix is making the report take seconds, not making the foreman fill out a form back at the trailer that competes with going home.

FieldOS puts the daily report in the foreman's pocket: hours by cost code and quantities in place, logged on site while the memory is fresh and the work is in front of him. The hours and the quantities land on the same code at the same time, which is the only way the production rate comes out true. A clean rate is built on clean field data, and clean field data is built on a report nobody dreads filling out.

Reading the gap: real problem or coding error

The variance between the actual rate and the budgeted rate is the signal, but the first job when a number looks bad is to make sure the number is real. A cost code showing a productivity factor of 0.60 is either a crew in real trouble or a data problem, and chasing the wrong one wastes the week. Before you change how the work is run, confirm the hours and the quantities landed on the right code and got measured the right way.

The coding errors are predictable. Hours charged to formwork that were actually spent on layout or cleanup. Quantities counted differently than the estimate counted them. A code that captured the hours but not the rebar that went in with them, so the rate looks terrible because the output is missing. These show up as a factor that is wildly off rather than a little off, and a factor that swings hard between weeks is usually a coding problem, not a crew that doubled and halved its speed.

Once the data is clean and the gap holds, it is a real problem and it points somewhere. A rate that is steadily a little under budget is usually a sequencing, staging, or crew-mix issue. A rate that fell off a cliff is usually a specific event: a detail harder than the takeoff, a stop-and-go week, a change nobody priced. The size and shape of the gap tells you where to look before you ever walk the deck.

Productivity is a leading indicator of the outcome

The cost report is a lagging indicator. It tells you what a job cost after the cost has landed, after the invoices posted and the payroll ran, which is true and useful and too late to change anything. Productivity is a leading indicator. The rate the crew is hitting this week predicts where the labor cost is heading weeks before the cost report admits it, because the hours are being spent now and the report is always looking backward.

That lead time is the entire value. A crew running at a 0.85 productivity factor on the biggest cost code is going to blow the labor budget on that code, and you can see it in week two of an eight-week operation, with six weeks left to do something. The cost report will deliver the same news after the operation is finished and the hours are gone. Same fact, six weeks apart, and the six weeks are where recovery lives.

So act on the productivity signal before the cost report confirms it. The instinct to wait for the official number feels prudent and is exactly backward, because the official number arrives the day it stops being actionable. Trust the rate, verify the data, and move while the work is still in front of you. The job-costing guide covers the lagging cost side that closes the books; productivity tracking is the early read that lets you change the books before they close.

What hurts construction productivity

Productivity rarely dies from one cause. It bleeds from a handful of conditions that stack, and most of them trace back to the work not being ready when the crew gets there. The factors below are the recognized ones, drawn from decades of industry study, and the pattern across all of them is the same: the crew is on the clock but cannot put work in place at the rate the bid assumed.

Know which ones are biting your job, because the fix is specific to the cause. A rework problem and an overmanning problem both show up as a low productivity factor, but one is solved by getting it right the first time and the other by thinning the crew. The factor is the symptom. The condition in the table is the disease.

Extended overtime lowers the rate, not just the morale

Overtime buys hours, not proportional output, and past a point it buys fewer units per hour than straight time did. A crew on a few weeks of moderate overtime to hit a pour date is fine. A crew on sustained 50- and 60-hour weeks for months gets tired, makes more mistakes, and puts less work in place each hour than it did at 40, so you are paying premium wages for degraded production. The hours go up and the rate comes down at the same time.

The industry studies that quantify this, including the well-known mechanical and labor productivity factor research, put the loss meaningful and growing with duration. A commonly cited figure is on the order of a 20 to 30 percent productivity loss from working extended 50-plus-hour weeks for roughly twelve weeks or more, with the loss deepening the longer it runs. Treat those numbers as a planning warning and a documentation reference, not a guarantee, because the real loss depends on the work, the crew, and the conditions.

The field lesson holds even where the exact percentage does not. If you watch the productivity factor on a crew you have pushed into long weeks, you will usually see the rate erode after the first few weeks, which is the curve showing up in your own numbers. That is the signal to add a shift or more bodies instead of more hours, and it is also the data you keep if the overtime was forced on you by a delay you did not cause.

Overmanning and congestion: more bodies, less per body

There is a crew size that suits the work and the area, and pushing past it buys diminishing returns. Add people to an operation that does not have room or work fronts for them and the extra hands wait, get in each other's way, and pull the rate per worker down. A four-person forming crew that does 200 lf a day does not become a six-person crew doing 300. It often becomes a six-person crew doing 240, which is more hours for less output per hour.

Trade stacking is the same problem across companies. When the schedule compresses and every trade ends up in the same area at once, supervision gets thin, material and access get tight, and coordination breaks down, so each crew works slower than it would with the space to itself. The recognized productivity research treats stacking of trades and overmanning as two of the heavier hitters, because the loss is not one crew's fault, it is the congestion itself.

The cure is fewer people working ready fronts, not more people working a crowded one. Size the crew to the work the area can actually absorb, open more work fronts before you add bodies, and watch the productivity factor when you scale a crew up. If the rate per hour drops as the headcount climbs, you have passed the point where another worker helps, and the timesheet is lying about how much that worker added.

Rework is pure lost productivity

Rework is the most expensive kind of lost productivity because you pay for the work twice and the second time earns you nothing. The hours that strip a bad wall, re-form it, and re-pour it are hours against a cost code that already counted the quantity as installed. The output does not move. The hours climb. The productivity factor craters, and it craters for a reason that quality control should have caught before it became labor.

It also hides in the numbers in a particular way. When you see a cost code where the hours keep rising but the installed quantity has stalled or gone backward, that is rework signature, because backing out finished work literally reduces the quantity in place. A crew that is busy all week with nothing new to show for it is usually redoing, and the productivity reading is the first place it surfaces if you are watching the rate and not just the hours.

The fix is upstream of the field math. Get the layout right, get the inspection before the pour, build the mockup, and catch the error while it is cheap to fix instead of after it is concrete. Productivity tracking will tell you that rework happened. Quality the first time is what keeps it from happening, and the two together are how a crew holds its rate.

Make-ready and the look-ahead protect the rate

The single biggest lever on productivity is whether the work is ready when the crew arrives, and that is a planning problem, not a crew problem. A skilled crew on a constrained front, waiting on a submittal, a missing embed, an inspection that was not scheduled, or predecessor work that is not done, will post a terrible rate through no fault of its own. The hours burn while the crew waits, and waiting earns zero units.

This is exactly what the look-ahead and make-ready process exists to prevent, and it is covered in depth in the scheduling guide. The short version: pull the next three to six weeks of work, find every constraint that has to clear before each activity can start, and knock those constraints down ahead of the date so the crew shows up to work that is actually buildable. The constraint log is productivity protection, because every constraint left standing is a crew standing too.

Tie the two together and they reinforce each other. The look-ahead removes the constraints that would tank the rate, and the productivity numbers tell you whether the make-ready is actually working. If a cost code keeps posting a low factor and the field reports the crew kept waiting on something, that is a make-ready failure showing up as a productivity loss, and the place to fix it is the constraint log, not the crew.

The levers that actually move the rate

Improving productivity is mostly about removing the friction between the crew and the work, and the levers are unglamorous because the real ones usually are. Plan the work so the crew has a ready front every day. Stage the material where it gets used so the crew is installing, not hunting and carrying. Get the crew size right for the area instead of overloading it. These three do more than any pep talk, because they attack idle time and travel time, which is where the hours leak.

The bigger structural levers are prefabrication and reducing travel. Prefab moves work off the critical front and into a controlled setting where a rebar cage or a wall panel gets built faster and more consistently than it would in place, then sets in a fraction of the field hours. Cutting travel, by locating the gang box, the material, and the work close together, recovers hours that never showed up as anybody's fault because walking is not on a timecard as a line item.

Clear direction ties it together. A crew that knows exactly what to build, in what order, to what line, works at its rate. A crew waiting on a decision or guessing at the sequence does not. None of these levers is exotic, and that is the point: productivity is won by making the ordinary conditions right, every day, on every front, not by finding a trick. Watch the rate after you pull each lever and keep the ones that move it.

Use your own historical rates as the benchmark

The most useful production rate is the one your crews actually hit on your kind of work, not a number from a published reference. Published rates and estimating manuals are a starting point when you have nothing else, but they carry assumptions about crew, conditions, and methods that may not match yours, and the spread between sources is wide enough that two of them can disagree by a third on the same operation. Your own history is the benchmark that fits your business.

Build the database from the jobs you already track. Every completed cost code with clean hours and quantities is a data point: this crew formed wall at this rate, set rebar at that rate, placed slab at the other, under these conditions. Captured over a few jobs, those numbers become a real production-rate library that prices the next bid and sets the target on the next job, both grounded in what your people actually do rather than what a book guessed.

Hedge every rate to the conditions it came from. A formwork rate from a clean, repetitive parking deck does not transfer to a tight, congested, heavily detailed foundation, and treating it like it does is how a bid goes wrong. Keep the conditions with the rate, segment the database by the work type that actually drives the difference, and confirm a historical rate fits the new job's conditions before you bid or budget against it.

Loss-of-productivity claims and the measured mile

When something outside your control wrecks the rate, an owner-driven acceleration, a stack of changes, a site you could not access, the productivity records are what turn a loss into a recoverable claim instead of an absorbed cost. A loss-of-productivity claim argues that the crew would have hit a certain rate but for the disruption, and that it hit a worse rate during the impacted period, and the difference in hours is the damage. The whole argument stands on numbers you either kept or did not.

The most accepted way to prove it is the measured mile. You compare the productivity rate during an unimpacted, or lightly impacted, period of similar work against the rate during the impacted period, and the gap between them is the lost productivity, measured from your own job rather than from a disputed estimate. AACE International addresses the methods for estimating lost productivity, with the measured mile generally treated as the most preferred approach because it sidesteps arguments about whether the original bid was reasonable.

The catch is that the comparison periods have to be genuinely similar work, and finding a clean unimpacted stretch on a badly disrupted job is the hard part, so the method gets attacked exactly there. Either way, the claim lives or dies on contemporaneous records: dated production quantities, hours by cost code, the events that caused the disruption, and the notice the contract required. The change-order and scheduling guides cover the contract and time side; the productivity records covered here are the proof of the loss. Get the documentation reviewed for your specific contract and jurisdiction, because the rules and the accepted methods vary.

Feed the actual rates back to estimating

Productivity data that never reaches the estimator is a diary. It records what the crews did and changes nothing about the next bid, which is where the data is worth the most. The loop only closes when the actual production rates from finished jobs become the rates that price the next ones, so the estimate stops being a hopeful number and starts being a record of what your crews actually do.

Work it concretely. The estimate priced wall formwork at 0.04 hours per SF, and the last four jobs came in between 0.05 and 0.055. The rate is off by a quarter, and you have four jobs of proof, not a hunch. Update the estimating rate to what the crews actually hit, and the next bid for that work is priced from reality. Do this across the operations you repeat and the estimating database gets more accurate every year instead of staying a guess hardened by habit.

This is the same loop the job-costing guide describes for cost, run on the production rate instead of the dollar. The estimate predicts the rate, productivity tracking measures it, and the measurement is wasted if it never corrects the prediction. The contractors who win over time are the ones whose rates get truer every year because the actuals keep feeding them. The ones who keep estimating from the old book keep getting surprised by the same operation.

The records that make the rate provable

The productivity record is two streams kept against the same cost codes over the life of the job: the actual hours and the installed quantities, period by period, with the rate and the trend that fall out of them. Kept consistently, those streams are the management tool while the job runs and the evidence if a claim comes later. Kept sloppily or reconstructed at the end, they are neither, because a rate nobody can trace back to a clean count proves nothing.

The trend matters as much as any single number. A productivity factor of 0.90 that is steady is a different story than a 0.90 that is falling week over week, and only the period-by-period record shows you which one you have. The trend is what separates a crew that hit a hard stretch and recovered from a crew that is sliding, and it is the shape an owner's analyst will look for if the rate ever lands in a dispute.

FieldOS keeps both streams against the cost codes as a side effect of the daily report: hours and quantities logged on site, the rate computed each cycle, the trend visible across the job, and dated field records sitting behind the numbers. The point is that the evidence exists before anyone knew they would need it, captured live by the people doing the work, instead of assembled from memory after the job is cold and the argument has already started.

How productivity tracking fails in practice

The failures are predictable and almost none of them are about the arithmetic. The first is having no labor budget by cost code to measure against, so you are tracking production against nothing and cannot tell a good rate from a bad one. The second is tracking labor as one lump instead of by cost code, which hides the operation that is actually losing inside the operations that are fine.

The rest are about timing and data. Looking monthly when the slip needed catching in week one turns the whole exercise into a faster autopsy. Inaccurate field hours or uncounted quantities make the rate fiction in whichever direction is most flattering. Ignoring the early productivity signal because the cost report has not confirmed it yet throws away the lead time that is the entire point. And never feeding the actual rates back to estimating means the same operation gets underbid at the same wrong rate, job after job.

Each one alone weakens the number. Stacked, they produce the contractor who is busy, confident, and slowly losing on labor, because every signal they trust is reading a job as more productive than it is. The fix for all of them has the same shape: budget by cost code, capture hours and quantities live, read the rate weekly, act on it early, and close the loop back to the estimate.

What to document

The productivity record answers the question that comes months out, whether the crew was actually slow or the job was disrupted, and the only thing that settles it is what you captured as the work ran. Capture enough that someone who was not there can reconstruct the rate on each cost code, period by period, and see what moved it.

Field checklist

Common mistakes

• Having no labor budget by cost code, so production is measured against nothing.
• Tracking labor as one lump instead of by cost code, hiding the operation that is actually losing.
• Looking at productivity monthly, when the slip needed catching in week one.
• Inaccurate field hours or uncounted quantities, which make the rate fiction.
• Ignoring the early productivity signal because the cost report has not confirmed the loss yet.
• Never feeding the actual rates back to estimating, so the same operation is underbid at the same wrong rate.
• Adding bodies or overtime to a low rate without watching whether output per hour actually rose.

Standards and references

Labor productivity tracking is a recognized construction-management practice rather than a single enforceable code, so the references here are methods and bodies of work to build your system around, not standards an inspector signs off. The earned-value and production-rate framework comes out of project-controls practice, with AACE International publishing recommended practices for estimating, earned value, and forensic analysis, and the Construction Industry Institute and similar research bodies publishing the productivity studies that quantify how the common factors degrade output.

For loss-of-productivity work specifically, AACE addresses the accepted methods for estimating lost productivity, with the measured mile generally treated as the most preferred because it compares your own impacted and unimpacted work rather than relying on a disputed estimate. The mechanical contractors' productivity factor research and similar industry studies catalog the factors, overtime, stacking of trades, overmanning, weather, and the rest, with ranges of impact. Treat those published ranges as planning references and documentation support, and hedge the actual loss to your own records, because the real number depends on the work and the conditions.

Three things to hold onto across all of it. Budget and track by cost code, because a lump number cannot tell you where the loss is. Read units per labor hour weekly as a leading signal, because the rate predicts the outcome before the cost report does. And feed the actual rates back into estimating, because the loop is what makes the next bid real. The specific rates and factors vary with your crews, your methods, and your jurisdiction, so build the benchmark from your own historical data and confirm any published figure against the project in front of you.

Units and terms

Productivity carries its own vocabulary, and the same idea reads differently across an estimate, a cost report, and a delay claim. These are the terms that have to mean the same thing to the field and the office for the tracking to work.

Production rate

Units of work installed per labor hour, such as 25 lf formed per hour, or its inverse, hours per unit

Productivity factor

Earned hours divided by actual hours; above 1.0 the crew beats the budget, below 1.0 it loses (confirm which way your report runs)

Cost code

The operation the hours and quantities both charge against, such as wall formwork or rebar, so the rate lands where you can act on it

Earned hours

Installed quantity times the budgeted hours per unit, the credit the estimate gives for work in place; also percent complete times budgeted hours

CPI

Cost performance index from earned value: earned value over actual cost; above 1.0 favorable, below 1.0 an overrun, the dollar version of the productivity factor

Measured mile

A loss-of-productivity method comparing the rate in an unimpacted period against an impacted period of similar work, the gap being the loss

Labor budget

The estimate's budgeted hours by cost code and the production rate behind them, the baseline the field has to beat

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