Guides
A monthly KPI routine for a moving company
Nine moving company measures defined precisely: what each one counts, the document it comes from, how it is computed, and the decision it should change.
What to take away
- A measure is only useful when it has a definition, a source document, and a decision attached. Nine are enough for a moving company, and most yards cannot compute four of them because the close-out sheet is incomplete.
- Report everything by estimator and by crew lead. A yard-wide average tells you something is wrong; the breakdown tells you where.
- Two of the nine are leading measures, meaning they move before the money does: survey-to-actual variance and access hours charged against access hours worked.
- No target figures appear here. A number that is good in one yard is bad in another, and the useful comparison is against your own previous month.
How to read the definitions
Each measure below states four things: what it counts, where the number comes from, how it is computed in words, and what you do when it moves.
If your records cannot supply the source document, fix that gap first. The software and KPI guide sets out the fields that have to exist before any of this is possible.
1. Survey-to-actual hour variance
Counts: the difference between the crew-hours the survey predicted and the crew-hours the job took.
Survey vs Actual Hours
Positive variance
- Meaning
- Surveys optimistic
- Cause
- Access underestimated
- Acts on
- Estimator
Negative variance
- Meaning
- Jobs overpriced
- Cause
- Quotes lost
- Acts on
- Estimator
2. Access hours charged against access hours worked
Counts: stairs, long carry, elevator wait, and shuttle time that was priced, against the same time that was actually spent.
Access Hours Ratio
Ratio well under 1
Largest recoverable margin
Fix by better access questions
Not by raising prices
3. Paid crew-days sold
Counts: crew-days that produced revenue, not days the yard was open. Source: the dispatch calendar. Computed: a simple count per month, split into peak weeks and quiet ones. Acts on: capacity and marketing. Compare against the crew-days you must sell to cover fixed cost, which is the break-even figure the yard should already have.
4. Contribution per crew-hour, by service
Counts: what an hour of crew time earns after the direct costs of the service it was spent on. Source: the estimate, the job sheet, and the materials record. Computed: revenue attributable to the service, less loaded labor, materials, and equipment time, divided by the crew-hours it occupied. Acts on: what the office sells at the survey, and what gets peak hours.
5. Claims per hundred moves, with cause
Claim Cause Classification
- Building damage
- Item damage in transit
- Item damage in a carton
- Missing item
- Service failure
Source: the claims ledger. Computed: count per hundred completed moves, then the same by cause. Acts on: method and training. The cause split is the whole value of the measure. Building damage points at protection at the door; carton damage points at packing or at customer-packed cartons that were not inspected.
6. Callback and complaint rate
Counts: customers who contacted the office after the move with a problem, whether or not it became a claim. Source: the office log. Computed: count divided by completed moves. Acts on: the gap between what was sold and what was delivered. A rising callback rate with a flat claims rate usually means the estimate is promising something the crew is not doing.
7. Quote-to-booking rate
Counts: written estimates that became jobs. Source: the estimate log. Computed: bookings divided by estimates issued, reported separately for surveyed and unsurveyed quotes. Acts on: pricing and sales method. A very high rate usually means prices are low, not that the sales process is excellent.
8. Crew hours per unit of volume
Counts: how long your crews take to move a given quantity of goods under ordinary access. Source: the survey volume and the job sheet hours. Computed: crew-hours divided by cubic feet moved, filtered to jobs without unusual access. Acts on: training and crew composition. This is the productivity figure the estimator's assumptions rest on, and it should be rebuilt from real jobs rather than carried forward.
9. Equipment downtime days
Counts: days a truck was unavailable, and how many of those fell in peak weeks. Source: the maintenance log and the dispatch calendar. Computed: a count, split peak and off-peak. Acts on: the fleet decision. Downtime in season is what makes a cheap vehicle expensive.
The monthly review
Read the nine in a fixed order, because the order encodes causation. Estimating first, since a bad survey makes every crew look slow. Then crew method. Then equipment. Then the commercial measures. The output should be a short list of actions with a name against each, not a report.
Monthly Review Order
- Estimating
- Crew method
- Equipment
- Commercial measures
- Action list with names
Three of the nine metrics, numbers one, two, and eight, rely fully on complete close-out data. If crew leads are not recording actual hours by phase and deviations from the survey, fix that first. It feeds the measures that matter most.
Training crews to close out properly is part of the written method, not an extra request. The hiring and training guide treats it that way.
Measures that are not on the list
Skip revenue by month; it hides hours. Skip truck utilization as a percentage; a truck busy on unprofitable work looks the same as one busy on good work.
Skip online review counts; they result from numbers five and six, not a direct measure you can act on. Skip any industry benchmark; it assumes wages, access, and building types that are not yours.
What the numbers cannot tell you
They cannot tell you whether you are complying with the rules that govern your moves. Compliance is a file of dated answers from named authorities, not a metric. The licensing and compliance guide sets out how to build it.
They also cannot tell you whether a second market is a good idea. That is a demand question the expansion and market guide works through. A yard with excellent numbers in one territory can still be wrong about the next one.
The records behind the measures
Every measure here traces to a document created during the job. The Internal Revenue Service's guidance on what kind of records should I keep leaves the system to the business, provided it clearly shows income and expenses. A job-numbered file that carries hours, materials, and services delivered satisfies that and makes these nine computable.
Those records include customer addresses, dates their homes will be empty, and inventories of what is inside. Treat access to them as a control.
The National Institute of Standards and Technology's small business quick-start guides offer a practical starting point for risk management at this scale. The Cybersecurity and Infrastructure Security Agency's small and medium business resources cover the operational side, including access removal when someone leaves.
Common questions
How many measures should a two-truck yard track?
Three: survey-to-actual variance, paid crew-days sold, and claims with cause. Add the rest as the records improve.
What is a good variance figure?
The one that is tighter than last quarter. A published benchmark assumes an estimating method, a crew, and a set of buildings that are not yours.
Should crews see their own numbers?
Yes, with the caveat that raw hours are not a fair measure of a crew. Variance and claims by cause are, because they separate the crew's work from the estimator's.
How long before the numbers mean anything?
Roughly a season. Household moving is seasonal enough that a single month compared to the one before it can be misleading in both directions.
