On-time delivery
A 13% funnel drop, hidden in five healthy numbers.
Every stage of the order-to-delivery funnel reports a strong pass rate. Read one at a time, nothing looks wrong.
Operational Analytics
57,669 indents raised.
49,845 trucks moved.
Every stage of the indent funnel reports a healthy number. Read the row instead of the cell and one in eight loads never becomes a moving vehicle. Operational Analytics is how you find out which one — and what it cost.
Indents created
57,669
Across 12 sites, last six months.
Indents fulfilled
49,845
87% of what was raised.
Never moved
7,824
Promised, accepted, and no truck at the gate.
Detention / indent
₹26,483
The price of every hour that plan didn’t hold.
Definition
What is Operational Analytics?
Operational Analytics is the practice of measuring a physical operation at every handoff — not just its outcome — so that a miss can be traced to the stage, the owner and the cost that produced it. In fleet and transport, that means holding the indent funnel open from creation to gate-out, and refusing to let a stage-level failure average itself into a healthy monthly number.
Indent analysis · all sites · last 6 months
All SitesAll RoutesLast 6 Months
Indent created100%
Indent accepted98%
Vehicle assigned93%
Vehicle reported92%
Indent fulfilled87%
−13%No single stage looks like a problem. 98% acceptance is a good month. 93% assignment is a good month. Compounded, thirteen percent of everything you raised has quietly disappeared.
The problem
Most teams have data. Almost none have a number they can act on.
Every operation runs on summary metrics. Each one looks healthy on a dashboard. Each one is an average, and the average is exactly where the decision hides.
On-time %
One “on-time %” for two completely different failures.
A six-hour slip and a two-day slip both count as one late delivery. The metric treats a nuisance and a stockout as the same event.
Acceptance rate
Acceptance mistaken for commitment.
A transporter accepts 53% of the indents you send. The dashboard reads that as reliability. Acceptance and fulfilment are not the same promise.
Transit delay
Blame pointed at the wrong door.
The delay report blames the highway. Break the trip into stages and the longest one is not on the road at all.
Every one of these numbers was true. Not one of them was a decision. Intelligence begins where the average ends.
Analytics ROI
What is poor operational visibility costing you?
No multipliers, no benchmark hand-waving. Your indent volume, your detention cost, your fulfilment rate. The arithmetic is the argument.
Indents raised per month
4,800
Average detention cost per indent
₹26,483
Current fulfilment rate
87%
Ad-hoc placement premium
₹8,200per load
Fulfilment points recovered
+3
iAssumptions are conservative and fully configurable.
Core capabilities
Most tools stop at dashboards nobody opens.
Each rung only earns its place if the one below it holds. A number you cannot explain is not a number you can act on.
01 — SEE
Every KPI on one performance view, not five dashboards.
Indent funnel, fulfilment delay, transit adherence, detention cost and transporter score — same period, same filters, same page. A metric that lives in its own tab can never be compared to the one that caused it.
12 sitesRoute-levelPer transporter
Tracked trip source
SIM · 71%
GPS · 29%
Before any trend, the coverage. 71% of live visibility rides on SIM consent a driver can revoke at a toll plaza. An untracked trip is not a gap in the number — it is absent from it.
02 — CATCH
Cost leakage caught against baselines, not thresholds.
A threshold fires when a number is bad. A baseline fires when a number is different — which is weeks earlier, and is the only version of the alert that is still cheap to act on.
Severity-bandedLane baselinesDrift detection
Live trips · open
Open
46
On time
08
Delayed
03
Tracked
08
Untracked
01
SIM consent missingThe platform reports its own blind spot with the same prominence as its performance. Coverage is a number you are allowed to interrogate.
03 — EXPLAIN
A delay has four doors. Only two are the transporter’s.
Order execution time, split at the handoffs. The single longest stage in the chain is reported-to-gate-out — which is not a road problem, a driver problem or a vendor problem. It is a yard problem, and it has been sitting inside the on-time percentage the whole time.
Stage attributionOwner namedReason coded
Door 1
~2 hrs
Published → Accepted
TransporterDoor 2
~4 hrs
Accepted → Assigned
TransporterDoor 3
~12 hrs
Assigned → Reported
Driver / routeDoor 4
~42 hrs
Reported → Gate out
Your yard04 — ACT
Every review turned into owners, actions and a rupee.
Ad-hoc placement is the tax you pay for a plan that didn’t hold — the largest line in the cost of poor quality, and the one most often filed as freight rather than failure. Naming it is what turns an operations metric into a budget conversation.
ROI-ranked actionsNamed ownerModelled recovery
Cost of poor quality
Ad-hoc placementExpressOrigin detentionDestination detentionStoppages
How Taabi is different
From reporting to operating intelligence.
Two transporters can miss the same target for opposite reasons. On a monthly scorecard they look identical. On this table they don’t.
| Transporter | Requested | Accepted | Assigned | Fulfilled | On-time reporting | On-time fulfilled | LITR / DITR | Score |
|---|---|---|---|---|---|---|---|---|
| Transporter A | 15,955 | 8,49353% | 8,09397% | 1003% | 77% | 67% | 11% | 57 |
| Transporter B | 22,943 | 18,49382% | 18,293100% | 932% | 92% | 92% | 5% | 60 |
| Transporter C | 19,282 | 5,49326% | 5,493100% | 50010% | 99% | 99% | 4% | 61 |
| Transporter D | 15,322 | 7,49350% | 7,48199% | 4936% | 98% | 98% | 1% | 72 |
| Transporter E | 10,348 | 4,49343% | 4,40398% | 2,19850% | 99% | 99% | 2% | 74 |
| Transporter F | 29,348 | 2,6648% | 2,664100% | 51% | 93% | 93% | 1% | 77 |
Transporter F — a capacity problem
Asked for 29,348 vehicles, accepted 2,664. But everything accepted was assigned — 100%. This vendor is not unreliable, it is over-allocated. The fix is share-of-business, not a penalty clause.
Transporter A — a commitment problem
Accepted 53%, assigned 97% of that, fulfilled 3%. On-time reporting 77%. The acceptance is real; the truck is not. The fix is fewer indents, not more escalations.
Same miss. Opposite causes. Opposite actions. A composite score that cannot separate the two is a number you cannot negotiate with.
Business impact
Why teams invest in Operational Analytics.
Leakage
13%
Funnel leakage made visible
The gap between indents raised and trucks moved, held open stage by stage instead of averaged into a monthly percentage.
Detention
₹26,483
Priced per indent, not per month
Origin and destination detention separated, so the cost lands on the gate that caused it.
Root-cause
4doors
Delay attributed to a stage
Published, accepted, assigned, reported, gate-out. Each handoff timed and owned by a named party.
Coverage
100%
Tracking source disclosed
SIM versus GPS versus untracked, reported alongside every trend so the denominator is never assumed.
Accountability
1score
One ledger per transporter
Requested, accepted, assigned, fulfilled, on-time and LITR/DITR on a single row a vendor can be shown.
Reporting
0pivots
No Monday rebuild
Every panel filters by site, route, transporter and period, and exports as the same table the review runs on.
Who it’s for
Built for leaders and teams managing physical operations.
Enterprise shippers
The indent you raised is not the truck you got
Supply chain and logistics heads who own a fulfilment number they cannot decompose, and a detention line they cannot attribute.
Fleet operators
Halt days are the asset conversation
Operators measuring utilisation in running hours while the vehicle spends five days a month stationary at somebody else’s gate.
Leadership teams
One model across ops and finance
Leaders who need the operational number and the cost-of-poor-quality number to reconcile to the same period, the same filter and the same source.
Use cases
How teams use Taabi Operational Analytics.
Rebalancing share of business
Separate the vendor who cannot take the volume from the vendor who takes it and does not run it. One gets more lanes; the other gets fewer indents. Both used to get the same email.
Defending the detention line
Origin versus destination detention, split by site and gate. The number stops being a freight overrun and starts being a yard SOP with an owner.
Cutting ad-hoc placement
Every spot-bought load is a plan that failed upstream. Trace it back to the stage it failed at, and the premium becomes preventable rather than payable.
Closing the tracking gap
Move trips off revocable SIM consent and onto durable telemetry, lane by lane, prioritised by the value of the loads currently invisible.
Operational intelligence
Analytics is where Taabi turns operations into a learning system.
Every indent that fails leaves a record of where it failed. Enough of those records and the system stops describing the past and starts pricing the next one — which lane will slip, which vendor will accept and not run, which gate will hold a truck long enough to turn a plan into a premium.
FAQ
Operational Analytics, answered.
What is operational analytics in logistics?
It is the measurement of a physical operation at every handoff rather than only at its outcome. In transport, that means tracking an indent from creation through acceptance, assignment, reporting and gate-out — so a fulfilment miss can be attributed to the stage, the owner and the cost that produced it, instead of appearing as a single monthly percentage.
Why does a 98% acceptance rate still produce a 13% shortfall?
Because the stages compound. Acceptance at 98%, assignment at 93%, reporting at 92% and fulfilment at 87% each read as a good month in isolation. Multiplied across the funnel, roughly one in eight indents raised never becomes a moving vehicle — and the drop happens at a different stage each week, which is exactly what a monthly average erases.
How is transporter acceptance different from transporter commitment?
Acceptance is a response to an indent; commitment is a truck at the gate. A transporter can accept half the indents raised and fulfil a small fraction of them. Reading acceptance, assignment and fulfilment on the same row is what separates a vendor who is over-allocated (a capacity problem, solved with share-of-business) from one who accepts and does not run (a commitment problem, solved with fewer indents).
What is the cost of poor quality in transport operations?
The rupee value of operational failure once it is added up: ad-hoc placement premiums, express freight bought to recover a missed slot, origin and destination detention, and stoppage cost. Each typically sits in a different ledger under a different owner, which is why the total is rarely seen — ad-hoc placement in particular is usually filed as freight rather than as failure.
Does operational analytics work if some trips are untracked?
It works, but only if the coverage is disclosed. Consent-based SIM tracking is cheap and revocable; hardware GPS is durable and slower to deploy. Most fleets run a mix and report neither. Taabi reports the tracking source alongside the trend, because an untracked trip is not a gap in the number — it is absent from it, and a trend built on an unstated denominator is decoration.
Get started
Turn every report into a decision.
See the indent funnel, the transporter ledger and the cost of poor quality run against a live operation — and what the same view would surface in yours.