Business problem

Customer Service & Fulfillment

Whether the order arrived complete, on the date you committed to.

Metrics

Computable definitions from the KPI Dictionary — every decision switch made explicit, with the formula behind it.

KPI	Formula	What it answers
OTIF — On Time In FullK-01	$\text{OTIF} = \frac{\sum_{\ell \in E} \mathbf{1}\!\left[t^{\mathrm{arr}}_{\ell} \le t^{\mathrm{prom}}_{\ell}\right] \cdot \mathbf{1}\!\left[q^{\mathrm{ship},1}_{\ell} \ge q^{\mathrm{ord}}_{\ell}\right]}{\lvert E \rvert}$	Did the customer get what they ordered, when they were told, complete — and which of the six definitions of that are you actually reporting?
Fill RateK-02	$\text{Fill rate} = \frac{\sum_{\ell} q^{\mathrm{ship},1}_{\ell}}{\sum_{\ell} q^{\mathrm{ord}}_{\ell}}$	Of what the customer ordered, how much shipped — counted in units, lines, or orders, at first pass or eventually, against the original ask or the ask after cancellations?
Perfect Order RateK-07	$\text{Perfect order rate} = \frac{\sum_{o \in O} \prod_{c \in C} \mathbf{1}\!\left[\text{pass}_{o,c}\right]}{\lvert O \rvert}$	Did the order arrive on time, complete, undamaged, and correctly billed — and which of those tests are actually inside your version of perfect?
Lead Time — Order-to-Delivery & SupplierK-09	$\begin{aligned} \text{LT}_{\ell} &= t^{\mathrm{stop}}_{\ell} - t^{\mathrm{start}}_{\ell} \\ \text{Reported} &= \operatorname{median}_{\ell}\!\left(\text{LT}_{\ell}\right),\; P_{90}\!\left(\text{LT}_{\ell}\right) \end{aligned}$	How long from commitment to arrival — which two timestamps define the clock, and is the reported number a mean or the percentile customers and planners actually feel?

OTIF has no single definition, and the spread between the defensible ones is wide enough to change what a supply chain review concludes. Order grain or line grain, measured against the original commitment or the current one, on the ship date or the delivery date — each pairing produces a different, honest number. The definitions here publish every switch and the denominator each figure was computed over; perfect order gets the same treatment, published as the AND across its four components beside the product of their rates, which is the answer that looks right and is not. Lead time is here too, read as a distribution rather than an average, because a promise date set from a mean is wrong about half the time by construction.

SAP modeling guides

Start from the business question, not the table. Each guide covers the table set, the joins and their traps, the grain decision, extraction into Databricks, and working SQL.

SAPDeliveries & shipmentsDid we ship on time, what's still open, how did orders turn into shipments, and can we prove goods actually left?

Reference builds

Reference builds for this business problem, implementing the definitions above wherever one exists, running over frozen, simulated data. Not a resource and not a case study — no client data, and no client named.

In the references

Where this data lives in each source system. A way into the ERP references, not an index of them — every reference landing lists all of its modules.

SAPSales & Distribution SAPLogistics Execution EWMDelivery Processing (Warehouse Requests)JDESales Order Management D365Sales & Marketing M3Deliveries

The other business problems

Inventory & Working Capital — What you're holding, why it's there, and what it costs to hold it.
Demand Planning & Forecasting — How wrong the forecast is, in which direction, and where the error is worth fixing.
Procurement & Supply — What's on order, when it lands, and how the supplier actually performs.
Manufacturing & Production — Whether the plant built what the plan said it would build.
Data Foundation & Governance — Landing ERP data in a lakehouse without losing deletes, history, or control of who reads it.

See this domain in the whole library