ERP
Sales orders with confirmed and revised delivery dates, delivery notes, invoices, and the customer record they belong to.
Customer
Reliability per customer, not one number for everyone
A company-wide on-time figure of ninety-four percent sounds healthy right up until you learn the missing six percent is concentrated in four accounts, two of which are up for renewal. Customers do not experience your average; they experience their own orders. And the two halves of that measurement, what you promised and what actually arrived, sit in different systems, which is why most companies can quote a total and not a customer. Coheed measures it per account, so reliability becomes something you report on and act on.
- Systems combined
- TMSERPCRM
- Runs
- Daily at 7am
Sound familiar?
Teams bring us this use case when one or more of these is true.
- A customer asks for your delivery performance on their account and you cannot produce it.
- You have a company-wide on-time figure and no idea how it is distributed.
- Account managers hear about a string of late deliveries from the customer, not from a report.
- Contract and tender conversations include service levels you do not measure per account.
How it works
Coheed runs this as a scheduled insight over your connected systems, then hands the result to an agent.
- 1
The promise is captured where it was made
The confirmed delivery date on the order, plus any revision agreed later, is taken from the ERP and the CRM, so performance is measured against what the customer was actually told rather than the original date alone.
- 2
The delivery is captured where it happened
Actual shipment and arrival are read from the warehouse and transport records, including partial deliveries, so an order delivered in two parts is judged on when the customer could actually use it.
- 3
Performance is aggregated per account, not per order
Results roll up per customer, per product group, and per period, with the size and direction of the miss included, because being a day early and being two weeks late are not the same event even though both are 'not on time'.
- 4
The insight becomes an action
Accounts whose reliability is deteriorating are handed to an agent that prepares the account review, and combined with the customer's value and contract dates so attention goes where the relationship risk is real.
Which data it uses
Only the fields this use case needs are read. Nothing is copied that the insight does not use.
TMS
Planned versus actual arrival per shipment, delivery confirmations, and the route the order travelled.
CRM
Account ownership, agreed service levels, contract and renewal dates, and complaints logged against deliveries.
Coheed
The cross-system order and account links, and the performance history that shows whether an account is trending up or down.
What changes
What a team notices once this runs. No invented percentages: the effect depends on your data and your process.
- Reliability per account becomes a number you can put in front of a customer.
- Deteriorating relationships surface from delivery data before they surface as churn.
- Tender and contract conversations start from measured performance rather than a claim.
- The misses stop hiding inside an average that looks acceptable.
From insight to action
Delivery Reliability Agent
Available as an agent
Watches per-account delivery performance, alerts the account owner when an account's reliability drops below its agreed or historical level, and prepares the account review with the underlying orders attached. Customer-facing messages go out only after approval.
Mode: Human-in-the-loop
Every insight can stay read-only, run with human approval, or run autonomously. You decide per action type, and you can change it later.
FAQ
Frequently asked questions
Do you measure against the original date or the revised one?
Both, once we can. Measuring only against the revised date makes any operation look excellent, because every promise gets moved until it is met. There is a practical limit: most ERPs overwrite the confirmed date when it is revised, so the original is gone. Where yours keeps the revision history we read it; where it does not, Coheed records the date it sees on every run and builds that history from go-live. So the revised-date figure is available for your existing orders, and the how-often-did-the-first-promise-hold figure starts accumulating the day we connect, rather than reaching back over last year.
How do partial deliveries count?
As you decide. The default treats an order as delivered when the customer can actually use it, which for most businesses means the last line rather than the first, but you can measure per line where that fits your agreements better.
Can we share this with customers?
Yes, and that is often where the value sits. The measurement is built per account with the underlying orders attached, so a reliability report is something you can hand over rather than a number a customer has to take on faith.
Which systems does it need?
An ERP for the promised date and the customer, plus whatever records actual delivery, your WMS or TMS. Adding the CRM is what connects performance to contract dates and account ownership.
Built on these maturity levels
Most relevant for
Logistics & Transport
Combine your TMS, telematics, fleet, and finance systems into insights no single tool can produce.
B2B Commerce
Unify your webshop, ERP, and CRM so pricing, stock, and accounts stay in sync, and turn insight into agents.
B2B Wholesale
Close the gaps between CRM, ERP, and SCM so promises, stock, and margin hold across the whole order chain.
Manufacturing
Connect the quote, the shop floor, and purchasing so promised dates, real cost price, and margin per order finally agree.
Other use cases
Predictive Customer Lifetime Value
Score churn risk and future value per account by combining CRM engagement decline with ERP order frequency and value trends.
Lead-to-Quote Readiness
Surface correct ERP pricing, live stock, discounts, and customer agreements on every new CRM lead so sales can quote immediately.
Order Exception Monitoring
Catch stock gaps, unrealistic delivery dates, pricing errors, and missed agreements after the order, before the customer notices.
See this on your own data
Tell us your ERP, CRM, and SCM stack and we will show what this use case looks like on your systems.