What the data says
Sales funnelThe Dynamics 365 sales process from lead to invoice: how many records move on at each step, and why the rest drop out
Processes (BPMN)How an order moves through Dynamics 365, from lead to cash and after-sales service, with the export's numbers on every step
Modelled in BPMN 2.0: download a diagram and open it in Camunda Modeler or bpmn.io. Numbers cover the last 12 months.
Lead to cash, in days
11 hwhat the export says about a step2.4 dayswhere time or money leaksClick a step for its Dynamics 365 table; scroll or drag to move around.
Market & marginRevenue follows the steel price as much as the tonnage
Monthly orders. The price index averages every product's list price, 100 = the first month.
Revenue, tons and the steel price index
Price per ton: list, realized and cost
Product groups, last 12 months
| Group | Revenue | Tons | Margin / t | Margin | Win rate |
|---|
MarketingFrom campaign response to won deal, and what each channel returned
First-touch attribution through the lead. Lifetime ROI counts every order from the accounts a campaign brought in.
Lead quality by source
Return on marketing spend, by channel
Channel scorecard
Spend, leads and results for every channel over the 24 months of data. Returns are gross margin per rial spent: 1x breaks even.
| Channel | Spend | Leads | Cost / lead | Won deals | Accounts won | Revenue from them | First-deal return | Lifetime return |
|---|
Pipeline & win modelA gradient-boosting model against the probability reps enter in Dynamics
Win rate by time to first quote
Promised vs. delivered: calibration
Open pipeline by stage
What drives a win
How much the model's accuracy (AUC) drops when each input is shuffled.
Open deals worth the most, by the model's expected value
For a deal not yet quoted, the model assumes the quote goes out today, so its number is what a quote now is worth.
| Customer | Rep | Product | Tons | Stage | Value | CRM says | Model says | Quote |
|---|
Win / lossWhy deals are lost, and what a discount really buys
Every closed deal in the data. Loss reasons come from the custom ahn_lossreason option set.
Why deals are lost
Discount on the first quote: win rate and margin
Win rate by customer industry
Win rate against each competitor
Sales teamLast 12 months, per account owner
CRM optimism: how far a rep's last CRM probability sat above the actual outcome, on deals closed in the last six months.
| Rep | Revenue | Tons | Won | Win rate | Avg discount | Hours to quote | Margin / t | Open pipeline | CRM optimism |
|---|
DeliveryFrom the order to a signed proof of delivery: the warehouse, the trucks and the weighbridge
Where the days go, by sourcing
On time by carrier
Weighbridge: loaded against ordered tons
Warehouses
| Warehouse | Orders | Tons | Days | On time | In full | OTIF |
|---|
Customers & creditWho buys, who has gone quiet, and who owes money
Receivables aging by industry
Revenue by province, last 12 months
Win-back list: regular customers gone quiet
| Customer | Owner | Orders | Lifetime revenue | Prior-year revenue | Last order | Days silent |
|---|
Top customers, last 12 months
| Customer | Revenue | Tons | vs prior year |
|---|
Credit by industry
| Industry | Open receivables | Overdue | DSO | Days late |
|---|
Customer serviceDynamics 365 Customer Service cases after delivery: claims, requests, SLAs and satisfaction
Cases opened in the last 12 months. SLA by priority: first response in 2, 4 or 8 hours; resolved in 2, 5 or 10 days.
Cases by category
Service and churn
Claims and requests
Median hours to resolve, share resolved within the SLA, claims upheld, and credit notes or replacements given.
| Category | Team | Cases | Time | In SLA | Upheld | Credit | CSAT |
|---|
Agents
| Agent | Cases | First reply | Reply in SLA | Resolved in SLA | CSAT |
|---|