Start from the question,
not the dashboard.
Most analytics work fails because it answers questions nobody was asking. Below is an index of the ones our clients do ask, by function — with the data each needs and what it is usually worth. Pick one and we will scope it.
Which accounts are quietly disengaging?
Weekly logins, one account, twelve weeks before it churned
- Data it needs
- Product usage · support volume · contact recency
- Typical payback
- Churn caught a quarter earlier
- Time to first answer
- 6 weeks
Twelve questions worth answering
Payback figures are ranges we have seen, not promises. The honest number for your business comes out of the first two weeks.
Which customers will miss their next payment?
Invoice history · payment timing · support contacts
3–5% of receivables recovered earlier
6 weeks
Where is margin leaking by product and channel?
Order lines · landed cost · discounts · returns
1–3 points of gross margin
8 weeks
What will cash look like in thirteen weeks?
AR/AP ageing · payroll calendar · committed spend
Fewer emergency facility draws
5 weeks
Which orders are going to be late, today?
Work orders · capacity · supplier lead times
20–40% fewer surprise escalations
7 weeks
Which assets should we service before they fail?
Sensor history · maintenance log · failure records
Unplanned downtime down by a third
10 weeks
Where is inventory sitting that nobody will order?
Stock on hand · movement history · forecast
Working capital released
6 weeks
Which open deals are actually going to close?
CRM activity · engagement signals · won/lost history
Forecast accuracy inside 10%
5 weeks
Which accounts are quietly disengaging?
Product usage · support volume · contact recency
Churn caught a quarter earlier
6 weeks
What is a channel worth after the refunds land?
Spend · attributed revenue · refunds · service cost
Budget moved off vanity channels
4 weeks
Where are we about to lose people we can't replace?
Tenure · role scarcity · internal moves · survey trend
Targeted retention, not blanket raises
6 weeks
Which roles take longest to fill, and why?
Requisition stages · source · offer outcomes
Weeks off time-to-hire
4 weeks
Is overtime a demand problem or a rostering problem?
Shift plans · actual hours · volume by site
Overtime spend down without service loss
5 weeks
Showing 12 of 12 use-cases.
One question, answered in ninety days
We deliberately do not build a platform first. The first question funds the foundations, and the second one is faster because of it.
Agree the question and find the data
We confirm the decision this will change, who makes it, and whether the data can actually support it. If it can't, you find out in two weeks rather than two quarters.
Build the model and the pipeline behind it
A governed data model, tested transformations and the one interface the decision-maker will actually use — nothing more.
Put it in the decision
The answer lands in the meeting, the tool or the workflow where the decision gets made, and we measure whether behaviour changed.
“The forecast stopped being an argument. We spend the Monday meeting deciding things instead of reconciling spreadsheets.”
Commercial Director, industrial distributor — first use-case live in 11 weeks
- Forecast error
- 23% → 8%
- Hours of manual reporting per month
- −140
- Use-cases live in year one
- 6
Tell us which row matters most
We will come back with the data you need, the effort to answer it, and what it is worth — as a plan you can approve or shelve.