Transparent economics of commercial operations
Finance director
See what the gap between the best and the average people across departments actually costs, and read revenue growth together with the cost of acquiring a customer.
Who it is for
Transparent economics of commercial operations
Put a number on the gap
The gap between the best and the average exists in every department, but nobody usually prices it. Once the work is described in measurable terms, the difference between best-case and average stops being a feeling and becomes an amount.
Model the effect before rollout, not after
The economics of an initiative are built during the assessment: baseline, assumptions, an effect formula, and the criteria under which the work stops. That lets you decline an initiative before the spend rather than rationalise its outcome afterwards.
Know the cost of ownership
An AI solution carries a running cost: models, integrations, support, exceptions. We state it before work begins and show how it moves with volume — otherwise the savings on paper are eaten by the operating bill.
Questions the data cannot answer today
- How much does the company lose on the difference between its best and average people?
- What does the effect of an initiative consist of, and which assumptions in it are weakest?
- What is the full cost of ownership over a year?
- How does revenue growth compare with the cost of acquiring a customer?
What stays in your hands
Stays with you
- a baseline: the starting state, fixed, with the measurement method stated
- an effect model with assumptions listed explicitly and rated for reliability
- a cost-of-ownership estimate: models, integrations, support, exceptions
- stop criteria — the values at which the work does not continue
The metrics this moves
- customer acquisition cost
- gross margin by line of business
- cost per operation in a process
- return on what was invested in the initiative
What we use for this
AI Workflow Automation
Removes repetitive manual steps from end-to-end business workflows.
Explore this solutionDocument & Reporting Automation
Cuts the time spent producing documents and reports and moving data between systems.
Explore this solution
Cases
How this looked for others
eCommerce and retailAI Workflow AutomationClient under NDA
An online store's support front line stopped growing with its order volume
Operators were absorbed by repeat questions, complex enquiries got lost in the queue, and the knowledge base went stale faster than anyone could fix it.
- Enquiries that reach an operator
- −25–40%
- Ticket handling time
- −30–50%
- Support satisfaction (CSAT)
- +10–18%
Marketing and digital agenciesDocument & Reporting AutomationClient under NDA
The first ten days of the month stopped going into client reports
For the first 8–10 days of the month the team assembled reports instead of doing project work. Approvals dragged, payments moved with them, and every new client meant either overtime or a hire.
- Time to prepare a monthly report
- 10 days → 5 minutes
- Projects handled by the same team
- +30%
- Monthly saving on manual work
- ≈$5,000
EdTechAI Workflow AutomationClient under NDA
One account manager runs twenty-five cohorts instead of five
Account managers kept cohort statuses in their heads. Every new course meant either overload or loss of control: missed classes and blown deadlines surfaced after the fact, when the student had already fallen behind.
- Cohorts per account manager
- 5 → 25
- Cost of running one course
- −40%
EdTechDocument & Reporting AutomationClient under NDA
Course materials stopped going stale faster than they could be updated
A new module or an update took weeks. The load on methodologists grew faster than the team, and the product aged between releases: a student would see an example on a library version that no longer exists.
- Speed of releasing and updating material
- ×10
- Share of manual work in content production
- −50%
- Cost of producing content
- −40%
Consulting and professional servicesAI Workflow AutomationClient under NDA
Answers stopped living in people's heads: search across company documents, with the source attached
Finding an answer took time, and what turned up could be out of date. Different people answered the client differently, and the surest route was to ask a colleague — that is, to interrupt one more person.
- Time spent finding information
- −40–60%
- Errors caused by out-of-date instructions
- −20–35%
eCommerce and retailAI Workflow AutomationClient under NDA
Nurturing stopped being one campaign to the whole list
The customer profile was described from gut feel, nurturing was launched by hand and identically for everyone, and hypotheses took weeks to test. Sales received leads with no readable warmth and spent time on people who were not ready.
- Stage-to-stage funnel conversion
- +30–40%
- Conversion to sale
- +20–50%
EdTechAI Workflow AutomationClient under NDA
AI across four departments of a school: marketing, sales, content and operations in one loop
Growth meant one of two things: losing quality, or hiring into every department in proportion to volume. No single department was the bottleneck — the seams were, and nobody owned them.
- Revenue
- ×3 in 4 months
- Operating costs
- −60%