Reporting narrates the past; simulation rehearses the future. In Clixer that rehearsal needs no separate tool, no modelling project and no data-science team: the what-if module runs on the same real data and the same semantic metric set as your cockpits.
Industry-agnosticism is the heart of it. Simulation variables are not a fixed template; they are defined around your business. Rent, staffing, average discount and revenue target in fashion retail; raw-material cost and waste rate in manufacturing; occupancy and hourly cost in services. Whatever your industry, the engine is the same: define the variable, set the range, run the scenario.
The power of store-level runs is simple: a company-wide average misrepresents both your best store and your weakest one. Run the simulation per store (or branch, warehouse, line, whatever your unit is) and break-even is computed with that store's own rent and staffing. 'At what revenue does this store turn profitable?' gets that store's answer.
Scenarios sit side by side: compare optimistic, base and pessimistic arms on one screen; walk into the meeting with 'these variables give this outcome', not 'I think'. Scenario outputs can be shared as reports, the decision is archived together with its rationale.
Highlights
- Industry-agnostic variable sets: rent, headcount, discounts, raw materials, defined around your business
- Store / unit-level break-even, profitability and cost thresholds
- Compare optimistic / base / pessimistic scenarios side by side
- No code, no modelling project: drag, change, save
- Runs on real data: scenarios use the same metric set as your cockpits
- Scenario outputs can be shared as reports and archived
This page is a starting text; we will refine it together around your simulation scenarios.