Simulation & Prediction
Scenario Simulation Workspace
Compare current state, no action, recommended, upside and downside scenarios for one journey or issue.
Journey
Churn & Retention
KPI under simulation
Monthly churn
Current
2.9%
Target
No stored target
Scenario outcome cards
Base case
Current trajectory with in-flight initiatives only.
- Stated outcome
- Revenue at risk (annualised): $6.8M
- Risk / trade-off
- —
- Monthly churn in 6 mo
- 2.9% ACTUAL
Do nothing
No targeted response.
- Stated outcome
- $0
- Risk / trade-off
- Churn reaches 3.3%
- Monthly churn in 6 mo
- 3.43% SCENARIO
Targeted retention bundle
30% bonus data for 3 months to 48k at-risk users.
- Stated outcome
- $2.1M protected
- Risk / trade-off
- Offer cost $0.4M
- Monthly churn in 6 mo
- 2.37% SCENARIO
- Expected value
- Revenue protected: USD 2.1M expected; USD 780k legacy recorded amount — excluded from current reporting · Not verified
Mass price match
Match competitor offer for all urban prepaid.
- Stated outcome
- $3.0M protected
- Risk / trade-off
- Cost $2.2M; ARPU dilution
- Monthly churn in 6 mo
- not modelled
Bundle + network fix
Retention bundle plus capacity in top-20 cells.
- Stated outcome
- $2.6M protected
- Risk / trade-off
- Capex $0.8M
- Monthly churn in 6 mo
- not modelled
Not stored for this journey: Upside, Downside. Shown as a gap rather than invented.
Scenario comparison — stated value vs cost/risk (USD M)
Amounts parsed from each scenario's stored results; ★ = recommended. Non-monetary outcomes plot as zero.
Risk / return matrix
Top-left = high value for low stated cost/risk.
Monthly churn — actual vs scenario paths
Same projection as the journey Predict stage and the Forecasting page. Open full forecast →
Comparison table
| Scenario | Role | Assumptions | Projected KPI (6 mo) | Stated impact | Risk / trade-off |
|---|---|---|---|---|---|
| Base case | Current State | Current trajectory with in-flight initiatives only. | 2.9% | Baseline | — |
| Do nothing | No Action | No targeted response. | 3.43% | $0 | Churn reaches 3.3% |
| Targeted retention bundle | Recommended | 30% bonus data for 3 months to 48k at-risk users. | 2.37% | $2.1M protected | Offer cost $0.4M |
| Mass price match | Alternative | Match competitor offer for all urban prepaid. | — | $3.0M protected | Cost $2.2M; ARPU dilution |
| Bundle + network fix | Alternative | Retention bundle plus capacity in top-20 cells. | — | $2.6M protected | Capex $0.8M |
Scenario → decision
Recommended scenario: Targeted retention bundle — $2.1M protected; trade-off: Offer cost $0.4M.
No decision is saved here; the decision is recorded in the journey at Decide.
Source data, assumptions, methodology & limitations
Source data
- Telecom KPI data (current period, target, prior)
- Historical KPI trend data (monthly history Apr–Sep 2026)
- Scenario library (assumptions, results, recommended flag)
- Value realization records (expected / actual value)
- Evidence records
Assumptions
- No action: continues the 6-month stored trend (+0.09 per month).
- Recommended action: reverses the trend at the same monthly rate (no stored target).
- Scenario outcomes, costs and risks are as stored for each scenario.
Methodology
- Scenarios of the selected journey are ordered Current State → No Action → Recommended → Upside → Downside → Alternatives.
- With an originating issue, alternatives sharing no words with the issue move to the bottom of the table.
- Projected KPI per scenario uses the shared deterministic forecast; only Current State, No Action and Recommended are modelled.
Limitations
- Scenario outcomes are governed figures stored with each scenario — they are not re-computed by a simulation engine.
- Forecasts are straight-line projections of six stored months; they ignore seasonality, shocks and interactions between measures.
- Many KPIs have no stored target; where absent, the recommended path reverses the trend at the same monthly rate.
- No downside scenario is stored for any journey; downside coverage is shown as a gap rather than invented.
| Evidence type | Item | Source |
|---|---|---|
| model output | Churn propensity scores 48k high-value subscribers scored above 60% churn propensity. | CRM |
| methodology | Churn & Retention methodology Segment churners by value, region and tenure; Correlate churn with network and competitor signals; Score base for churn propensity. | Finance Planning Dataset |
| assumption | Retention offer take-up Offer take-up modelled at 25% of targeted base. | CRM |