Simulation & Prediction
Forecasting
Historical actuals with run-rate, no-action and recommended-action projections against target.
Latest actual
ACTUALUSD 22.4M
Run-rate (6 mo)
FORECASTUSD 22.4M
No action (6 mo)
FORECASTUSD 25.81M
Recommended (6 mo)
SCENARIOUSD 25.81M
Target
TARGETNot stored
Digital revenue — Digital Services
Solid = stored actuals (Historical KPI trend data). Dashed = deterministic projections in the shaded period. Band = ±1σ of historical residuals around the no-action line, widening with horizon. Direction of good: higher.
Forecast table
| Period | Type | Actual | Run-rate | No action | Recommended | Spread (±1σ) |
|---|---|---|---|---|---|---|
| Apr 26 | ACTUAL | USD 19.6M | ||||
| May 26 | ACTUAL | USD 20.1M | ||||
| Jun 26 | ACTUAL | USD 20.8M | ||||
| Jul 26 | ACTUAL | USD 21.3M | ||||
| Aug 26 | ACTUAL | USD 21.9M | ||||
| Sep 26 | ACTUAL | USD 22.4M | ||||
| Oct 26 | FORECAST | — | USD 22.4M | USD 22.97M | USD 22.97M | USD 22.92M – USD 23.02M |
| Nov 26 | FORECAST | — | USD 22.4M | USD 23.54M | USD 23.54M | USD 23.47M – USD 23.61M |
| Dec 26 | FORECAST | — | USD 22.4M | USD 24.11M | USD 24.11M | USD 24.02M – USD 24.2M |
| Jan 27 | FORECAST | — | USD 22.4M | USD 24.67M | USD 24.67M | USD 24.56M – USD 24.78M |
| Feb 27 | FORECAST | — | USD 22.4M | USD 25.24M | USD 25.24M | USD 25.12M – USD 25.36M |
| Mar 27 | FORECAST | — | USD 22.4M | USD 25.81M | USD 25.81M | USD 25.68M – USD 25.94M |
Source data, assumptions, methodology & limitations
Source data
- Telecom KPI data (current period, target, prior)
- Historical KPI trend data (monthly history Apr–Sep 2026)
Assumptions
- Run-rate baseline: holds the latest stored actual flat.
- No action: continues the 6-month stored trend (+0.57 per month).
- Recommended action: reverses the trend at the same monthly rate (no stored target).
Methodology
- Least-squares straight line through 6 stored months (slope +0.569 per month).
- Residual standard deviation σ = 0.053; spread = σ × √(months ahead).
- Identical arithmetic feeds Decision Journey Stage 5 — Predict.
Limitations
- 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 | Congestion forecast 214 sites forecast to exceed 85% utilisation within 90 days. | OSS network data |
| model output | SIM-box detection output 1,240 SIM-box incidents flagged; 91% detection rate. | Revenue assurance data |
| methodology | Network Performance & Risk methodology Aggregate availability and KPIs from network counters; Classify outages by root cause; Score sites by risk and revenue exposure. | Finance Planning Dataset |
| assumption | FX assumption All figures in USD at a constant planning rate. | Finance Planning Dataset |
| model output | Churn propensity scores 48k high-value subscribers scored above 60% churn propensity. | CRM |
| limitation | Regulatory data lag Regulator returns lag by one quarter; current quarter is estimated. | Regulatory Reporting Store |