Simulation & Prediction
Forecasting
Historical actuals with run-rate, no-action and recommended-action projections against target.
Latest actual
ACTUAL2
Run-rate (6 mo)
FORECAST2
No action (6 mo)
FORECAST2.86
Recommended (6 mo)
SCENARIO1.14
Target
TARGETNot stored
Regulatory breaches — Regulatory & Compliance
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: lower.
Forecast table
| Period | Type | Actual | Run-rate | No action | Recommended | Spread (±1σ) |
|---|---|---|---|---|---|---|
| Apr 26 | ACTUAL | 1 | ||||
| May 26 | ACTUAL | 1 | ||||
| Jun 26 | ACTUAL | 1 | ||||
| Jul 26 | ACTUAL | 1 | ||||
| Aug 26 | ACTUAL | 1 | ||||
| Sep 26 | ACTUAL | 2 | ||||
| Oct 26 | FORECAST | — | 2 | 2.14 | 1.86 | 1.79 – 2.49 |
| Nov 26 | FORECAST | — | 2 | 2.29 | 1.71 | 1.8 – 2.78 |
| Dec 26 | FORECAST | — | 2 | 2.43 | 1.57 | 1.83 – 3.03 |
| Jan 27 | FORECAST | — | 2 | 2.57 | 1.43 | 1.88 – 3.26 |
| Feb 27 | FORECAST | — | 2 | 2.71 | 1.29 | 1.94 – 3.48 |
| Mar 27 | FORECAST | — | 2 | 2.86 | 1.14 | 2.01 – 3.71 |
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 (+0.14 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 +0.143 per month).
- Residual standard deviation σ = 0.345; 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 |