EX

Simulation & Prediction

Back to journey: Digital Services & Channels

Forecasting

Historical actuals with run-rate, no-action and recommended-action projections against target.

Latest actual

ACTUAL

USD 22.4M

Run-rate (6 mo)

FORECAST

USD 22.4M

No action (6 mo)

FORECAST

USD 25.81M

Recommended (6 mo)

SCENARIO

USD 25.81M

Target

TARGET

Not 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

PeriodTypeActualRun-rateNo actionRecommendedSpread (±1σ)
Apr 26ACTUALUSD 19.6M
May 26ACTUALUSD 20.1M
Jun 26ACTUALUSD 20.8M
Jul 26ACTUALUSD 21.3M
Aug 26ACTUALUSD 21.9M
Sep 26ACTUALUSD 22.4M
Oct 26FORECAST—USD 22.4MUSD 22.97MUSD 22.97MUSD 22.92M – USD 23.02M
Nov 26FORECAST—USD 22.4MUSD 23.54MUSD 23.54MUSD 23.47M – USD 23.61M
Dec 26FORECAST—USD 22.4MUSD 24.11MUSD 24.11MUSD 24.02M – USD 24.2M
Jan 27FORECAST—USD 22.4MUSD 24.67MUSD 24.67MUSD 24.56M – USD 24.78M
Feb 27FORECAST—USD 22.4MUSD 25.24MUSD 25.24MUSD 25.12M – USD 25.36M
Mar 27FORECAST—USD 22.4MUSD 25.81MUSD 25.81MUSD 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.
Forecast horizon: 6 months (Oct 2026 – Mar 2027)Model status: deterministic arithmetic — no AI or machine-learning model.
Evidence typeItemSource
methodology

Digital Services methodology

Combine app analytics and transaction platforms; Attribute revenue to digital channels; Track cohort retention.

Finance Planning Dataset