AI & Data Consulting practice

Forecasts built from your own history, not a generic model.

Demand, revenue or booking forecasts modelled on your historical data — sized to actually be useful for planning decisions.

Practice line · AI & Data Consulting Format · Project-based with optional retainer Best for · Teams planning inventory, staffing or revenue targets
Overview

A forecast is only useful if it changes a decision.

Forecasting models are easy to build and easy to ignore if they don't map onto a real planning decision — staffing levels, inventory orders, pricing changes. We scope the model around the specific decision it needs to inform.

This pairs naturally with Hospitality's revenue management work and Business Consulting's feasibility studies, where forecasts directly inform pricing and investment decisions.

What you get

What's included.

01

Historical Data Modelling

Structuring your historical data into a form a forecasting model can actually use.

02

Forecast Model Build

A model sized to your data volume and the specific metric you're forecasting.

03

Scenario Planning Support

"What if" scenario modelling to stress-test planning assumptions.

04

Ongoing Recalibration

Periodic recalibration as new data comes in, so the forecast doesn't go stale.

Frequently asked

Before you book a call.

How much historical data do we need?+
At least 12–18 months is ideal, though useful directional forecasts can sometimes be built with less, depending on the metric.
How accurate are these forecasts?+
Accuracy is reported honestly per model and improves over time as more data feeds back in — we don't promise certainty, only a better-than-gut-feel starting point.

Want to talk through predictive analytics & forecasting?

A short discovery call tells us both whether this is the right starting point.

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