Predictive Analytics & Forecasting
Demand forecasting and anomaly detection for UK SMEs. Two distinct services: forecasting estimates future states so you can plan ahead; anomaly detection flags present deviations so you can respond faster. Time-series forecasting for business—choose what fits your challenge.
Forecasting Services
Sales forecasting, demand forecasting, and workload prediction—we build forecasting tools that help you plan ahead using your real business data.
The Problem
- Planning is based on instinct or last month's numbers
- Seasonal effects are poorly understood
- Teams are often over- or under-prepared
- Demand changes are noticed too late
What You Get
- Baseline forecast model
- Forecast accuracy summary
- Dashboard with confidence/uncertainty bands
- Guidance on interpretation and use
What Forecasting Helps You Plan
- Seasonal product demand
- Incoming quote volume by week
- Workload for staffing decisions
- Sales pipeline and revenue
- Cash flow and working capital
- Material and inventory requirements
Typical results: 15-30% reduction in stockouts, 15-25% reduction in overstock, earlier visibility of demand changes.
Results vary by data quality. We agree success metrics upfront.
What We Need From You
- Historical time-stamped data (sales, demand, activity)
- Definition of what you want to forecast
- Context on promotions, outages, or special events
Anomaly Detection & Monitoring
We build systems that flag unusual activity in your data so issues can be reviewed earlier.
The Problem
- Irregular events are easy to miss in large datasets
- Teams detect problems late—after they've caused cost
- Manual review doesn't scale
- There's no reliable early-warning mechanism
What You Get
- Monitoring rules or anomaly model
- Alert logic and thresholds
- Review dashboard or flagged report
- Documentation on how to interpret signals
Where Anomaly Detection Helps
- Unusual stock movement
- Irregular process readings
- Unexpected site-monitoring patterns
- Abnormal transaction behaviour
- Quality or measurement drift
- Operational threshold breaches
Typical results: Earlier warnings, faster response, lower incident costs. Problems caught before escalation rather than after.
What We Need From You
- Historical observations or transactions
- Known examples of abnormal events if available
- Process thresholds or operational expectations
Our Approach
We use proven methods—from classical statistics to modern machine learning—chosen based on your data, not our preference.
Explainable
You understand why it predicts what it predicts. No black boxes.
Validated
Tested on historical data before deployment. You see accuracy upfront.
Practical
Integrated into your workflow, not a standalone curiosity.
Ready to plan ahead or catch problems earlier?
Book a discovery call to discuss your forecasting or monitoring challenges.