Data Intelligence & Reporting

See what’s coming with predictive analytics

Use your historical data, machine learning and location intelligence to forecast outcomes.

Problem 01

“We find out about churn after it happens”

Customers leave, equipment fails and fraud slips through, and you only find out afterwards.

How we fix it

Predictive modelling & classification

  • Outcome prediction for churn, equipment failure and sales performance
  • Risk classification for fraud, credit and security
  • Lead scoring and anomaly detection in transactions and sensor data
Problem 02

“Demand catches us out”

Stock runs out at the worst time, rosters don’t match demand and cash flow surprises the finance team, because plans are based on last year’s numbers and gut feel.

How we fix it

Forecasting

  • Demand and sales forecasts by product and region
  • Workload forecasts for staffing and rosters
  • Scenario modelling for planning
Problem 03

“We can’t see patterns by location”

Your data is full of addresses and coordinates, but it’s shown in tables.

How we fix it

Geospatial intelligence

  • Route optimisation and logistics planning
  • Market, demographic and site analysis
  • Interactive spatial dashboards tied to your KPIs

What changes for your team

Act earlier

Better allocation

Lower risk

Evidence-based decisions

Where predictive analytics helps

Healthcare

Readmission rates, disease progression and patient risk scores.

Finance & insurance

Fraud risk, loan eligibility and claims scoring.

Manufacturing

Equipment health, failure forecasts and maintenance scheduling.

Transport & logistics

Route efficiency, delivery planning and fleet utilisation.

Common questions

How much data do we need?

It depends on the question, but many useful models can be built from a few years of CRM, sales or operational history.

Can predictions appear inside our CRM?

Yes. Scores and predictions can be written back to Dynamics 365, Salesforce, HubSpot or Zoho so your team sees them where they work.