Stop Reacting. Start Predicting.
Predictive Analytics for Enterprise Operations
Most businesses have data. Few are using it to see what’s coming. Predictive Analytics from TSC turns your historical data, operational signals, and market patterns into forward-looking intelligence — so your teams can act before problems escalate, not after they do.
What Our Predictive Analytics Service Covers
Demand Forecasting & Inventory Optimisation
Predict demand patterns by SKU, location, and season — simultaneously reducing stockouts and excess inventory using machine learning on your Dynamics 365 data.
Customer Churn & Behaviour Prediction
Identify at-risk customers before they disengage. Behavioural signals, transaction frequency, and engagement patterns are analysed to surface who needs attention and when.
Financial Risk & Cash Flow Forecasting
Forecast cash positions, receivables risk, and budget variances weeks ahead — not after the period closes. Finance teams act on forward data, not historical reports.
Predictive Maintenance & Asset Risk Scoring
Score equipment health from IoT data, maintenance history, and usage intensity before failures occur. Know which asset to service before the breakdown happens.
Sales Pipeline & Revenue Forecasting
Machine learning models that improve forecast accuracy across product lines, regions, and sales channels — built directly on your CRM and ERP pipeline data.
Fraud & Anomaly Detection
Pattern-based detection models that flag unusual transactions, procurement activity, or operational deviations in real time — before financial exposure grows.
Typical outcomes achieved in comparable engagements:
- 25–35% improvement in forecast accuracy across demand, sales, and financial plans
- 18–30% reduction in unplanned asset downtime through predictive maintenance scoring
- 20–40% faster identification of at-risk customers and anomalous transactions
Why TSC for Predictive Analytics?
We don’t build models that sit in a lab. We build predictions that drive decisions on the shop floor, in the boardroom, and across the supply chain.
How do we do it?
Predictive Analytics is not about collecting more data. It’s about finding the signal in the data you already have — and building a model that turns that signal into a decision your business can act on.
Data Landscape Assessment
We start with what exists — not what’s ideal.
- Data source inventory: ERP, CRM, IoT, finance, external feeds
- Data quality scoring, completeness audit, and cleansing plan
- Identification of prediction-ready datasets and time-series signals
- Gap analysis and data enrichment roadmap
Prediction Use Case Definition
We define what we’re predicting — and why it matters to the business.
- Business problem alignment workshops with operations, finance, and leadership
- KPI definition for model accuracy and business success
- Prioritisation matrix: impact vs. readiness vs. effort
- Approved use case roadmap with business owner sign-off
Model Development & Training
Built on Azure ML — trained on your data.
- Feature engineering and variable selection from enterprise data
- Model selection and training: regression, classification, time-series forecasting
- Cross-validation, accuracy benchmarking, and threshold calibration
- Explainability documentation: what drives the prediction, in plain language
Integration & Operationalisation
Predictions need to live where decisions are made.
- Embedding predictions into Dynamics 365 workflows and screens
- Power BI dashboards with forecast overlays and confidence bands
- Alerting and threshold triggers for operational teams
- Real-time and batch scoring architecture design
Model Monitoring & Continuous Learning
A model that doesn’t evolve, deteriorates.
- Model drift detection and accuracy monitoring
- Monthly accuracy reviews with business feedback loops
- Scheduled model retraining as new data patterns emerge
- Ongoing optimisation roadmap and enhancement backlog
Use Cases by Industry
TSC deploys predictive models tailored to each industry’s unique data patterns, operational rhythms, and business KPIs.
| Industry | Use Case | Predicted Outcome |
|---|---|---|
| Distribution & Trading | Demand forecasting by SKU, warehouse, and season | 25–30% reduction in overstock and stockout events |
| Banking & BFSI | Credit risk scoring, churn prediction, fraud detection | 15–20% reduction in credit losses and fraud exposure |
| Oil & Gas | Predictive maintenance, production output forecasting | 25% reduction in unplanned downtime |
| Transportation | Route demand forecasting, fleet utilisation prediction | 15% reduction in empty miles and deadhead trips |
| Education | Enrolment forecasting, student dropout risk scoring | 10–15% improvement in seat utilisation |
| Technology & Consulting | Project revenue forecasting, resource demand prediction | 28% improvement in utilisation and capacity planning |
