As societies and corporations around the world wrestle with disruption from the economic downturn, data and analytics appear more vital than ever to delivering enterprise value.
But on which fronts do organisations stand to gain the most from forward-looking insights achieved through a fusion of big data and digital analytics?
Taking business process mapping to the next level
In recent years, more and more business owners have begun to recognise that machine-led insights are essential for achieving maximum ROI(Return on Investment) throughout the value chain.
The challenge is keeping up with the sheer volume and variety of data streaming in from across the organisation. After all, how do you map and model processes you barely have sight of?
The answer is: let machines do it for you.
Process mining is an emerging field that combines multiple data science techniques to extract insights from event logs created by any enterprise controlling system (e.g., customer care, CRM, ERP). Analytical techniques powered by machine-learning then go beyond basic process modelling by:
- Discovering and mapping the true processes that run throughout the company.
- Checking conformance. Documenting each process to verify conformance with compliance procedures.
- Testing models and detecting bottlenecks. Determining throughput and overhead times; predicting and identifying previously unseen, undiagnosable bottlenecks.
Process mining can be useful in any organisation that has a complex process map. For instance, in manufacturing:
- Better supply chain management – Factoring in weather and road conditions to shorten delivery times.
- Improved risk management planning – Predicting costly stock-outs, comparing supplier quality.
- Tracking operations in real-time – Reducing miscommunication, eliminating waste.
- Analysing customer buying patterns – Enabling build-to-order processes, reducing the cost of inventory, shortening lead times.
- Monitoring equipment – Early detection of breakdowns, issuing tasks automatically to engineers.