In recent years, a new saying has grown popular among many business leaders: “Data is the new oil.” With the advent of IoT, mobile devices, and web services, the volume of data available has increased exponentially. Forward-thinking companies are realizing that there are hidden riches locked inside their information systems; and with the right data strategy, there is even more value to found.
Many of those insights have an impact at the strategic level; but the benefits of such insights may be difficult to measure, and monetize, especially in the short-term.
Fortunately, there are some excellent examples of data-driven decision processes that can produce far more tangible and immediate results. For companies that deal in physical products, should claim the number one spot on that list.
It is indisputable that supply-chain decisions can produce immediate, measurable value. When information flows freely, with little or no friction, those decisions happen faster and therefore produce better results. When slow-moving inventory sits on the shelf, it is (at best) tying up resources that could be deployed elsewhere. More importantly, it could be losing value with every day that passes. When it comes to supply-chain decisions, speed matters.
But speed is not the only important factor. Supply-chain decisions
must be informed by data that is accurate, up-to-date, and as
comprehensive as possible. With end-to-end (E2E) monitoring
of the supply-chain, including shipment status, demand factors,
external events, and more, managers have more input and are
therefore capable of driving better decisions.
The AI Advantage
With all that data, decision-making has the potential to grow in complexity. Fortunately, AI and machine learning have advanced considerably in recent years. When these technologies are applied to a specific domain, – such as supply-chain management, – they empower managers to make on a consistent basis.
Machine learning analyzes past decisions, new algorithms, and results to provide a basis for constant improvement over time. The net result is the simplification of a very complex domain.
Machine learning drives better results, and management-by-exception ensures that the time and attention of key personnel is spent where they will have the greatest impact. OpsVeda leverages machine learning and other advanced analytic techniques to continuously monitor your supply-chain in real-time and provides specific quantity and value assessments relating to exception events.