Optimize operations, and
counter fraud and threats
Organizations in every industry struggle to do more with less. But complex operations and incomplete visibility into all areas of the business can lead to inefficient processes and high costs. And more streaming data—much of it unstructured or machine-generated—needs to be assessed in real time. You must be able to sense and respond in the moment.
Three-quarters of organizations surveyed by the IBM Institute for Business Value are beating their competitors by using analytics to uncover insights that are hidden within their data. These insights can help detect and prevent fraud, and help ensure operations run efficiently. By combining descriptive, predictive and prescriptive analyses into a system that identifies anomalies and recommends action, decision makers get the answers they need—when they need them.
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When assets are down, costs go up. Whether it’s manufacturing equipment, field assets or products, you need to keep downtime and failures to a minimum. Predicting when assets may fail can help you take a proactive approach to prevent or minimize costly outages.
Organizations face many threats on a daily basis, whether from external sources or their own employees and systems. To minimize the costs and damage associated with fraud and other threats, you must detect threats sooner and prevent them from affecting your business.
Top-performing organizations achieve a high level of operational excellence by streamlining processes to meet changing demands. They don’t merely react; they predict upcoming trends, risks and opportunities, using analytics technologies embedded within operational processes to make real-time improvements.
Fraud is difficult to identify and expensive to investigate. Indicators hide within multiple systems in many different forms. A collaborative, flexible system can extract volumes of data and analyze it in real time, then provide visualization—graphical representations of patterns and relationships—illustrating fraud.
Reduce costs, increase efficiencies and productivity, and limit threats
Business process optimization
Increase operating margins with improved process efficiency by basing real-time decisions on an optimized blend of predictive models, new data sources and business rules.
Infrastructure and asset efficiency
Reduce costs, improve service levels and prevent failures, using machine data with predictive root-cause analysis to optimize operations and identify repair actions.
Identify fraudulent activity, financial crimes and improper payments, and determine appropriate actions to mitigate these events with the intent to reduce loss and improve customer experience.
Public safety and defense
Anticipate threats and risks, uncover crime patterns and trigger factors, derive and use new insights to make better decisions, resolve problems proactively and manage resources effectively.
Featured use case: Operations analysis
Organizations can gain real-time visibility into operations, customer experience, transactions and behavior through the analysis of
in-motion and streaming machine data captured by IT systems, sensors, meters and GPS devices.