Advanced Analytics Solutions
Advanced analytics empower you to uncover hidden patterns in data, that you can tap into to inform decisions and deliver better business outcomes. Our solutions integrate both predictive and prescriptive analytic models directly into your business processes, so you can make the right decisions every time, without the need for advanced statistical or mathematical skills.
These solutions enable classification, association, segmentation, simulation, time-series analysis and forecasting.
Who uses advanced analytics?
Geospatial analytics - Insight into relationship between data and geographic locationOur geospatial analytics solutions let you use historical data such as location, the type of event, and the time an event happened to describe the occurrences of events, such as crimes or disease outbreaks. Use measurements taken over time at locations in 2D and 3D space, to predict how those areas may change over time.
Entity analytics - Detect related entities across large, sparse, and disparate collections of dataImprove the coherence and consistency of data by resolving like entities even when the entities do not share any key values. This capability is especially useful in applications like customer relationship management, national security, fraud detection and preventing money laundering.
Social network analysis
Examine the relationships between social entities and the implications of these relationships on behaviour.These capabilities allow you to identify and better understand groups, group leaders and spheres of influence:
- Build predictive modelsa about individuals and enhance these models with their group and social behaviour data.
- Capture consumer data from social media to understand attitudes, opinions and trends, and manage your online reputation.
- Predict customer behaviour and improve customer satisfaction by anticipating customer needs and recommending next best actions.
- Enable customized campaigns and promotions that resonate with social media participants.
Prescriptive analytics Optimize operational decision making and automate business decisions that control critical business processes
Prescriptive analytics allow you to automate and optimize transactional high-volume decisions in processes, at the point of impact.
- Combine predictive models, business rules and scoring to deliver recommended actions in real time.
- Make better decisions about whether an applicant’s loan should be approved, or which patients are most likely to respond to a particular treatment program, and whether allocating scarce resources to a prevention program is the most effective care approach.
Prescriptive analytics also empowers you to optimize complex, frequently occurring, and repeatable operational decisions to maximize profit, performance, or yield; or minimize loss, risk, or cost
Determine the best trade-offs given a set of business rules and constraints, so you can optimize decisions like:
- Pricing time-sensitive products
- Delivery routes and schedules
- Machine or equipment preventative maintenance schedules
- Staff scheduling
- Machine control or resource distribution to maximize yield
Integration, scalability, extensibility and deployment Intuitively integrate data from multiple sources
Integrate structured, unstructured or semi-structured analytical data from traditional relational database management systems, social media data, big data stored in Hadoop, and more, without extensive technical skills or coding.
- For atypical problems, extend your analytics with “R”, Spark and Python, as well as Hadoop.
- Deploy analytic models, business rules and event management on premise or in cloud-based platforms.
“IBM Predictive Analytics helps us provide the customer with individualized and specific products and also offer the customer with seamless interaction with our Operations”
Dr. Shivaji Dasgupta, Head of Big Data & Advanced Analytics
They profile the severity of suspicious activity in payments and payers as interactions occur in social welfare payments, financial services, healthcare, insurance, retail, credit cards, taxes, identity theft, insider trading and money laundering. Prevention and detection minimizes losses, and speeds non-fraudulent transactions, increasing customer satisfaction.
Both detect failure patterns to improve asset productivity and product quality. It helps you monitor, maintain and optimize assets for better availability, utilization and performance. It analyzes various types of data, including usage, wear and conditional characteristics from disparate sources, and detects failure patterns and poor quality parts earlier than traditional quality control methods, to reduce unscheduled asset down time and ensure quality metrics are achieved or exceeded.
It meets the needs of the “always on” consumer, and personalizes the customer experience including:
- Lift Analytics for Retail and Personalized Promotions for Retail Customers.
- Behavior Based Customer Insight for Banking, Personalized Customer Experience for Mobile Banking Customers, Behavior Based Client Insight for Wealth Management
- Next Best Action Recommendations into Insurance Call Center Interactions
- Next Best Action for Telecommunications Call Centers and Telecommunications Customer Management with Mobile Service Insights
- Behavior Based Customer Insight and Customer Experience Analytics for Communication Service Providers
- Proactive Customer Relationship Management for Energy and Utilities
It can be optimized in areas such as:
- Allocation and Assignment – transportation, routing and scheduling of resources or people
- Supply chain management: managing the flow of raw materials and products based on uncertain demand for finished products
- Globalizing operations processes in order to take advantage of cheaper materials, labor, etc.
- Efficient customer response and messaging
- Location planning - designing the layout of equipment in a factory or components in an assembly to reduce manufacturing time; locating facilities, such as factories, warehouses or stores, or people with specialist skills and knowledge
- Project planning, identifying those processes which affect the overall duration
- Network optimization: for instance, setup of telecommunications networks to maintain quality of service during outages
- Automation or integration of robotic systems in human-driven operations processes
- Queue optimization
- Blending of materials, e.g., in a manufacturing process
Line-of-Business (LoB) organizations use self-service, automated, guided discovery to experiment and understand which are the business drivers and questions that reveal important insights, before engaging IT. Automated analysis and recommendations enable you to draw conclusion about what's happening, and why; statistical analysis, correlation and predictions help you see what's most likely to happen and what you can do about it; visualizations in dashboards communicate what's important to support decision-making and communicate effectively with others.