IBM Systems Magazine, Mainframe Edition - March/April 2011 - 34

Applying Analytics
Most commercial organizations share similar goals: attract the best, most profitable customers; grow the business through up- and cross-sell; retain high-quality customers; minimize risk to the organization; and detect and prevent fraudulent activity. Supply-chain considerations, such as effective assortment planning in retail stores and efficient production lines in manufacturing, are also key considerations that can significantly affect the customer experience and ultimately customer value. In short, the goal is to grow revenues and minimize costs, thereby producing profitable revenue growth. Typical applications include:

hÁGovernment agencies that manage functions as diverse as tax audit selections, military force recruitment, and proactive policing and public safety. hÁHealthcare organizations that seek to proactively manage their resources and fine-tune their practices to provide better patient care. hÁColleges and universities that manage the entire student lifecycle: recruiting the right mix of students, offering a selection of programs and assistance to keep students enrolled, and managing alumni development programs.

ensuring our investigative resources focus on genuinely high-risk cases. Integrating the results of analytics with business processes and operational systems, or deployment, can be relatively simple: one point of integration in one process and system. For example, at a single point in processing tax returns, a predictive model scores every return on the likelihood of noncompliance, and adds those with high scores to an investigations-team audit list. In other solutions, the approach might be more complex.

Data-Driven Decisions
At the highest level, predictive analytics enables better business decisions. Analysis might reveal new insights that help senior management drive far-reaching strategic decisions and deliver step changes in business value. However, these insights are more often applied at the individual-case level, enhancing key business decisions that are made frequently and repeatedly, where improvement leads to a higher proportion of good outcomes and clearly measurable, incremental ROI. A helpful way to think of these decisions is: If we could make better decisions about “X,” we could deliver greater value by doing “Y.” For example:

Predictive Analytics
n. Predictive analytics draws reliable conclusions about current conditions and future events and thus helps connect data to effective action. It enables organizations to make predictions and then proactively take action based on that insight to drive better business outcomes and achieve a measurable competitive advantage.

h ÁDelivering well-targeted campaigns h ÁClassifying high-quality customers and, conversely, identifying those who are costly hÁFocusing investigators and minimizing the effect of fraudulent activity hÁLeveraging effective and reliable inventory management hÁPredicting maintenance needs
Public agencies manage a unique set of challenges and often face additional scrutiny because of the personal nature of public security, healthcare and education. Because they’re also often funded or subsidized by government-run agencies, these organizations face additional pressures and bureaucracy around operational budgets. Typical public-sector applications include:

Why System z?
While organizations strive to deliver analytics that will make decision making smarter, better and faster, they also must ensure that analytic processes are secure, transparent and compliant with external and internal governance regulations. While information infrastructures must be high-performing, management strives to make them less costly. IBM recently released versions of the SPSS predictive analytics solutions designed specifically for IBM System z* environments. By running analytics on System z servers, you can deliver sharp and timely insights that everyone, from senior executives to frontline managers, needs. You can also meet requirements for expanded data-accessibility and security, process transparency, information-systems efficiency and cost savings.

h ÁIf we could reliably predict which of our high-net-worth customers were likely to defect to a competitor, we could ensure their continued business by offering incentives. h ÁIf we knew how likely each of our customers would be to respond to a particular cross-sell offer, we could reduce the size and cost of campaigns (and increase response rates and revenues) by not targeting people unlikely to respond. hÁIf we could accurately assess the risk of each insurance claim as we receive it, we could reduce costs and increase customer satisfaction and loyalty by fast-tracking safe claims and increase our fraud-detection rate by



IBM Systems Magazine, Mainframe Edition - March/April 2011

Table of Contents for the Digital Edition of IBM Systems Magazine, Mainframe Edition - March/April 2011

IBM Systems Magazine, Mainframe Edition - March/April 2011
Table of Contents
Editor's Desk: Predicting a Good Read
Dashboard: Charging Ahead
Data Display: Smarter Cities Large and Small
Think Smarter: Capture Insight From Real-Time Operational Data With Smart Analytics Systems
Insider: Agnostic Development Tools Support Mainframe-Centric Businesses
Trends: DataPower Support for zEnterprise Extends its Multiplatform Capabilities
Case Study: Citigroup tames its backup environment with dedicated mainframes.
Driving Outcomes: Successful companies fuel business with predictive analytics.
Hurdling Barriers to Success: IBM demonstrates Cognos BI on Systems z is less expensive than x86 deployments.
Tips and Techniques: Overcome Eight Key Service-Delivery Challenges and Reduce Costs
Solutions
Advertisers’ Index
Stop Run: Bijan Davari Changed the Computer Chip®
Reference Point
IBM Systems Magazine, Mainframe Edition - March/April 2011 - IBM Systems Magazine, Mainframe Edition - March/April 2011
IBM Systems Magazine, Mainframe Edition - March/April 2011 - Cover2
IBM Systems Magazine, Mainframe Edition - March/April 2011 - 1
IBM Systems Magazine, Mainframe Edition - March/April 2011 - 2
IBM Systems Magazine, Mainframe Edition - March/April 2011 - 3
IBM Systems Magazine, Mainframe Edition - March/April 2011 - Table of Contents
IBM Systems Magazine, Mainframe Edition - March/April 2011 - 5
IBM Systems Magazine, Mainframe Edition - March/April 2011 - 6
IBM Systems Magazine, Mainframe Edition - March/April 2011 - 7
IBM Systems Magazine, Mainframe Edition - March/April 2011 - 8
IBM Systems Magazine, Mainframe Edition - March/April 2011 - 9
IBM Systems Magazine, Mainframe Edition - March/April 2011 - 10
IBM Systems Magazine, Mainframe Edition - March/April 2011 - 11
IBM Systems Magazine, Mainframe Edition - March/April 2011 - Editor's Desk: Predicting a Good Read
IBM Systems Magazine, Mainframe Edition - March/April 2011 - 13
IBM Systems Magazine, Mainframe Edition - March/April 2011 - Dashboard: Charging Ahead
IBM Systems Magazine, Mainframe Edition - March/April 2011 - 15
IBM Systems Magazine, Mainframe Edition - March/April 2011 - Data Display: Smarter Cities Large and Small
IBM Systems Magazine, Mainframe Edition - March/April 2011 - 17
IBM Systems Magazine, Mainframe Edition - March/April 2011 - Think Smarter: Capture Insight From Real-Time Operational Data With Smart Analytics Systems
IBM Systems Magazine, Mainframe Edition - March/April 2011 - 19
IBM Systems Magazine, Mainframe Edition - March/April 2011 - 20
IBM Systems Magazine, Mainframe Edition - March/April 2011 - 21
IBM Systems Magazine, Mainframe Edition - March/April 2011 - Insider: Agnostic Development Tools Support Mainframe-Centric Businesses
IBM Systems Magazine, Mainframe Edition - March/April 2011 - 23
IBM Systems Magazine, Mainframe Edition - March/April 2011 - 24
IBM Systems Magazine, Mainframe Edition - March/April 2011 - 25
IBM Systems Magazine, Mainframe Edition - March/April 2011 - Trends: DataPower Support for zEnterprise Extends its Multiplatform Capabilities
IBM Systems Magazine, Mainframe Edition - March/April 2011 - 27
IBM Systems Magazine, Mainframe Edition - March/April 2011 - Case Study: Citigroup tames its backup environment with dedicated mainframes.
IBM Systems Magazine, Mainframe Edition - March/April 2011 - 29
IBM Systems Magazine, Mainframe Edition - March/April 2011 - 30
IBM Systems Magazine, Mainframe Edition - March/April 2011 - 31
IBM Systems Magazine, Mainframe Edition - March/April 2011 - Driving Outcomes: Successful companies fuel business with predictive analytics.
IBM Systems Magazine, Mainframe Edition - March/April 2011 - 33
IBM Systems Magazine, Mainframe Edition - March/April 2011 - 34
IBM Systems Magazine, Mainframe Edition - March/April 2011 - 35
IBM Systems Magazine, Mainframe Edition - March/April 2011 - Hurdling Barriers to Success: IBM demonstrates Cognos BI on Systems z is less expensive than x86 deployments.
IBM Systems Magazine, Mainframe Edition - March/April 2011 - 37
IBM Systems Magazine, Mainframe Edition - March/April 2011 - 38
IBM Systems Magazine, Mainframe Edition - March/April 2011 - 39
IBM Systems Magazine, Mainframe Edition - March/April 2011 - Tips and Techniques: Overcome Eight Key Service-Delivery Challenges and Reduce Costs
IBM Systems Magazine, Mainframe Edition - March/April 2011 - 41
IBM Systems Magazine, Mainframe Edition - March/April 2011 - 42
IBM Systems Magazine, Mainframe Edition - March/April 2011 - 43
IBM Systems Magazine, Mainframe Edition - March/April 2011 - 44
IBM Systems Magazine, Mainframe Edition - March/April 2011 - Solutions
IBM Systems Magazine, Mainframe Edition - March/April 2011 - 46
IBM Systems Magazine, Mainframe Edition - March/April 2011 - Advertisers’ Index
IBM Systems Magazine, Mainframe Edition - March/April 2011 - Stop Run: Bijan Davari Changed the Computer Chip®
IBM Systems Magazine, Mainframe Edition - March/April 2011 - Cover3
IBM Systems Magazine, Mainframe Edition - March/April 2011 - Cover4
IBM Systems Magazine, Mainframe Edition - March/April 2011 - Reference Point
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