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The Agenda

Join us for one of more of these live predictive analytics sessions. If you are unable to attend the whole event, please feel free to attend the sessions which are of most value to you

Agenda

Time Description
9:00 - 9:30

30m

Opening Welcome and Keynote Address: The Predictive Advantage
Leveraging advanced analytics to drive better outcomes and maximise ROI
Speaker: Rich Holada, WW Leader for Predictive Analytics at IBM [view bio]

9:30 - 10:30

60m

Session 1: Predictive Customer Analytics
Achieving Customer Intimacy

10:30 - 11:00

30m

Morning Tea/Coffee Break

11:00 - 12:00

60m

Session 2: Predictive Operational Analytics
Achieving Operational Excellence

12:00 - 13:00

60m

Session 3: Predictive Threat and Fraud Analytics
Protecting Your Organisation from Threats and Fraud

13:00 - 14:00

60m

Networking lunch

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Session Abstracts

Opening session: The Predictive Analytics Advantage

Predictive analytics informs and directs decision making by applying a combination of advanced analytics and decision optimisation to an organisation’s data, with the objective of improving business processes to meet specific organisation goals. It is through the analysis of past, actual data, that organisations are better equipped to predict future outcomes and make decisions appropriately.

This opening session will introduce you to the concept of Predictive Analytics, what it is, how it works, and what it can do for your organisation. Explore case studies from IBM SPSS customers across a wide range of industries to find out how they have benefited from the implementation of predictive analytics.

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Predictive Customer Analytics

Achieving Customer Intimacy

Recent technology advances have not only changed the way people purchase products and services, but have also raised the bar in terms of customer support. B2B and B2C customers today expect a more personalised buying experience—and they’re leaving volumes of digital fingerprints behind that provide valuable clues about their needs and preferences.

By embedding predictive customer analytics within your business processes, you can deliver a positive customer experience that builds greater customer loyalty.

In this session, you’ll hear how innovative organisations are optimising operations, attracting and retaining highly profitable customers, using social media to capture new markets and improve the customer experience, and how IBM SPSS solutions work together with campaign management solutions to increase visibility into customer intentions and needs, and help you automate highly effective marketing programs.

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Predictive Operational Analytics

Achieving Operational Excellence

Being smarter means moving away from the broad brush long-term planning approach to becoming much more agile and able to respond to each customer uniquely - we call this operational excellence. Operational excellence allows an organisation to become agile by focusing on the intricacies that a business faces on a daily basis.

In this session you will find out how IBM SPSS solutions can help you act smarter by helping you manage your physical and virtual assets -- from identifying the right physical inventory to stock in your multi-tier supply chain to assessing how many components to purchase to support your production facilities. You will also take away knowledge on how to maintain your physical infrastructure and capital equipment and maximise your capital – ensuring you are allocating your people and cash in the most efficient manner, in the context of your business processes

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Predictive Threat and Fraud Analytics

Protect your Organisation from Threats and Fraud

As organisations become more instrumented, interconnected and intelligent this also brings slightly different challenges to light, with new possibilities comes new complexities and new risk. Organisations must protect themselves and control how they manage and act on threat and fraud; moving towards a more preventative and proactive approach rather than a corrective one.

In this session you will learn how organisations are using predictive analytics across their operations to manage threat and fraud, including how to monitor your environment by including a wide variety of data from across multiple sources. Detect suspicious behaviour to identify threats, information breaches, crime or fraud and control outcomes to deliver the best response to reduce exposure or loss and maximise the impact of any action taken.

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Rich HoladaRich Holada heads IBM’s predictive analytics group, which includes the SPSS line of software and solutions. Holada is responsible for setting the strategic and technological direction of the group, as well as overseeing its day-to-day operations, from global product development to sales and marketing. With Business Analytics as a key growth area for IBM, Holada is focused on helping customers solve real-world business problems through predictive analytics to create a Smarter Planet.

Previously, Holada was CTO of predictive analytics which included global responsibility for product marketing, product strategy, research and development, and technical support for the IBM SPSS predictive analytics brand. He joined SPSS, prior to its acquisition by IBM, in November 2006 as Senior Vice President of Research & Development, bringing with him nearly 20 years of deep software research and development background and diverse experience in the technology industry.

Previously, Holada has held senior level posts with Oracle Corporation and PeopleSoft, Inc., both leading CRM technology organisations. At PeopleSoft, Inc. he was the senior technical executive responsible for creating the industry-leading PeopleSoft CRM product offering.

Holada has also held senior research and development positions at Trimark Technologies, Inc., where he transformed the firm from a consulting operation to a software product company, as well as at Intelligent Trading Systems, Inc. and Sun Microsystems, Inc.

Holada received his B.S. in Computer Science from University of Illinois, Champaign, and his Juris Doctorate from John Marshall Law School in Chicago, graduating cum laude with honors.