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One-on-One with Kris Hackney
Vice President, SPSS Worldwide Strategic Accounts and Services

by Karly Gaffney, Media Relations, Dashboard InsightTuesday, May 26, 2009

Dashboard Insight recently spoke with SPSS's Kris Hackney about her vast global customer network, her deployment methodology, and why predictive analytics software helps solve such a variety of issues.


 

Dashboard Insight: Tell us about the history of SPSS Inc.

Kris Hackney:  SPSS Inc., a leading global provider of predictive analytics software and solutions, was founded in 1968.  Its founders developed a revolutionary software system based on the idea of using statistics to turn raw data into information essential to decision making.  The company recognized early that data and how it is analyzed is the driving force behind sound decision making — the DNA of intelligence.

Focused on data about people, the company’s complete portfolio of predictive analytics software (PASW) products (data collection, statistics, modeling and deployment) allows organizations to capture people’s attitudes, behaviors and opinions, to predict outcomes of future customer interactions, and then act on these insights by embedding analytics into business processes to attract, retain and grow customers, reduce fraud or mitigate risk.

Throughout its 40-year history - headquartered in Chicago, Illinois - SPSS has produced software that enables its customers (commercial organizations, academic institutions and government agencies) to focus their operations to better manage the present, and more importantly, improve the future.

DI:  Where does SPSS sit on the B.I. stack?

KH: There is a big difference between business intelligence (BI) and predictive analytics.  Traditional BI technologies focus on what’s happening now or what’s happened in the past by primarily using static financial or product data.  For organizations to take the most effective action, they need to know and plan for what may happen in the future by using people data – and that’s harnessed through predictive analytics. 

Another way to look at it – predictive analytics covers the entire capture, predict and act continuum – from the use of survey research software to capture customer, employee, patient or constituent feedback (attitudinal data), to creating models to predict behaviors, and then acting on the results to improve business processes.  Predictive analytics, unlike BI, answers the question: “What will the customer do next?”

Predictive analytics technology also enhances and extends the value of traditional BI platforms, which is why the leading BI organizations choose to partner with SPSS, including SAP BusinessObjects, IBM Cognos and Microstrategy.

DI: SPSS is used in more than 100 countries, all 50 U.S. state governments and the largest U.S. newspapers.  Tell us about your customers, who are some key clients?

KH: Whether its insurance companies identifying fraud and minimizing risk (MetLife), retailers improving marketing effectiveness to attract and retain customers (Advance Auto), universities ensuring proper enrollment and retention (Indiana University), health organizations finding cures for diseases and improving treatments (CDC), manufacturers predicting equipment failures (Sikorsky Aircraft), telcos reducing churn (Cablecom), police departments fighting crime (Richmond PD), or even people making love connections with eHarmony, SPSS predictive analytics technology is used by customers in every industry around the world.

DI:  PASW is the new name for the complete portfolio of SPSS predictive analytics products.  What was the reason behind this rebranding and how will it help your business?

KH:  PASW unifies the product families — data collection, statistics, modeling and deployment — under consistent and descriptive nomenclatures to reflect the broad functionality and seamless integration among all SPSS products.  Everything SPSS Inc. does is predictive analytics, from our first to market deployment methodology – pr3 – to our training, to the technology we provide.   Predictive analytics encapsulates advanced mathematical and statistical expertise to extract predictive knowledge that when deployed into existing processes makes them adaptive to improve outcomes.

DI: Can you elaborate on your Predictive Analytics Suite, and what tools are incorporated in it?

KH: The portfolio of SPSS PASW allows organizations to better understand and predict future customer behavior by analyzing, modeling and scoring demographic and transactional data from operational systems, and attitudinal data gathered through customer interaction and surveys.  SPSS predictive analytics unlocks the value of existing data to identify which customers to target, how to reach them, when to make contact, and the most appropriate action to take.  The SPSS product families include: 

  • Data collection – feedback management and survey research software helps researchers and organizations proactively incorporate data about people’s attitudes and preferences into their analytical decision making. 
  • Statistics – the world’s leading statistical software suite used by commercial, government and academic organizations to solve business and research problems.
  • Modeling – data mining workbench helps organizations (commercial and government) model future behavior, making predictions about how people will behave using leading data mining techniques.
  • Deployment – provides a foundation to share, publish and integrate analytical results into operations to improve business processes and efficiently deliver results to decision makers across the enterprise.

DI:  Tell us about your deployment methodology - pr3 - and how it meets the three aspects of convergence.

KH: Predictive analytics is tremendously powerful and creates value when applied within an organization.  However, when integrated into business processes and supported by IT architecture, it penetrates the organization much more deeply and creates exponentially greater value and ROI.  To achieve this, SPSS created the pr3 deployment methodology, an incremental, phased approach to deploying predictive analytics across any organization by aligning analytics, business process and a customer’s IT infrastructure.

A convergent organization, what we call the Predictive Enterprise, has deployed predictive analytics across several departments, established a shared platform or service-oriented architecture (SOA) to promote consistent and standardized use of the analytic tools - and deployed analytic frameworks and decision models within various business activities.  This includes marketing campaigns, cross/upsell techniques or a claims process in an insurance company to identify fraud.

 DI: Tell us about SPSS’s four focuses on: the conversation, the transformation, the value and the method.

KH:  Success today is defined by customer knowledge and that occurs by not only listening to what a customer is saying, but by responding strategically.

SPSS helps organizations incorporate the full, complete view of their customers into daily business activities by dynamically capturing every interaction, and continuously enhancing and expanding the wealth of people data to create richer customer profiles.  The more information organizations know about their most and least profitable customers, the more intimate and valuable customer relationships become.

By transforming an organization through the use of predictive analytics, SPSS ensures that the right decisions are made and the best actions are taken on a consistent, repeatable basis.  These are customers that embark on the journey to become a predictive enterprise by embedding analytics into key business processes and drive core business decisions based this actionable data.

And by helping organizations see the convergence of analytics, IT architecture and business process, they are on their way to having unparalleled customer intimacy, resulting in profitable revenue growth.

DI: What is the process if someone wants to evaluate your solutions?

KH: Most of our customers use SPSS predictive analytics to solve the following business problems: attracting new customers, retaining the most profitable customers, growing current customers, reducing fraudulent activity or mitigating risk.
     
Through our pr3 deployment methodology, we take a consultative approach in matching our customers' business goals and objectives to our analytic capabilities — and then define an incremental, phased approach for deploying analytics across the enterprise.

We also encourage any prospective customers to read any of our customer case studies or press articles, or talk to industry analysts who continuously rank SPSS and its products at the top of their short-lists for ROI, functionality and performance, including Gartner and Nucleus Research.  Customers should also go to our website to see our products in action, and schedule time to see a demo.

DI: What can we expect to see from SPSS in the coming months?

KH: SPSS will continue to soar to new innovative heights and lead the predictive analytics market with new products, enhanced performance, and robust deployment capabilities, while delivering the highest levels of customer satisfaction. 

We will continue to extend and automate the power of predictive analytics to the business user, while significantly enhancing the productivity, flexibility and performance of the expert analyst.  And we will help customers leverage the exponential growth of unstructured data – in the form of email, call center notes, blog postings – and take advantage of social network analysis to uncover hidden patterns, relationships and various trends.

SPSS will continue to support the democratization of data – both structured and unstructured – while welcoming open source users into its analytics framework.  SPSS also believes in the benefits of a cloud computing environment, which is why all of our applications are designed with service-oriented architecture components.  We are currently analyzing business and technical issues related to SPSS technologies in the cloud, such as the scoring and delivery of analytics.  




Kris Hackney is responsible for the SPSS solutions business, focused on selling and delivering predictive analytic solutions to worldwide strategic accounts.  She also leads Global Services, consisting of consulting, training, and software as a service.  In 2006, Kris successfully launched SPSS Global Solutions Engineering, focused on the design, delivery and support of high-value business solutions.  This formed the underpinnings for today’s solutions strategy.  Prior to joining Global Services in 2005, Kris led multiple engineering teams as VP, Research & Development.   

Kris joined ShowCase Corporation in 1997 and became Vice President, R&D at SPSS when SPSS acquired ShowCase in 2001.  She holds a B.A. from Hamline University in St. Paul, Minnesota.

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