SPSS Enterprise Platform for Predictive Analytics

Transcription

1 Butler Group Subscription Services TA000904BIN Business Intelligence SPSS Enterprise Platform for Predictive Analytics Written by: Michael Azoff Date: September 2005 Abstract SPSS has been active in the past year in capitalising on its expertise in predictive analytics by offering an integrated suite: the Enterprise Platform for Predictive Analytics (EPPA). The suite includes new business applications such as PredictiveMarketing, PredictiveCallCenter, and PredictiveClaims, which are based on data mining technology but are aimed at business users. The EPPA integrates all of SPSS data/text/web mining, predictive analytics, statistical, survey, and reporting capabilities into a single platform. An important differentiator for SPSS is that the EPPA can provide real-time guidance embedded in user applications, exploiting the knowledge gained in predictive analysis. Customers running call centres and other time-sensitive operations can benefit from instant recommendations on what action to take. The EPPA offers reporting capabilities, but can also complement existing BI investment, thus SPSS can be used side-by-side with established BI vendors that have advanced reporting and querying functionality for example. The EPPA will be found useful by BI users needing advanced analytical and predictive capabilities but without needing to be experts in data mining. Business users will find it easy to build analysis models in the EPPA and the visual workflow provides an effective means of working with sophisticated models. KEY FINDINGS Key: Product Strength Product Weakness Point of Information Best-in-class advanced analytics with visual data mining workflow. Pre-built analytics applications supporting decision-making in real-time environments. Integrated platform of well-established SPSS tools and applications. Aimed at business users, as well as specialists. Easily integrates into user applications for action based on predictive analysis. Available on Windows and Linux/UNIX platforms. Does not offer end-to-end BI, except for IBM AS/400 with another product (ShowCase). No dedicated data quality capability. LOOK AHEAD Each application or tool within the EPPA has its own release strategy, but the general pattern is for one major product release per year, with several minor releases or updates following throughout the year. Butler Group believes the integration offered by the EPPA is a positive step for SPSS and is being well received in the market. Analysis without compromise 1

2 Technology Audit FUNCTIONALITY The Business Intelligence (BI) market is roughly divided into sectors comprising vendors with particular historical core strengths and that have subsequently expanded out, whether through acquisition or organic growth. These sectors correspond to the main categories in BI: Data Quality and Extract Transform Load (ETL), Reporting & Query, Data Warehousing and OLAP, Analytics, and Performance Management. SPSS built its original market in providing statistical and predictive analysis tools, the Analytics segment of BI, and this continues to provide the main focus for the company. Building on this core strength, SPSS launched in 2004 its Enterprise Platform for Predictive Analytics (EPPA). A key benefit of the EPPA is that it provides an integrated platform for a number of well-established SPSS products, such as Clementine, as well as introducing new out-of-the-box applications targeting specific vertical markets. SPSS does have an end-to-end BI solution, ShowCase Suite, but this is targeted at the IBM AS/400 market (covered in a separate Butler Group Technology Audit). In the EPPA SPSS is not competing head on with other vendors offering end-to-end, integrated BI, rather the EPPA provides an integrated platform for the core strengths of SPSS, areas for which customers turn specifically to SPSS because of its leadership in these areas. Furthermore, for customers not needing advanced end-to-end BI, the general BI capabilities in the EPPA, such as reporting and querying, will be found to be sufficient to meet their needs. Product Analysis The EPPA addresses a growing problem in the enterprise, which is that knowledge has been built up through applying analytics to a vast repository of information that has accumulated over time, but while gaining this knowledge is an important step, there remains an inability to execute on this knowledge. The source of this problem may be the sheer quantity of knowledge itself, or the fact that introducing automation to make use of this knowledge is a non-trivial undertaking, and most organisations are not geared up to developing custom execution solutions without considerable effort. However, without implementing some form of action on the knowledge gained, all the effort so far spent is wasted. This is where the EPPA particularly shines: it has integrated tools that help carry through the final leg of the journey from raw data to action. Also, through closedloop analysis (i.e. monitoring how customers respond to recommended action) the EPPA can ensure that the strategy it offers is continually being refined. Thus the core philosophy of the EPPA follows a three-step process: Understand, Predict, and Act. The first step involves gathering data from operational processes and systems, including CRM data, customer service information, financial and risk statistics, and so on. This detailed information on customers, products, and events is stored in enterprise data repositories. The next step is the analysis of this data source, which involves a historical analysis, but crucially, also a predictive element. SPSS has a range of powerful predictive tools that can analyse data and offer business operations guidance on where a process is heading, or on the likelihood of certain events occurring, such as risk assessments of customer applications. The third and crucial step is the action taken based on the predictions by integrating the EPPA with business processes it is possible for recommendations to be made in real-time so that operational systems and operational staff can act on the knowledge gained. The real-time aspect is important, as there are many situations, for instance in a call centre, where decisions need to be made on the spot by agents as a customer is being handled live. Having the EPPA provide guidance on the screen in plain English in a matter of a few seconds, can make a big impact on operational performance. Thus, the kind of action the EPPA can produce covers business rules that are combined with predictions to steer decision-making on-the-fly, ensuring that the recommendations are efficiently delivered at the right point in time, to the right people or systems, in order to have an impact. The technology enables the bringing together of the past and present analysis with future projected outcomes, defines the desired outcome in the context of the stated business goals, and delivers the optimal decisions and related support information to the systems and people who can take appropriate action. The EPPA consists of a package of integrated tools: Advanced Analytics, Predictive Enterprise Services, and Decision Optimisation technology and services. Figure 1 shows the EPPA architecture: where data gathering, understanding, and prediction are integrated into channel and operational processes with the opportunity to act on the intelligence. 2 SPSS Enterprise Platform for Predictive Analytics Butler Direct Limited

3 Technology Audit Product Operation Figure 1: SPSS Enterprise Platform for Predictive Analytics Architecture SPSS provides comprehensive predictive analytics enterprise-wide with best-of-breed analytics (both advanced analytics and decision optimisation working in tandem), and is built on open technology compatible with J2EE and.net, that allows predictive analytics to be performed across disparate systems. The EPPA leverages CRM, service, risk, and operational processes and strongly focuses on enabling organisations to: Understand: provide insight into historic and current business performance. Predict: analyse past behaviour to predict future events and anticipate what will happen. Act: monitor operational processes and recommend what action will drive the best outcome. The ability to incorporate action into business operations also ensures that the Total Cost of Ownership (TCO) of the EPPA is recouped directly through business performance improvement. The EPPA offers the following: A 360 view of the customer, based not only on data from databases but also on interaction data directly from customer contact channels, as well as text, Web, and survey data. Hence the EPPA incorporates the four dimensions of the customer: descriptive data, behavioural data, attitudinal data, and interaction data. Comprehensive and advanced predictive analytics technology, not found in traditional BI. An integrated, enterprise-scalable platform. Real-time decision optimisation capabilities. Easy integration with existing operational systems. Open, standards-based architecture. Leveraging of investment in existing databases. Butler Direct Limited SPSS Enterprise Platform for Predictive Analytics 3

4 Technology Audit One of the key tools in the EPPA is Clementine, the enterprise data-mining workbench that is designed to be used by business analysts and end-users, as contrasted with tools that require specialist technical expertise in the field. Predictive models can be easily developed in Clementine, using visual interactive drag-and-drop techniques to build workflows made up of models linked by data streams. Clementine supports CRoss Industry Standard Process for Data Mining (CRISP-DM), a standard for implementing data mining as a business process. The tool s open architecture allows it to be integrated easily with existing IT investments and support data mining business processes. Two examples of extended data mining with Clementine are Text Mining and Web Mining. Text Mining is used, for example, to better target marketing campaigns, minimise customer defection or churn, reduce fraud, and improve security. As much as 80% of the average organisation s information is in unstructured, or textual form, as compared with structured tables and databases. That means that customer s, call centre notes, open-ended survey responses, Web forms, and other text sources that hold valuable company data, often remain unused. With Text Mining for Clementine it is possible to extract key concepts, sentiments, and relationships from unstructured data, and convert it to a structured form, suitable for predictive modelling. Text Mining uses LexiQuest, a linguistic extraction technology, to access and process virtually any type of unstructured data: it can analyse approximately one gigabyte of text (or 250,000 pages) per hour, with 90% or better accuracy, in all common document types, including plain text, HTML, XML, PDF, and Microsoft Office document formats, and is available for processing Dutch, English, French, German, Italian, Japanese, Arabic, Chinese, and Spanish text. Clementine s data-mining techniques, such as classification, clustering, and predictive modelling are applied to the extracted text for predictive analysis. So for example, as a call centre agent is making notes during conversations with customers, this information can be analysed in real-time. Alternatively, associations between people and events that may indicate potential security threats can be detected. Web Mining for Clementine overcomes the difficulties inherent in extracting data from the Web in a form suitable for data mining, thereby allowing business analysts to perform ad hoc predictive Web analysis within Clementine. The module transforms raw Web data into analysis-ready business events using the integrated Web mining source node powered by SPSS NetGenesis Web analytics technology. These business events are then available within predictive Web analysis applications for delivery of action based on the gained insight. Clementine can be integrated with custom applications or with SPSS pre-built applications, including: PredictiveMarketing, PredictiveCallCenter, PredictiveClaims, and PredictiveWebSite. The various component products that make up the EPPA are shown in Figure 2. The technology scales easily: it can be used for large data volumes, for channels requiring high performance such as the Web (scoring hundreds of thousands of customers per hour), and in complex IT environments. The full EPPA comprises the following analytic applications and tools: Reporting, Statistics, Data Mining, Web Mining, Text Mining, Predictive Enterprise Services, Campaign Optimisation, Interaction Optimisation, Realtime Scoring, Batch Scoring, Realtime Risk Assessment, and Feedback Management. Product Emphasis SPSS regards the EPPA as providing an edge over offerings from rival vendors in the way it can fulfil the last leg of intelligence delivery and overcome the execution gap : the action needed to exploit knowledge gained. The ease with which the EPPA can be integrated into customer applications means that recommendations can be made in real-time, with immediate Return On Investment (ROI) benefits such as reducing risk and customer churn rate, or identifying high-value customers and treating them in a way that is more likely to provide business. While the EPPA makes integration easy through accessible Application Programming Interfaces and open standards, there is as yet no support for Business Process Management standards. In Butler Group s opinion this type of integration is a natural area for SPSS to be involved in with the EPPA. Another key emphasis of the EPPA is the availability of out-of-the-box analytic applications. SPSS has always been differentiated from others in the BI market in providing these analytic solutions many customers find they turn to SPSS because creating such applications is too difficult in other BI tools. The pre-built analytical applications are now integrated into the EPPA, which Butler Group believes is a welcome development. 4 SPSS Enterprise Platform for Predictive Analytics Butler Direct Limited

5 Technology Audit Figure 2: SPSS Enterprise Platform for Predictive Analytics Application Areas DEPLOYMENT The resources to implement the EPPA can be found within the typical customer organisation, although third-party System Integrators (SIs) can be used if desired: SPSS works with the leading SIs in the market space. Implementations typically require involvement from the organisation s marketing intelligence, BI, or data analysis department for advanced analytics aspects. For the deployment part, business management, such as marketing and customer service would be involved, and the IT department would be brought in for the underlying technical infrastructure and integration support. SPSS will supply Technical Consultants and Project Management where needed. The average implementation time is between three and six months, though this naturally depends on the project scope and/or the characteristics of the company. The EPPA offering is available on any platform: all Windows, and UNIX/Linux variants. SPSS recommends the move towards the Predictive Enterprise to be taken in phases, so this involves following a modular implementation. Companies typically start with a well-defined and smaller scale project: for example, modelling customer behaviour to improve cross-sell marketing campaigns. In subsequent phases the usage is expanded with predictive analytics software for broader use in the organisation, such as exploring different channels like the call centre or the Internet, or different purposes, such as reducing fraud or risk. SPSS provides a full set of different classroom training offerings that are usually provided at SPSS offices, but can also be held on-site at the customer organisation when requested. This can include for instance technical training for the more advanced power user, business training for the users with less analytical / statistical skills, in-depth workshops, technical training for system management, and so on. The required training depends on the product and project. SPSS offers different packages of ongoing technical support e.g. Standard and Premium Technical Support. Butler Direct Limited SPSS Enterprise Platform for Predictive Analytics 5

6 Technology Audit Legacy integration is provided through the open architecture of the SPSS platform, the products can easily be deployed in any legacy environment. Business procedures should change in order for predictive analytics to become an automated part of operational business processes, and for the organisation to benefit fully from the solution. For instance, when deploying predictive analytics in real-time, such as in a call centre, the software will automatically generate recommendations for the call centre agent that will anticipate customer behaviour and steer the agent to the next best action to take. This does not mean that the user will lose control over his/her actions, but it will actually strongly assist him/her in taking the right decisions based on all available information and in the shortest possible time, thus speeding up decision processes considerably. That is the overall benefit of implementing an EPPA or predictive analytics solution across the enterprise: it improves business processes by making more decisions data-driven, and delivers recommended actions on-demand to the people and systems that can take effective action. PRODUCT STRATEGY The target market for the EPPA is both vertical and horizontal. The EPPA is used by any vertical organisation, for example, specific solutions are available for Finance, Insurance, Telco, Retail, Media, Leisure, Public Sector, and so on, and also by multiple horizontal organisations or business areas, such as CRM, customer service, product and market, finance and risk, and operations. Calculating expected ROI depends on the tool or application that is being implemented and the issue or business goal that is being addressed. Benefits are calculated in terms of cost savings and waste reduction, increased sales results or profits, achieved time savings, productivity increases, and so on. SPSS cites the following typical benefits that its customers have reported when using SPSS predictive analytics: 40% reduction of the mail volume leading to a 35% cost reduction on direct mail campaigns, plus a 29% increase in campaign profit. US$35 million saved by reducing credit card fraud. 30% cost reduction on acquisition campaigns, while maintaining the same conversion rates. 50% reduction of the mail volume, and 109% increased returns on campaigns, resulting in EUR 1.6 million additional revenue by better-targeted campaigns. US$30 million additional sales generated in the call centre in one year, turning a cost centre into a profit centre. Twice as much insurance fraud detected during claim handling. Completion time for marketing campaigns decreased by two to four weeks. The target market comprises mid- to large-sized organisations that have made significant investments in operational systems, particularly software for CRM, campaign management, finance and accounting, and ERP. Organisations store more and more data on their customers and processes, and hidden in this data there is a tremendous amount of valuable knowledge that could be used to improve the business. However, as discussed above, most organisations are not able to get the value out of this data due to the knowledge gap and execution gap. The EPPA is designed to address both gap problems. The EPPA products are sold by SPSS direct offices as well as its global network of franchises and distributors. Key businesses that support this product are for instance: IBM, Accenture, Microsoft, Oracle, and Hyperion. SPSS emphasis is focused on predictive analytics and it sees this as a key differentiator in the BI market. It can offer the full spectrum of best-of-breed capabilities in both advanced analytics and decision optimisation that are required by and across a Predictive Enterprise (even including the unique ability to combine/augment predictive analytics with data collection through survey research). These tools are based on open technology allowing for predictive analysis across disparate systems throughout an organisation. Pricing for licenses and implementation depends on the implementation. Annual Maintenance & Support is 20% of the licensing costs. 6 SPSS Enterprise Platform for Predictive Analytics Butler Direct Limited

7 Technology Audit COMPANY PROFILE SPSS (NASDAQ:SPSS) was originally founded in 1968, and has its worldwide headquarters in Chicago, Illinois, USA. It also has offices in other major cities across North America, and in over 40 other countries worldwide. Since its foundation, the company has consistently focused on providing new approaches to statistical and analytical technologies. SPSS introduced the first mainframe statistical package to appear on a PC, and was first again to release statistical products for the Microsoft Windows PC operating system. The advent of the Internet has opened up new opportunities and SPSS has developed BI and analytical solutions to provide information about traffic flows, clickstream analysis, and automated Web surveys. As SPSS acquired DataDistilleries in November 2003 (formerly a part of the Dutch National Research Centre for Mathematics and Computer Science), the company specialised in real-time predictive analytic applications for business users. In the past 12 months, SPSS launched new business applications such as PredictiveMarketing, PredictiveCallCenter, and PredictiveClaims, which are based on data-mining technology and aimed at business users. The company is publicly owned, and employs around 1200 staff worldwide, with 55% employed in the USA, 35% in Europe, and 10% in the Asia-Pacific region. The split between R&D, S&M, Support & Services, and Administration is approximately 27%, 31%, 27%, and 15% respectively. Revenue is split 44% North America, 34% Europe, and 22% rest of the world. Base company financials are shown in the table below: 2004 (US$ million) 2003 (US$ million) 2002 (US$ million) Revenue: Total Net Income/(Loss): (16.7) For the full year of 2005, the revenue guidance is between US$230 million and US$235 million. Overall, more than 250,000 commercial, academic, and public sector customers worldwide rely on SPSS technology, spread across its product range. These customers include: American Airlines, BT, Credit Suisse, First Boston, HSBC Bank, Proctor & Gamble, Sun Microsystems, and Verizon Wireless. Example customer deployments include: Insurance company RVS (part of ING Group) is using PredictiveClaims to reduce insurance fraud, improve the claims process and cut costs. SPSS PredictiveClaims solution allows us to better identify and investigate possible insurance fraud, which effectively results in a considerable contribution to RVS profits. French bank insurer Natexis Assurances (part of Groupe Banque Populaire) has implemented PredictiveMarketing to better target its lead generation campaigns. The company achieved a 50% reduction of the direct mail volume, and increased its returns on campaigns by 109%, which is EUR 1.6 million of additional revenue on a single campaign. Financial institute Spaarbeleg (part of AEGON) has generated US$30 million additional sales in its service call center in one year, using PredictiveCallCenter to deliver real-time recommendations to its call center agents during each customer interaction. Dutch insurer FBTO (part of Achmea) has implemented PredictiveMarketing to better target its customers for marketing campaigns. Using the software, the company has reduced mail volumes by 40% and direct mail costs by 35%, whilst increasing profits across its multiple marketing campaigns by 29%. SUMMARY SPSS has for many years stayed within its core expertise of advanced statistics and analysis tools, and apart from the ShowCase product for IBM AS/400 users, has not offered an integrated BI suite until the EPPA was launched in The EPPA however is not a comprehensive end-to-end BI offering, rather it has core competencies that it exploits to the full through integration on a common platform. While offering features available in BI suites, such as reporting, it can also be used to complement existing BI investments. Its key message is delivering predictive analysis to a far wider user community than achieved before, through tools that business users can work with, rather than just data-mining specialists. Butler Group believes that where advanced predictive analytics is required, SPSS EPPA should be considered. Butler Direct Limited SPSS Enterprise Platform for Predictive Analytics 7

8 Technology Audit Contact Details Worldwide Headquarters SPSS Inc 233 S. Wacker Drive 11 th Floor Chicago, IL USA Tel: +1 (312) Fax: +1 (312) UK Headquarters SPSS St. Andrews House West Street, Woking Surrey, GU21 1EB UK Tel: +44 (0) Fax: +44 (0) Headquarters: Australian Sales Office: End User Sales Office (USA): Europa House, Butler Direct Pty Ltd., Level 21, Butler Group, 184 Ferensway, Tower 2, Darling Park, 245 Fifth Avenue, 4th Floor, Hull, East Yorkshire, 201 Sussex Street, New York, NY 10016, HU1 3UT, UK Sydney NSW 2000, Australia USA Tel: +44 (0) Tel: + 61 (0) Tel: Fax: +44 (0) Fax: + 61 (0) Fax: Important Notice This report contains data and information up-to-date and correct to the best of our knowledge at the time of preparation. The data and information comes from a variety of sources outside our direct control, therefore Butler Direct Limited cannot give any guarantees relating to the content of this report. Ultimate responsibility for all interpretations of, and use of, data, information and commentary in this report remains with you. Butler Direct Limited will not be liable for any interpretations or decisions made by you. For more information on Butler Group s Subscription Services please contact one of the local offices above. 8 SPSS Enterprise Platform for Predictive Analytics Butler Direct Limited