Slide #1: Title Slide It ’s my pleasure to join you today at SmarterBusiness her in Copenhagen. Our goal over the next 45 minutes is to illustrate some of the external forces driving big data, what we’re hearing from clients and the nearly unlimited potential of analytics to help business and technology leaders re-invent and transform every aspect of their organizations.
Slide #2: Smarter Planet and the Role of Analytics Four years ago, IBM started a new conversation about building a smarter planet – an initiative that reflects our efforts to instrument and interconnect the flow of data, information and devices between our physical and virtual worlds. When we first launched smarter planet, we knew advanced analytics would have a fundamental role to play, however, it has quickly become the silver thread woven throughout our portfolio.
Slide #3: Evolution of Analytics What we ’ve learned from these engagements is that analytics continues to evolve, continues to be applied in new ways to identify new patterns and unlock new insights in ways previously unimaginable. Amidst the chaos created by a hyper-connected society of empowered consumers, we are seeing a pattern of automation emerging. This pattern is driving the instrumentation of the physical world around us as organizations interconnect and aggregate information in massive data warehouses in order to apply analytics to gain greater insight. This pattern repeats across every industry, extending throughout both the virtual and physical worlds. If done correctly, the insight gained can enable an organization to completely re-invent their products, deliver new service capabilities and optimize their workforce and processes . . . all part of the relentless pursuit of innovation required to compete successfully in today ’s global marketplace. But to do so requires us to move from enterprise data to big data . . . business initiatives to business imperatives . . . and from advancing a single organization to transforming entire industries.
Slide #4: IBV-MIT DATA You see the data on this chart… from study conducted by our Institute of Business Value and MIT Sloan Management Review Number of enterprises using analytics to create a competitive advantage jumped almost 60 percent in just one year… Nearly 6 out of 10 organizations now differentiating through analytics. We found that the overall increase in advantage went almost exclusively to organizations who were already experienced users of analytics… so the early adopters are extending their leadership. Those organizations are more than twice as likely to substantially outperform their peers So we ’re seeing early bifurcation of the market – leaders and followers. Reinforced by a separate MIT Study that found analytics led to 5-6 percent productivity increases… which is big enough in most industries to separate the winners from the losers. That ’s all change that’s happening within enterprises…. Who hear is using analytics to give your enterprise a competitive advantage
Slide #5: Analytics Moving from Enterprise Data to Big Data The implications of this pattern are clear – a major transformation is underway. This transformation is fundamentally changing how organizations are structured, how daily operations are managed and where new investments are made to create value. It is being powered by the onset of big data, which in turn is being instrumented and analyzed by new computing systems with deep analytic capabilities. Analytics has grown beyond enterprise data to big, largely unstructured data from billions and billions of diverse sources: . . . there are 200 million tweets sent each day, or roughly 12 TB data. . . every second of high-definition video creates 2,000 times as many bytes as a single page of printed text. . . . . . all told, there are 1.8 trillion gigabytes of information available in today ’s digital world . . . a truly remarkable figure that continues to grow at an alarming rate. Yet, it is through the complexities caused by big data that we can start to recognize new patterns that we simply couldn ’t before: . . . insurance companies are identifying fraud patterns by combing different data sources in real time to analyze massive transactional databases . . . financial institutions that are trading based on trending social content . . . energy companies that are analyzing 350 billion meter readings each year to predict power consumption . . . With every new challenge created by big data comes an equal opportunity . . . for those who are truly prepared to leverage it . . . to significantly improve organizational decision making.
Slide #7 VESTAS ,NATIONWIDE and XO Communications Simple premise: In the 20th century, economic value was derived by scarcity of data … those that had data, could derive the insight and apply it first to create new value and wealth. In the 21st century, flip that equation. Economic value will be created by those who can deal with wildly abundant data … capture it, make sense of it, derive the keenest insight from what ’s available. What new possibility would my business have it could look at: 100M call data records; 10M meter reads; 5M cash register scan transactions; 20M ATM transactions… Every day. We collect it all. Now we can convert it... do real pattern recognition... get real insight… and convert that into better businesses Vestas Great Danish company.. world ’s largest maker of wind turbines… Vision to have wind take its place alongside oil and gas power… by generating and sustaining the greatest return on wind for its customers. To fulfill that vision, has to know.. with incredible precision… how much breeze to plan for over any bit of land… in order to know where to locate turbines. Now they do… and they ’ve cut time for wind forecasting from weeks to hours, and radically improved the time to develop new turbine farms. Nationwide One of the largest insurance and financial services companies in the world… Two strategic issues… customer retention and managing operating expense. Using analytics to gain new insight…and make those insights available at every point of contact between the company and the customer… Analytics predicting which customers would most value a conversation about policies with an agent. Development of new policies, renewal options and products… With the ability to offer them… to specific customers… at the right time… from a conversation with an agent…. to a call to a contact center. Increased retention rates up to 40 percent Saved more than $5M in operating expense over the first three years. Economic value extracted from massively available information… the majority of which… wasted until now. XO Communications One of the largest U.S. communications service providers…. needed ways to identify customers who are at the highest risk of “churn” before switching to another carrier. The goal was to take preventive actions, contacting high-risk customers before they decide to make a change. Adopted IBM SPSS Statistics and IBM SPSS Modeler software to predict customer behavior and proactively reach out to customers with a high potential to churn. Results ….. Reduced customer churn from by 35% within the first year Increased retention rates by 60 percent Improved billed revenue retention rate by 60% Achieved 376% ROI in 5 months Decreased the number of client service agents needed for the same level of customer contact
Slide #8 : FOUR INITIATIVES What we ’ve found working with our clients is that enterprises that are going to drive change around business analytics tend to start in one of the four areas. Customer Analytics In a moderate-growth market, with profit pools stagnating… the mandate for customer relationship management is about taking that share from competitors. Best way to do that... insight on behaviors, as well as understanding the return or impact of promotional spending, loyalty programs, And of course, make existing customers loyal customers. Operational Efficiency And across industries, the opportunities in: Predictive maintenance… preparing, not repairing Optimizing supply chains… and the claims process. Financial Operations and Processes To do more with less, all enterprises must understand their sources of profit, and sources of cost. Roll that insight into the planning processes Accelerate the time and integrity in the closing process. Regulatory, Risk and Fraud In the post-2008 era of increasing regulation and oversight… reporting analytics is the response to governmental controls in every industry, not just financial services. Including insight into traditional and emerging categories of risk… predicting and getting ahead of future regulation. As well as fraud detection. DK: Question – is this something you can recognise? How many of you have started with Customer Analytics? How many have started in Operational Efficiency? How many in Financial Operations and Processes and how many in regulatory, risk and fraud?
Slide #9: IBM Smarter Analytics – A Holistic Approach To capitalize on the transformative opportunities requires a different approach to analytics, one that is holistic in its ability to turn information into insight and insight into business outcomes. In the era of big data, organizational leaders will be distinguished by their ability to make all decisions – big and small, strategic and tactical – based on a complete view of the world around them. This is not a one-time- or one-size-fits-all exercise. Transformation doesn ’t happen in a vacuum. It’s a constant cycle of optimizing and refining your data sources, learning from the outcomes of previous actions, and applying that knowledge to transform how you achieve those outcomes in the future. At IBM we ’ve been at analytics for over 30 years. Through thousands of client engagements we have developed and share this approach to Smarter Analytics to help our clients realize the transformative business outcomes that can be achieved through analytics. We help our clients align their organizations around information. To start with the business questions they need to answer and then determine the kind of information they need to answer those questions and how to get it. We help our clients leverage the right analytic capabilities to anticipate, predict, and shape business outcomes. Capabilities that are tuned to the task – whether for optimizing a marketing campaign, closing their financial books faster and more accurately, or managing fraud in claim processing – and integrated across the organization for shared insights. We help our clients embed analytics into their business processes so that they can act with confidence at the point of impact to optimize outcomes. Each time the align-anticipate-act cycle is executed, an organization ’s systems and people learn from the outcomes of the decisions taken. The models get smarter and decisions more accurate each time through. And, organizations take this learning to transform how they do business – not just making incremental process improvements, but truly transforming the way they operate to drive breakthrough results.
Slide #10: Align your Organization around Information It starts with the ability to align your organization around information . . . what are the business challenges or questions you need to solve, and are you looking at every relevant data source . . . large or small, structured or unstructured . . . that could impact the outcome? Combined with our recent acquisition of Netezza, IBM has long been investing in solutions that help our clients deploy information and big data strategies that align with their underlying business strategy. This in turn creates a trusted information foundation that improves IT economics and optimizes analytic workload performance. This includes the integration and governance of information to ensure business confidence and the voracity of the underlying data. It also incorporates the instrumentation of lifecycle governance to ensure the right information is captured, activated and accessible while unnecessary data is promptly dispose. By leveraging the volume, velocity and variety of internal and external information allows clients to unlock new, deeper insights. We believe we are uniquely positioned to give clients an enterprise-class big data platform as part of a comprehensive information management foundation. Big Data Platform Data Warehousing and Management Information Integration and Governance Enterprise Content Management Defensible Disposal
Slide #11: Anticipate to See, Predict and Shape Business Once you ’ve aligned and captured the right data, do you have the right analytics capabilities to leverage that data to anticipate and predict possible business outcomes . . . whether that means optimizing a marketing campaign, managing risk and fraud, optimizing your workforce or improving operational dexterity? We believe IBM is uniquely positioned to deliver a set of analytics capabilities that are tuned to the task at hand and integrated by design to drive a complete view of the organization including partner, supplier and other stakeholder interactions……and interconnected to support shared insights. IBM is helping organizations deploy analytic capabilities that allow you to spot trends, opportunities, anomalies; make plans based on those insights; measure your performance to those plans. We have invested in and developed these capabilities over the last decade to help clients leverage all information, people and perspectives in enabling all decisions. Business Intelligence Performance Management Predictive and Advanced Analytics Risk Analytics Sentiment Analytics Big Data Analytics Content Analytics Web and Digital Analytics Online Benchmark Spend Analytics
Slide #12: Acting with Confidence at the Point of Impact When we think about the application of these capabilities, we are seeing a democratization of analytics and how it can truly empower every individual across an organization . . . in a way that aligns to and integrates with the overall analytics platform and underlying business strategy. Whether it is a call center rep who gets the right offer at the right time to make to a customer on the phone, a system managing automated claim processing, or a supply chain manager leveraging the latest predictive models on prices of raw materials. It ’s about analytics when you need them to take action. As part of our Smarter Analytics portfolio, we are investing in our development teams and new acquisitions to help clients weave intelligence into the very fabric of their organizations . . . to optimize decision making and outcomes . . . regardless of whether those decisions are tactical or strategic, automated or manual. To act with confidence at the moment of impact requires an organization to embrace information in all formats . . . social media, emails, live chats, data warehouses, videos, sensors and others . . . reflect all perspectives past, present and future . . . and consider all sources from subject matter experts to senior leaders to individual employees, constituencies and other stakeholders. Decision Management Advanced Case Management Digital Marketing Optimization Cross-channel Selling and Marketing Pricing, Promotion, and Assortment Optimization Marketing Performance Optimization Supply Chain Optimization Organization and Workforce Transformation
Slide #13 : TRANSFORM The reason we ’re so passionate about this opportunity… is summarized on this chart. Simple message. The is about transformation that unlocks new possibilities… things we couldn’t do just a couple of years ago… answers we couldn’t see… to question we couldn’t even ask. So if we step back, and think about this fairly remarkable point in time… Climbing out of the global downturn Entering a new normal set of economic conditions. In an environment of accelerating complexity and unpredictability. And yet… an emerging, and very encouraging sense… that the question on the minds of global business leaders isn ’t just… “what’s my hardest problem” but… “what’s my greatest possibility?” That’s a remarkable difference. Being able to seriously ask… “What are my prospects? What’s available to my enterprise now that wasn’t before?” Now, that’s easy to say… a good bit harder to do. This is about focusing on accelerating the time to value and delivering game-changing results that enable you to go beyond solving the problem to identifying and capturing new opportunities. Only IBM offers market-leading consulting services, world-class research and industry solutions that accelerate time to value and help you transform through analytics
Slide #14: Learn from Solutions that Get Smarter with Every Outcome In order to extract meaningful and actionable insight in a short period of time – such as we see in healthcare or financial services – organizations need to consider both data at rest and data in motion. What do we know empirically versus what are we seeing in real-time? The combinatorial effect of cross-referencing streaming data with referential data unlocks even greater insights. In order to process that high volume, high variety data requires a new style of analytics, one that enables the semantic understanding of information that is structured and unstructured, at rest and in motion. IBM Watson is a new system of technologies that allow it to learn from evidence and outcomes, and to get smarter with every interaction. It is able to navigate human language, dynamically generate possible hypothesis to complex questions, and apply analytics to weight and optimize responses. Learning systems, such as IBM Watson, represents a new class of industry specific analytic solutions that can leverages deep content analysis and evidence based reasoning to accelerate and improve decisions, reduce operational costs, and optimize outcomes. This is accomplished based on transformational technologies which leverage natural language, hypothesis generation, and evidence based learning. These technologies are combined and applied to massive parallel probabilistic processing techniques to fundamentally change the way businesses look at quickly solving problems. Over the last 12 months, we have put Watson to work with clients to help them move from search towards discovery, from possibilities to probabilities, and from simple outputs to intelligent outcomes. In healthcare . . . Seton Health, an integrated healthcare provider in North America . . . Watson is helping reduce readmission of congestive heart failure patients by modeling unstructured data to predict future patient trends and provide an integrated view of clinical and operational data. This will allow Seton to drive more informed decision making and optimize patient and operational outcomes. These early interventions play a critical role in reducing costs, mortality rates and improving patient quality of life. And in financial services . . . we are working with Citigroup to identify new opportunities for the deep content analysis and evidence based learning capabilities found in IBM Watson to help advance customer interactions, and improve and simplify the banking experience. This represents the first application of IBM Watson technologies in consumer banking. When considering systems that learn, situations that involve large volumes of information, unstructured data, and benefit from speed, accuracy and confidence of responses are ideally well suited.
Slide #17 : Deep Engagement Experience It takes a lot of capability to address the requirements of this market in a meaningful way. It ’s not just data warehousing, or business intelligence, or a dashboard. And you certainly don’t do it with a niche acquisition or an analytic engine that accesses a single data source. Our clients give us credit for an unmatched technical portfolio. Their question is… “How do I extract the business value of analytics… and apply it to my enterprise?” That’s why everything we’re going to talk about next is oriented to the strategic agendas of these C-Suite executives. That requires: Strategy consulting… People who understand supply chains like McKesson ’s… Or financial services… for clients like Seton… who we ’ll hear from on our panel… Experts in organizational design… or customer relationship management…. The expertise to drive business value from the technical implementation. So you ’ll see us much more closely integrating our Strategy and Change consulting with our analytics practice… Where we have the deep intellectual capital of 9000 consultants… Experience drawn from more than 20,000 analytics engagements over the last three years Complemented by thousands of Software, Research and Consulting skills across 8 global Analytic Solution Centers. And of course with the massive, and exclusive capability of IBM research.
Slide #18 : How to get started ? When organizations are looking for ways to get started or advance their analytics initiatives we suggest a simple five step approach. Focus on the biggest and highest value opportunities by identifying an area that is most important to your business. If you try to tackle everything at once, you ’re bound to get overwhelmed, as there’s always room for improvement. Focusing on your biggest opportunities will help you to narrow the scope. Start with questions, not with the data. Organizations today can easily get caught up in looking at what they can do with the information they have. This can immediately limit your thinking and your approach. Embed insights to drive actions and deliver value. Your analytics initiative will only be meaningful if you use the insights gained to deliver value. Analytics for the sake of analytics is clearly not enough. This is about embedding the very insights you gain into your actions across the organization. Keep existing capabilities while adding new ones. Don ’t think of the project or initiative as a starting point. You’re not replacing old capabilities with new ones. Instead we’re integrating new and expanded capabilities into the fold. Use an information agenda, or strategy, to align your information with your business objectives. It will allow you to refine the scope, evaluate your core capabilities and competencies and do it with an eye towards how the proposed initiatives will be able to extend across the business. It also allows you to stay focused on delivering business value very early in the lifecycle. However you choose to get started, the important thing is that you do. The gap is widening between those who use analytics and those who do not. Make sure you don ’t get left behind.
Slide #20 : Conclusion To close off this section, one additional point... and it's not trivial. We've talked about the mandate we see in our clients. They do not consider the embrace of analytics optional. It's foundational to competitive position. All industries. All size of enterprise. We've looked at examples of how that's playing out in industries, and the solutions we're delivering for industry impact... which means outcomes and time to value. Very real. And I hope we've conveyed that its takes a fairly sophisticated set of capabilities to address this market in a meaningful way... which is the intentional engineering of our business model, development model, and go to market model across IBM Software and Services... along with the massive -- and exclusive -- capability of IBM Research. We think this constitutes a credible approach to this market, and it ’s also why understand that the barriers to entry here are extreme. The point I'll end on is this: Last year as we marked our Centennial anniversary... one of the things that came clear... is that over that time there really have been just a few constants… and one of them is that at our core... is this enduring passion for discovery. We value thinking. We believe the core of our brand promise to our clients is access to experts and expertise. We enjoy grand challenges, and we have the will to stay with them. So from our inception… right through to today… the opportunity to unlock new value... to think in terms of complex systems… to apply this great technology portfolio and tens of thousands of people who cherish the search for the possibility... that's the DNA of our company and the deep intellectual capital of IBM. It's the kind of work we seek. And it ’s the essence of what we mean when we talk about a Smarter Planet. With that… I ’ld wish you all a very wonderful day ahead DK – where you will find that we have build a SmarterAnalytics track with sessions that show you how our business analytics customers have engaged in the analytics journey within the four areas that I mentioned earlier Customer Analytics, Operational Efficiency, Financial operations and processes and finally Regulatory, Risk and Fraud.
https://w3-03.sso.ibm.com/sales/support/apilite.wss?appname=crmd&mostrecentsort=yes&crv=no&additional=summary&alldocs=TRUE&infotype=CR&others=RFCS%20RFVI&title=SunTrust SunTrust Banks, Inc., with total assets of $172.6 billion on September 30, 2011, is one of the US ’s leading financial services holding companies. Through its subsidiary, SunTrust Bank, the company provides deposit, credit, trust and investment services to a broad range of retail, business and institutional clients. Other subsidiaries provide mortgage banking, insurance, brokerage, investment management, equipment leasing and capital markets services. SunTrust’s 1,658 retail branches and 2,889 ATMs are located primarily in Florida, Georgia, Maryland, North Carolina, South Carolina, Tennessee, Virginia, West Virginia and the District of Columbia. Challenge SunTrust wanted to more quickly and accurately assess the bank ’s expose in a number of key business areas. Corporate headquarter produced a limited number of high level reports for executive management. The regions and lines of business were largely self-reliant. From an enterprise perspective, people were spending 40% of the time looking for data and creating their own analysis. There was no centralized data management capability, and no governance function existed and data quality was a real concern. Solution Starting with Risk Analytics in 2006, SunTrust deployed a comprehensive risk management framework across their business servicing every region and line of business with customized risk information and analytics supported by a robust technology platform that assured the quality of the data. Starting in early 2010, SunTrust launched a corporate initiative to establish a companywide Business Intelligence and Analytics capability that has implemented a common operating model including governance, rules and guidelines. Analytics: Cognos, Unica, and Open Pages (target close June 2011) Data Mgmt InfoSphere Warehouse on Smart Analytics System 7700 ECM SW: FileNet, BPM, Content Mgr, ECM Database: InfoSphere Warehouse (DB2) Other IBM SW: WebSphere, Tivoli HW: Power-based, Smart Analytics System 7700, other System Power systems. GBS or GTS Svc: heavy GBS presence (GBS BAO: BI & PM, EIM, GBS CRM-BI), AMS Services, STG Lab Services Committed to IA: anchor client for Banking Framework Results SunTrust ’s investment in Risk Analytics paid off when it helped them navigate the financial crisis of 2008 to 2010. They were able analyze emerging problem areas such as capital markets, auto dealers, homebuilders, and residential mortgages and proactively deal with them including mitigating losses, shaping strategy and responding to requests from regulators using complete and reliable data. In the area of Operation Analytics across the business, SunTrust have introduced analytics for Channel Management, Fraud Analytics, Client Analytics and Consumer Loads. For example, SunTrust have programmed business rules and analytic models that intelligently monitor, route, and process loans so loan officers stay focused on their clients. The result is reduction in the average time required to complete a mortgage loan process by more than 30 percent. SunTrust realized significant efficiency gains by redeploying resources previously devoted to data gathering and report creation to more productive use. There implemented rigorous data quality management and clear reporting standards. Analysis that used to take SunTrust days to create now is available in seconds with a single Cognos query from one consolidated data mart.
Background Seton Healthcare is a not-for-profit organization, the Seton Family is the leading provider of healthcare services in Central Texas, serving an 11-county population of 1.8 million. Seton Healthcare identified an opportunity to significantly reduce the occurrence of high cost CHF readmissions by proactively identifying patients likely to be readmitted on an emergent basis. Objectives Seton will partner with IBM to implement content and predictive analytics to identify patients who should receive proactive medical case management and intervention. The expectation is that Seton can reduce the occurrence of costly readmissions, mortality rates and improve the quality of life for these patients. Project Description CHF prevention and reduced re-admission is a main focuses of Seton ’s Clinical Design Center. The key clinical, financial, and contextual data for CHF patients span many applications and are stored in both structured and unstructured content. To achieve the Design Center objectives, the following capabilities are needed: Integrate these data into longitudinal patient records Identify important information in the unstructured data Develop predictive models that show Likelihood of readmission Likelihood of ambulatory-sensitive ED visits and admissions Forecasted next year costs Display predictive model results along with aggregated patient record data in an visual, easily-navigable system
The adoption rate of disposition requests is somewhere below 9.1 percent at the moment. With the new system the current estimate is more than 90 percent because we have a legally defensible disposition schema. ” —Scott Bancroft, Group Head of Information Governance and Management and Chief Information Security Officer at Novartis AG Global companies face global headaches when it comes to complying with diverse country regulations for record keeping, privacy and compliance, and legal holds on data for litigation and regulatory inquiries. Not only do regulations differ from country to country—information and business needs for it vary widely from business unit to unit. Novartis implemented a holistic information governance program with a global retention program at its backbone to scale across 154 countries with 256 corporate entities. The program complements the company ’s rigorous eDiscovery process. Information growth outpaced governance and records processes Like other large companies, Novartis was experiencing tremendous information growth and already had enormous amounts of electronic and physical content, including paper and other physical materials such as lab samples. Novartis had an inefficient records and retention schedule originally designed for physical records that no longer applied to the company ’s business and information environment. The records management and schedule management processes were cumbersome and created challenges with audit findings. The inefficient use of resources across divisions and functions left employees unsure of their obligations. Inaccurate identification and declaration of records and unnecessary indefinite retention incurred excess risk and cost as information growth outpaced retention management and governance processes and capabilities. Novartis selected the IBM® Global Retention Policy and Schedule Management because it met all their requirements and it was easy to use and intuitive. When they tested it on their end user community, they found it easy to use and very convenient. The system ensures that records disposal complies with national laws, regulations and company policies. It is a corporate-wide, cross-function, “electronic rule-book” to manage the retention and disposition of information assets. Novartis ’ Global Master Retention Management System (GMRM) system enables individual teams and business groups to fulfill their legal and regulatory obligations and prevent over retaining (saving substantially on storage cost). It establishes a consistent ontology and records classification scheme globally and cross-divisionally while supporting the natural variations across business units and geographies. GMRM ensures a legally defensible retention and disposition scheme of information assets. The system is now enabling Novartis to mitigate major information management risks and establish harmonized, globally functional retention schedules for both electronic and physical records. It helps Novartis ensure stakeholders have sufficient knowledge of information location, use and value, and it enhances its ability to meet internal audit standards and respond to legal requests. Effective disposition of records is already significantly reducing risk.
http://www-01.ibm.com/software/success/cssdb.nsf/CS/SSAO-8DFLBX?OpenDocument&Site=software&cty=en_us Solution components: IBM Content Analytics IBM BigSheets IBM LanguageWare North Carolina State University Matches research assets to potential partners with analytics The need: Large research institutions like North Carolina State University (NC State) have thousands of research projects — intellectual property assets — that could be used to build a smarter planet. Licensing and commercialization of assets help the university recoup its costs and provide further funding for projects and departments. It is a time-consuming process to discover which assets have the most potential and then find the public or private partnership that can bring those assets to the commercial market. The sheer volume of information inevitably results in assets that are underutilized. The NC State Office of Technology Transfer needed a way to help its small staff of 19 people — s even of them licensing professionals — to comb through more than 3,000 research assets and then find the most promising partners that could bring them to market. The solution: IBM built an intelligence solution for the university that uses IBM BigSheets software to process large amounts of data; IBM LanguageWare software to analyze data from 1.4 million documents, websites and enterprise applications; and IBM Cognos Content Analytics software to create insight from the content. The solution uses advanced contextual searching, including customized dictionaries for particular areas of research, to create a highly efficient process for discovering the asset profile and then narrowing down the most appropriate potential partners based on structured and unstructured data from within the institution and the public Internet. In a pilot program, the university was able to find partnerships for two research assets that showed promise but would otherwise have been abandoned. The assets — a salmonella vaccine and a drug delivery system for domestic animals — were analyzed for keywords. Then searches were conducted that found 2,000 potential matches. Additional searches eventually led to a narrowing of potential partners to 10 to 15 prospects, a manageable number that allows office staff to maximize its efforts with a higher probability of finding a match. What makes it smarter: The solution goes beyond a traditional keyword search. It analyzes both the research assets and the partner pool by providing customized context. It allows the licensing staff to focus on brokering the best deals for the university without having to become experts in the subject matter for every asset. IBM software searches a massive volume of dynamic data that would be impossible to manually contextualize, reducing the time and effort required to find the best match. It allows the university to extend the solution and create connections with other research institutions, helping to further funding for projects and departments. Industry : Education
The explosion of information and the availability of information… is a boon if you can harness the analytic capabilities and bring the insights that are present in that information to improve the experience that customers have with you or to improve your operation to become more efficient. Several benefits – lower cost, cross selling and service/privacy benefits with MDM Predict customers who would most value an interaction with a client rep, thereby increasing agents ’ retention rates by up to 40% in some cases Estimated IT savings more than US$1.5M each year and greater than $5M over first 3 yrs. Gives insurer ability to capture, manage & analyze vast amounts of customer & transaction info, turn it into new policies, renewals or new product offers Analytics sw: Previously SAS, moving to Cognos and SPSS Data Mgmt SW: InfoSphere MDM, Information Server, Optim ECM SW: Some FileNet—moving remaining Content Mgr to FileNet Database: DB2 on z/OS and distributed (also has some Oracle and MS) Other IBM SW: Has all brands-- $99M 3-year ELA signed Sept 2010. Big SAP shop. HW: IBM & HP GBS or GTS Svc:: Significant GBS with BAO project underway focused on analytics strategy and displacing SAS with SPSS Enterprise- wide 360 degree view of customer information, for analysis and to make the same info available to any touch point with a customer. Single view using InfoSphere MDM, Information Server, DB2 on Z (some distributed), Optim, industry models IAA. NW is significant MDM customer, the backbone of their business strategy to know the customer and offer specialized products based on key customer data points. NW is expanding it use of analytics to accelerate the implementation of this strategy. For more than 80 years, Nationwide ’s products and services have helped millions of people protect what matters most to them--- their homes and cars, their businesses and their financial security as they prepare for and live in retirement. Nationwide is The 6th largest auto insurer in the United States The 6th largest homeowner insurer in the United States 118 on the Fortune 500 list The 11th largest variable annuities provider The No. 1 provider of defined contribution plans Solution Components: Nationwide is using a combination of InfoSphere MDM, Business Analytics (Cognos, SPSS, BAO services), and FileNet to help accelerate the implementation of their strategy to know their customer and offer better products and services targeted at their customer. What are you doing with I&A/BAO and why is it valuable to your co.? Nationwide ’s strategy is to deliver a differentiated and personalized customer experience at a competitive price. This customer centric strategy is highly dependent on our ability to Know our customers and understand their preferences Know their needs and how they like to do business with us, and Be a proactive advocate for our customers and always act on their behalf. The core of this strategy is a single customer file that helps us to know and understand our customers. The second component is the ability to capture and understand all customer contacts across all channels. This contact management capability is further enhanced by interactions that our customers have with other related entities. The third component is an advanced Business Analytics capability that allows us to use data from multiple sources to derive patterns and gather insights about what our customers need. This capability also allows us to identify and highlight breakpoints in the customer experience. Finally, the fourth component is our ability to derive and recommend the Next Best Action that we can take to help our customers have a differentiated and personalized experience with Nationwide. What are some of the specific business results you have realized? Over the past 18 months, we have released several Customer Marketing Actions (our term for Next Best Action) into all of our distribution and servicing channels. These CMAs have been focused on improving retention and increasing cross-sell within our customer base. These efforts include identifying the best time to conduct “Comprehensive On Your Side” reviews that help our agents deliver a differentiated customer experience to current policy holders, increasing the use of EFT to improve retention, making proactive calls when policy holders experience a premium change and many others. Where are you going next? Our analytics journey has focused on leveraging structured data from internal and external sources. The next steps include the use of unstructured data (text, voice, video, etc.) from internal sources (IVR, call recordings, etc.) and external sources (social media). We are also looking at leveraging techniques to speed up the delivery of insights and CMAs to distribution and servicing channels. We are also expanding out analytics capabilities into other domains including Operational Analytics and Financial Analytics.
Smarter Analytics giver dig indsigt i hele forretningen, Rich Holada, IBM US