Dianne Fodell Global University Programs IBM Corporation

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1 Tell Your Students to Major In Analytics!!! Dianne Fodell Global University Programs 2013

2 Analytics - Guaranteed Jobs! The United States alone faces a shortage of 140,000 to 190,000 people with analytical and managerial expertise and 1.5 million managers and analysts with the skills to understand and make decisions based on the study of big data (exhibit). New McKinsey Global Institute Report May mgi/publications/big_data/pdfs/ MGI_big_data_exec_summary.pdf Global University Programs

3 Why Analytics? Because We Have Data BIG Data!! 2.5 quintillion bytes of data are created each day 90% of the world data was created in last two years alone. Source: IBM Big Data Website Global University Programs

4 Where is All the Data Coming From? Global University Programs

5 Advanced Analytics Opportunity Analytics Business Need Data sources Examples Reactive Real Time Decision Making Sensors, Monitors, Crowd Sourcing Traffic Analysis Real time crime center Weather alerts Reflective Deep analysis to generate predictions and insights Historical records, logs, web posts, transaction logs, web and library text Insights into customer preferences New business opportunities Social trends Examples of Potential from Analytics According to McKinsey: $300 billion value to US Health care 250 billion Euros to Europe s public sector administration $600B annual consumer surplus from using personal location data 60% increase in retailer's operating margins Global University Programs

6 Trends in Analytics, Types of Analytics Stochastic Optimization Optimization How can we achieve the best outcome including the effects of variability? How can we achieve the best outcome? Prescriptive Degree of Complexity Competitive Advantage Predictive modeling Simulation Forecasting Alerts Query/drill down What will happen next if? What could happen? What if these trends continue? What actions are needed? What exactly is the problem? Predictive Ad hoc reporting How many, how often, where? Descriptive Standard Reporting What happened? Source: Davenport Competing on Analytics Global University Programs Based on: Competing on Analytics, Davenport and Harris, 2007

7 Analytics Skills Areas to Support IBM and Clients Understanding Analytics Types and Trends Database Design Data Collection & Mining (finding, cleansing, normalizing) Database systems (design, implementation, OLAP) Rules-based Data Integration and Reduction (using tools like InfoSphere Steams) Statistical analysis Stream computing and computing for multiple, parallel processing Predictive analytics (modeling and analytics) Prescriptive analytics (optimization, simulation) Descriptive analytics (scoring, dashboards, alerts) Analytics electives (marketing, text, web, risk, transportation, energy, etc.) Risks, Privacy, Security, Legal Implications Project management Inference and Decision Making Applying Analytics to Real World Challenges Global University Programs

8 Broad Range of Skills Categories Data experts to manipulate and integrate big data Domain strategy skills to develop the right questions, determine which data is important Mathematical and operations research to develop analytics algorithms Executive and management skills to know when and how to use data for making decisions Tool developers to mask the complexity of data and analytics to lower skill boundaries Visualization skills to interpret data and present in meaningful ways Global University Programs

9 Sample Analytics Programs Business Analytics, Predicative Analytics Information Architecture Deep Computing Analytics Business School Computer Science or IT Mgmt Engineering, Math or Computer Science Knowledge Discovery Decisions in Market Mgmt Customer Relationship Mgmt Analytic Tools for Business Data Mining & Analysis Business Intelligence Image Analysis & Visualization Precision Marketing Predictive Analytics Internet and Interactive Mktg Data Querying & Reporting Advanced Data Analytics Inventory Management Supply Chain Optimization Channel Performance Policy, Security, Privacy Information Structures Quantitative Methods Database Design Information Systems Analysis & Design IT Strategy & Management Data governance & Security IT Security Policies and Procedures Dating Mining for BI Design & Implement Data Warehouse Analysis & Information Mgmt Enterprise Architecture Enterprise Information Design Analytics and Info Mgmt Database Administration Analytic Tools & Techniques Data Querying & Reporting Data Cleaning Statistical Programming Data Mining Geospatial Data Analytics Data Visualization Multiple Linear Regression Logistics Regression Forecasting Linear Programming Advanced Modeling Statistical Methods for Process Improvement Data Privacy & Security Advanced Data & Text Mining Financial Analytics Risk Analytics h Global University Programs

10 IBM Resources for University Faculty q Academic Initiative Web Portal q Access to Software Portfolio q Examples of University Programs q Open Data Sources q Skills Categories q White Papers q Publications and Trend Reports q Case Studies and Real World Challenges q Cool Videos, Serious Games q Access to IBM Experts Global University Programs

11 Analytics Teaching/Learning Portal Academic Initiative Global University Programs

12 Richard Rodts 2013 IBM SPSS Analytics in Public Sector Information Management

13 Information Management Data is 2X every two years. This is the driving force behind 21 st century skill development. Volume of Digital Data 57% CAGR for enterprise data through 2010 Variety of Information 80% of new data is unstructured Velocity of Decision Making In 2001, there were 60 million transistors for every human on the planet... in 2010 there were 1 billion transistors per human In 2005 there were 1.3 billion RFID tags in circulation last year there were 33 billion RFID tags and growing more than 100% each year. Worldwide mobile telephone subscriptions reached 5 billion in An estimated 2 billion people will be on the Web by with over a trillion connected objects 13

14 Information Management Information is becoming more complex High-value, dynamic - source of competitive differentiation Social data - / chat transcripts - Call center notes - Web Click-streams - In person dialogues Attitudinal data - Opinions - Preferences - Needs & Desires Descriptive data - Attributes - Characteristics - Self-declared info - (Geo)demographics Traditional Behavioral data - Orders - Transactions - Payment history - Usage history Operational Systems

15 Information Management Driving force behind the 21 st Century Skill Sets Individuals who can use their ability to turn information especially information generated in real time into insight will drive the business world. 1 in 3 Leaders frequently make major decisions with incomplete information or information they don t trust. 1 in 2 Leaders don t have sufficient information from across their organizations to do their jobs. 3 in 5 Institutions don t share critical information with partners and constituents for mutual benefit Source: IBM Institute for Business Value study: Business Analytics and Optimization for the Intelligent Enterprise, April 2009.

16 Information Management The DNA of Predictive Analytics 16

17 Information Management Predictive Analytics empowers you to make this 2010 IBM Corporation

18 Information Management feel like this IBM Corporation

19 Business Analytics software What if you could predict illness and prescribe treatment earlier? What if you could predict where traffic congestion will occur? What if you could detect crime before it happened? 19 What if you could create a more productive work environment What if you could detect which tax returns were likely fraudulent? 2011 IBM Corporation

20 Business Analytics software The Smarter Campus What if you knew which prospective students to recruit? What if you could detect financial aid fraud? What if you could identify which students were at -risk of dropping out? What if you knew which alumni would donate and when? What if you could detect campus crime before it happened? IBM Corporation

21 Business Analytics software Hamilton County Dept. of Education K-12 Student Performance Challenge Determine why students were testing below state target levels Improve student performance, especially for the large number of atrisk students struggling with school Solution Utilized IBM SPSS predictive analytics to: Create predictive models that demonstrated how students were likely to score on future tests and their propensity for dropping out Results Achieved best No Child Left Behind results in its history Identified that strongest predictor of student attrition was age Reduced annual dropout rate by 25% Reduced dropout rates among older students by opening an adult high school Provided teachers with pay incentives if students scored higher than their predicted scores IBM SPSS predictive analytics has allowed our educators to put a face on every number, and the personalization of the data has resulted in the best NCLB results in our history! - Dr. Kirk Kelly, Director of Testing and Accountability 2011 IBM Corporation

22 Business Analytics software City of Memphis Police Department Predictive Policing Challenge Traditional policing practices unable to thwart rising rates of criminal activity while also facing shrinking budget Solution Implemented IBM Analytics to: Isolate trends and patterns in existing data Effectively place resources where they Results are needed before crime occurs 30% reduction in serious crime overall, including 36.8% reduction in crime in one targeted area 15% reduction in violent crime 4x increase in the share of cases solved in the MPD s Felony Assault Unit, from 16% to nearly 70% The IBM solution has allowed us to take a new look and gain a totally different perspective on our data that we ve always had - Jim Harvey, Deputy Chief of Administrative Services, MPD 2011 IBM Corporation

23 Business Analytics software APUS Higher Ed. Student Retention Challenge APUS sought to boost student retention and academic excellence by identifying the factors driving student behavior and predicting the likelihood of an individual student staying on course or dropping out. Results Can now predict with approximately 80% certainty whether a given student is going to drop out Developed effective intervention strategies to retain students by addressing the individual challenges to keeping them engaged Determined that a key variable for student retention was his or her social presence Before we started using IBM SPSS predictive analytics, we were just guessing from among hundreds of variables and trying to put them together by hand. - Phil Ice, Director of Course Design Solution Utilized IBM SPSS predictive analytics to: Identify variables crucial to student retention Provide administrators with online dashboards to identify at-risk students Build intervention strategies, including better course designs, to keep students on track for graduation 2011 IBM Corporation

24 Business Analytics software University of Ontario Proactive Patient Care Challenge Influx of data makes it challenging for medical professionals to identify onset of life threatening infections in infants. Results Data streams now include information from monitoring devices at over 1000 times per second Clinicians are able to detect medically significant events 24 hours before patients exhibit symptoms The challenge we face is that there s too much data. In the hectic environment of the neonatal intensive care unity, the ability to absorb and relfect upon everything presented is beyond human capacity, so the significance of trends is often lost.. - Dr. Andrew James Solution First of a kind streaming analytic platform that: Scours through thousands of data points in real time Flexible system that adapts to variety of monitoring needs Integrates clinician knowledge and experience with technology 2011 IBM Corporation

25 Information Management IBM SPSS Academic Programs New Deal Campus wide unlimited license featuring special bundles and license riders Analytic Certification in Education (ACE) a software certification program underwritten by IBM providing independent testing of student skills Statistics and Mining in Academic Research and Training (SMART) a partnership between IBM and universities that facilitates projects around commercial challenges Mining in Academic (MAP) a program which provides technology access to all students in the areas of data and text mining Turnkey Teaching library of resources (course materials, teaching notes, syllabi, exercises, pre-lab vignettes) to facilitate the teaching of statistics and data mining. Virtual Computer Lab allows academic institutions to utilize IBM SPSS software in a virtualized computing environment for broader access to students and faculty MAP ACE SMART

26 Information Management Real-World Experience Getting SMART! In the Classroom (examples) Yale University Intuit and Glaxo Smith Kline Enhancing Client Experience Brand Analysis Kansas State University Sigma Xi Member Retention DePaul University - MSK Resource Planning University of Connecticut Save the Children Resource Planning Northwestern University - Toyota Social Media & Corporate Reputation Management Michigan State University General Motors Brand Management Southern Methodist Andrews Distributing Product Mix 26 26

27 Information Management Degree Programs Advise Core Curriculum Development Assist in Gaining Corporate Sponsors Software Assets Faculty Enablement Student Practicum (SMART) Centers of Excellence Public Relations Support 27

28 Business Analytics software 2011 IBM Corporation