© 2010 IBM Corporation Business Analytics software Business Analytics: Big challenges and solutions CS321 – Current Uses of Computers in Business and Industry

© 2010 IBM Corporation Business Analytics software ++ The world is getting smarter Intelligent Instrumented Interconnected 220 Billion pieces of user generated content exists on the web today and 200M tweets are sent daily In 2008 over 10B CPUs were produced, up from 1B in The average car has over 50 processors and the 5B mobile phones in use have at least 1 An estimated 2 billion people will be on the Web by and a trillion connected objects – cars, appliances, cameras, roadways, pipelines 3

© 2010 IBM Corporation Business Analytics software IBM has been involved with Business Analytics for a long time….. Electrical Tabulating and Accounting Machines analyze the facts of a business. They supply executives with details of sales, costs and operating data, permitting the formulation of policies and assisting in the proper control of business. These machines compile data quickly and with a great saving in clerical expense, furnishing reports which it would be impracticable to obtain by manual methods.

© 2010 IBM Corporation Business Analytics software The past, present and future of Business Analytics What is Business Analytics? Who uses Analytics software? What are the benefits? What are the big trends in Analytics?

© 2010 IBM Corporation Business Analytics software What is Business Analytics?

© 2010 IBM Corporation Business Analytics software Watch -

© 2010 IBM Corporation Business Analytics software Buzzwords from the video Predict those customers with most value Use data in a meaningful way Greater insights Fine-tune inventory Pervasive across the organisation What’s the optimal price Barriers to analytics are reduced Drive business decisions Run more efficiently

© 2010 IBM Corporation Business Analytics software Relevant Information Actionable Insights Smarter Decisions Better Outcomes

© 2010 IBM Corporation Business Analytics software The past, present and future of Business Analytics Who uses Analytics software?

© 2010 IBM Corporation Business Analytics software 11 How are we doing? IT SALES MARKETING CUSTOMER SERVICE HR OPERATIONS PRODUCT DEVELOPMENT FINANCE How are we doing? Why? What should we be doing? Actionable Insights to Answer Key Questions

© 2010 IBM Corporation Business Analytics software  Improve competitive positioning  Prioritize profitable product delivery  Drive greater demand  Maximizing pipeline effectiveness and customer profitability  Reduce customer churn  Increase satisfaction and loyalty  Improve production capacity  Reduce buffer inventory  Reduce portfolio gaps  Reduce development risk  Optmize staffing mix  Benchmark benefits  Align resource plans for intelligent growth and profit  Comply with confidence Business Analytics Across the Enterprise IBM Business Analytics

© 2010 IBM Corporation Business Analytics software A leading user of IBM Business Analytics

© 2010 IBM Corporation Business Analytics software The past, present and future of Business Analytics What are the benefits?

© 2010 IBM Corporation Business Analytics software The more you infuse analytics into your business, the higher your AQ and the better you and your business will perform = Analytics Quotient Realized Potential =

© 2010 IBM Corporation Business Analytics software 16 Manual, slow, error prone, cumbersome, fragmented Data quality concerns Automated, instant, accurate, seamless, converged Data governance is in place AQ maturity determined by:  Decision-making savvy  Readiness and capacity to leverage analytics across critical roles and processes  Mastery of information The AQ Journey

© 2010 IBM Corporation Business Analytics software Demonstration  Planning, Analysing and Forecasting with IBM Cognos software

© 2010 IBM Corporation Business Analytics software 18 You rely on spreadsheets with information gaps The rear view is your only view STEP 1: Novice Manual, slow, error prone, cumbersome, fragmented Data quality concerns Automated, instant, accurate, seamless, converged Data governance is in place The AQ Journey

© 2010 IBM Corporation Business Analytics software 19 You rely on spreadsheets with information gaps The rear view is your only view STEP 1: Novice You have a view into current results and a little of what’s driving them Results are shared with other teams within your department STEP 2: Builder Manual, slow, error prone, cumbersome, fragmented Data quality concerns Automated, instant, accurate, seamless, converged Data governance is in place The AQ Journey

© 2010 IBM Corporation Business Analytics software 20 You rely on spreadsheets with information gaps The rear view is your only view STEP 1: Novice You have a view into current results and a little of what’s driving them Results are shared with other teams within your department STEP 2: Builder Your VP sets the strategy Your department’s metrics map to other departments metrics You look forward as much as you review the past STEP 3: Leader Manual, slow, error prone, cumbersome, fragmented Data quality concerns Automated, instant, accurate, seamless, converged Data governance is in place The AQ Journey

© 2010 IBM Corporation Business Analytics software 21 You rely on spreadsheets with information gaps The rear view is your only view STEP 1: Novice You have a view into current results and a little of what’s driving them Results are shared with other teams within your department STEP 2: Builder STEP 4: Master Your VP sets the strategy Your department’s metrics map to other departments metrics You look forward as much as you review the past STEP 3: Leader Top-down goal setting Insights flow freely across divisions and departments. You allocate resources, minimize risk and maximize outcomes with equal ease and speed Manual, slow, error prone, cumbersome, fragmented Data quality concerns Automated, instant, accurate, seamless, converged Data governance is in place The AQ Journey

© 2010 IBM Corporation Business Analytics software The past, present and future of Business Analytics What are the big trends in Analytics?

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Businesses on a Smarter Planet are “dying of thirst in an ocean of data” 1 in 2 business leaders don’t have access to data they need 83% of CIOs cited BI and analytics as part of their visionary plan 5.4X more likely that top performers use business analytics 80% of the world’s data today is unstructured 90% of the world’s data was created in the last two years 20% is the amount of available data traditional systems leverages Source: GigaOM, Software Group, IBM Institute for Business Value" 26

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Business Analytics can be applied to all big data problems  Integrated  Enterprise-ready  Open Source Based  Real-time Scoring  Predictive Analytics  Sentiment Analysis  Real-time Monitoring Business Analytics 28 Big Data Platform

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Cloud  “Analytics as a Service”  Cloud deployment increasingly relevant  Cloud-optimized: multi-tenancy, resource sharing, scaling in/out and up/down, workload optimization, license/cost optimization, business and regulatory constraints  Public data streams more accessible – exchange rates, crime rates, economic statistics  New data/access models  Hadoop  Columnar  Many clients – computers, mobiles, tablets 31

32 Mobile Analytics  Author centrally  Secure, broad access to analytic content  Simplified user experience across devices  Schedule reports for immediate access  Wide device support (iPad, iPhone, BlackBerry, PlayBook, Android etc.)  Sensor Based Query (Location Aware, accelerometer etc) better decisions Analytics is about information for better decisions ‘anywhere’ Mobility is about access to information ‘anywhere’

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IBM Evolving the Analytics Experience Personal Analytics Enterprise Analytics Next Generation Analytics: Reasoning & Learning

36 Today Future A new class of systems that will be transformative to the enterprise Programming and Data transform to Learning and Intelligence 2 Competitors General Purpose System A Software with Function C General Purpose System B Software with Function C ++ Same Output 2 Competitors Learning System A Experiences from Company 2 Learning System B Experiences from Company 1 + Different Output; Differentiation Learning Systems Attributes The Learning Paradigm The Calculating Paradigm + Learn & Self-train (e.g. beyond programming) Interface Naturally & Accessibly with Humans and the World (including multi-modal real time sensory input and output) Provide Insights, Create and Test Hypothesis Enable Better Outcomes

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