Oracle Big Data Action Plan for Finance Professionals
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This is my keynote for the 2014 Institute of Management Accounting National Conference in Minneapolis
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Oracle Big Data Action Plan for Finance Professionals
- 1. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | Big Data Action Plan
- 2. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | Big Data Action Plan for Finance Professionals Rich Clayton Vice President Business Analytics Product Group
- 3. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. |
- 4. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | What’s the Big Deal with Big Data? US HEALTH CARE $300 B “In a big data world, a competitor that fails to sufficiently develop its capabilities will be left behind.” Increase industry value per year by McKinsey Global Institute US RETAIL 60+% Increase net margin by MANUFACTURING –50% Decrease development assembly costs by GLOBAL PERSONAL LOCATION DATA $100 B Increase service provider revenue by EUROPE PUBLIC SECTOR ADMIN €250 B Increase industry value per year by
- 5. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 90% Of the World’s Data 2 Years Has Been Created in the Last The World is Making a Digital Copy of Itself
- 6. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 22×2011-2016 12.5 Billion 2020 1.3 Billion Today Smart Device Growth Data Production Increase
- 7. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | Thoughts Things Processes Datafication of Everything
- 8. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | Use Data 12% Executives who feel they understand the impact data will have on their organizations Produce Data Big Problem with Big Data
- 9. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | MACHINES METHODS Implications of New Data METRICS
- 10. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. |
- 11. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | MYTH #1 Big Data is for Big Companies MYTH #2 Big Data is not for Finance MYTH #3 Big Data is an Unproven Technology
- 12. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | Small to Medium Businesses Are Taking Action Gathering Knowledge, 31% Developing Strategy, 27% Piloting, 31% Deployed, 11% 12 • Enhance customer experience • Improve process efficiency • Define new products/business models Source: Gartner, Big Data Primer for SMBs
- 13. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | MYTH #1 Big Data is for Big Companies MYTH #2 Big Data is not for Finance MYTH #3 Big Data is an Unproven Technology
- 14. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | “Big Data can offer accountants and finance professionals the possibility of reinvention, the chance to take a more strategic, ‘future-facing’ role in organizations.”
- 15. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | HR Professionals Looking to Big Data to Modernize Recruiting and Talent Management • Data discovery allows exploration of diverse data sets • Companies can improve relationship with workforce through an understanding of data patterns Big Data is the New Signal for Finance Not Just for Data Scientists….
- 16. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | Potential Benefits of Big Data for Finance 3.08 3.19 3.19 3.55 3.55 1 2 3 4 5 Identifying Accounting Irregularies Identifying Bad Credit Risks Determining Financing Amounts for Customers Measuring Risk Budgeting/Forecasting/Planning 16 Source: TATA Consultancy Services, “The Emerging Big Returns on Big Data,” 2013 Global Trend Study Moderate Benefits Very High BenefitsNo Benefits
- 17. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | MYTH #1 Big Data is for Big Companies MYTH #2 Big Data is not for Finance MYTH #3 Big Data is an Unproven Technology
- 18. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | By 2015, organizations that build a modern information management system will outperform their peers financially by 20 percent Mark Beyer, Gartner
- 19. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | Big data has already improved overall performance by 26% Big data will further improve overall performance by 41% by 2015 Impact of Big Data on Operational Performance 0% 5% 10% 15% 20% 25% 30% 35% 40% 45% Average CEO/President CFO/Treasuer CIO/CTO 2012 2015 Source: Economist Intelligence Unit, .”The Deciding Factor: Big Data and Decision Making“
- 20. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | Where is the greatest opportunity for Big Data in your company? (choose 3 answers) GO TO M.POLLEV.COM ON YOUR SMARTPHONE
- 22. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | Impact on Society
- 23. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | Finding Solutions to Breast Cancer Answering New Questions; Basis for Personalized Medicine “Researchers have been able to integrate clinical and genomic information on 140 breast cancer patients.
- 24. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | Preventing Brain Damage from Concussions
- 25. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | Changing the Fan Experience
- 26. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. |26 Nate Silver Source: nyt.com And Polling Processes….
- 27. 27
- 28. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. |
- 29. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | How well prepared is your organization to harness power of new data sources? GO TO M.POLLEV.COM ON YOUR SMARTPHONE
- 31. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | Big Data Action Plan for Finance and Accounting Professionals All TasksTask s Add Tasks High Priority Search More Data in Decisions New Analytic Methods Analytic Culture
- 32. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | Social Media / Sensors Unstructured data External sources 1 Consider More Data in Decisions 1
- 33. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 695,000 Status updates 510,040 Comments 2,000,000 Search Queries 204,166,667 Emails 571 New Websites Data Variety Creates Biggest Opportunity
- 34. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 88% of data is left on the cutting room floor Forrester Research
- 35. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | More Data into Decisions • New relationships • Behavior patterns • Predictive outcomes BIG DATA YOUR DATA ERP HCM CRM Sentiment data Images Web logs Documents Location data Sensor data
- 36. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | Untapped Insights from Unstructured Enterprise Data Example for Procurement and Spend 36 Parts Catalogues Customer Call Center Data Customer Geocodes Supply Chain Data Inventory Data Customer Surveys Warranty Data Supplier Costs
- 37. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | What are the top obstacles for putting more data indecisions? GO TO M.POLLEV.COM ON YOUR SMARTPHONE
- 39. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | Data Discovery Predictive Analytics Machine Learning 1 Develop New Analytic Methods 2
- 40. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | Amazing Volume of Data @ High Speeds 300 Sensors 3,000 Data points per second 1GB Raw data every sailing day Mast Strain Hull Stability Sail Tension Wind Speed Sail Strength Hull Pitch Amazing Volumes of Data in Real-Time
- 41. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | Finance’s Opportunity is to Make Big Data small THE FROM THE
- 42. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | BUSINESS INTELLIGENCE DATA DISCOVERY Data Discovery Provides Fast Insights to New Data Determine value of data to business Incorporate new data into enterprise model
- 43. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | • 20% increase in volumes, 30% increase in profit • Quickly explore across 50 diverse sources • Saved 1.5 years and $4M implementation costs • 2013 Gartner BI Excellence Award Maximize sales of seed and crop protection products Finding New Patterns in Agriculture
- 44. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | Driving Growth Through Predictions Anticipate Behavior and Forecast Business Adoption is Low 70%Predictive Analytics Is Critical 8% Use Predictive Extensively
- 45. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | Open Source Technology Lowers Costs R Statistical Programming Language Open source language and environment Used for statistical computing and graphics Strength in easily producing publication-quality plots Highly extensible with open source community R packages
- 46. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | • Potential loss: millions of dollars • 100 TB compressed data • 10 billion records/day • Data volumes double annually • Shortened turnaround by 4 hours Managing Risk in Real-Time Turkcell Preventing Fraud in Prepaid Calling cards
- 47. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | “The sophisticated analytics solutions that statisticians and scientists devise must be embedded into frontline tools so simple and engaging that employees will be eager to use them daily.” McKinsey 47
- 48. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | $132M Incremental Revenue in 2012 Increase in Conversions 30% Increase in Satisfaction 30% Big Data Farm Machine Learning Algorithms Machine Learning Case Study: Dell Offline Customer Data Social Media Website
- 49. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | Invest in analytic competencies Form a center of excellence Learn to tell visual stories with data 1 Extend Your Analytic Culture 3
- 50. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 50
- 51. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | Get Ahead in the War for Analytic Talent 1.5 million more data-savvy managers needed to take full advantage of big data in the United States In which of the following areas do you think your direct reports most need to improve your skills and capabilities? 21% 24% 24% 29% 33% Change Mgt. Technology Leadership Analytical Communications
- 52. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | Constellation of Data Science Programs Wide range of MBA, MS and Certificate programs available.
- 53. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | DATA CLUBHouse Rules The first rule of data club: You don’t admit to being in data club The second rule of data club: You don’t admit to being in data club The third rule of data club: no spreadsheets The final rule of data club: SELECT DISTINCT = Poor data knowledge
- 54. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | Capability GAP Analysis of our skills and capability Training focussed on the right areas Partnering with business and 3rd party consultant Organisation Working with existing headcount and no new hires Establish clear data ownership with the business Clear roles and responsibilities across the organisation Process Defining how we operate Testing with the business and refining to suit the culture Being agile and meeting the business needs Competency building
- 55. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | The accountants and finance professionals who succeed in the future will form a bridge between data science and data art, combining analytical skills and sophisticated models developed by statisticians with the skills of data art and ‘storytelling’.
- 56. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | Sexy Dashboards Must Have Clear Purpose 56
- 57. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | Telling Stories with Data turn it upside down learn to distill think infographic
- 60. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | All TasksTask s Add Tasks High Priority Search More Data in Decisions New Analytic Methods Analytic Culture Big Data Action Plan for Finance and Accounting Professionals
- 61. Oracle Confidential – Internal/Restricted/Highly Restricted 61 Count what is countable, measure what is measurable, and what is not measurable, make measurable.
Editor's Notes
- - Clarify confusion surrounding big data - Dispel a few myths that are emerging - Perspective on the impact on society - Share a few success stories - Provide you with an action plan on how to get started
- Depending on your background, you may think Big Data is purely more the same. Is it a technology? A strategy? A really big database? What is it? All depends on perspective, technology experience, etc. Our View = Business Trends.
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- TRENDS>BIG DATA Every day, we create 2.5 quintillion bytes of data This data comes from everywhere: sensors used to gather climate information, posts to social media sites, digital pictures and videos, purchase transaction records, and cell phone GPS signals to name a few. This data is big data.
- And this is just the BEGINNING Smart Devices are predicted to grow from 1.3B in 2013 to 12.5B in 2020 And data generated from “things” is growing at a rate of 22 TIMES OVER 5 YEARS, from 2011-2016 There’s lots of available data, representing huge new opportunities to create new value. So, WHAT’S THE PROBLEM?
- DATAFICATION of our thoughts and opinions. For example, in just one minute, Facebook users share over 500,000 pieces of content DATAFICATION of things through sensors collecting information from cars, medical devices, stop lights, and factory equipment. Consider this: A single jet engine can generate 20TB of data an hour. With more than 25,000 flights per day, Running on the treadmill at the gym? Chances are good you might be wearing a heart-rate monitor or a Nike Fuel Band to track your physical activity
- The problem is the world’s ability to produce data has outstripped most managers ability to use it. One of the largest airlines in the world, employing dozens of operational research analysts, throws away most of its fleet operational data at the end of the day because it’s so big there’s nowhere to put it and analyze it. The same is true for many businesses: the information they need to improve products and services already exists, they’re just not quite sure how to use it. Only 12% of executives feel they understand the impact data will have on their organizations over the next three years.
- New Machines that can be engineered for performance. That can address scaling needs of the enterprise. Provide superior price/performance advantage. New methods for analyzing new data. Model-oriented BI no longer is sufficient. We need new technologies that can help non-technical users discover patterns faster. Data Discovery technology designed for combining structured and unstructured data. Separating noise from signal. Allowing user to hypothesize and experiment. Creating value from data. New metrics. What does success look like? We know not all sources are predictive or valuable so what metrics do we need to measure success?
- Like the Discovery Channel’s Mythbusters, we’ll bust a few Big Data myths this morning.
- In higher education, small private colleges are using social media to boost enrollment and alumni engagement. In small restaurant businesses, they’re using big data to do micro-advertising.
- Sales and marketing get the biggest shares of the Big Data pie; Finance and logistics expect the highest ROI on Big Data. Learn more
- Ok, so how do you quantify the impact of integrating big data analysis into your day-to-day operations? Well, in this recent survey conducted by the Economist, they posed the question about Big Data to C-level executives - and they asked what benefit they have already seen and what do they expect to see. And you can see the numbers. There’s an average 26% improvement today with more growth to come. Again, it’s numbers like these that drive interest in big data, not just the new technology.
- Poll Title: Where is the greatest opportunity for Big Data in your company? (choose 3 answers) http://www.polleverywhere.com/multiple_choice_polls/NaoGBMoO0A8GxZ7
- Cancer is a complex disease involving many genes and we’ll never understand it if we get bogged down in the time consuming process of testing cause-and-effect relationships one at a time. Need to measure as many variables as possible in as many cases as we can collect without bias from preconceived ideas. Two modes of research working in tandem each enhancing the other. Greatest impediment to cancer research has been the sheer volume of data: billions of measurements and combinations of measurements on a diseasy-by-disease basis.
- New system called Shockbox that assesses playes after hits. University of Indiana found that it wasn’t a single hit but rather the reptitive hits that had the greatest impact.
- CHALLENGES/OPPORTUNITIES The Chicago Police Department (CPD) needed a better way to use crime incident data, case notes, suspect information, 311 data, etc to better help detectives with criminal investigations. Difficult today to do unscripted discovery to find: For these types of crimes show me who the suspects are For this suspect show me who is similar to this SOLUTION OIED for ad hoc discovery on incidents, suspects, cases, etc Still in early stages. Incident discovery is a huge project and will take time to get in production. There are massive amounts of data to combine from very diverse sources – this is part of a larger Big Data project that is still to be completed. A second, instant-app was built for tracking social media data during the NATO Summit in May 2012 and was used for that purpose. The application allowed the CPD to track twitter activity during the event and better understand patterns of what people are saying, where they’re gathering and then how best to assign/deploy resources around the city. This real-time analytics app was built over a weekend, the first iteration deployed on Monday and in production for the Summit by the Wednesday of that same week. Objective is to help detectives with criminal investigations Difficult to efficiently combine and use data from crime incidents, case notes, suspect information, 311 call transcripts, etc Short term objective: ability to better track social media data for a one-time event, NATO Summit in May 2012
- Poll Title: How well prepared is your organization to harness power of new data sources? http://www.polleverywhere.com/multiple_choice_polls/y39tiIJxMC0xvyS
- Call to Action – Key Steps to 21st Century Finance Get the Basics Right Consolidate ERP Instances to reduce IT costs Optimize process and operational controls Streamline the Financial Close and Reporting process Become More Strategic Incorporate Risk Management into Strategic Planning Integrate Strategic, Financial and Operational planning processes Gain better insights into costs and profitability by product, service, customers etc. Become a Catalyst for Change Consider Cloud-based deployments for new applications and upgrades Standardize Information Delivery and BI tools, go mobile! Leverage advanced analytics to harness big data and improve decision-making
- Call to Action – Key Steps to 21st Century Finance Get the Basics Right Consolidate ERP Instances to reduce IT costs Optimize process and operational controls Streamline the Financial Close and Reporting process Become More Strategic Incorporate Risk Management into Strategic Planning Integrate Strategic, Financial and Operational planning processes Gain better insights into costs and profitability by product, service, customers etc. Become a Catalyst for Change Consider Cloud-based deployments for new applications and upgrades Standardize Information Delivery and BI tools, go mobile! Leverage advanced analytics to harness big data and improve decision-making
- Recent Forrester Research study found that even without big data, firms are leaving most data on the cutting room floor. Why is that? We not asking the right questions?
- With all the excitement over new data, it’s easy to lose site of one important fact. The most business value comes from the combination of new data and the stuff you already have in your data warehouse today. That new data does help deliver new insight, but you need to look at it in conjunction with the valuable data you already have. Let’s take a quick example. Sentiment data may tell you if a particular individual likes or doesn’t like your company and product. But when you combine this information with other data, you can tell if they are a big spending customer, a regular customer, or not yet a customer. You can compare their spending patterns and income to see if they are spending as much with you as you might expect, or less than their income might suggest they could. You can see if they are a key influencer with others in your customer base, and so on. When you combine all this data and analyze it appropriately you can uncover hidden relationships that you would otherwise not be aware of. You can determine behavior patterns that people exhibit, sometimes quite unconsciously. And ultimately, and here’s the real payoff, you can use all this new information to predict what others might do in a similar situation and use this to advantage in many ways. Some of which you’ll see in later slides.
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- Poll Title: What are the top obstacles for putting more data in decisions? http://www.polleverywhere.com/multiple_choice_polls/kpMrWxLwFiWK52c
- Call to Action – Key Steps to 21st Century Finance Get the Basics Right Consolidate ERP Instances to reduce IT costs Optimize process and operational controls Streamline the Financial Close and Reporting process Become More Strategic Incorporate Risk Management into Strategic Planning Integrate Strategic, Financial and Operational planning processes Gain better insights into costs and profitability by product, service, customers etc. Become a Catalyst for Change Consider Cloud-based deployments for new applications and upgrades Standardize Information Delivery and BI tools, go mobile! Leverage advanced analytics to harness big data and improve decision-making
- The Oracle Team USA boats are loaded with about 300 sensors that gather data on things like strain on the mast, the effectiveness of sail adjustments, and the strength and stability of the hull. When the OTUSA is sailing, these sensors measure 300 variables 10 times per second. That’s about a gigabyte of raw data every sailing day per boat. 100 variables are sent continuously to the team’s chase boat during training. The entire data set from all 300 sensors is stored on the racing yacht and taken off the boat at the end of each day. This data gets used in both real-time and historical data analysis to improve the boat itself and help the sailors perform at the highest levels. For example, the performance team runs live analysis on the chase boat while the yacht is sailing to predict things like the weather for the next few seconds, minutes, and even hours. The team also combines sensor data with meteorological data about the Bay’s tides, winds and currents, to help them calculate the most efficient navigation route for the course.
- Distilling vast amounts of data into actionable insights is a core competency of finance professionals today.
- Finally to innovate to create new revenue opportunities, Executives are particularly keen to use data to anticipate where the business is headed and how to best position it for growth. Executives overwhelmingly consider predictions (70%) to be the most critical type of data insight, when it comes to supporting C-suite-level decisions, followed by insights into trends (43%) YET: organizations have low adoption and usage of the predictive modeling, optimization, and data-mining capabilities.
- Turkcell is the leading mobile provider in Turkey and a big Oracle customer. Their data warehouse is over a petabyte in size (advanced compression cuts that to 100 TB) and occupies 6 full racks of Exadata. Most customers in Turkey prefer prepaid calling plans. They use calling cards a lot, and those card act a lot like cash. They can be converted into other forms of money relatively easily. That means there is the potential for fraud from individuals all the way up to full scale money laundering. Most transactions aren’t fraudulent, but the potential costs (or potential savings) add up to millions of dollars annually. Like a lot of companies, they use analytics to look for fraudulent transactions. But it was taking a long time (not to mention a lot of skilled expertise) to move data into a separate analytics cluster and do the analysis. So they looked at using Oracle Advanced Analytics running in the database to do that work instead. No need to move the data, and the turnaround time was shortened by 4 hours. A determined person could commit a lot of fraud in 4 hours – time really is money here.
- ONE CLICK Dell is a great example of a company using predictive analytics to improve their customer experience with targeted cross-sell and upsell offers. Dell brings together data from its website, social media channels, as well as offline customer data into a big data farm. This big variety of data then drives predictive analytics for promotions at the website, in the call center, in email campaigns, and even on-demand print materials. CLICK Since deploying the system, Dell has realized $132M in incremental revenue for FY12 They have also seen a 10% increase in revenue, and a 20% increase in profit margin per call at their call centers This also is the power of Big Data At Work – predictive analytics driven by machine-learning algorithms chewing on masses of diverse and changing data. This new non-relational technology is now integral to Dell’s cross-channel customer experience. Here, change-the-business analytics have become the way Dell runs its business.
- Think about the conclusion and actions you want the data to affect. Test thesis and iterate Learn to distill data rapidly. Avoid infoxication – too much data has the same affect as too much alcohol Let the data speak for itself. Clean and simple.
- Call to Action – Key Steps to 21st Century Finance Get the Basics Right Consolidate ERP Instances to reduce IT costs Optimize process and operational controls Streamline the Financial Close and Reporting process Become More Strategic Incorporate Risk Management into Strategic Planning Integrate Strategic, Financial and Operational planning processes Gain better insights into costs and profitability by product, service, customers etc. Become a Catalyst for Change Consider Cloud-based deployments for new applications and upgrades Standardize Information Delivery and BI tools, go mobile! Leverage advanced analytics to harness big data and improve decision-making
- In the words of Galileo….