Understanding the Transformative Power of Big Data & Predictive Analytics

Understanding the Transformative Power of Big Data & Predictive Analytics Dallas Fort Worth Area IMA Meeting September 18, 2014

Today s topics Demystify the buzz of big data and analytics Discuss the relevance of data and analytics to the finance & accounting professional Explore value-creating use cases Discuss the DO s and DON Ts : final considerations for a data led strategy 5/13/2014 ValueScope, Inc. 1

Understanding the buzz around data and analytics The practice is not new, what s new is the combination of components: Proliferation of data from new sources Sensors and tags; social media; loyalty programs and credit cards Majority generated in last 2 years, doubling in size every 2 years Reduction in storage expense Development of advanced analytical techniques (time and cost) Data informed strategies are now a business necessity transcends public vs. private, small vs. large, B2B vs. B2C, regulated vs. deregulated 5/13/2014 ValueScope, Inc. 2

Understanding the jargon data small data big data unstructured data data exhaust Information that represents a source for ongoing discovery. Now classified based on size and other factors Datasets that can be manipulated with traditional database software tools Requires specialized infrastructure to store and analyze. Differs from small data in extent of volume, velocity and variety (structured vs. unstructured) Data that does not reside in a traditional column/row format. Growing faster than structured data Examples: text in documents and comments; audio files; videos Data created by online activities The value of data is not defined by being big or small it is defined by it s ability to inform business decisions 5/13/2014 ValueScope, Inc. 3

Overview of the types of analytics and their adoption Descriptive Predictive Prescriptive Purpose Summarizes what happened Forecasts what might happen in the future using a variety of modeling and statistical techniques Determines likely outcome & prescribes the optimal course of action; uses feedback to repredict/re-prescribe Example Profitability by client segment Identifying customers who are most likely to churn Identifying intervention models to improve clinical care Adoption Common, but often underutilized Growing Rare, burgeoning field 5/13/2014 ValueScope, Inc. 4

Practical uses of data and analytics in business Data and analytics are predominately used to do one or more of the following: Understand the customer (increase revenue) Optimize operations (reduce cost, reduce time, improve quality, etc.) Identify and address risk, fraud and/or security Create a new asset for internal benefit or for customers 5/13/2014 ValueScope, Inc. 5

Understanding the payoff of data and analytics distinctive business processes count among the last remaining points of differentiation. Analytical competitors wring every last drop of value from business processes and key decisions. Competing on Analytics: The New Science of Winning. Thomas Davenport & Jeanne Harris 2011 Big Data: The Management Revolution companies in the top third of their industry in the use of data-driven decision making were, on average, 5% more productive and 6% more profitable than their competitors. Harvard Business Review, October 2012 2013 2007 Big data: The next frontier for innovation, competition, and productivity McKinsey Global Institute, May 2011 2012 The analytically elite are 2X more likely to be in the top quartile of financial performance and 3X more likely to execute decisions as intended Bain & Company, September 2013 companies that put data at the center of the marketing and sales decisions improve their marketing return on investment by 15-20%. Big Data, Analytics and the Future of Marketing and Sales, Court, et. al., July 2013 5/13/2014 ValueScope, Inc. 6

Impact to the role Rising expectations for CFO and team Pure finance function vs. strategic partner (growth & improvement) Historical vs. forward looking Rising expectations for information Exploration of value of many data sources Higher level analyses Changing tools and practices SAP HANA: reducing the 10 day financial close http://www.saphana.com/docs/doc-1670 72M monthly users Stream 30B ads/month Measure location, ad revenue and gross margin by user Finance uses gross margin to inform sales resource deployment Predicting users, songs for 1-5 years for planning purposes Work done in Anaplan 5/13/2014 ValueScope, Inc. 8

Understanding why finance & accounting is so critical Originators/owners of primary data Understand the scope of data available Know veracity of data Understand stakeholders and agendas within the organization Often the source for descriptive analytics - comprehensive view of the business and key drivers Bring accuracy and clarity to data as well as the implications of analytics insights purveyor of truth Relentless focus on ROI 5/13/2014 ValueScope, Inc. 9

Scope of influence in data led strategy formation & execution STEPS 1&3 Lead role in descriptive analytics and data gathering and vetting 1. Descriptive analytics 2. Opportunity identification STEP 5 Owner of controls, reporting and tracking 5. Implementation 4. Analysis & interpretation 3. Data vetting & gathering Thought partner in identifying, prioritizing, and understanding implications STEPS 2 &4 5/13/2014 ValueScope, Inc. 10

Implications for professional service providers Need an awareness and understanding of the changing expectations for your client Be a source for ideas, best practice sharing and analytical support Explore internal data and information that can be used to create value Use data and analytics to transform your business model (case study available) 5/13/2014 ValueScope, Inc. 11

MARKETING: customer acquisition 5/13/2014 ValueScope, Inc. 13

OPERATIONS: eliminating waste, addressing outages, reducing peak load 5/13/2014 ValueScope, Inc. 14

INFORMATION & KNOWLEDGE: organize and connect 5/13/2014 ValueScope, Inc. 15

HUMAN CAPITAL: talent retention and aging workforce 5/13/2014 ValueScope, Inc. 16

CUSTOMER SERVICE: knowing customer s social influence 5/13/2014 ValueScope, Inc. 17

SUPPLY CHAIN: optimizing distribution channels 5/13/2014 ValueScope, Inc. 18

EQUIPMENT & DOWN TIME: identification and prevention 5/13/2014 ValueScope, Inc. 19

Data DO s and DON Ts Today, 70% of the work is in data collection and gathering. Plan with the end game in mind Be purposeful (intent vs. found data) Adoption and understanding begin by solving a small, discrete problem. From there, momentum and vision build Be real - there is no benefit in pursuing analytics for the sake of being or appearing analytical. Adoption requires cultural change and acceptance, and will impact operations as well as how decisions are made 5/13/2014 ValueScope, Inc. 21

Final thoughts Empowering better business decisions through the use of analytics is not a trend it s a wholesale change in management. Start now Companies that become skilled in using data to drive decisions will outpace their peers in market share and financial performance Becoming an analytical competitor is a journey, not a destination Techniques and tools will continue to develop over time Business dynamics change, new data will become available The finance & accounting professional will play a key lead role in the process, as well as a valuable thought partner in the interpretation and application 5/13/2014 ValueScope, Inc. 22

Contact information Cyndy Carr, Ph.D. cyndy@schmidtcarr.com LinkedIn: http://www.linkedin.com/in/cyndycarr/ 5/13/2014 ValueScope, Inc. 23