Proven Techniques for Exploiting Big Data Analytics Bill Schmarzo CTO, EIM&A EMC Consulting

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1 Proven Techniques for Exploiting Big Data Analytics Bill Schmarzo CTO, EIM&A EMC Consulting 1

2 5x 2

3 The Big Data Analytics Business Opportunity Through 2015, organizations integrating high value, diverse new information sources and types into a coherent information management infrastructure will outperform industry peers financially by more than 20% Gartner July

4 Companies are trying to exploit data and technology to answer key questions about their customers, products, and operations Suppliers Manufacturing Inventory Physical Assets Distribution Services Mass Marketing Customers Today s Business Model Who are my most valuable customers? What are my most important products? What are my most successful campaigns? Suppliers Manufacturing Inventory Physical Assets Distribution Services One-to-One Marketing Additional Profits Customers Big Data Analytics Business Model 4

5 But many of today s key business decisions are being made on intuition and gut! 33% of business leaders make critical decisions without the information they need 50% of business leaders don t have access to the information across their organization needed to do their jobs 75% of business leaders say more predictive information would drive better decisions Dilbert by Scott Adams IBM Institute for Business Value March

6 Big Data Analytics enables data monetization through more timely, more accurate, more complete, more granular, more frequent decisions Business decisions, and their related business questions, forms the heart of the Analytics Value Chain and supports the corporate mandate for data (analytics)-based decision making New Big Data Sources Advanced Analytics Business Questions Business Decisions SBI* (Value Decision -Cost Data ) ROI Heart of the Analytics Value Chain *Strategic Business Initiative 6

7 Think Different Apple Ad Campaign,

8 Big Data Analytics History Lesson: In the 1980 s, the CPG / Retail industry transition from bi-monthly audit data to scanner data changed the dynamics of the industry In late 1980 s, POS scanner data replaced bi-monthly audit data Data volumes jumped necessitating next generation of platforms and analytic tools Leading companies exploited new data and technologies for competitive advantage Competitive Advantage Demand-based Forecasting Supply Chain optimization Trade Promotion Effectiveness Market Basket Analysis Category Management and Merchandising Price Optimization and Merchandise Markdown Customer Loyalty Programs 8

9 New industry shift underway, and key to success is defining a process where organizations can continuously uncover and publish new insights about the business Analytics Lifecycle 1) Business 5) Business Consumes insights and measures effectiveness 4) IT Publishes new insights Defines mandate and requirements 5 1 Strategic Business Initiative ) IT Acquires and integrates data 3) Data Scientists Build and refine analytic models 17% of enterprises feel they have a strategic shortage of Data Scientists! a role that many did not even know existed 12 months ago 1 1 Source: Enterprise Strategy Group,

10 Take Purposeful Action on the Big Data Imperative Select a few high-potential areas in which to experiment with big data, and then rapidly scale successes McKinsey May

11 The key to exploiting Big Data Analytics is focusing on a compelling business opportunity! an organization s Strategic Business Initiative Focus on an organization s Strategic Business Initiatives in order to be relevant to the business Public statement of business intent Delivers compelling business value Cross-functional Championed by a senior executive Has measurable goals Has well-defined delivery timeframe Use visioning methodology to identify where and how Big Data Analytics can power an organization s Strategic Business Initiatives 11

12 An organization s strategic business initiatives set the company investment focus, and is the best place to leverage Big Data Analytics for business value!and relevance Strategic Priorities Be the Power Merchandiser of athletic footwear and apparel with clearly-defined Brand Banners Develop a compelling Apparel Assortment Make our stores and internet sites Exciting Places to shop and buy Aggressively pursue Growth Opportunities Increase the Productivity of all of our assets Build on our Industry Leading Retail Team 12

13 The Vision Workshop drives organizational alignment, and the Functional Decomposition Process identifies the supporting Big Data Analytics components 1 Vision Workshop: understand strategic business initiatives 3 Capture business questions & decisions 5 Identify big data analytics ramifications Prioritize Engage key business stakeholders Group into common business themes Design big data analytics solution 13

14 Prioritization Matrix identifies the right business opportunity upon which to focus given the trade-off between business value and feasibility of success Quantifies the business value of Big Data Analytics on key business initiatives Identifies potential impediments (technology, organizational) to successful implementation 14

15 Q&A 15

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