Published on September 26, 2014
From Big Data to Real-Time Business Value Greg Girard, Program Director World-Wide Omni-Channel Retail Analytics
BDA is Transformational, not Trendy § Data-driven society § New business models § A medium of exchange § Balance sheet asset © IDC Visit us at IDC.com and follow us on Twitter: @IDC 2
Where’s your big data? Sales Analysis $ 5,000,000,000 Total Revenue $14 $/Transac6on 357,142,857 Transac6ons 20 A<ributes/Transac6on 7,142,857,143 Transac6on A<ributes 3 Items/Transac6ons 10 A<ributes/Item 10,714,285,714 Item Transac6on A<ributes © IDC Retail Insights Visit us at IDC-ri.com 3 Marke.ng Decisions 4,000 Products 10 Promo6on Types 20 Channels/Touch Points 20 Customer Segments 16,000,000 Intersec6ons/Promo6on Event 100 Events/Year 1,600,000,000 Intersec6ons/Year
Reaching the top—never a sprint § Where are we? § What do we need? § Why climb higher? can we § How did they do it? © IDC Visit us at IDC.com and follow us on Twitter: @IDC 4
Big Data and Analytics Priorities of North American Retailers Q10. Which of the following areas have been identified as significant drivers of your organization's big data and analytics initiatives over the next 12 to 24 months? 0 20 40 60 80 Customer Acquisition and/or Retention Pricing Strategies and Programs Market and Competitive Intelligence Customer Service and Support Supply Chain Management and Logistics Product, Service, or Program Improvement and Information Technology Optimization and/or Process and Operations Optimization and Operational, Fraud, and Malicious Risk Regulatory Compliance, Financial Controls Human Capital Management Plant, Facilities, and Equipment Design, Other Basis: % of Retailers Who are Pursuing BDA Initiatives Non-Food Retail CPG manufacturer or retail grocer © IDC Visit us at IDC.com and follow N =us2 o0n0 T wSiotteur:r c@eID: CID C's 2013 BDA Survey, July 2013 5
Dissecting BDA Maturity: “5 by 5” Dimensions Levels Ad Hoc Opportunistic Repeatable Managed Optimized People Process Data Technology Intent Sub-‐dimensions ~90 © IDC Retail Insights Visit us at IDC-ri.com 6
Big Data and Analytics Maturity Levels Op.mized Managed Repeatable Opera.onalized and con.nuous and coordinated BDA process improvement value realiza.on Measured; project, process, and program performance measurement influences investment decisions and standards emerge Accepted, recurring projects, budgeted and funded program management, and documented strategy and processes with stakeholder buy-‐in Inten.onal, defined requirements and processes, unbudgeted funding, and project management and resource alloca.on inefficiency © IDC Visit us at IDC.com and follow us on Twitter: @IDC 7 Ad hoc Opportunis.c Experimental, siloed proof-‐of-‐concept or pilot projects, undefined processes, lack of resources, and individual effort
Some have it, some not so much Figure 1: Big Data and Analytics Maturity Distribution Across Stages: Retail Source: IDC, Business Strategy: IDC MaturityScape Benchmark — Big Data and Analytics in Retail in North America, #RI246594 © IDC Visit us at IDC.com and follow us on Twitter: @IDC 8
IDC Big Data and Analytics Dimensions of Capabilities Dimension Enablers © IDC Visit us at IDC.com and follow us on Twitter: @IDC 9 Intent • Level Strategy Set • Justification • Impact on Roles and Functions Data • Analytics • Data Quality • Integration Technology • Fit for Purpose • User Satisfaction with Tools • IT Responsiveness to Business Needs Process • Strategy and Planning • Information Mgmt and Apps Development • Data Analysis and Information Consumption • Measurement and Management • Governance People • Skills on Hand and Human Capital Mgmt Thereof • Collaboration, Communications, and Coordination • Location of BDA Tasks • Sponsorship
BDA Maturity Increases Success Rates n = 200 Source: IDC's Big Data and Analytics Maturity Benchmark Survey, 2013 © IDC Retail Insights Visit us at IDC-ri.com 10 Definitions • Highest achievers. Recent BDA projects met or exceeded expectations • Low achievers. Recent BDA project did not meet expectations or delivered no benefits 3rd 1st 5th 2nd 4th Skew right Skew left *Differential = (Repeatable + Managed + Optimized)Highest Achievers - (Repeatable + Managed + Optimized)Low Achievers Figure 3: Comparison of Big Data and Analytics Maturity Between High and Low Achievers Dashboard: Retail
New Metrics, Techniques, and Data Drive Higher Achievement Q. How has the type of data analysis performed in your organization changed in the past 12–24 months? Q. In aggregate, what type of benefits has your organization achieved from recent big data and analytics projects? Scenarios New Capability 1 2 3 4 5 6 7 8 New metrics or KPIs Y Y Y Y New analytic techniques Y Y Y Y New data Y Y Y Y None Y % High Achievers 26% 23% 21% 10% 15% 19% 15% 6% n = 700 Source: IDC's Big Data and Analytics Maturity Model Survey, July 2013 © IDC Retail Insights Visit us at IDC-ri.com 11
High Achievers Excel in All Five Dimensions of BDA Competence © IDC Visit us at IDC.com and follow us on Twitter: @IDC 12 Maturity Dimension Key Traits Differen.a.ng High Achievers Intent Fund and budget BDA program at the enterprise level. Data Ensure 6mely, trusted, and clean data. Data Integrate customer-‐interac6on data with other data types. Technology Balance development of structured repor6ng tools and advanced analy6cs (predic6ve analysis and data mining). Technology Enable mobile decision making and data consump6on. Process Address strategy and planning, governance, applica6on development, and data analysis and informa6on consump6on. People Recruit and develop skills for data and content collec6on, integra6on, prepara6on, and management in addi6on to skills for performing mul6dimensional analysis, predic6ve analy6cs, and data discovery. People Build culture of collabora6on, communica6on, and coordina6on across analy6cs groups and lines of business. People Recruit and development skills for administra6on and maintenance of big data and analy6cs–related IT hardware. People Engage execu6ve management in BDA efforts and extend BDA insights to customer-‐facing associates. Source: IDC Retail Insights, 2014
Essential Guidance § Intent • Align, align, align • Focus on Collaborative Governance and Closed-Loop Management • Set and Manage BDA Strategies at the Enterprise Level • Fund and Budget BDA Programs Annually with Flexibility § Data • Exploit Enterprise Data Assets • Introduce New Data Types and Analytic Methods § Technology • Ensure Users are Satisfied with the Tools of Their Trade • Complement BDA Technology with Mobility § People • Complement Skills and Expertise with Culture Collaboration • Embed BDA Insights into Decision-Making and Customer Interactions § Process • Start with Information Mgmt, App Dev, and Strategy and Planning • Finish with Information Consumption—The Last Mile of BDA Success © IDC Visit us at IDC.com and follow us on Twitter: @IDC 13
Contact Information Greg Girard, Program Director firstname.lastname@example.org @gregorydgirard www.idc-ri.com https://idc-insights-community.com/retail © IDC Retail Insights Visit us at IDC-ri.com 14
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