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SDNC13 -Day1- The Danger of Big Data by Kerry Bodine

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The Danger of Big Data by Kerry Bodine - Forrester research …

The Danger of Big Data by Kerry Bodine - Forrester research

Service design teams can glean big data insights from social media, financial systems, emails, surveys, call centers, and digital and analog sensors. But companies that fixate on amassing new data sources put themselves at risk of neglecting small data insights gathered through qualitative research methods. How can firms achieve balance?

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  • So theyasked some of their customers to create online diaries. Where they asked them questions about Virgin’s brand values:
  • Just looking at Twitter alone, you can see customers’ frustration with companies in every industry and across a range of touchpoints.Why? Why is creating great customer experiences so dang hard for companies?
  • Sources:http://cutesoft.net/data/live-support-client-window.gifhttp://www6.pcmag.com/media/images/301505-apple-iphone-5-at-t.jpghttp://fitbit.com
  • These things should be working together in a coherent way.
  • This is from the Matt Anderson, the Former COO.“We weren’t interested in being up to par with industry standards. We wanted to create a differentiated customer experience: one that was uniquely Virgin.”To do that, they had to take an Outside In view, and EXAMINE what the Virgin brand meant from the customer perspective.
  • Source: Kentico
  • Transcript

    • 1. The Danger Of Big Data Kerry Bodine, Vice President & Principal Analyst @kerrybodine November 19, 2013
    • 2. Anthropologists! Anthropologists!
    • 3. This is little data. Low volume (relatively) Human brains can process © 2013 Forrester Research, Inc. Reproduction Prohibited 6
    • 4. Individuals And Companies Deal With Four Types Of Content In The Digital Self © 2013 Forrester Research, Inc. Reproduction Prohibited
    • 5. © 2013 Forrester Research, Inc. Reproduction Prohibited
    • 6. © 2013 Forrester Research, Inc. Reproduction Prohibited
    • 7. © 2013 Forrester Research, Inc. Reproduction Prohibited
    • 8. © 2013 Forrester Research, Inc. Reproduction Prohibited
    • 9. © 2013 Forrester Research, Inc. Reproduction Prohibited
    • 10. This is big data. High volume Requires technology to process © 2013 Forrester Research, Inc. Reproduction Prohibited 15
    • 11. A credit card company retains customers by understanding social relationships. Studies have found that if one person defects from a product or service, other customers with social connections to that person may also. To capitalize on this study, a financial services firm is mining point-of-sale transactions at a massive scale to identify these social relationships based on card usage patterns to conduct targeted retention campaigns. As a result, it is increasing revenue and profit.
    • 12. A credit card company retains customers by understanding social relationships. Studies have found that if one person defects from a product or service, other customers with social connections to that person may also. To capitalize on this study, a financial services firm is mining point-of-sale transactions at a massive scale to identify these social relationships based on card usage patterns to conduct targeted retention campaigns. As a result, it is increasing revenue and profit. A public utility improves efficiency and saves natural resources. The Tennessee Valley Authority implemented a system to analyze 1.5 trillion smart grid data points. As a result, it now performs sophisticated analysis on power grid anomalies that improves efficiency and ultimately saves natural resources.
    • 13. A credit card company retains customers by understanding social relationships. Studies have found that if one person defects from a product or service, other customers with social connections to that person may also. To capitalize on this study, a financial services firm is mining point-of-sale transactions at a massive scale to identify these social relationships based on card usage patterns to conduct targeted retention campaigns. As a result, it is increasing revenue and profit. A public utility improves efficiency and saves natural resources. The Tennessee Valley Authority implemented a system to analyze 1.5 trillion smart grid data points. As a result, it now performs sophisticated analysis on power grid anomalies that improves efficiency and ultimately saves natural resources. A hospital saves babies’ lives using massive streams of monitoring data. The University of Ontario is sponsoring research to collect nearly 100 million data points per day from premature babies and analyze them in real time. As a result, changes in patient vitals are correlated with the probability of sickness, allowing early action. Ultimately lives are saved that would otherwise have been lost.
    • 14. So where’s the danger? © 2013 Forrester Research, Inc. Reproduction Prohibited 19
    • 15. 1. We’ll get completely overwhelmed. © 2013 Forrester Research, Inc. Reproduction Prohibited 20
    • 16. Big Data Poses A New Set Of Information Management Challenges For Organizations 21
    • 17. One major energy company reported using fewer than 5% of the potential 25,000 data points per second available from an operating oil rig.
    • 18. 2. We will miss out on the why. © 2013 Forrester Research, Inc. Reproduction Prohibited 23
    • 19. Big data Little data Validate statistical significance of insights Identify customers’ needs / desires / problems Identify specific issues / behaviors Understand why issues / behaviors exist and what types of solutions are appropriate
    • 20. “We want customers to get the first bill and love us. If they don’t have a strong positive opinion of us after three or four months, we haven’t sufficiently engaged with them.” Adam Elliott Head of customer insights E.ON Energy
    • 21. Week 1 2 3 4 5 6
    • 22. Week 1 2 3 4 5 6
    • 23. 3. We’ll come to the wrong conclusions. © 2013 Forrester Research, Inc. Reproduction Prohibited 29
    • 24. Source: Kentico 30
    • 25. Source: ClickSoftware 31
    • 26. 4. We’ll waste a whole lot of money. © 2013 Forrester Research, Inc. Reproduction Prohibited 32
    • 27. Four Characteristics Make Extreme Scale Difficult: The volume exceeds what can be cost-effectively stored. The velocity of change prohibits timely decisions. The variety of formats makes integration expensive. The variability of data structures produces results that are hard to interpret.
    • 28. A call to action © 2013 Forrester Research, Inc. Reproduction Prohibited 34
    • 29. A (few) calls to action © 2013 Forrester Research, Inc. Reproduction Prohibited 35
    • 30. As a design community, we need to: Become fluent in the language of big data. Educate others on how big data and little data inform design. Find more effective ways to visualize big data and little data. © 2013 Forrester Research, Inc. Reproduction Prohibited 36
    • 31. As a design community, we need to: Become fluent in the language of big data. Educate others on how big data and little data inform design. Find more effective ways to visualize big data and little data. © 2013 Forrester Research, Inc. Reproduction Prohibited 40
    • 32. Thank you Kerry Bodine kbodine@forrester.com blogs.forrester.com/kerry_bodine @kerrybodine

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