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Moving Big Data to Big Value


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It seems the world is all fascinated with amazing insight from Big Data... but we all know what really matters is the VALUE unlocked from those insights...

Too often we assume that smart people will know what to do if the Masters of Data Science unloads new wisdom on the business. The reality is we have to empower the ultimate people who have to act on these new insights with processes and business levers that also smarter.

In this presentation, we explore what is the difference between insight and value... the difference between a finding that is interesting, and a finding that has impact.

The presentation captures a career of learnings in Big Data and Advanced Analytics as the Lead Partner who established and led Deloitte's Advanced Analytics practice in WA

Published in: Data & Analytics

Moving Big Data to Big Value

  1. 1. Moving Big Data to Big Value Crossing the last mile May 2015 +61406313111 / @coertdup UWA – Institute of Advanced Studies Presented by Coert du Plessis, Advanced Analytics Lead Partner (WA) Deloitte
  2. 2. The average Big Data talk in 30 seconds … and the effort curve (x-axis)
  3. 3. Deloitte. © 2012 3 Source a lot of data from different places % of Effort
  4. 4. Deloitte. © 2012 4 Structure, clean, link and make the data smarter % of Effort
  5. 5. Deloitte. © 2012 5 Analyse and apply an impressive algorithm % of Effort
  6. 6. Deloitte. © 2012 6 And wozzaa – Amazing Insight! Visualised beautifully. % of Effort
  7. 7. Wow, that is interesting!
  8. 8. Really….
  9. 9. Really…. INTERESTING?????
  10. 10. Deloitte. © 2012 10 … the real effort curve to impact % of Effort
  11. 11. Deloitte. © 2012 11 There is a giant chasm between insight and value; the difference between interesting and impact.
  12. 12. Deloitte. © 2015 12 What is impact?
  13. 13. Deloitte. © 2012 13 My “Interesting” haunt – knowing who gets hurt next…
  14. 14. … and what happened next? Nothing….
  15. 15. Big Data Vocabulary Alignment a.k.a. the sucking eggs section
  16. 16. 5 “V”s of Big Data Its not just the size
  17. 17. 5 “V”s of Big Data Volume Its not just the size
  18. 18. 5 “V”s of Big Data Volume Variety Its not just the size
  19. 19. 5 “V”s of Big Data Volume Variety Velocity Its not just the size
  20. 20. 5 “V”s of Big Data Volume Variety Velocity Veracity Its not just the size
  21. 21. 5 “V”s of Big Data Volume Variety Velocity Veracity Value Its not just the size
  22. 22. Deloitte. © 2015 22 The three time horizons of data insight (near] Real Time [Stream] Real time data and insight collected fromprocessing equipment and machinery sensors during operation Historical [Pool] Historical data and insight gained fromanalysing trends, patterns and opportunities for improvement learned from experience Future [Make] Future insight derived fromhistorical analysis to improve planning, simulate and predict future outcomes Success is where all three horizons access the same structured, well-governeddata to inform decisions Shared Data Operate Analyse and ManagePredict and Plan
  23. 23. What stops insights? In other words, what prevents us making it 33% of the way?
  24. 24. Deloitte. © 2012 24 The common barriers to insight and wisdom… but ultimately a process exists to over-come each one Security Disparate systems Cost Volume of data Privacy & Confidentiality Analytic skills & experience Data quality Wisdom
  25. 25. The Hoodies & The Suites
  26. 26. What stops impact? In other words, what prevents us making the last 66% of the way?
  27. 27. Because somehow we expect smart people “will just know” what to do with the new, uncommon insights…. … yet, the new custodians of these insights are only armed with the same old processes and the usual “levers” they had before… stuck! …unless we also “inside-out” redesign the levers and processes to act and empower the new insight custodians.
  28. 28. How do you become and Insight Driven Organisation?
  29. 29. • What are the analysis options? • Which options should we select and why? How Many iterations? • What data and analytics tools and technologies are currently in-use? • What platforms can be shared or scaled? What can we rent aaS? • Who are the teams currently delivering insights? • What kinds of skillsets are required? Do we have a purple person? • What datasets linked to value are readily available? • How can we iterative build the foundational data stores? • What services are required / available to solve problems? • How do people access and use these services? • What are the pressing business questions for Research,, Corporate and Execs? • What is the link to value? • What are the myths? Supporting Capabilities • What visualisations and user interfaces are required to enable the end user to perform their own analysis and access the data and insights in an intuitive manner? Services Visualisation and Reporting Technology Data People Processes BusinessValue Insight Platform Insight Centre Decision Makers You need a service and operating model
  30. 30. You need Insights centre Centralised, De-centralised and Center led models all work
  31. 31. Deloitte. © 2015 31 Linda’s Journey to Insight How is the solution visualised? For Linda, the analysis is presented in a beautiful interactive format in an online tool she can view on any device in any location with internet access. Linda is able to augment the data set herself with additional data. UI & Visualisation How is the data managed? The team utilised a cloud based Analytics Data Store with data discovery/visualisation tools. The data and logic used to create the solution for Linda is drawn from existing analytics data stores where possible Data How is the problem approached? Jenny has a team of professional data scientists who work with Linda to develop a solution in an agile and iterative manner Various data structures and visualisations are rapidly constructed and used. Processes What is the business imperative? Linda wants to understand the Student use of after hours facilities in her faculty are and what capabilities and services matter to students most…. Which aid retention? Customers How is the problem communicated? Linda reaches out to Jenny via the Insight Chat group. Jenny, understand the student life cycle, technology and analytical techniques and works with Linda to understand the priority and clarify the problem. People What service is applied to the problem? Linda’s solution is best delivered through an on demand approach, empowering Linda to explore the analysed data in her own time and drill down deeper into the areas of the data that helps her with her project. Services
  32. 32. Technical Genius Commercially Astute You need Purple People Purple Person
  33. 33. You need to change Mind-Set Creating the shift from “gut feel” to insight driven decision making is critical to embedding the change Democratization of access and action on data Culture of crunchy questions Do you think or do you know?
  34. 34. A personal example of Big Data impact … Project 67 A personal side-project Project 67 is a “Stream Analytics” decision engine with an embedded annealing intelligence with deep error identification algorithms, performance optimisation engine, impact simulation engine and decision making system that automatically updates the network for low risk items; flags high risk items for human review.
  35. 35. Project 67 is about making human work meaningful Moore’s law “applies” to communications network management… Exponential complexity growth.
  36. 36. A current example of impact… Project 67 • ~100,000+ Cells • ~7000 Counters / Cell/ 15 min • Millions of user events / min • Thousands of alarms / day • Thousands of configuration changes / day BOTTOM LINE: >15TB of data every hour and growing. Only a fraction processed, mostly by Humans
  37. 37. Deloitte. © 2012 37 One Example: Step change in performance Network Location 1 - element Network Location 2 - element Network Location 3 - element
  38. 38. Deloitte. © 2012 38 What the operator sees Network Location 1 - element Network Location 2 - element Network Location 3 - element
  39. 39. Deloitte. © 2012 39 What the algorithm sees Network Location 1 - element Network Location 2 - element Network Location 3 - element
  40. 40. Deloitte. © 2012 40 The step change modelled for action Network Location 1 - element Network Location 2 - element Network Location 3 - element
  41. 41. … so what? Moving Big Data to Big Value means… 1. Plan for the whole journey – aim for impact, not just insight 2. Uncommon wisdom and insight cannot be managed with the same processes as the “old’ knowledge; Think Inside-Out data driven transformation 3. Be ready to be proven wrong… by yourself. Knowing is a double edged sword as you measure each step, and being wrong is part of the journey to an insight driven organisation 4. … and the move to value can only flourish with courageous leadership from the top
  42. 42. Be the courageous leaders we need! Coert du Plessis, May 2015
  43. 43. General information only This presentation contains general information only, and none of Deloitte Touche Tohmatsu Limited, its member firms, or their related entities (collectively the “Deloitte Network”) is, by means of this presentation, rendering professional advice or services. Before making any decision or taking any action that may affect your finances or your business, you should consult a qualified professional adviser. No entity in the Deloitte Network shall be responsible for any loss whatsoever sustained by any person who relies on this presentation. About Deloitte Deloitte refers to one or more of Deloitte Touche Tohmatsu Limited, a UK private company limited by guarantee, and its network of member firms, each of which is a legally separate and independent entity. Please see for a detailed description of the legal structure of Deloitte Touche Tohmatsu Limited and its member firms. Deloitte provides audit, tax, consulting, and financial advisory services to public and private clients spanning multiple industries. With a globally connected network of member firms in more than 150 countries, Deloitte brings world-class capabilities and high-quality service to clients, delivering the insights they need to address their most complex business challenges. Deloitte has in the region of 200,000 professionals, all committed to becoming the standard of excellence. About Deloitte Australia In Australia, the member firm is the Australian partnership of Deloitte Touche Tohmatsu. As one of Australia’s leading professional services firms. Deloitte Touche Tohmatsu and its affiliates provide audit, tax, consulting, and financial advisory services through approximately 6,000 people across the country. Focused on the creation of value and growth, and known as an employer of choice for innovative human resources programs, we are dedicated to helping our clients and our people excel. For more information, please visit our web site at Liability limited by a scheme approved under Professional Standards Legislation. Member of Deloitte Touche Tohmatsu Limited © 2015 Deloitte Touche Tohmatsu