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5 Factors in Modern Data Design

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5 Factors in Modern Data Design

Audience: Non-technical executives, tech-savvy managers and technical people who want fresh ideas and perspectives on modern enterprise data strategy and design.

As infrastructure and services rapidly commoditize, IT is being asked to assume a more strategic and proactive role in most large businesses. This document introduces a set of concepts and tools that may be helpful in integrating and aligning a data strategy with the overall enterprise.

Five key factors that have proven relevant to the survival of firms and strategies are introduced along with five practical tools that can be used to consider integrative strategies from a robust set of perspectives.

Audience: Non-technical executives, tech-savvy managers and technical people who want fresh ideas and perspectives on modern enterprise data strategy and design.

As infrastructure and services rapidly commoditize, IT is being asked to assume a more strategic and proactive role in most large businesses. This document introduces a set of concepts and tools that may be helpful in integrating and aligning a data strategy with the overall enterprise.

Five key factors that have proven relevant to the survival of firms and strategies are introduced along with five practical tools that can be used to consider integrative strategies from a robust set of perspectives.

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5 Factors in Modern Data Design

  1. 1. Modern Data Strategy By Dan 5 Design Factors Daniel Sexton, Red Chip Ventures© 2017
  2. 2. Audience 2 Ideas For Data Strategy Non-technical executives, tech-savvy managers and technical people who want fresh ideas and perspectives on modern enterprise data strategy and design. Daniel Sexton, Red Chip Ventures© 2017
  3. 3. Abstract 3 Ideas For Data Strategy Abstract: As infrastructure and services rapidly commoditize, IT is being asked to assume a more strategic and proactive role in most large businesses. This document introduces a set of concepts and tools that may be helpful in integrating and aligning a data strategy with the overall enterprise. Five key factors that have proven relevant to the survival of firms and strategies are introduced along with five practical tools that can be used to consider integrative strategies from a robust set of perspectives. Daniel Sexton, Red Chip Ventures© 2017
  4. 4. Modern Data Strategy Table of Contents Laying The Foundation 1. Revisiting The Basics 2. AWS Basics 3. Design Snapshot in AWS 5 Factors in Data Strategy 1. Movement 2. Uncertainty 3. Defensibility 4. Responsiveness 5. Alignment 4 5 practical tools to prepare for the rise of the machines Daniel Sexton, Red Chip Ventures© 2017
  5. 5. Revisit The Basics Often Data Strategy: A plan designed to improve all of the ways data is acquired, stored, managed, shared and used. ▪ What is truly valued at the organization? ▪ What does the competitive landscape look like? ▪ What does the company do well? ▪ What are the strategic opportunities for growth? 5 https://hbr.org/2015/03/why-strategy-execution-unravelsand-what-to-do-about-it https://hbr.org/2015/01/we-still-dont-know-the-difference-between-change-and-transformation http://dataconomy.com/2014/11/why-organizations-need-a-data-strategy/ https://www.sas.com/content/dam/SAS/en_us/doc/whitepaper1/5-essential-components-of-data-strategy-108109.pdf Daniel Sexton, Red Chip Ventures© 2017
  6. 6. Why revisit the “obvious” basics often? New brain research indicates that there are two distinct modes of thinking-- focused and diffuse. The transition between modes is the key to creativity and productivity. 1. Brain Science: Breakthrough ideas are more likely to come during casual reflection after new technologies and information have been absorbed. 6 Source Prof Barbara Oakley :http://tdlc.ucsd.edu/educators/educators_webinar_oakley_031213.html NIH Study: https://www.ncbi.nlm.nih.gov/pubmed/24904169 The Innovator’s Mindset: http://georgecouros.ca/blog/archives/5715 Science of Creativity: https://blogs.scientificamerican.com/beautiful-minds/the-real-neuroscience-of-creativity/ Focused Diffuse Prefrontal cortex, concentrated Diffused, dispersed Writing code, spreadsheets Big picture, mind wanders Deadlines, functionality, complexity Revisit basics, reflection, simple solutions, more with less Daniel Sexton, Red Chip Ventures© 2017
  7. 7. Why revisit the “obvious” basics often? According to research, it is not possible to be in both thought modes at the same time. Planning activities that encourage relevant modes of thinking at different stages may lead to more a effective dynamic. 7 Implementation & Execution: https://hbr.org/2015/03/defining-strategy-implementation-and-execution 5 Pillars of Strategy: https://www.cebglobal.com/blogs/the-five-pillars-of-strategy-execution/ Strategy Analysis Strategy Formation Strategy Execution Measure & Observe Results Daniel Sexton, Red Chip Ventures© 2017 No plan survives this More Diffuse Thought More Focused Thought
  8. 8. Why revisit the “obvious” basics often? Modern strategies are integrative 2. Collaboration helps strategy 8 70% fail: https://www.forbes.com/sites/insead/2016/01/08/five-reasons-most-companies-fail-at-strategy-execution/#e0ef3c33480a Strategy Execution: https://hbr.org/2015/03/why-strategy-execution-unravelsand-what-to-do-about-it 4A Model: https://ideas.darden.virginia.edu/2015/09/beyond-strategy-three-lessons-and-four-ingredients-of-execution/ According to research, at least 70% of corporate strategies fail. Strategy execution often breaks down across departments. Revisiting basics provides a common ground that people with diverse backgrounds can understand and contribute to. This can facilitate communication, teamwork, and a collaborative culture which can improve strategic analysis, formation and execution. Strategy Analysis Strategy Formation Strategy Execution Daniel Sexton, Red Chip Ventures© 2017
  9. 9. Why revisit the “obvious” basics often? 3. Discretion is key ▪ Change often happens faster than execution ▪ > 60% of IT projects fail 9 Source: https://www.linkedin.com/pulse/why-45-all-software-features-production-never-used-david-rice 50% fail: http://www.cio.com/article/3068502/project-management/more-than-half-of-it-projects-still-failing.html Daniel Sexton, Red Chip Ventures© 2017
  10. 10. Industry Trends 10 MicroservicesMonolith CloudOn-Premises Daniel Sexton, Red Chip Ventures© 2017
  11. 11. Industry Trends 11 Microservices Cloud Daniel Sexton, Red Chip Ventures© 2017 ? ?
  12. 12. Industry Trends Getting too far ahead… 12 ? ? Daniel Sexton, Red Chip Ventures© 2017 ??? ???
  13. 13. Monolith to Microservices Cloud platforms encourage modern design such as microservices. i.e. AWS Lambda coerces serverless, microservices 13 Monolith Microservices Scaling Vertical Harder Expensive Horizontal Simpler Cheaper Release Cycles 2-6 weeks, Error-prone 1-7 days Decoupled Deployment Model Simple, Unified Discrete Design Contracts Refactoring Large Codesets Strong Module Boundaries Degradation Binary Failure 100% Limits- CPU, Memory, Disk Graceful AWS Lambda, S3 Adapting Technologies Technology Monoculture Technology Diversity Teams Larger, Diffuse Responsibility - UI Team - App Logic Team - DBA Team Smaller, More Vertical - Accounts Team - Personalization Team - Mobile Team Strangling the Monolith: https://developer.ibm.com/tv/microservices-tv-episode-16-strangling-monolith/ Monolith to Microservices: https://www.nginx.com/blog/refactoring-a-monolith-into-microservices/ Microservices: http://microservices.io/patterns/microservices.html https://www.youtube.com/watch?v=oRIYtOsAlzk - Monolith to Microservices, AWS Daniel Sexton, Red Chip Ventures© 2017
  14. 14. Modern Data Design Overview Some Key Activities 14 Source Data Analytics & ETL Data Ingestion Business Intelligence Analytics Data Onsite Data Metadata & Delta Capture Service Discovery Lifecycle Management Data Governance Daniel Sexton, Red Chip Ventures© 2017
  15. 15. Modern Data Design using AWS Current Snapshot See Index 15Daniel Sexton, Red Chip Ventures© 2017
  16. 16. 5 Factors in a Modern Data Strategy the machines are coming 16 Movement Defensibility Uncertainty Alignment Agility Daniel Sexton, Red Chip Ventures© 2017
  17. 17. Factor 1 Movement 17 Movement Movement is the changing of technology, its place in the business cycle, and its use and adoption. The best strategies and designs anticipate movement. ● Commoditization ● Convergence ● Technology Adoption Daniel Sexton, Red Chip Ventures© 2017
  18. 18. Commoditization is the process by which technologies that are at first innovations-- scarce, expensive and distinguishable -- become commodities-- ubiquitous, inexpensive, homogenous, interchangeable. This curve depicts the path that all business activities follow from inception to commodity. 18 Movement As value chain components move up commoditization curve, the associated project loses strategic value. Innovation Commodity Inputs Highly Differentiated Products Strategic Advantages Less Differentiated Products Services, Commodities Buy, Outsource, Cheap Build, Assemble, Higher Costs Prevalence Maturity Moore’s Chasm Daniel Sexton, Red Chip Ventures© 2017 Agile Six Sigma Geoffrey A. Moore, Crossing the chasm (Chichester: Capstone, 1998). Rogers, Everett M. Diffusion of innovations. New York: Free Press, 2005.
  19. 19. The Value Chain is the set of inputs or components that are used to deliver a product or service. Each of these components exists somewhere along its lifecycle on this curve. Where these components are on their lifecycle is critical to overall strategy, design, marketing and other activities. 19 Movement Example Project Value Chain Prevalence Maturity Daniel Sexton, Red Chip Ventures© 2017 Predictive Analytics Salesforce Search, Solr IoT Commodity Inputs Strategic Advantages
  20. 20. Value Chain 12-18 months later 20 Movement Competition increases as it becomes cheaper and easier to enter market Prevalence Maturity Daniel Sexton, Red Chip Ventures© 2017 Predictive Analytics Salesforce Search, Solr IoT Buy? Build
  21. 21. Value Chain Costs 21 Prevalence Maturity Daniel Sexton, Red Chip Ventures© 2017 Difficultly/Cost Maturity $1000 $10 $0.10 $1 Build Buy $100 Services, Commodities
  22. 22. Value Chain Costs 22Daniel Sexton, Red Chip Ventures© 2017 Custom-built provides competitive advantage Costs justify the results? Products cheaper/better than building
  23. 23. Value Chain Costs Example: Big data strategy moves into ancillary components. 23Daniel Sexton, Red Chip Ventures© 2017 Hadoop ecosystem, 2005 Hadoop ecosystem, 2012 Hadoop ecosystem, 2020 BI driven by business more than IT
  24. 24. Convergence is the tendency for different technological systems to evolve toward performing similar tasks. This appears to happen when new technological value chains emerge to address customer needs at a viable value proposition level. 24 Movement As technologies change, different systems may converge towards solving similar tasks. Daniel Sexton, Red Chip Ventures© 2017
  25. 25. 25 Movement Daniel Sexton, Red Chip Ventures© 2017 Technology Adoption refers to the adoption of a new technology according to the demographic and psychological characteristics of defined adopter groups. Technology Adoption Lifecycle Geoffrey A. Moore, Crossing the chasm (Chichester: Capstone, 1998). Rogers, Everett M. Diffusion of innovations. New York: Free Press, 2005.
  26. 26. 26 Movement Daniel Sexton, Red Chip Ventures© 2017 Technology Adoption Custom-built IT projects and their value chains also have adoption lifecycles. Where are your projects on the lifecycle? What type of consumer are you? Moore’s Chasm refers to the marketing problem of driving adoption across populations (mostly) with tech startups. Technology Adoption Lifecycle Pace of Adoption: https://hbr.org/2013/11/the-pace-of-technology-adoption-is-speeding-up IoT Predictive Analytics Solr Salesforce
  27. 27. Factor 2 Uncertainty Strategy, design and organizational structure should handle several possible future scenarios. 27 Uncertainty Trends and movement, such as commoditization, are somewhat predictable. Other factors are not. Technology solutions are vulnerable to uncertain future scenarios. Daniel Sexton, Red Chip Ventures© 2017
  28. 28. 28 Company-Level Examples Daniel Sexton, Red Chip Ventures© 2017
  29. 29. Factor 3 Defensibility Being big doesn’t work anymore 29 Defensibility Democratization of technology is moving defensibility for large enterprises away from engineering costs into other areas. Threat of substitutes and new entrants is high as value chains commoditize. Data is the asset. The data itself should be defensible. Democratization: Amazon Data Center Daniel Sexton, Red Chip Ventures© 2017 Defensibility: https://techcrunch.com/2016/09/15/defensibility-creates-the-most-value-for-founders/ Design, Technology and Design: https://www.bipsync.com/blog/three-moats-defensible-scalable-internet-startup/
  30. 30. Strategic Data Matrix 30Daniel Sexton, Red Chip Ventures© 2017
  31. 31. Strategic Data Matrices 3 Axes Defensibility of Data It should be difficult or impossible for others to recreate the content and capabilities of strategic data. The data itself should be defensible. Fitness To Modeling The data and design should allow for data scientists and statisticians to test valid hypotheses. Hypotheses tested against defensible data can provide strategic advantages. 31 Robustness to Strategic Possibilities The data and design should be robust to an organization’s strategy and possible future scenarios. Hypothesis testing should align with strategy. Data & design should allow a wide range of viable options to be tested and explored. Daniel Sexton, Red Chip Ventures© 2017
  32. 32. Factor 4 Agility 32 Agility is the ability to adapt quickly and effectively to: ● Markets ● Competitors ● Threats, including security threats ● Technology Movement Agility Daniel Sexton, Red Chip Ventures© 2017
  33. 33. Factor 4 Agility Market favors those who execute quickly. 33 Agile software development is an important part of overall agility. Agility Daniel Sexton, Red Chip Ventures© 2017
  34. 34. Factor 5 Alignment the machines are coming 34 Alignment Daniel Sexton, Red Chip Ventures© 2017
  35. 35. Factor 5 Alignment 35Daniel Sexton, Red Chip Ventures© 2017 Time New studies say time is a factor Traditional Alignment Factors McKinsey 7S Strategy Structure Systems Skills Style Staff Shared Values Internal & External Mini- Innovation
  36. 36. Timelines can be misaligned McKinsey Three Horizons Moore’s Zone To Win 36Daniel Sexton, Red Chip Ventures© 2017 Time Horizon 1 - 0-12 Months Horizon 2- 12-36 Months Horizon 3- 36-72 Months Three Horizons: http://www.mckinsey.com/business-functions/strategy-and-corporate-finance/our-insights/enduring-ideas-the-three-horizons-of-growt h Moore. 2015. "Zone To Win: Organizing To Compete In The Age Of Disruption". Slideshare.Net. Accessed June 29 2017. https://www.slideshare.net/rstrad1/zone-to-win-organizing-to-compete-in-the-age-of-disruption. Many companies struggle taking Horizon 2 projects to market. TotalReturns Time A common misconception is that companies fail because they fail to innovate. If all of a company’s effort and resources are tied up in operations, disruptions will eventually put it out of business.
  37. 37. Thanks! Hope you found this SlideShare helpful in generating ideas for your own Data Design! Please send helpful comments and suggestions to Thanks! Dan

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