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11 Principles of Applied Analytics

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Applied analytics is all about creating actionable insights that can be injected back into a business process at the point of highest impact. This slideshow walks you through the "11 Principles of Applied Analytics" from Georgian Partners.

Published in: Data & Analytics
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11 Principles of Applied Analytics

  1. 1. How to Use Analytics to Create Value, Enhance Your Business and Disrupt Your Industry The 11 Principles of Applied Analytics
  2. 2. Applied analytics is all about creating actionable insights that can be injected back into a business process at the point of highest impact. Applied Analytics
  3. 3. The idea is to use the insights to make your business processes more intelligent, efficient and valuable. Applied Analytics
  4. 4. Get it right and you can create better experiences for your customers, grow your business, and even disrupt your industry. Applied Analytics
  5. 5. But we’re getting ahead of ourselves. First we’ve got to understand how to approach applied analytics. Applied Analytics
  6. 6. To help, we’ve put together the following 11 principles of applied analytics to help frame your thinking. Applied Analytics
  7. 7. Understand the process.1 Applied Analytics
  8. 8. Understanding the process means not just thinking about the data you already have access to or the analytics technologies you currently understand. Applied Analytics
  9. 9. Instead, you’ve got to identify the most actionable and valuable insights that could change outcomes in the business process your solution drives. Applied Analytics
  10. 10. Identify and prioritize the most valuable insights. 2 Applied Analytics
  11. 11. Since not all analytic insights are of equal value, you have to figure out which ones are going to have the greatest impact. Applied Analytics
  12. 12. And don’t just consider the value of a particular insight. You’ve also got to look at how refined the insight is and how widely it can be used across an organization. Applied Analytics
  13. 13. To determine the value of your insights, use this simple equation: value of insight degree of refinement consumption x x The value of analytic impact = Applied Analytics
  14. 14. Create a data set that is unique and broad.3 Applied Analytics
  15. 15. Try to draw data from the widest range of sources possible and to get exclusive usage rights whenever possible. Applied Analytics
  16. 16. WHY?Because it would be hard to duplicate your data, making it difficult for others to provide the same insights. Applied Analytics
  17. 17. Ultimately, your goal is to create a dataset that no one else can using data from across a market eco-system. Applied Analytics
  18. 18. Recognize that raw data alone is of little or no value. 4 Applied Analytics
  19. 19. Simply storing as much data as possible isn’t useful. Your data needs be refined to support insights. Guess what. Applied Analytics
  20. 20. data validation cleansing and de-duplication data integrity checks creating aggregates & standardizing the structures definitions of your data ✔ ✔ ✔ ✔ ✔ That means: Applied Analytics
  21. 21. Oh, and by the way, if you’re bringing together multiple data sets, you’ve got to use a common data model. Applied Analytics
  22. 22. Insights are more valuable the closer they are to being actionable. 5 Applied Analytics
  23. 23. Then you’ve got to reduce the amount of interpretation and effort required to take action. Want to succeed with data and analytics? Applied Analytics
  24. 24. In other words, your goal should be to minimize the effort that a user —or even a downstream process — needs to turn an insight into an action. Applied Analytics
  25. 25. That effort is the “analytic delta.” The closer that any insight is to the point where an action could be taken, the smaller the delta will be. Applied Analytics
  26. 26. Leverage the shortage of data scientists to your advantage. 6 Applied Analytics
  27. 27. Ok, so there aren’t enough people out there with big data and analytics talent. Applied Analytics
  28. 28. The good news is that if you can deliver insights from big data as a solution, or part of a wider offering, you’ll have a competitive advantage. Applied Analytics
  29. 29. In fact, the lack of data scientists will give you the opportunity to drive higher margins, provided you can deliver analytic insights in your product. Applied Analytics
  30. 30. Separate analytic insight from how it’s consumed. 7 Applied Analytics
  31. 31. Don’t limit your options for delivering insights to the particular analytic tool or platform your company knows best or has access to today. Applied Analytics
  32. 32. Instead, consider all of your delivery options, including: reports dashboards search & query UIs alerts rules engines and APIs “Insight as a Service” ✔ ✔ ✔ ✔ ✔ ✔ The bottom line is don’t let your choice of analytic tool define your method of delivery. Applied Analytics
  33. 33. Inject insights into business processes at the moment of highest impact. 8 Applied Analytics
  34. 34. is to enable insights that have an impact on a business process at the right time and in the most appropriate way. The goal of applied analytics Applied Analytics
  35. 35. You can increase the value of those insights by automating their delivery either to the right person or into the right business process. Applied Analytics
  36. 36. It’s not about “owning” the data.9 Applied Analytics
  37. 37. Whether a company “owns” a particular set of data, or not, is less relevant than what that company’s rights are to use the data. Applied Analytics
  38. 38. In other words you need the right to use data. And you have to ensure that your usage complies with both regulations and marketplace expectations. Applied Analytics
  39. 39. ✔ Once secured, these information rights will become the basis for your applied analytics strategy. Applied Analytics
  40. 40. Governance and compliance is a foundational discipline. 10 Applied Analytics
  41. 41. When you don’t have a pro-active strategy you wind up with ad-hoc and reactive responses to events. Applied Analytics
  42. 42. That means taking a proactive approach to privacy needs to be a top priority. So should customer business continuity. Applied Analytics
  43. 43. Be analytical in your own business.11 Applied Analytics
  44. 44. You should be leveraging analytics within your own company to optimize your operations. Applied Analytics
  45. 45. That means analytically enabling all of your employees and making your entire organization more analytical. Applied Analytics
  46. 46. Your goal should be to embrace data-driven decision-making about both your solutions and your customers. Applied Analytics
  47. 47. Applied analytics represents a huge opportunity for companies to create value as business process knowledge, big data, and information rights converge. Applied Analytics
  48. 48. Understand the process. Identify and prioritize the most valuable insights. Create a data set that is unique and broad. Recognize that raw data alone is of little or no value. Insights are more valuable the closer they are to being actionable. Leverage the shortage of data scientists to your advantage. Separate analytic insight from how it’s consumed. Inject insights into business processes at the moment of highest impact. It’s not about “owning” the data. Governance and compliance is a foundational discipline. Be analytical in your own business. To unlock that opportunity, keep these 11 principle in mind: ✔ ✔ ✔ ✔ ✔ ✔ ✔ ✔ ✔ ✔ ✔ Applied Analytics
  49. 49. Want to learn more about applied analytics? Download our white paper Applied Analytics

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