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Birst Webinar Slides: "Build vs. Buy - Making the Right Choice for a Great Data Product"

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Birst Webinar Slides: "Build vs. Buy - Making the Right Choice for a Great Data Product"

  1. 1. Build vs. Buy: Making the Right Choice for a Great Data Product
  2. 2. 2 Webinar logistics Please send questions using the online interface Attendees muted upon entry
  3. 3. Presenter ksmith@birst.com @kevinmsmith kevinmichaelsmith Kevin Smith VP, Embedded Solutions ksmith@birst.com
  4. 4. ‹#› What is a data product?
  5. 5. ‹#› A story of building analytics gone wrong
  6. 6. ‹#› Our mission Make our existing SaaS application more engaging by adding analytics
  7. 7. ‹#› We have smart Engineers… Let’s build it ourselves and save some money!
  8. 8. ‹#› We had resources. I’m an analytics user story. Please implement me! I’m an analytics user story. Please implement me! I’m an analytics user story. Please implement me! I’m an analytics user story. Please implement me! I’m an analytics user story. Please implement me! I’m an analytics user story. Please implement me! I’m an analytics user story. Please implement me! I’m an analytics user story. Please implement me! I’m an analytics user story. Please implement me! I’m an analytics user story. Please implement me! I’m an analytics user story. Please implement me! I’m an analytics user story. Please implement me! + +
  9. 9. ‹#› We had a vision. $ $ $ $ $
  10. 10. ‹#› What we actually got.
  11. 11. ‹#› Why was this so painful?
  12. 12. ‹#› The Truth about Buy vs. Build for Embedded Analytics
  13. 13. ‹#› The BI bar has been raised 1
  14. 14. ‹#› Time has changed the analytics game It’s on the web? NICE! 1990 It’s only 30 days old? NICE! 1995 I can sort by column headers? NICE! 2000 A chart? In color? NICE! 2005 Real-time data? NICE! 2010 I can’t drag this chart to a new location, apply filters and have it notify me when it exceeds the targets I uploaded? 
 FAIL. 2015
  15. 15. ‹#› Because table stakes & delighters aren’t static Table Stakes • Expected • Can’t compete here • Your competition has them • Can’t charge for this • Increases over time Delighters • Unexpected • The place to compete • Useful for differentiation • Can charge • Transition to table stakes over time
  16. 16. ‹#› Delighters become table stakes Table Stakes • Nice looking visuals • Drill down • Filter • Dimensions Delighters • Personal settings • Customize • Notifications • Trends • Targets • Predictive • Annotations
  17. 17. ‹#› It will take longer & cost more than you expected 2
  18. 18. ‹#› We can build it for less! • Pay for Highcharts • Cost to build ETL • Cost to build SSO • Cost to build pages Build it year 1 year 2 year 3 • Possibly buy more storage • Possibly buy more bandwidth maybe $150K? +20K? • Possibly buy more storage • Possibly buy more bandwidth +20K? Our cost to build = $190,000 over next 3 years
  19. 19. ‹#› Buy it Buying is expensive! year 1 year 2 year 3 $250K • Pay platform fee • Pay for implementation • Pay for training • Pay platform fee• Pay platform fee $100K $100K Our cost to buy = $350,000 over next 3 years
  20. 20. ‹#› Our cost to buy = millions and millions over an infinite timeframe Buy it Buying is, like, SUPER expensive! year 1 year 2 year 3 $250K • Pay platform fee • Pay for implementation • Pay for training • Pay platform fee• Pay platform fee $100K $100K infinity $100K times infinity
  21. 21. ‹#› • Pay for Highcharts • Cost to build ETL • Cost to build SSO • Cost to build pages Build it Buy it • Possibly buy more storage • Possibly buy more bandwidth year 1 year 2 year 3 • Possibly buy more storage • Possibly buy more bandwidth • Pay platform fee • Pay for implementation • Pay for training • Pay platform fee• Pay platform fee $190K 
 (but probably even less) Infinite money Clearly, we should build it!
  22. 22. ‹#› What we all think we need to do… Buy charting package Build ETL Build Charts Build Dashboards Connect via SSO
  23. 23. ‹#› In reality, there’s a bit more. Buy charting package Build data load Build Charts Build Dashboards Theming Aggregate data Build roll-ups User permissioning Admin pages Multi-tenancy Connect via SSO Filters DimensionsTarget setting Target setting Transformations UI controls Drill down Drill Across QA
  24. 24. ‹#› $ What are you skipping in order to build? 3
  25. 25. ‹#› Cost to build analytics Cost to support analytics Cost of NOT working on your core application The cost of missed core product value
  26. 26. ‹#› Your most talented people should work on unsolved problems. 50% of companies base their decision to build on the fact that they have the necessary talent to build analytics
 From Wayne Eckerson, “Embedded BI: Putting Reporting and Analysis Everywhere”, TechTarget, December, 2014.
  27. 27. ‹#› Where can we add the most differentiating value? Ask Core Product Analytical Platform • Do we have all the features we need to solve the customers’ needs? • Could we build features that differentiate us from the competition? • Could we build functionality that would be hard to copy? • Is analytics where we want to compete? • Do we need to build the infrastructure in order to achieve this? • Can we build BI functionality that is differentiating?
  28. 28. ‹#› Can you build what you need down the road? Category Types of Analytics Questions Answered Prescriptive • Optimization • Randomized testing • What’s the best that can happen? • What happens if we try this? Predictive • Predictive modeling/forecasting • Statistical modeling • What will happen next? • What is making this happen? Diagnostic • Data exploration • Intuitive visuals • Why did this happen? • What insights can I gain? Descriptive • Alerts • Query/drill-down • Ad hoc reports/scorecards • Standard reports • What actions are needed? • What is the problem? • How many, often, where? • What happened? SOURCE: Disambiguating Analytics, July 2, 2013, Sanjeev Kumar, International Institute for Analytics SOURCE: Magic Quadrant for Business Intelligence and Analytics Platforms, February 5, 2013, Analyst(s): Kurt Schlegel, Rita L. Sallam, Daniel Yuen, Joao Tapadinhas Capability Easy (er) to build Hard to build Much harder to build YOU have to build this
  29. 29. ‹#› It’s hard to build fast enough to differentiate 4
  30. 30. ‹#› Two ways to compete on analytics Differentiate (we’re the leaders!) Neutralize (we’ve got BI too!) Core Value Key Metric Main Challenge Separation Unmatchable How far? Comparability Good enough How fast? Framework adapted from Reaching Escape Velocity, Geoffrey Moore, 2012
  31. 31. ‹#› Two ways to compete on analytics Differentiate (we’re the leaders!) Neutralize (we’ve got BI too!) Core Value Key Metric Main Challenge Separation Unmatchable How far? Comparability Good enough How fast? Framework adapted from Reaching Escape Velocity, Geoffrey Moore, 2012 Can you build fast enough to differentiate?
  32. 32. ‹#› Build fast enough outrun the competition…
 and STAY ahead
  33. 33. ‹#› Two ways to compete on analytics Differentiate (we’re the leaders!) Neutralize (we’ve got BI too!) Core Value Key Metric Main Challenge Separation Unmatchable How far? Comparability Good enough How fast? Framework adapted from Reaching Escape Velocity, Geoffrey Moore, 2012 Are you willing to cede your development roadmap to the competition?
  34. 34. ‹#› The risk: your competition dictates your pace
  35. 35. ‹#› You need to make a balanced decision 5
  36. 36. ‹#› It’s an equation, not a single number Total cost to buy analytics - Total cost to build analytics ≥ Opportunity cost of building + Risk of not being able to execute now & future Cost Side Strategy Side
  37. 37. ‹#› It’s an equation, not a single number Total cost to buy analytics - Total cost to build analytics ≥ Opportunity cost of building + Risk of not being able to execute now & future What’s the TCO for purchasing analytics What’s the real cost to build What aren’t we doing if we build and how important is it? Will we be able keep up the development pace for the foreseeable future?
  38. 38. ‹#› 1 The cost to buy embedded analytics Total cost to buy analytics - Total cost to build analytics ≥ Opportunity cost of building + Risk of not being able to execute now & future What’s the TCO for purchasing analytics What’s the real cost to build What aren’t we doing if we build and how important is it? Will we be able keep up the development pace for the foreseeable future?
  39. 39. ‹#› 2 The real cost to build Total cost to buy analytics - Total cost to build analytics ≥ Opportunity cost of building + Risk of not being able to execute now & future What’s the TCO for purchasing analytics What’s the real cost to build What aren’t we doing if we build and how important is it? Will we be able keep up the development pace for the foreseeable future?
  40. 40. ‹#› Capture all of the true costs Task Type Task Title Description Licensing Buy the software to make the visuals Purchase of the software to make the charts + maintenance & support for Hi Charts (10 developer license) -- this ONLY includes production ETL Build connector to data source Create processes which will connect the charting software to the data source(s) ETL Perform transformations Transform the data into an analytic ready state for charting Data Modeling Create data aggregations Perform the roll-ups of data so that you can compare to previous yrs , qtrs, etc. UI Create dashboard page Create the page which will contain your analytics QA Perform QA Inspect the analytics and all calculations for accuracy UI Create dimensions Create the dimensions by which measurement can be examined Data Modeling Create filters Create the filtering element to include/exclude data by dimension Data Modeling Build drill-down/across paths Link analytics together so that users can drill down and across to explore causes Security Build multi-tenancy model Develop model to ensure that customers can't see each other's data Security Build security model Develop model to ensure that users see only the data they are allowed to see Data Create data model for targets Build a model to store targets for the metrics UI Build UI for target setting Create an interface to allow for the setting of targets by metric UI Build UI for alerts Create the interface for setting alers and notifications for user self-service Data Modeling Create visualizations Build the visualizations to display the data such as bar charts, line charts, infographics, etc. Data Modeling Create reports Build the pixel perfect reports that use the metrics and dimensions to display the data in a tabluar format with rollups, sub-groups, totals, etc. Administrative Build user mangement capabilities Create the functionality that allow you to add and remove customers and companies from the analytical functionality Administrative Build monitoring Develop the monitoring capabilities so that you can see the total usage by customer (for billing purposes)
  41. 41. ‹#› And calculate both money & time Variable Value Hourly rate $150.00 # of data sources 2 # of visualizations 15 # of reports 2 # of metrics 30 # of dashboards 1 # Dimensions/metric 2 Task Type Task Title Description QuantityHours per Item Total Hours Total Cost for Task Licensing Buy the software to make the visuals Purchase of the software to make the charts + maintenance & support for Hi Charts (10 developer license) -- this ONLY includes production 1 n/a n/a $3,600.00 ETL Build connector to data source Create processes which will connect the charting software to the data source(s) 2 20 40 $6,000.00 ETL Perform transformations Transform the data into an analytic ready state for charting 30 10 300 $45,000.00 Data Modeling Create data aggregations Perform the roll-ups of data so that you can compare to previous yrs , qtrs, etc. 30 10 300 $45,000.00 UI Create dashboard page Create the page which will contain your analytics 1 20 20 $3,000.00 QA Perform QA Inspect the analytics and all calculations for accuracy 30 5 150 $22,500.00 UI Create dimensions Create the dimensions by which measurement can be examined 60 5 300 $45,000.00 Create the filtering element to include/exclude data by The Powered by Birst Buy vs. Build Calculator * not including the time to manage the project $226,350 Building your dashboard in-house would cost at least: that's 1485 hours or 0.67 FTE years not working on your core product How much does it REALLY cost to build dashboards for your product on your own? Your cost to build using these parameters Our expected cost to build:
  42. 42. ‹#› 3 Opportunity costs & risks of building Total cost to buy analytics - Total cost to build analytics ≥ Opportunity cost of building + Risk of not being able to execute now & future What’s the TCO for purchasing analytics What’s the real cost to build What aren’t we doing if we build and how important is it? Will we be able keep up the development pace for the foreseeable future?
  43. 43. ‹#› Four parts to this side of the equation Can we build it FAST enough? What ELSE could we build with the time? Do we want to KEEP building it? Can we build it GOOD enough? 1 2 3 4
  44. 44. ‹#› Can we build it FAST enough? • Do you have the resources to build it? • Can you build it quickly enough to meet demand? • Can you build it fast enough to outpace the competition? 1
  45. 45. ‹#› Can we build it GOOD enough? • Do we have the talent to build this? • Can we get to the “delighter” functionality in the near term? • Will we be able to meet the “table stakes”? • Do we know what our customers need? 2
  46. 46. ‹#› Do we want to KEEP building it? • Will we have the resource to continue to support this? • Will we have the resources to continue to develop this? • Will we be able to meet one-off requests and future table stakes? 3
  47. 47. ‹#› What ELSE could we build with the time? • Is this as or more important than our core functionality? • Are we willing to delay core product functionality to build (and maintain) analytics? • Is this the best use of our resources - is this why customers buy our product? 4
  48. 48. ‹#› Use The Matrix
  49. 49. ‹#› Low Risk Medium High Risk Can we build it fast enough? We’ve got a development team dedicated to analytics, fully- trained in the entire stack, and can build quickly. We have resources, but may have trouble building quickly enough to achieve table stakes. We don’t have the resources/ don’t want to dedicate the resources to build analytics. Can we build it good enough? Yes — we can build all the basics plus functionality to differentiate ourselves from the competition. Maybe — we can add some table stakes, not all. Maybe our delighters will outweigh the gaps in functionality. Nope — we’d have trouble getting to table stakes. Do we want to keep building? Yes — this is where we will compete so we’ll devote equal resources to analytics develop as our core app. Maybe — we could add some functionality over time but it would secondary in importance to the core app. No — we’d prefer to use our resources on other things. Could we be doing other things? No — analytics are the app for us. We consider this to be the core of what we do. Maybe — analytics are important and our core app roadmap is not full. Yes — we can add more value by working on our core application. The Buy vs. Build Decision Matrix
  50. 50. ‹#› Low Risk (1 point) Medium (3 points) High Risk (5 points) TOTAL Can we build it fast enough? We’ve got a development team dedicated to analytics, fully-trained in the entire stack, and can build quickly. We have resources, but may have trouble building quickly enough to achieve table stakes. We don’t have the resources/ don’t want to dedicate the resources to build analytics. 3 Can we build it good enough? Yes — we can build all the basics plus functionality to differentiate ourselves from the competition. Maybe — we can add some table stakes, not all. Maybe our delighters will outweigh the gaps in functionality. Nope — we’d have trouble getting to table stakes. 3 Do we want to keep building? Yes — this is where we will compete so we’ll devote equal resources to analytics develop as our core app. Maybe — we could add some functionality over time but it would secondary in importance to the core app. No — we’d prefer to use our resources on other things. 2 Could we be doing other things? No — analytics are the app for us. We consider this to be the core of what we do. Maybe — analytics are important and our core app roadmap is not full. Yes — we can add more value by working on our core application. 2 GRAND TOTAL (possible 20 points) 10 points The Buy vs. Build Decision Matrix
  51. 51. ‹#› Low (1 point) Medium (3 points) High (5 points) Our Rating Importance (1=low to 3=high) TOTAL Can we build it fast enough? We’ve got a development team dedicated to analytics, fully-trained in the entire stack, and can build quickly. We have resources, but may have trouble building quickly enough to achieve table stakes. We don’t have the resources/don’t want to dedicate the resources to build analytics. 5 2 10 Can we build it good enough? Yes — we can build all the basics plus functionality to differentiate ourselves from the competition. Maybe — we can add some table stakes, not all. Maybe our delighters will outweigh the gaps in functionality. Nope — we’d have trouble getting to table stakes. 5 3 15 Do we want to keep building? Yes — this is where we will compete so we’ll devote equal resources to analytics develop as our core app. Maybe — we could add some functionality over time but it would secondary in importance to the core app. No — we’d prefer to use our resources on other things. 3 2 6 Could we be doing other things? No — analytics are the app for us. We consider this to be the core of what we do. Maybe — analytics are important and our core app roadmap is not full. Yes — we can add more value by working on our core application. 2 3 6 GRAND TOTAL (possible 60 points) 37 points The Buy vs. Build Decision Matrix x =
  52. 52. ‹#› The Buy vs. Build Decision Spectrum Consider building your own analytics You likely will be able to build fast enough and keep building fast enough to hold off the competition Consider buying your analytics It is unlikely you will get to market fast enough or be able to stay ahead of your competition Consider a combination strategy You may be able to build fast enough and keep building fast enough to beat the competition in select areas Low Risk High Risk The red zone Medium Risk 0 - 20 points 21 - 40 points 41 - 60 points The yellow zoneThe green zone
  53. 53. ‹#› Weigh the pros & cons to make the decision that’s right for your situation Cost Side May save $53K Strategy Side Medium High risk to build & keep building
  54. 54. ‹#› In summary: don’t use “internal” criteria 4 Make a balanced decision The BI bar has been raised It will take longer & cost more than you expected You can’t let up on the pace for your strategy What are you skipping in order to build?3 5 2 1
  55. 55. ‹#› Get the e-book at birst.com ©2015 Birst, IncBEYOND THE TECHNICAL The complete guide to designing, pricing, & launching embedded analytic products BEYOND THE TECHNICAL The complete guide to designing, pricing, & launching embedded analytic products ©2015 Birst, IncBEYOND THE TECHNICAL The complete guide to designing, pricing, & launching embedded analytic products BEYOND THE TECHNICAL The complete guide to designing, pricing, & launching embedded analytic products
  56. 56. ‹#› Thank you! ksmith@birst.com @kevinmsmith kevinmichaelsmith

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