Leeds Digital Festival - Make Analysis Great Again!
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The Data Shed's view on how to get away from the churn of maintaining reports, analytics and scorecards... and Make Analysis Great again!
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Leeds Digital Festival - Make Analysis Great Again!
- 1. Make Analysis Great Again!
- 2. Ed Thewlis CTO Doesn’t do much work anymore. Can be found at the coffee bar or laid on the sofa. Tony Jozefek Head of Analytics Hates dogs, balloons and people. Loves Data and Statistics
- 3. Once upon a time, analytics was fun…
- 5. Fix the less ‘technically’ challenging questions
- 6. Who are my customers? How should I talk to my customers? What does revenue look like in 12 months? Will my customers repay their loans? Which customers might want to buy my new product?
- 7. Who are my customers? How should I talk to my customers? What does revenue look like in 12 months? Will my customers repay their loans? Which customers might want to buy my new product? Clustering (describe) or Decision Trees (value) Logistic Regression (Channel preference/ propensity) Time Series Forecasting Logistic Regression, Survival/Hazard Model Logistic Regression, Matchbox recommender
- 8. The journey should be fun…
- 9. 0 1 2 3 1 2 3 4 5 6 7 8 9 10 Bodies The Utopia… Model 1 Model 2
- 10. 0 1 2 3 4 5 6 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 Bodies Where does all our time go?! Monitoring Model 4 Model 3 Model 2 Model 1
- 11. Now you’re stuck in drudgery...
- 12. Insight ≠ Action Changes to capacity don’t lead to incremental insights Monitoring > Thinking KPI Paralysis Effort > Incrementality
- 13. MAKE ANALYSIS GREAT AGAIN!
- 14. Step one: Automate all of the things
- 15. Build Experiment Publish Analytical Pipeline Evaluate Monitor High Value Human Interaction Low-to-Zero Value Human Interaction
- 16. Build Hypothesis/Exp eriment Publish Analytical Pipeline Evaluate Monitor DevelopSpike/Design Release Engineering Process Test Monitor
- 17. ...But which tools should I use?!
- 18. The Analyst’s Best Friends Monitoring & Alerting Reporting Framework Alerting Tool Analytics Workspace Notebooks Git Repositories CI/CD Tool Ticketing System Data Stores “Data Lake” Reporting Repository Self-Service ETL Tool
- 19. Monitoring & Alerting Power BI Logic Apps Analytics Workspace Azure Notebooks Azure DevOps Azure DevOps Azure DevOps Data Stores Blob Storage/Data Lake Azure SQL Logic Apps/Data Factory
- 20. Monitoring & Alerting AWS Quick Sight AWS Lambda Analytics Workspace AWS SageMaker BitBucket BitBucket Pipelines JIRA Data Stores S3 RDS Glue Monitoring & Alerting AWS Quick Sight AWS Lambda Analytics Workspace AWS SageMaker BitBucket BitBucket Pipelines JIRA Data Stores S3 RDS Glue
- 21. Step one: Automate all of the things Why? So you can free up your time and focus on the exciting and valuable work
- 22. Step two: Measure yourselves.
- 23. Time to Insight How efficiently can you generate the insight to a key decision point Time to Action How efficiently can the business act on your insight Time to Value Over what horizon are you able to measure your impact
- 24. Understand where you can make the biggest difference
- 25. 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 0. Gut Feel 1. Report 2. Segmented Report 3. Target Segments 4. Scorecard 5. Neural Network CumulativeValue Analysis Type/Effort Incrementality of Analytical Effort Simple Levers Feature Overload
- 26. Backlog 3 12 50 Unsuccessful 1 3 6 Delivered 1 Average: 85 days 2 Average: 22 days 12 Average: 5 Days Large Medium Small £1.5mil incremental margin £300k incremental margin £200k incremental margin £2mil incremental margin
- 27. Step two: Measure yourselves Why? So you can easily explain why focussing effort in certain places is potentially hugely valuable
- 28. Step three: Collaborate Effectively
- 30. Collaborate! Analytics -> Technology • Demonstrate your adoption of their best practices • Show them what analytics can do for them • Demonstrate your firm plan for automation (they’ll love it!) Analytics -> Operations • Learn their jobs • Sit with them daily • Understand their problems, and make sure they make it onto your backlog • Celebrate your successes with them!
- 31. So... what should I do tomorrow?
- 32. What should I do tomorrow? Collaborate Start collaborating effectively •Learn the right language to allow you to influence strategic thinking •Ensure you are at the forefront of ‘What if’ questions Measure Measure yourselves •Do you what you do best – but to yourselves •Let the business case for growth write itself •Celebrate your successes publicly Automate Automate all of the things •Free yourself of drudgery •Build a more efficient team •Steal the best of the engineering teams Understand Know the levers of your value-chain •Where can you influence decisions? •What is the size of the opportunity? •What is the type of problem? •How will you measure your influence?
- 33. Analytics is awesome. Stop making it boring. MAKE IT GREAT AGAIN!!
- 34. Any questions?
Notas del editor
- Ed So - a warm welcome to our 2nd LDF event! Thanks to our friends at RSM for providing such a lovely space for us. We're here to talk about the life of an analyst - and how to make it thb
- Quick intro – 1 minute Tony: As Head of Analytics, my role is to help businesses understand their problems and how they can use their data to solve them...in a scalable, efficient manner...doing all of the things Ed just mentioned
- 1 minute Back in the good old days... Ed
- Ed
- ed
- Ed
- Ed
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- Tony
- Tony
- Ed -> Tony
- Internal automation - Can those decisions conceivably be made by a machine if it magically ingested all the data my people have? Handling change – Can my business decisions automatically learn from changes in environments and populations, and adapt accordingly? Optimisation of time - Where do people in my company today apply knowledge to make decisions that could be automated, so their skills could be better leveraged elsewhere?
- Ed
- Ed
- Ed
- Tony
- Tony Time to Insight – Availability & Automation Time to Action – Decision-making & engineering/implemetation Time to Value – Value-chain understood & new reporting available to measure the changes
- Tony Measuring: Backlog Capacity Time to Deliver Time to Insight Time to Action Value of Action Success rate of Experiments If you have exhausted the options, time to move on
- Tony - FINISH ON POINT ABOUT FAILURE
- Ed How many experiments have I performed? What was the Time to Insight? What was the Time to Action? What was the Value of Action? What was the Success rate of Experiments?
- Measuring: Backlog Capacity Time to Deliver Time to Insight Time to Action Value of Action Success rate of Experiments If you have exhausted the options, time to move on
- Tony
- Tony How can these teams work & learn together… …Learn the language
- Ed You can do all the things….it doesn’t mean you should You can hand it over to be re-engineered…but you lose context and introduce risk You need to understand the problems the business has
- Ed
- Tony -> Ed Evaluate where you currently spend most of your time & effort Do you have a set of tasks that stop you solving other problems? If so, work with your Software/IT teams to automate the everyday tasks...learn from DevOps principles Spend your new found time discovering new ways to add value to your organisation. Rinse & Repeat.
- Tony ->. Ed
- Ed