Connecting Kafka to Cash (CKC) (Lyndon Hedderly, Confluent) Kafka Summit London 2019
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We all know real-time data has a value. But how do you quantify that value in order to create a business case for becoming more data, or event, driven? The first half of this talk will explore the value of data across a variety of organizations, starting with the five most valuable companies in the world: Apple, Alphabet (Google), Microsoft, Amazon, and Facebook. We will go on to discuss other digital natives; Uber, Ebay, Netflix and LinkedIn before exploring more traditional companies across Retail, Finance and Automotive. Whether organizations are using data to create new business products and services, improving user experiences, increasing productivity, managing risk or influencing global power, we’ll see that fast and interconnected data, or ‘event streaming’ is increasingly important. After showing data value can be quantified, the second half of this talk will explain the five steps to creating a business case around Kafka use cases. Most businesses focus on: 1. Making more money, or conferring competitive advantage to make more money 2. Increasing efficiency to save money, and / or 3. Mitigating risk to the business, to protect money. We’ll walk through examples of real business cases, discuss how business cases have evolved over the years and show the power of a sound business case. If you’re interested in Big Money and Big Business, as well as Big Data, this talk is for you.
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Connecting Kafka to Cash (CKC) (Lyndon Hedderly, Confluent) Kafka Summit London 2019
- 1. 1 Connecting Kafka to Cash K $ Lyndon Hedderly Director, Customer Solutions
- 2. 22 1. Why measure value? 2. Problems with measuring value - and solutions 3. Three examples of measuring Kafka’s business value 4. Conclusion
- 3. 333 Kafka is in production in tens of thousands of companies Major shift in data infrastructure Kafka is a Foundational technology - Event Streaming represents a new paradigm, unleashing innovation and new business outcomes
- 4. 44 70% 80% 90%10% 20% 50% 60%40%30% 60% of the Fortune 100 Identifying value can be a before, during and after exercise... Enormous range of use-cases
- 5. Investing $50kin 10 companies using data to deliver Great User Experience The UX Fund:
- 6. $50k in 10 companies in 2006 became $306kin 2016. A 503% gain S&P 50%
- 7. Gain as a % $157k >3,000% return! Almost 900% return! S&P Return c.50%
- 8. Netflix Digital Native At Scale 50+ clusters 4000+ brokers 2+ trillion msgs/day
- 10. 1010 Problems with measuring value - and solutions ?? ⅓ ⅓ ⅓
- 11. 1. We’ve often wildly miscalculated business cases and ROI’s, which has made people skeptical. From 1 hr 21m to <50 mins = 30 mins saving / journey X £20 / hr (av. productivity) = £10 / journey X 3M journeys / yr = £30M / Yr, or £300M over 10 yrs. > £1Bn
- 12. 1. From Batch to Real-Time 2. Enterprise-wide source of events (no silos or point to point connections) 3. Build for scale 4. Store events while maintaining real-time replay 5. Contextual Business Applications
- 14. 14Confidential $21 M 2018 £11.4 M 2007 £2 M 2001
- 16. 16Confidential $940 k 1999 $65 M 2018 68x in 19 yrs Hard CASH
- 17. 17Confidential
- 18. The Subjective Element of valuing a (contextual) piece of technology 1. The iWatch? $83 / $350 2. With fitness information? 3. Medically accurate electrocardiogram?
- 20. 20Confidential $= Data Data is the new Oil. It is valuable, but if unrefined it cannot really be used. It has to be changed into gas, plastic, chemicals, etc. to create a valuable entity that drives profitable activity; so must data be broken down and analyzed for it to have value.
- 21. It’s not just the data that is important, it is how it is moved around - and how timely it is → The ability to move the oil becomes almost as valuable as the oil itself → Now imagine a pipeline that also processed the oil – in real time
- 22. 2222 Three examples of measuring Kafka’s business value
- 23. 2323 7-9,000 disputes / month Agents = 3-5 hrs to resolve a dispute Significant number paid off Costs c. £3M / yr
- 24. 24 Universal Event Pipeline Data Stores Logs 3rd Party Apps Custom Apps/Microservices from ATM’sContextual Information - Bank Accounts Analysis / Historic info - feeds from other ATM / banks ATM Disputes Universal event pipeline --- high throughput, persistent, ordered, and has low latency --- All events and systems are connected
- 25. 25 Universal Event Pipeline Data Stores Logs 3rd Party Apps Custom Apps/Microservices ATM Disputes App Real-Time Fraud Detection Real-Time Customer 360 Machine Learning Models Real-Time Data Transformation ... Contextual Event-Driven Apps ATM Disputes ● 50% reduction in agent time ● 75% reduction in avoidable payments
- 26. ATM Disputes Project Costs = £1.5M + Ops Costs (total 5 yr TCO) = £2.2M ATM Dispute Savings = From $9M to $2M = $7M Total Net savings = £4.8M. 2.2x ROI Breakeven: Mid Yr 1
- 27. Customer 360
- 28. 29 Universal Event Pipeline Data Stores Logs 3rd Party Apps Custom Apps/Microservices Real-Time Fraud Detection Real Time Inventory Real-Time Customer 360 Machine Learning Models Real-Time Data Transformation ... Contextual Event-Driven Apps Customer 360 From on-line click throughsStock / Warehouse / Inventory Info Analysis / Weather info - feeds from other data sources ● On-line; Personalized, targeted offers: uplift revenue ● Better manage inventory - for offers, with dynamic pricing
- 29. Customer 360 Breakeven: in Yr 2 Project Costs = $2M + Ops Costs (total 5 yr TCO) = $6.3M Total Gain in Revenue + Savings in System Costs Total Net gain = $13.5M. 2.14x ROI
- 30. Fraud OK Sir... Here you go… ...but don’t you know you can do all this much more easily online.
- 31. 32 Universal Event Pipeline Data Stores Logs 3rd Party Apps Custom Apps/Microservices Real-Time Fraud Detection Real Time Inventory Real-Time Customer 360 Machine Learning Models Real-Time Data Transformation ... Contextual Event-Driven Apps Fraud Detection Mobile Banking AppsMainframe Core Banking Apps Analysis / location information, other Cyber Sec info ● Detection and prevention of Fraud (real-time) ● Improvement over time - better CX + Other benefits not modelled
- 32. Fraud Breakeven: in H1 Project Costs = £3M + Ops Costs (total 5 yr TCO) = £6M Total Fraud Prevention = $27M Total Net gain = £21M. 3.5x ROI
- 35. 36
- 36. 37
- 37. 38 Real-Time Inventory Real-Time Fraud Detection Real-Time Customer 360 Machine Learning Models Real-Time Data Transformation ... Contextual Event-Driven Apps Event Streaming Platform
- 38. 3939 5-step value assessment process 1. Baseline As-Is State & Negative Consequences (3-5 yr costs) 2. Target State Desired Solution 3-5 yr costs + Project Costs 3. Benefits Top-line business Benefits & Bottom-line Savings (TCO comparison / ROI) 4. Soft Benefits Non-Financial Impact & Analysis: Incl. Scenarios, Sensitivities & Risks 5. Proof- Points Metrics (definition of success) Case Studies ● Below the line - Universal Pipeline benefits of Kafka ● Above the line - Contextual Business Applications