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Accelerating Digital Transformation to Drive Business Impact About Me Director Data Science, SparkBeyond 18 years in Data Science & Analytics, leading companies through their digital transformations. Professor of Data Science at


  1. Accelerating Digital Transformation to Drive Business Impact

  2. About Me ● Director Data Science, SparkBeyond 18 years in Data Science & Analytics, leading companies through their digital ● transformations. Professor of Data Science at NYU. ● 2

  3. SparkBeyond: If data is the new oil...

  4. SparkBeyond = Elastic Refinery People - Technology - Process

  5. Components of Digital Transformation Data (necessary but not sufficient)

  6. Components of Digital Transformation Data (necessary but not sufficient) Insight (necessary but not sufficient)

  7. Components of Digital Transformation Data (necessary but not sufficient) Insight (necessary but not sufficient) Action (no action, no impact)

  8. Components of Digital Transformation Organizational + Executive Alignment Data (necessary but not sufficient) Insight (necessary but not sufficient) Action (no action, no impact)

  9. Avoid Failure Points for Successful Transformations Common DT Failure Patterns/Solutions Anti-Pattern : IT + Data Science/Analytics not aligned in goals & priorities with business stakeholders, resulting in data and insights that don’t solve the right problems. Solution: Peg all IT, Data & Analytics investments with a business KPI in mind. Have business stakeholders share goals and prioritization. Anti-Pattern : Analytics research & insight discovery is slow with unpredictable outcomes Solution: Leverage technology where possible to boost productivity, and be agile. Goal is to fail fast or succeed quickly. Anti-Pattern : Organizations don’t operationalize their insights and models in a testable way to drive and measure impact. Solution: Define possible operational paths prior to starting any data and analytics projects. Don’t proceed unless there are viable paths.

  10. Avoid Failure Points for Successful Transformations Common DT Failure Patterns/Solutions Anti-Pattern : IT + Data Science/Analytics not aligned in goals & priorities with business stakeholders, resulting in data and insights that don’t solve the right problems. Solve with: People & Process Solution: Peg all IT, Data & Analytics investments with a business KPI in mind. Have business stakeholders share goals and prioritization. Anti-Pattern : Analytics research & insight discovery is slow with unpredictable outcomes Solve with: Technology Solution: Leverage technology where possible to boost productivity, and be agile. Goal is to fail fast or succeed quickly. Anti-Pattern : Organizations don’t operationalize their insights and models in a testable way to drive and measure impact. Solve with: People, Process & Solution: Define possible operational paths prior to starting any data and analytics projects. Don’t proceed unless there are viable paths. Technology

  11. Our Product Thesis - Accelerate Insights Many organizations get stuck in the Insights phase as a result of human cognitive bottlenecks, lack of data science resources, lack of data and the time to code up ideas. Discovery Platform • Generates millions of hypotheses in minutes • Connects the dots between disparate events and data sources • Discovers patterns, explanations, correlations in complex data • Focus on model transparency

  12. SparkBeyond, Enabling Digital Transformations INSURANCE FINANCIAL SERVICES PHARMACEUTICALS A ‘glass-box’ underwriting solution SparkBeyond created over 170 Discovered a novel technique increased automated drivers that were able to capture for colon cancer detection underwriting by 4x ; discovering 86% of the fraudulent cases through blood tests; developed who was surrendering from within the top 15% ranked cases a unique three-way partnership retirement accounts and why for a global services company between HMOs and drove $26m in impact . investigating fraudulent credit card pharmaceutical companies to payments. scale drug testing. RETAIL CPG TELCO / MEDIA A leading retailer optimized SparkBeyond improved a Major US telco was suffering from locations for the rollout of the partner’s annual gross churn and exhausted meaningful next 1,000 branches . margins by $6M patterns to predict who would SparkBeyond augmented the by identifying store segments leave. SparkBeyond generated client’s sales history with external where tailored pricing schemes $100m in impact by identifying datasets, identifying unexpected could be applied. over 20 new churn drivers in a drivers, such as the proximity to week covering 80% of churners. laundromats. 20 Most Promising Cognitive Entrepreneurial Company of the Year 2016 Machine Solution Providers 2017 2016 Award in ML Analytics in Oil Gas Intelligence 3.0 highlight

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