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Forecasting uncertainty at Airbnb

O'Reilly on Data

Theresa Johnson outlines the AI powering Airbnb’s metrics forecasting platform. Continue reading Forecasting uncertainty at Airbnb.

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The Lean Analytics Cycle: Metrics > Hypothesis > Experiment > Act

Occam's Razor

To win in business you need to follow this process: Metrics > Hypothesis > Experiment > Act. We are far too enamored with data collection and reporting the standard metrics we love because others love them because someone else said they were nice so many years ago. That metric is tied to a KPI.

Metrics 157
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What you need to know about product management for AI

O'Reilly on Data

Machine learning adds uncertainty. Underneath this uncertainty lies further uncertainty in the development process itself. There are strategies for dealing with all of this uncertainty–starting with the proverb from the early days of Agile: “ do the simplest thing that could possibly work.”

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Highlights from the Strata Data Conference in San Francisco 2019

O'Reilly on Data

Forecasting uncertainty at Airbnb. Theresa Johnson outlines the AI powering Airbnb’s metrics forecasting platform. Watch " Forecasting uncertainty at Airbnb.". Watch " Winners of the Strata Data Awards 2019.". It’s in the game: A rare look into how EA brought data science into the creative process of game design.

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iostudio delivers key metrics to public sector recruiters with Amazon QuickSight

AWS Big Data

Our previous solution offered visualization of key metrics, but point-in-time snapshots produced only in PDF format. In this post, we discuss how we built a solution using QuickSight that delivers real-time visibility of key metrics to public sector recruiters.

Metrics 98
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3 ways to avoid the generative AI ROI doom loop

CIO Business Intelligence

Make ‘soft metrics’ matter Imagine an experienced manager with an “open door policy.” Meaningful improvement is likely to include some quantifiable metrics like time savings or employee satisfaction. He specializes in removing fear, uncertainty, and doubt from strategic decision-making through empirical data and market sensing.

ROI 72
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AI Product Management After Deployment

O'Reilly on Data

Ideally, AI PMs would steer development teams to incorporate I/O validation into the initial build of the production system, along with the instrumentation needed to monitor model accuracy and other technical performance metrics. But in practice, it is common for model I/O validation steps to be added later, when scaling an AI product.