Remove Data Collection Remove Measurement Remove Metrics Remove Uncertainty
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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.

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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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Measuring Validity and Reliability of Human Ratings

The Unofficial Google Data Science Blog

E ven after we account for disagreement, human ratings may not measure exactly what we want to measure. Overview Human-labeled data is ubiquitous in business and science, and platforms for obtaining data from people have become increasingly common. And for thousands of years, measurement was as simple as this.

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Viral, Social, Sentiment, Mobile: 4 Delightful Web Analytics Solutions

Occam's Razor

Let's go look at some tools… Measuring "Invisible Virality": Tynt. Please click on the above image for a higher resolution version , including all the other metrics.]. In the last month data was copied off one of my posts 5,616 times, with most of it being content and some of it images. People matter.

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Human-centered design and data-driven insights elevate precision in government IT modernization

IBM Big Data Hub

Government executives face several uncertainties as they embark on their journeys of modernization. How to quantify the impact : Quantify, articulate and measure the expected long-term benefit of a capability to justify the investment. Through the analysis of collected data, potential opportunities for improvement are uncovered.

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Responses to Negative Data: Four Senior Leadership Archetypes.

Occam's Razor

Sadly still, negative data to the person/team receiving it. A decade ago, data people delivered a lot less bad news because so little could be measured with any degree of confidence. In 2019, we can measure the crap out of so much. Why be hurtin’? It is a lot of stuff! To provide context.

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Product Management for AI

Domino Data Lab

Companies with successful ML projects are often companies that already have an experimental culture in place as well as analytics that enable them to learn from data. Ensure that product managers work on projects that matter to the business and/or are aligned to strategic company metrics. That’s another pattern.