Measurement Metrics Optimization Uncertainty 
O'Reilly on Data
JUNE 15, 2023
If we want prosocial outcomes, we need to design and report on the metrics that explicitly aim for those outcomes and measure the extent to which they have been achieved. The creators of generative AI systems and Large Language Models already have tools for monitoring, modifying, and optimizing them.
Occam's Razor
APRIL 8, 2013
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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Smart Data Collective
AUGUST 19, 2021
Businesses worldwide, especially SaaS businesses, have discovered that smart, measurable content marketing is the key to achieving their business goals. Then, you can simply plan, create, measure, optimize and repeat. Analytics helps you to know who exactly is reading your content and helps you optimize for them.
O'Reilly on Data
MARCH 31, 2020
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.”
The Unofficial Google Data Science Blog
APRIL 23, 2024
the weight given to Likes in our video recommendation algorithm) while $Y$ is a vector of outcome measures such as different metrics of user experience (e.g., Crucially, it takes into account the uncertainty inherent in our experiments. the fraction of video recommendations resulted in positive user experiences).
Jedox
DECEMBER 17, 2020
As businesses around the world look to move past the uncertainty and unprecedented change of 2020 and toward a fresh start in 2021, the discussion around FP&A maturity has been renewed. A: “The maturity curve is essentially a measure of efficacy for the FP&A function. It has two main purposes.
Andrew White
DECEMBER 16, 2019
After sifting through several year’s worth of formally written data, analytics, and data and analytics strategies, we found about 85% of them did not include a measurable business outcome. See Data and Analytics Strategies Need More-Concrete Metrics of Success. The article notes this as cognitive uncertainty. It’s called ROAR.
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