CIO Business Intelligence

NOVEMBER 21, 2023

CIOs need a way to capture lightweight business cases or forecast business value to help prioritize new opportunities. At the same time, CIOs, CISOs, and compliance officers need to establish a risk management framework to quantify when shadow IT creates business issues or significant risks.

IT 137

IT Risk Cost-Benefit Data Science 137

CIO Business Intelligence

JUNE 11, 2024

That definition was well ahead of its time and forecasted the current era’s machine learning and generative AI capabilities. Bigger steps include defining digital KPIs markedly different from IT system uptime and ticket-based metrics. Joanne Friedman, PhD and CEO of Connektedminds, takes a pragmatic approach to IT rebranding.

IT 136

IT Digital Transformation Broadcasting Business Objectives 136

DataRobot Blog

JULY 28, 2022

In addition to the accuracy of the models we built, we had to consider business metrics, cost, interpretability, and suitability for ongoing operations. Initially, the customer tried modeling using statistical methods to create typical features, such as moving averages, but the model metrics (R-square) was only 0.5 initial_value_guess.

Data Science 72

Data Science Machine Learning Statistics Modeling 72

DataRobot

APRIL 29, 2021

This year’s theme of The Hunt for Transformational Growth is designed to help organizations unleash the power of enterprise AI to improve forecasts, generate actionable insights, and unlock exponential growth for businesses worldwide. Eric Weber is Head of Experimentation And Metrics for Yelp.

Machine Learning 59

Machine Learning Experimentation Data Science Data-driven 59

IBM Big Data Hub

MARCH 4, 2024

This culture encourages experimentation and expertise growth. They understand that if one area of the business adopts AI while others lag or resist it (due to valid concerns), this exacerbates issues like Shadow AI, making it challenging to implement a holistic strategy.

Enterprise 96

Enterprise ROI Risk Strategy 96

DataRobot Blog

SEPTEMBER 30, 2022

By tracking service, drift, prediction data, training data, and custom metrics, you can keep your models and predictions relevant in a fast-changing world. Adoption of AI/ML is maturing from experimentation to deployment. How do you track the integrity of a machine learning model in production? Model Observability can help.

Slice and Dice 52

Slice and Dice Modeling Metrics Experimentation 52

Domino Data Lab

AUGUST 22, 2019

We need to take a brief break from natural language-specific content here to introduce a metric that will come in handy in the next section of the chapter, when we will evaluate the performance of deep learning NLP models. In that case, Calculating the ROC AUC Metric. The Area under the ROC Curve. 0.85 = 0.15. Yet, because 0.51

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

DataRobot Blog

FEBRUARY 15, 2023

Quite a few complex use cases, such as price forecasting, might require blending tabular data, images, location data, and unstructured text. This helps with getting more creative with your experimentation. The MLOps command center gives you a birds-eye view of your model, monitoring key metrics like accuracy and data drift.

Machine Learning 52

Machine Learning Modeling Cost-Benefit Metrics 52

Business Over Broadway

MAY 22, 2019

According to Gartner, companies need to adopt these practices: build culture of collaboration and experimentation; start with a 3-way partnership among executives leading digital initiative, line of business and IT. Juniper Research also forecasts that chat bots will save businesses about $8 billion annually by 2022.

Machine Learning 40

Machine Learning Technology Digital Transformation Data Science 40

O'Reilly on Data

JULY 28, 2020

The first step in building an AI solution is identifying the problem you want to solve, which includes defining the metrics that will demonstrate whether you’ve succeeded. It sounds simplistic to state that AI product managers should develop and ship products that improve metrics the business cares about. Agreeing on metrics.

Marketing 364

Marketing Experimentation Metrics Testing 364

The Unofficial Google Data Science Blog

OCTOBER 12, 2017

With more features come more potential post hoc hypotheses about what is driving metrics of interest, and more opportunity for exploratory analysis. We data scientists now have access to tools that allow us to run a large numbers of experiments, and then to slice experimental populations by any combination of dimensions collected.

Experimentation 62

Experimentation Testing Statistics Metrics 62

CIO Business Intelligence

MAY 20, 2024

In its planning role, budgeting is an annual forcing function with usually quarterly updates of rolling forecasts that assembles the latest knowledge. Instead, companies should use metrics other than budget targets for rewards. As a means of control, budgets measure performance against planned targets, influencing employee behavior.

Management 122

Management Interactive Measurement Marketing 122

Domino Data Lab

FEBRUARY 4, 2019

Spoiler alert: a research field called curiosity-driven learning is emerging at the nexis of experimental cognitive psychology and industry use cases for machine learning, particularly in gaming AI. Ensure a culture that supports a steady process of learning and experimentation. <3 <3 <3.

Data Science 66

Data Science Experimentation Machine Learning Data-driven 66

Occam's Razor

FEBRUARY 7, 2011

But each keyword gets "credit" for other metrics. The best option is to hire a statistician with experience in data modeling and forecasting. Brian Krick: Best way to measure and communicate "available demand" from available channels (social, search, display) for forecast modeling. Please see the advice above.

Analytics 94

Analytics Measurement Metrics Predictive Analytics 94

CIO Business Intelligence

FEBRUARY 5, 2025

Customer experience optimization, supply chain forecasting, demand prediction, and preventive maintenance tend to yield quick wins, he says. The first step is to define the metrics, says Scott Willson, a tech evangelist at ServiceNows multi-instance management platform xtype.

Cost-Benefit 117

Cost-Benefit ROI Metrics Measurement 117

CIO Business Intelligence

MAY 6, 2025

Ive seen clients use predictive models to forecast sales pipeline health, identify fraud risk in real-time, or assess which patients are most likely to be readmitted post-discharge. These capabilities are no longer theoretical or experimental. Its a symptom of needing one. What will happen? What should we do?

Prescriptive Analytics 78

Prescriptive Analytics Predictive Analytics Descriptive Analytics ROI 78