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How to Move from Real-Time Data to Real-Time Decisions

CIO Business Intelligence

Hubbard defines measurement as: “A quantitatively expressed reduction of uncertainty based on one or more observations.”. This acknowledges that the purpose of measurement is to reduce uncertainty. And the purpose of reducing uncertainty is to make better decisions. I call this point data saturation.

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Process Excellence: A transformational lever to extreme automation

IBM Big Data Hub

An efficient sustainable supply chain process with optimized CO2 footprint is an enterprise requirement as well as a societal need. It requires a combination of capabilities around process optimization. Process excellence is an intersectional play in the age of digital transformation.

KPI 66
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What are decision support systems? Sifting data for better business decisions

CIO Business Intelligence

A DSS supports the management, operations, and planning levels of an organization in making better decisions by assessing the significance of uncertainties and the tradeoffs involved in making one decision over another. Types of decision support system In the book Decision Support Systems: Concepts and Resources for Managers , Daniel J.

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CIOs press ahead for gen AI edge — despite misgivings

CIO Business Intelligence

If anything, 2023 has proved to be a year of reckoning for businesses, and IT leaders in particular, as they attempt to come to grips with the disruptive potential of this technology — just as debates over the best path forward for AI have accelerated and regulatory uncertainty has cast a longer shadow over its outlook in the wake of these events.

Risk 129
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Building Tax Planning into Enterprise Risk Management Strategies

Jet Global

Tax planning is playing an increasingly important part in corporates’ enterprise resource management (ERM) strategies, driven by the many uncertainties created by political, economic, and pandemic-related trends. Book a demo, or drop us a line.

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How to create a culture of innovation

CIO Business Intelligence

One instance of how that exploration led to real business benefits was with the application of machine learning to predict optimal product formulation using a set of desired consumer benefits. The team was given time to gather and clean data and experiment with machine learning models,’’ Crowe says.

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

Occam's Razor

Sometimes, we escape the clutches of this sub optimal existence and do pick good metrics or engage in simple A/B testing. This thought was in my mind as I was reading Lean Analytics a new book by my friend Alistair Croll and his collaborator Benjamin Yoskovitz. You're choosing only one metric because you want to optimize it.

Metrics 156