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CIO risk-taking 101: Playing it safe isn’t safe

CIO Business Intelligence

As CIO, you’re in the risk business. Or rather, every part of your responsibilities entails risk, whether you’re paying attention to it or not. There are, for example, those in leadership roles who, while promoting the value of risk-taking, also insist on “holding people accountable.” You can’t lose.

Risk 116
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Top 15 Warehouse KPIs & Metrics For Efficient Management 

datapine

This is no different in the logistics industry, where warehouse managers track a range of KPIs that help them efficiently manage inventory, transportation, employee safety, and order fulfillment, among others. It allows for informed decision-making and efficient risk mitigation. Let’s dive in with the definition.

Metrics 217
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Is it worth measuring software developer productivity? CIOs weigh in

CIO Business Intelligence

This has spurred interest around understanding and measuring developer productivity, says Keith Mann, senior director, analyst, at Gartner. Therefore, engineering leadership should measure software developer productivity, says Mann, but also understand how to do so effectively and be wary of pitfalls.

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Whether your technology is new or old, lifecycle management is key

CIO Business Intelligence

Business needs first, then the lifecycle management program Your infrastructure lifecycle management program should be aligned with your organization’s growth roadmap. This will involve comprehensive and proactive infrastructure management. This creates risk for the company, shareholders, customers and their brand.

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The steep cost of a poor data management strategy

CIO Business Intelligence

Such is the case with a data management strategy. That gap is becoming increasingly apparent because of artificial intelligence’s (AI) dependence on effective data management. For many organizations, the real challenge is quantifying the ROI benefits of data management in terms of dollars and cents.

Strategy 116
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How to use foundation models and trusted governance to manage AI workflow risk

IBM Big Data Hub

As more businesses use AI systems and the technology continues to mature and change, improper use could expose a company to significant financial, operational, regulatory and reputational risks. AI governance refers to the practice of directing, managing and monitoring an organization’s AI activities.

Risk 76
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The Ultimate Guide to Modern Data Quality Management (DQM) For An Effective Data Quality Control Driven by The Right Metrics

datapine

1) What Is Data Quality Management? 5) How Do You Measure Data Quality? However, with all good things comes many challenges and businesses often struggle with managing their information in the correct way. Enters data quality management. What Is Data Quality Management (DQM)? Table of Contents.