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10 AI strategy questions every CIO must answer

CIO

Many CIOs have work to do here: According to a September 2024 IDC survey, 30% of CIOs acknowledged that they dont know what percentage of their AI proofs of concepts met target KPI metrics or were considered successful something that is likely to doom many AI projects or deem them just for show. What ROI will AI deliver?

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Is your IT service management strategy empowering your employees or getting in their way?

CIO

Average First Assign Time: Also known as ‘in-queue’ time, this KPI measures the time taken to assign a new ticket to an agent. A high ‘in-queue’ time could indicate an understaffed IT service delivery team or ineffective assignment algorithms.

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Mitigating cyber risks: the essential role of collaboration for Middle East organizations

CIO

He further noted that building a culture of cybersecurity is a key performance indicator (KPI) for leadership teams, reinforcing the idea that securing the organization is a cultural challenge as much as a technical one. We need to ensure open communication and alignment across departments to protect our organization,” Mosa said.

KPI 402
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PepsiCo transforms for the digital era

CIO

Every data set, every data KPI, or every data field is as important as the app,” she says. What we are trying to do is operationalize all our analytics and algorithmic libraries.” Yes, the data is key. But the big unlock is MLops. The importance of using AI for data ops is critical.

KPI 543
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The Milkman always delivers via efficient and green last-mile operations

CIO

Since then, much has changed, but the last-mile delivery KPI remains: “deliver on expectations.” Snug in bed, you could hear the glass bottles clinking in those old wire milk baskets as he replaced your empties with full ones. You could count on it like birdsong. Or, why it didn’t arrive at all?

Retail 366
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13 power tips for Microsoft Power BI

CIO

AutoML suggests what columns of data to use for the model, selects and tunes the algorithm automatically, and includes the performance and reliability of the model created, along with what features influence the predictions it makes for which products are most likely to be out of stock at particular distribution centers.

Matrix 476
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Deciphering Value Points Of Salesforce Einstein Analytics With Big Data

Smart Data Collective

Then, once the data points are collected, the system starts processing them using sophisticated machine learning algorithms to analyze the data to find the patterns and interconnections. After the learning phase is finished, we are ready to receive insights. When it comes to Marketing Cloud, it also has things to offer.

KPI 310