article thumbnail

MRO spare parts optimization

IBM Big Data Hub

Many asset-intensive businesses are prioritizing inventory optimization due to the pressures of complying with growing industry 4.0 2 Unless your demand forecasting is accurate, adopting a reactive approach might prove less efficient. Do you have purpose-built algorithms to improve intermittent and variable demand forecasting?

article thumbnail

AI adoption accelerates as enterprise PoCs show productivity gains

CIO Business Intelligence

Like other CIOs, Katrina Redmond has been inundated with opportunities to deploy AI that promise to speed business and operations processes, and optimize workflows. At Eaton, for example, an AI-based sales forecasting tool has the potential to boost productivity dramatically. We want to maintain discipline and go deep.”

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Addressing cloud waste: 4 steps to cloud computing cost optimization

CIO Business Intelligence

The Azul State of Java Survey and Report 2023 , an independently run study of more than 2,000 Java users, found that 90% of companies with applications built in Java, the most prominent programming language used to build enterprise applications, are deploying in a public, private, or hybrid cloud environment.

article thumbnail

Reference guide to build inventory management and forecasting solutions on AWS

AWS Big Data

Forecasting is another critical component of effective inventory management. Accurately predicting demand for products allows businesses to optimize inventory levels, minimize stockouts, and reduce holding costs. However, forecasting can be a complex process, and inaccurate predictions can lead to missed opportunities and lost revenue.

article thumbnail

Dataiku Leveraged for Cash Flow Forecasting

Dataiku

Not only can organizations leverage data science and machine learning for things like time savings, more efficient processes, and cost optimization, but they can also use it for fully automated cash flow forecasting that can produce results precise enough for the modern enterprise and a changing environment.

article thumbnail

The impact of AI on edge computing

CIO Business Intelligence

Enterprises are moving computing resources closer to where data is created, making edge locations ideal for not only collecting and aggregating local data but also for consuming it as input for generative processes. over the 2023-2027 forecast period 1. Bandwidth optimization. over 2023 2. Security and privacy.

article thumbnail

Generative AI use cases for the enterprise

IBM Big Data Hub

The best option for an enterprise organization depends on its specific needs, resources and technical capabilities. Product development : Generative AI is increasingly utilized by product designers for optimizing design concepts on a large scale.