6 Manufacturing Problems ERP Solves Manufacturers face various challenges every single day. The challenges may vary from one manufacturer to another. However, there are common problems facing all the manufacturers alike. Some of these issues can be addressed using personalized company policies or well-designed SOPs (Standard Operating Procedures) while others can be addressed by implementing […]
Another Christmas has come and gone, which means it’s time to bring in the new year! The mark of a new year is always an exciting time of hope and anticipation for what the new year will bring. Like every year Nucleus has released what it anticipates for the next year in the technology world. Read this article to learn about some of those predictions.
- 1. The End of On-Premise Security Superiority
You read right, Nucleus predicts that cloud security naysayers will disappear in 2017. This may sound a little far-fetched at first, but when you consider the fact that 2016 has been a big year for cloud computing you will understand why. One of those reasons 2016 was the year for cloud computing is that it has been a turnaround year for many consumer’s perceptions of the cloud’s safety and privacy. A prime example of this is how a top tier business software company, Microsoft, came out with a new, completely cloud-based solution, Dynamics 365. And as such is poised to be one of the first tech companies to reach 1 trillion in market capitalization. Read more
What is Machine Learning?
Machine learning is a type of artificial intelligence that analyzes previously collected data and statistics to learn normal behavior. The purpose of machine learning is to promote positive customer experiences by learning what they like and automatically present the more desirable function or item.
If you use the Internet, chances are that you have already been subject to machine learning. Major companies such as Google, Facebook, and Amazon have already benefited from using this method on their customers. To better understand how machine learning works, let’s examine how much machine learning effects our everyday lives.
A recent Google survey hosted by AmeriQuest has uncovered an unfortunate truth some manufacturers may not want to admit — their business has a dysfunctional procurement process. When I say dysfunctional I don’t mean everyone argues about purchasing to the point of needing a therapy session – at least I certainly hope that’s not the case. What I mean is that there is a lack communication, visibility and sometimes a plan for procurement altogether.
In theory, one might think that the process of procurement should be easy. All you’re doing is finding a good vender for acquiring raw materials for your products, right? Sure it is, as long as it’s also a reliable resource, the materials fit into your budget, it’s in a good location for cheap, timely transportation to your warehouse, and the materials they send are up to quality standards. Many manufacturing companies don’t have a lot of time to waste on finding and negotiating with potential vendors. This usually leaves them to settle for a “good enough” vendor.