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What AI and Machine Learning in Cloud ERP Means for Businesses
Finding and implementing the right cloud ERP solution that embeds Artificial Intelligence and Machine Learning within its core offering may mean the difference between business growth and stagnation.
From limited access rights to a proprietary system (which means other applications, tools, and services can’t access it), businesses have essentially been handcuffed.
A Forbes post, 10 Ways to Improve Cloud ERP with AI and Machine Learning, hits on a key problem for businesses running on legacy ERP systems, and that’s the inability of their technology to provide the data and the insights modern businesses need to survive in today’s digital economy.
However, and as mentioned earlier, choosing the right cloud ERP solution and vendor are imperative if a business wants to achieve these results, and Acumatica’s cloud ERP solution is worth a look.
There are scenarios where we’re offering features powered by ML that our users can offer to their customers and other scenarios that are productivity driven, such as helping businesses catch errors before they occur (e.g.
“AI is the simulation of human intelligence processes by machines, especially computer systems.” It goes on to say that the process includes “learning, reasoning, and self-correction…without human intervention.” This doesn’t mean the human element is taken out completely.
“While most ERP systems feature dashboards that can provide real-time information on everything from inventory turnover to employee productivity, dashboards can’t tell you when to re-order inventory or hire your next employee.
But ML can take data gathering one step further and help [businesses] reduce repetitive tasks and make more strategic business decisions.” You can download the Acumatica Summit 2019 Keynotes (specifically Day Two at the 1:00 mark) to see exactly what Acumatica has been doing with AI and ML, including a demonstration of a Google Cloud Vision Product Search that highlights ML within Acumatica as well as the Acumatica Alexa for Business capability, using Natural Language input to accomplish real work, such as looking up inventory and approving expense claims (you can see more during the Day Two Keynote at the 1:20 mark).
Demand Planning Software
Demand planning and forecasting software is used across industries by businesses of all sizes.
Some vendors offer a complete supply chain planning suite with features such as inventory and replenishment planning, while others offer demand planning as an add-on or standalone feature.
This buyer’s guide aims to help you understand the features and functionality of demand planning and forecasting software in order to help you during the software selection process.
This type of system accomplishes the task by improving forecasting governance in order to eliminate errors or biases in the data and also by reducing data latency, which makes real-time demand planning possible.
To tackle these challenges and maintain visibility and connectivity across the entire supply chain, many demand planning and forecasting software solutions offer a digital monitoring feature that provides real-time updates.
Rather than having to purchase an entirely new system that covers every aspect of business operations, many buyers now seek solutions that allow them to easily import data, such as procurement, sales and operations, from their pre-existing software into the new solution without requiring extra manual effort.
As a result, business intelligence software vendors with predictive analytics capabilities have started offering demand planning and forecasting software for supply chain application.
In addition to controlling costs, trend analysis features can generate forecasts by capturing historical data and combining it with data related to seasonal variation and promotions.