Answering the question of what Supply Chain Management is, is as simple as breaking down the phrase into its component parts. Supplies are those inputs that a company relies upon to produce the product that will ultimately reach its customers. The chain is the group of suppliers that bring those inputs to a company and the process whereby those inputs are integrated into the company.
And finally, management is the coordination and organization of all these inputs and their implementation. So put
We have visited all the ERP functional areas during this journey and discovered how Artificial Intelligence gives its strength in suggestions, automation, and metric calculation, empowering every specific operation.
In this chapter, we will flush out how AI can even be part of all standard features. Text search and document storing can elevate to the next level of quality.
Independently from the feature, the most optimisable work on ERP is fulfilling fields of a form. Ma
The ERP's Project Management area enables the company to shape, follow, and predict long term plans. It delivers efficient orchestration of resources and actions for adapting to the occurrences happening during the project's development.
The human feeling in choosing the reaction to them, together with the calculations offered by AI for all the possible counteractions with costs and delays, offer the best collaboration for achieving the best performing administration of the company's program
Human capital is a crucial area in the ERP because it represents the engine of the company. Lately, some organisations have started a new strategy in recruiting involving AI.
Alternatively, people management needs always the usage of human choices. Let's see how artificial intelligence will provide practical insights for helping in human decisions.
The AI Recruiter
Artificial intelligence is increasingly amalgamating into recruiting processes: from CV classification to interview tagging.
During my many years in ERP implementation, I have observed this. Many companies approach ERP Implementation from a project mindset, not with a transformational vision.
What is the difference?
Project mindset asks the question 'How do I complete this project'. This mindset comes from the word 'Project' itself which evokes the idea of something with a start and end date like constructing a building or a mall or a new product. The goal is to erect that construction or deliver the product.
The best way to fail at an Enterprise Resource Planning (ERP) implementation is to choose the wrong software up front. Choosing software without following some basic guidelines is a sure-fire method for disaster. Probably the worst thing that someone has done (that we know of), was to buy their ERP software at a tradeshow, thinking it would be the cheap and easy way to solve their problems. They ended up spending more than they expected in finding ways to force the software into their business.
Financial management is the primary area of an ERP. It provides the tools for letting your company perform its work. Money availability is essential for personnel wages, for purchasing items to be sold, for parts you need to assemble into your products.
The journey reaches out to this ERP's section explaining the potential of Machine Learning in providing weighted suggestions supported by collected measurement. It sustains human choice with valued metrics.
Cash flow best fit
The service and maintenance area of the ERP is responsible for keeping up customer satisfaction minimising their downtime. Also, it assures the standard level of functionality by performing maintenance plans.
On the other hand, it involves order management, logistic, personnel organisation, contract management and customer care. Let's see how Artificial Intelligence can help here.
On-site service optimisation
The service on-site requires intelligent coordination of times, resources and l
The logic of stocks is complex. Starting from the management of (non-) perishable items with techniques like LIFO (Last-In-First-Out) or FIFO(First-In-First-Out), continuing with logistic costs, going ahead with lost, damaged, stolen or expired items, etc.
The warehouse people are the last line of quality assurance for sold items and purchased ones. On the other side, they are responsible for counting them and giving a consequenced value of the warehouse.
ML in choosing where and how to st
Optimising the bill of materials is a constant work in progress. Because of articles that supplier sometimes changes, sometimes evolves, sometimes dismisses. On the other hand, you also want to cut costs and adapt some of your items to more standardised ones.
If we look at this process more in the abstract, it comes out that it is a typical application of a machine learning pattern. Let's see how the implementation could help the production.
The bill of material is only part of
The purchasing area inside a company is pretty delicate. It involves investments, can cause delays or can bring to wasting unsold items that become outdated. The human feeling in choosing the time, the quantities and the supplier is the crucial side.
The aid of AI here focuses on giving the confidence of the evaluated metrics fine-tuned by specific parameters.
A different approach to orders
Machine learning here helps in the entire decision process. Firstly, it calculates customer orders
The first thought that jumps to mind when the main topic is customer care associated with AI is RPA (Robotic Process Automation). It is impersonated in most cases by a small icon, usually on the bottom right of a web page showing that you have an incoming message in the chat.
The implementation of Artificial Intelligence applied to the customer care area of an ERP is, of course, not only a bot. Let's discover this world with this fourth episode of our journey.
The sales manager returns with a signed contract. And the dance starts. The order gets into the ERP, then the production process runs. The logistic prepares the shipping, and the item arrives at the customer.
It looks like a simple workflow. Even so, it involves several people, several steps and several checkpoints.
The journey continues with the billing phase.
Predictions and proactive actions
The acquisition of a new customer is a trigger for many automatic procedures. For example, t
Selling is a profession with which only a few people can deal. It is frustrating. A sales manager gets so many Nos per day like every other person in an entire year. The good ones know that the low number of Yeses bring the prize, the commission. That's why they focus on them. They crave the Yes.
The best friend of the sales manager is ERP. It is perfect for collecting all the information regarding the customer and recovers the historical data precious for understanding the type of customer.
Doing marketing is an art. It is a delicate choice of timing, approaching method, and content based on empathy.
The path is long, from a description of a product or a service to a list of offers signed by newly acquired customers.
Let's start our journey with you. Your company is B2B, produces appliances for shops used for entertainment and advertising.
Your product is a device connected to the internet that automatically selects the background music and images and alternates them with the a
Following this article (https://erpcommunity.com/articles/ai-in-erp), it starts hereabout a journey in exploring ERP areas.
The subdivisions will be:
The creation of advertising campaigns will be the essence topic. Functionalities like the content list for storing the outbound articles, tv/radio recordings, etc. The branding strategies for specific products or product lines. Contact collection and benchmarking.
The sales manager consumes the forms for refining prospect inf
This idea came to my mind just starting this new year. After reading a Gartner's research reporting, organisations struggle to generate ROI supporting sets of specialised and isolated AI projects (see this LinkedIn post: https://www.linkedin.com/posts/francesco-mataloni_ai-dataops-modelops-activity-6752131020398616576-4Yrl) the concept flowered.
Doubtless, Artificial Intelligence will agitate the future of most of the software. We all know that its first application is to cut out the most repea
As UX designers, we’d all like our users to say that our apps are intuitive, easy to learn and use, and powerful without being overwhelming.
The problem is that these statements don’t convey anything to you, the designer, on how to actually achieve them. Just how do you make a UI intuitive? What makes an app easy to learn and use versus difficult, and precisely how do you give an app the power it needs to satisfy all its user’s functional requirements, without
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