Organized Incoming Job Orders with AI - Liew Yen Thung

Issue: Unorganized incoming job orders in the business field of manufacturing  

Solution:  

Artificial intelligence (AI) can be a useful tool to improve accuracy and efficiency in handling the incoming jobs. An order taking app that applies and implements AI features can truly help the company be more productive and efficient when handling the job orders.  

First, Natural Language Processing (NLP) can be applied to the order taking app used by the company. The reason for this is NLP can automatically detect and extract the keyword from the job orders, such as quantity, parts required, and deadlines. For instance, named entity recognition is the main thing that helps to extract the information. Therefore, it can reduce the time-consuming for manual data entry and decrease the chance of human error occurring. Next, Machine Learning also should be included in the order taking app. ML has an algorithm that can be trained to recognize the patterns and categorize them according to the job type, customers and more. Thus, it helps workers to identify the job and route the orders to the right departments faster. 

 

References: 

Tripathi, P. (2023, December 12). How NLP-driven information extraction solution streamlines and optimizes the process? https://www.docsumo.com/blog/nlp-information-extraction 

What is natural language processing. MonkeyLearn Blog. (2020, February 26). https://monkeylearn.com/blog/what-is-natural-language-processing/#:~:text=In%20natural%20language%20processing%2C%20human,the%20same%20way%20as%20humans.