Hello Everyone,
My chosen field and degree are the same (Business Administration and Entrepreneurship). A
file's information is sorted, stored, accessible, analyzed, and interpreted by knowledge
management systems and software. If I were to adapt KMS (knowledge management
systems/software) to my chosen business (the fashion industry), for instance, it would be similar
to the case study with a few minor adjustments. For instance, I am the only one controlling
everything. Specifically, this refers to placing orders with manufacturers, getting orders from
manufacturers, receiving orders from clients, packing orders, shipping products to clients,
handling refunds, etc. Without KMS, I would be more prone to mistakes and less cost-effective. I
could have an automatic database with KMS. Put this in a hypothetical situation. If I had an
automated database or system within my website, my system could automatically place an order
to my manufacturers anytime I was low on stock for a certain item (this would also allow a paper
trail with dates, price, order number, quantities, etc.) Another situation can be when orders are
packaged. I could have my website automatically fill in the address, order number, total amount,
products, and name when the consumer puts their purchase rather than having to manually type
everything in. In that situation, I could just push a button to have my label maker print out the
package's label with all the necessary information already printed on it (this could also work for
returning customers since their information would register in the system). The manual work is
halved as a result. Using KMS, I was able to learn what my consumers liked, where they were
(for shipping purposes), and what they didn't. Because information is gathered and converted
into data after being processed and stored, data and information are related to one another. For
instance, once clients keep ordering from my company, I may determine which colors, sizes, and
styles are most popular. When I get this data, I may classify it into categories like "most
favored," "least preferred," and "not selling." I'll be able to examine and interpret the data using
this information. I can boost the supply of an item or description if I find that tiny and extra small
versions of it are selling well. I can reduce the amount of stock in another item if sales are weak
(and potentially increase stock in an item that is popular). This enables me to increase my
competitive edge while maintaining cost effectiveness.
