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Inventory Analytics(으)로 돌아가기

러트거스 뉴저지 주립 대학교의 Inventory Analytics 학습자 리뷰 및 피드백

4.5
별점
171개의 평가

강좌 소개

Inventory analytics is the corner stone of supply chain analytics. A company in trade industries may have 30-50% of their assets tied up in inventory. An effective inventory management can improve revenue by increasing product variety and availability, and reduce cost and speed up cash cycle by reducing excessive inventory and waste. Through real-life examples (e.g., Amazon vs. Macy’s), you will learn hands-on tools and skills to discover and solve inventory problems by data analytics. Upon completion, you can answer the following questions: 1. For which industries is inventory important? 2. How may inventory drive a company’s financial performance? 3. How do I know that I have an inventory problem? 4. How to classify inventory and manage it accordingly? Note: This course is for beginners and thus focuses more on discovering inventory problems than solving them. It is my belief that discovering a problem and knowing which directions to go is at least equally important as solving the problem. We are planning to launch new courses or expand this course to cover more sophisticated inventory solutions in the future - thank you....

최상위 리뷰

S

2020년 7월 2일

This is an excellent course for those who would like to get the exact knowledge of how inventory is classified and its importance in industry

MA

2021년 4월 1일

I have gained tangible knowledge through this course. It is one of the best courses I have studied in Coursera Platform.

필터링 기준:

Inventory Analytics의 30개 리뷰 중 26~30

교육 기관: Vishal R S

2021년 3월 27일

More case studies needed

교육 기관: Shrikant P

2020년 7월 12일

Good

교육 기관: Fabiola R W

2020년 11월 13일

Just fine, not exceptional. Has some pretty basic concepts, maybe I would have liked to dig somewhat deeper in them.

교육 기관: Adrian S

2021년 3월 4일

no me fue posible continuar por el idioma, ni tenia la facilidad de subtítulos o alguna herramienta que me ayudara a traducir.

교육 기관: Jacob J R

2022년 5월 28일

did not understand one thing.