Big Data for supply chain management in industry 4.0

(0)0. Big Data for supply chain management in industry 4.0.

2 elements. To provide justified recommendations for the technology that is needed to support the company R ecommendations on how the business may make best use of the information generated by these systems..

The problem. Not propose specific recommendations for the technology needed to support the company which is in need of a data analytics tool.

Illustration. retailers might conduct research on how other enterprises make use of sentiment analysis or AI recommendation engines to develop their customer experience, or a financial services business might be more in need of fraud detection tools. Examples and statistics could be used to make the situation analysis more precise and understandable..

The problem. Specific codes of action were not listed out for the chosen company to take best use of the information generated by the systems.

Solutions. Identify the goal and priority Select and present appropriate data Research, analyze and made conclusion from that selected data Design a well-constructed strategy Measure the success and conduct repetition.

REFERENCE. Gai , P. J., & Klesse , A.-K. (2019). Making recommendations more effective through framings: Impacts of user- versus item-based framings on recommendation click-throughs. Journal of Marketing, 83(6), 61–75. Retrieved from https://doi.org/10.1177/0022242919873901 Wood, M. (2009). The pros and cons of using pros and cons for multi-criteria evaluation and decision making. SSRN Electronic Journal. Retrieved from https://www.researchgate.net/publication/228255043_The_Pros_and_Cons_of_Using_Pros_and_Cons_for_Multi-Criteria_Evaluation_and_Decision_Making ..