Utilization of advanced data analytics could help achieve this goal, although, a myriad of companies still don’t use it.

By detecting the priorities and problems that enterprises had faced before they proceeded to implementing advanced analyses, Big Data and machine learning, the new study found out that 30% of respondents identified the need to respond to the customer more quickly, accurately and with the option of individual approach to be crucial.

Logility and APICS interviewed more than 1 000 supply chain providers and found out that the effort to deal with customers’ orders doesn’t match the fact that most companies still use spreadsheets and old systems that don’t enable transparency and visibility of Big Data nor highlight opportunities and potential risks.

“Organizations can quickly become overwhelmed by the vast amount of data today’s enterprise systems, connected devices and social networks create,” said Allan Dow, president of Logility, to mhlnews.com. Dow pointed out that companies can get significant benefits from advanced analytics platform to make smarter decisions faster through greater transparency and predictive and prescriptive technologies.

“Through the innovative use of artificial intelligence and machine learning, we are able to better understand the dynamics that impact business, quickly uncover new opportunities and enhance customer service,” Dow added.

Several Research Outputs:

  • 36% respondents identify the opportunity to optimize their inventory as a top driver for their analytics initiative
  • 30% highlighted the need for faster responding to customers
  • 28% would like to interconnect data from multiple systems in order to achieve complete supply chain transparency
  • 19% of respondents stated that they want to leverage machine learning and predictive technologies to improve their company’s forecast accuracy