• September 12, 2018

How Major Retailers Are Hitting 99% Data Accuracy

  • By admin
Written by Yiping Hao, September 11, 2018

In today’s innovative, automated and connected world, there is no excuse for the retail industry not to have accurate data. Whether it be own brand product development, quality and supplier information or sample, production and delivery status, it’s imperative to have accurate own brand information flowing through the end-to-end supply chain process.

What causes data inaccuracies?

Retailers work very closely with multiple suppliers in multiple locations around the world, each with their own disparate systems and processes, which makes it very difficult to have one version of the truth. Disparate systems and processes also make it very hard to collaborate and share information, which causes outdated and inaccurate information to be used at times by the various teams responsible for bringing new products to market – Merchandising, Product Development, Procurement, Supplier Compliance, Quality and Logistics. Data inaccuracies will negatively impact the production schedule, on-time deliveries, among other business impacts such as but, not limited to the following:

  • Loss of Market Share – Product development, quality or supplier misinformation can lead to missed, “must arrive by dates”, resulting in customers meeting their needs elsewhere.
  • Increases in returns, exchanges, recalls and consumer dissatisfaction. Data inaccuracies cause labeling mistakes, product quality issues and can become very costly when it comes to a monetary value or damage to the brand.
  • Legal Issues – Inaccurate supply chain data can lead to consumer safety issues, injuries or even sometimes death, resulting in major lawsuits in impacts to the brand.

How important is data accuracy to the retail brand and consumers?

Data Integrity refers to the fact that data needs to be maintained – kept up-to-date and reliable over the course of the entire retail product lifecycle (Retail PLM). Data integrity has been seen as a serious issue for retailers over the past few years, due to the fact that many internal retail teams and consumers rely on correct information. Retailers make business decisions and consumers make buying decisions based on accurate product data and attributes. Other uses for product and supplier data are:

 

  • Forecasting – Measuring business performance and making sales predictions.
  • Planning Coverage – Deciding resource utilization and Allocations.
  • Intelligence – Gathering the satisfaction of customers and partners.

Dynamic real-time data integrity helps decision makers to strengthen retail performance and success in competitive markets. Using accurate and reliable data to analyze product development, sourcing, quality and suppliers is a crucial part for retailers to make important and efficient business decisions.

How to improve data accuracy through the entire end-to-end supply chain

In order to create profitable products that also satisfy consumers’ demands, retailers need collaboration-building insight, gathered across business silos and the extended supply chain. Thus, many retailers are beginning to discover that the latest innovations in Product Lifecycle Management (Retail PLM) are combining, Retail Sourcing, Supply Chain Lifecycle Management and Product Information Management (PIM) all on one holistic solution. This innovative PLM/PIM/SCM hybrid system could support useful supply chain insights and greatly improve whole chain data accuracy and integrity to maximize efficiency and accuracy and at the same time, minimize the impact and cost of supply chain data dysfunction. To learn more about today’s 99% data accuracyproduct lifecycle management (retail PLM) and supply chain management (SCM) tools or for more information about CBX Software please Contact Us and if you like what you read, please follow CBX on LinkedIn.

Written by Yiping Hao, September 11, 2018
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