Addressing Data Governance Challenges in Retail

Over the past decade, the retail industry has undergone significant transformation and continues to evolve. Among a series of changes that have impacted the retail landscape, the role of data has been one of the most significant. For retailers, data has always been integral to making intelligent business decisions; however, increasing data types and volumes have threatened the process. Many things are changing, including the tools used to store and utilize data.

Speaking of data utilization, retailers should tap the potential of technology to meet consumer expectations because personalization is key to keeping customers engaged. A study by Accenture concludes that more than 75% of customers have higher chances of buying from retailers that offer personalized shopping experience and 52% may switch brands if the retailer fails to do so.

Understanding data’s relevance in retail

Data is important in the retail industry as it allows businesses to view the consumers as individuals, identify opportunities that help improve efficiency across the supply chain and realize the impact of marketing on prospects.

Data quality impacts brand value, logistics, sales, and customer experience. According to Vend’s Retail Trends and Predictions 2019, retailers should listen to what their data tells them about customers so they can strategize better. In today’s world of retail, data related decisions require real-time input from all the data sources in a company.

Data’s relevance in retail is further evidenced through efficiency improvements – ranging from high-impact marketing initiatives to growing competition. Yet, businesses fail to capitalize on data and struggle to make the leap from insights to tactical business decisions that bring value.
The retail ecosystem is complex. New varieties of data, such as sensor data, social data, application usage data, and location data, are adding more complexity into the mix. A single compliance standard can’t cover all the vulnerability points. The better retailers understand these vulnerability points, the better they can develop a plan to manage the risks involved. In this post, we discuss data problems the retail sector encounters, possible solutions, and the role of technology in handling these issues.

Common data challenges in retail

Problem #1: Multiple touchpoints and siloed data
Retailers with several information systems for their business units struggle with the siloed data, multiple touchpoints and dependence on cross-departmental communication to make updates. Their struggle causes delays, which, in turn, result in missed opportunities to make profits.

Solution – Retailers who centralize their data no longer need to worry about their data being scattered across the company. Problems with legacy and data silos are also addressed since data updates occur in real-time and are executed once across the enterprise. With data centralization, visibility of data improves, and omnichannel retailing gets a boost.

Problem #2: Exposing sensitive data to third parties and vendors
Data sharing between retailers and third-party vendors helps to strengthen sales, marketing, and inventory optimization. At the same time, the risk of criminals gaining unauthorized access to networks and point-of-sale systems runs high. Moreover, the advent of the Internet of things (IoT) has made the consumers’ data vulnerable to threats.

Solution – Retailers should aim to protect all sensitive customer data, including cardholder’s data, regardless of where it exists and then restrict access. Use of data encryption, tokenization, and two-factor authentication ensure that hackers fail to access customer accounts even during breaches.

Problem #3: Data redundancy
In a POS environment, data redundancy occurs when identical data is stored in two separate repositories. Without careful management, data changes in one repository not linked or flagged to the other repository result in data inconsistency where pieces of data that were supposed to be identical have different values, which causes issues related to processing.

Solution – Using data pipeline can help in various activities like what data to gather, where and how, when to extract, modify, combine, validate, and further load the data for in-depth analysis and visualization. With data pipelines, driving faster analytics is made possible. It allows retailers to improve merchandising tactics, customize the in-store experience, and share on-time offers with customers.

How technology can extend a lending hand to retail data problems

Technological transformation has pushed retailers to consider automating their redundant tasks. This eMarketer study shows that retailers rely on technologies such as point-of-sale (POS) systems and fraud prevention software to address data privacy issues.

Retailers are continually on the watch for a competitive edge; businesses benefit from a solution that supports the following capabilities:

  • Detecting, protecting, and monitoring PII, PCI, and PHI data.
  • Compliance audits that will ensure adherence with state, federal, and global privacy mandates and regulations.
  • Breach assessments.

According to an NRF survey, approximately 80% of retailers may adopt point-to-point encryption and 89% will choose tokenization.

Conclusion

The quality and use of data decide the success of any industry and retail is no different. Hence, retailers should focus on governing their data. A solution capable of handling and managing the most critical data-related issues is what retailers should look for. The situation may seem challenging, but the opportunity is tremendous.

Solution Brief: Privacy and Security, Together for Greater Trust