The retail industry transformed in many ways in 2020, with online sales representing a clear example of such customer preference shifts. In analyzing these changes, retailers can find a veritable treasure trove of data. Those with the means to channel this data will uncover insights related to e-commerce, customer experience, inventory, marketing, staffing and supply chain trends. The data can also highlight what they did well, where they could have improved and, most importantly, how to respond in the coming year.
As retailers dig into the data, it is critical that they are doing so with data protection in mind. As data’s value increases, so does its risk. It is more important than ever that data protection best practices are employed to ensure that the ROI is not diminished by the enormous cost of data exposure. There are three areas where retail organizations should concentrate efforts in the coming year to preserve their data’s value: prioritizing cloud data protection, making data “share-ready” and addressing regulatory concerns.
Like so many industries, retail has seen a mass migration of data to the cloud due to the immediate need to maintain business continuity. Cloud data migration has often prioritized speed over security, leaving wide swaths of proprietary data unprotected and vulnerable to theft.
Organizations need to implement best practices for cloud data storage to ensure this valuable data is only viewable to those who are authorized to see it while maintaining the ability to analyze it.
In 2021, the modern data analytics pipeline will help retailers collect, classify and organize their data with state-of-the-art capabilities and help identify potential trends and make informed decisions that help them respond accordingly. Extracting market differentiation from retail data will begin with a review of Q4 2020. Having the data is great, but it comes with liabilities around protecting it. To protect the pipeline, organizations should explore solutions and best practices to ensure data is protected and essentially unusable to criminals who are able to penetrate default cloud security protections.
Protection comes in many forms, including masking, tokenization or encryption, so choosing the right method is critical to maintaining the utility of the data while not exposing it. This is especially important in data analysis, as protocols shift depending on how far upstream or downstream data is in the analytics pipeline. For example, as data moves downstream, it must be available in a format that allows it to be processed without leaving it in the clear.
Making Data “Share-Ready”
Retail organizations will also find great insight into industry-wide data sharing to help improve customer experiences by anonymously sharing information with and between suppliers. With the massive changes that occurred in retail over the last 12 months, being able to compare and contrast data before and after the pandemic can be a significant benefit. While organizations reap the benefits of data sharing, many may be reluctant to do so for fear of accidentally revealing proprietary information and customer data.
To offset this concern, retailers should consider advanced privacy-preserving technologies that allow them to reap the benefits of data sharing while ensuring that they are protecting data in a manner that reduces the risk of exposure. Such technology eliminates much of the hesitation that some organizations have with data sharing and opens the door for richer, usable industry insight.
Addressing Regulatory Considerations
The ROI data analytics can offer is certainly a main driver for creating an analytics pipeline beginning with collection, classification, storage, cleansing and, finally, processing data. The emergence of privacy regulations such as CPRA and GDPR are instituting data privacy practices, making data protection a mandatory step in that data analytics pipeline, as well as a critical part of doing business in order to build trust. And in the U.S., there seems to be growing momentum for a national privacy referendum to harmonize multiple state mandates. As such, privacy is becoming less of a necessary evil and more of a competitive differentiator for a business.
Regulatory expertise is a must. It is critical to have someone on staff or an outside, trusted partner to navigate the often confusing regulations that an organization must adhere to. The goal is to understand all of the regulations, how they intersect with one another and how to stay compliant with not only current laws but also those that are emerging.
As retailers become more reliant on data, they are also getting savvier about how information can help carve out significant market differentiators. As important as data is, its value can be neutralized if these organizations don’t implement appropriate data protection measures to ensure its ROI.
This article originally appeared in Forbes.
*** This is a Security Bloggers Network syndicated blog from Baffle authored by Ameesh Divatia, CEO and co-founder. Read the original post at: https://baffle.io/blog/preserving-retail-data-roi-means-protecting-it/