6 Steps to Turn Big Data into Better Retail Execution
In November 2012, Retail Info Systems News (RIS) produced a report discussing the steps retailers and retail brands can take to advance beyond big data. The data is only the first step toward retail insights and improving retail execution. As the study points out, retailers have already embraced the age of big data. There is more information available than ever before, which should benefit retail companies. However, the mass of data can be stifling and can get lost in over-worked IT departments.
The following six steps, as laid out by RIS, can help managers of retail execution and retail operations get from big data to insights, faster. The full report is worth a long look, but here is a summary of the key steps and our takeaways:
1) Identify high impact opportunity areas for big data:
Don’t collect data for the sake of collecting more data. The only way to make the data work for you is to have a plan for turning the data into action. Identify the most high impact data before starting a big data project, and make sure you have a plan for turning that data into action.
2) Accelerate the move toward self-service business intelligence:
Using self-service software takes out a significant bottleneck in any retail data project, that of an overworked IT department. As much as possible, companies must take the load off of IT and use solutions that are user friendly. If you’ve identified high impact opportunities, make sure the people who have access to that data can take action on the insights.
3) Use SaaS and cloud technology to spread analytics availability:
SaaS and cloud technologies allow retail management to access data anytime, anywhere. Retail companies, by nature, have resources on the move. If high impact insights are available to your mobile and field based employees, you have a much better chance of gaining buy-in at all levels of the organization.
4) Audit and upgrade data management capabilities:
Along with bring your own device (BYOD), mobile data management (MDM) has become a key topic for the retail enterprise. Making sure that data is clean, accurate, and secure is vital to any big data project. If your infrastructure can’t handle thousands of employees at a time, it might be worth an upgrade before launching a big data initiative.
5) Create a common set of metrics for use throughout the enterprise:
We frequently talk about structuring unstructured data when gathering retail insights. No matter how you say it, making sure that information is measured consistently, against the same metrics, and across the entire organization is vital to the success of any big data project.
6) Use analytics to improve understanding of omni-channel customer behavior:
This has to do with the scariest of retail trends to date… showrooming! Instead of living in fear, data from online purchases and consumer research can aid in improving the in-store experience and overall retail execution. This is the last step for a reason… it takes time. Getting to a point where online and in-store experiences are complimentary could be a game changer for your retail operations.
Again, the full report is available through RIS News here, entitled “Harnessing Business Analytics to Deliver Faster, Sharper Insights”. Subscribing to RIS News is a fantastic resource for staying up to date on retail execution trends.