Guest Column | December 6, 2013

The Road To Big Data

By Walker Thompson, VP Sales and Marketing, WhenToManage

Retailers have been using data to run and improve their businesses for many, many years. Only in the last few years has data become “Big” and a much larger focus for retailers as consumers have become more savvy and demanding. The use of mobile devices also has added complexity to the mix, making the old “spreadsheet method” a thing of the past. The advantages of Big Data analytics are endless — from marketing to operations — and a necessity for retailers of any size to remain competitive in a crowded marketplace. They key to good analytics, which retailers often overlook, is having the right process in place to collect and analyze the data. Without the proper technology, process and organizational adoption, it’s difficult to realize the potential of Big Data. Here are some key considerations for retailers considering upping their Big Data game:

  • Identify Big Data Goals. Retailers are often in a rush to jump on the Big Data bandwagon, but without proper goal setting, and not knowing what they want to do with the data, the outcome will be lacking. Are they simply looking to track sales records year over year or do they want to identify top customers and personalize a marketing plan for this select group? Are they looking to track buying behavior to guide how to stock their shelves? Identify which channels are pain points in order to get a better handle on the data being collected — is social media a weakness, perhaps an increase in mobile marketing is an initiative of importance, etc. If the Big Data process isn’t guided by business outcomes, you aren’t realizing its full potential. Ask yourself, “How is Big Data going to help us?”
  • The Right Technology To Do The Job. Technology required for Big Data will vary by size and need, but retailers must to be sure that they not only have the right tools for the outcome they desire, but also that all systems work together so that data from all touch points is combined for analysis. For example, restaurants will have a point of sale (POS) system for order taking, some type of inventory management tool, reservation tracking and staffing tools, and a system to track recipe performance. In most cases these systems are duplicated across multiple locations. By bringing all of this information together into reporting and intelligence software, data can be accessed and utilized in a cohesive manner. For multiple locations, the system should be flexible, while also being deployable across different locations.  This will provide a collective view of what is happening across all restaurants will allowing for educated decision making, and ultimately, higher profits.  
  • Organizational Buy-In. While technology is essential to the Big Data process, the right people powering that technology and leading the process are also vital. Any change is difficult, and without buy-in from top to bottom, data will not be collected properly and analysis will not be as accurate as it needs to be. A best practice often implemented is defining an “owner,” or group of “owners,” that will be responsible for educating and promoting the Big Data charge. This person or team would be the ambassador so to speak and is responsible for “selling” it to the executive team and employees on the receiving end of most data. Incentive programs are often used for encouragement. The key aspect is education. Unless there is a clearly defined and agreed upon reason behind the initiative, resistance will always prevail!
  • Performance Metrics. Now that the system is in place, knowing that it is working and how it is working will help to make the necessary changes needed and see where and how data analysis is having a positive impact. It’s helpful to segment goals into buckets with a measurable outcome — for example if staffing is an issue, set a goal of 10 percent less turnover at the end of a six-month period. Additionally, conduct a survey among staff for more tangible feedback on progress.

Retailers are taking advantage of all that Big Data Analysis has to offer and getting big rewards in return. The ability to reach the right customers, through the right channel, with the right messages, as well has have the right inventory, at the right time, is priceless. Big Data can be overwhelming which is why it is important to take the proper steps to develop and implement a process that will help reach and maintain goals.