Let's go back to my supermarket example that I previously wrote about
. As you could see, food waste has a great impact on how good a supermarket does business. In a traditional way of thinking, the food waste will affect the profit and loss on a daily basis in a supermarket, but in the long perspective it might also be a competitive advantage in terms of CSR (Corporate Social Responsibility). How a store handles waste could change the way the customers think and -- more importantly -- feel about the company. Who doesn't love a feel good story? This will improve customer loyalty and revenue. There must be a way to measure this, right? Correct!
Data-driven businesses use all of the useful data that's available to them, regardless of the source, and that means looking at other platforms in the organization besides just your ERP sytem. Here are some examples of the data sources I'm talking about, all of which would be relevant for your business intelligence for retail:
- Customer Relationship Management (CRM) data
- Point-of-sale data
- Data from ecommerce modules on company websites
- Supply Chain Management (SCM) data
- Google Analytics data
- Marketing automation data
- Market data from external data sources
- Social media
- Data from Excel files, etc.
All of this data is relevant for gaining a comprehensive view of your what's happening at your retail company. A successful BI solution pulls a combination of key data from the different data sources, and presents it to you in a user friendly front-end tool that gives you the power to observe, analyze, and make educated decisions and actions. In other words, it does all the hard work for you, collecting different data from disparate sources and delivers it to you in a concise, easily understood report or analyses. In this way, you can think of your business intelligence solution as a cowboy and your data sources as the cows. It's the cowboy's job to wrangle all those cows together, and keep them safe and organized.
Business intelligence takes all of that data from the back-end and beyond -- connecting multiple data sources when necessary both inside and outside of the organization -- crunches the numbers, and delivers a dashboard, report, or analyses that gives actionable insight into company health. Analytics allow you to drill into raw numbers or transactional data and make comparisons, in turn allowing you to better predict future analytics and trends.
Stay tuned for step three for becoming a data-driven retail organization in my next post. In the meantime, feel free to contact me for more information on ways to become data-driven and I'll be happy to get you started.
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