Business intelligence tools, more commonly known as BI, were originally created to give knowledge workers the ability to easily access the data contained within databases. Unlike traditional means of extracting data using Structured Query Language (SQL), BI solutions gave workers the ability to graphically generate the SQL and extract the data for creating reports.
As the capacity of data warehousing solution providers evolve and adapt, retailers can analyze greater amounts of data. With increased data, traditional legacy-reporting methods are becoming more difficult. However, most retailers still struggle with giving managers and executives answers to what’s impacting their business. To gain true business intelligence using traditional BI tools, the users need to have an idea of what they were seeking. Because of the increased complexity of BI, users are requesting the development of reports from the IT department. With ever changing demands come increased report requests. Before too long, the ability to read and keep up with the reports is no longer possible. More importantly, certain reports will require specialized talent to interpret the results, which ultimately will “reduce the time to know” and prohibit the ability to scale across the organization.
With traditional BI techniques, there is a high chance that you will miss an important opportunity to impact the business. The data itself should be pointing the analyst in the right direction. The answers already exist within the data in the form of patterns that can be automatically extracted to identify root causes for impacting the business. The patterns will tell the story and enable the retailer to “find without knowing.”
Unlike business intelligence, profit amplification is not a reporting tool, rather a pattern seeking solution that is IT independent. With profit amplification, algorithms perform the analysis and identify patterns that exist within the data coupled with business logic to remove false positives and prioritize the highest value opportunities. This provides the retailer with targeted direction toward prioritized opportunities for expanding margins by increasing revenue or decreasing cost. Profit amplification offers “best practices” to be used to address the prioritized opportunities that are identified through pattern analysis, which “tell the story,” and will provide the retailer with the chance to operate with excellence in the ordinary.
Business intelligence software, with the right analyst, will reveal opportunities. However, pattern seeking solutions will validate and prioritize them. If problematic behavior is happening in one store, on one day, just once, then it’s not a trend. Unlike Exception Based Reporting (see EBR is dead) which would generate a high percent of false positives, as problematic trends build, profit amplification accumulate ranking points that create greater visibility. By focusing on those problems with the biggest opportunity values and linking them with the prescribed solution, retailers will realize the most significant gains, thereby expanding margins.
So it is now up to you to determine which direction you choose to go. Sticking with traditional BI solutions mean the possibility of missed opportunities as the quantity of data in your systems grow. Profit amplification not only finds the root cause of anomalies, but prioritizes them and provides best practice solutions to correct them. I think the choice is simple, but it’s up to you.