by Courtney Manning
Given my background in site merchandising and digital analytics, as I cross paths with retail industry executives, I seek to understand how they are attempting to make sense of the data that lives across their organizations to truly make it actionable. The response I hear most often is that a team of analysts has been tasked with a business intelligence data visualization software that connects and displays data in a colorful, dashboard view (think Tableau, Domo or QlikView) that is then distributed to the retail product teams.
While a business intelligence (BI) tool may seem to fit the bill in terms of making data more accessible and digestible, these BI tools still do not provide a comprehensive, connected, and immediately actionable view of data that lives across a retail product organization. Here are 5 things to consider before signing your BI team on to dive head first into that waterfall chart:
1. You need to know what questions to ask to optimize data analysis.
There is no limit to the questions you can ask…as long as you can think of them. As a retail product organization, what are the most powerful insights you can derive from the data you have available? What connections could you make that are truly valuable in driving the business? BI data visualization tools are not custom built for retail, leaving the user to determine the questions and data sets needed to derive strategic insights for the business. Break out the pen (I recommend a pencil) and paper and large pot of coffee for that long meeting ahead.
Helpful hint: In addition to the typical metrics, ensure your tools quickly provide you answers to these 24 critical questions.
2. Business intelligence dashboards take valuable time and resources to build.
Creating a data visualization masterpiece takes time, brainpower and a whole lot of data. Typically, a small team of BI “artists” are trusted with designing dashboards based on their knowledge of the data, access to the data sets required and ability to navigate BI software. Once a desired dashboard framework has been determined, it can take weeks, if not months, to surface at the top of the project queue and build and validate it for wider use. Before the build even takes place, it must be ensured that the dashboard will contain all the information the product teams need for quick wins and deep insights, or be ready to start over—or worse, attempt to conduct business without the relevant metrics.
3. Dashboard updates happen at different cadences, making it difficult to derive insight.
Dashboards are great for recapping your business, but when they are updated on different cadences it can be difficult to derive insights in a timely manner. Those metrics you need before the leadership meeting regarding the recent promotion? Well, that report doesn’t come out until next month.
4. Each dashboard has a unique format—and you and your product teams have to understand and remember all of them.
Carving hours out of your week to try and understand how (or remember how) to manipulate a multitude of custom dashboards is time taken away from driving sales and profit for your business. Worse, analyzing each relevant dashboard detracts from the product team’s ability to take timely action. Time is money!
5. Even with a successfully adopted dashboard, the user still needs to determine a best course of action.
After spending valuable time combing through reports, one thing is still missing: a recommendation for a best course of action. Once the desired dashboard has been updated and its mechanisms understood, the user is still left to determine what should be done based on the metrics and graphs provided. So, while a BI tool might provide decision support via data discovery, it does not recommend next steps based on retail best practices.
Providing retail product teams with dashboards can shed a new light on data sets that were previously well-hidden and one-dimensional. However, the time and effort spent determining valid business questions, creating and adopting the dashboards one-by-one is often longer and more arduous than the business is willing to accept in order to move quickly in this fast-paced retail market.
Learn how DynamicAction delivers the best of Business Intelligence…and Big Data Analytics, Web Analytics, Personalization Software, Statistical Software, Task Management Software, and Prescriptive Analytics to help retail teams get to the right actions faster. Book a demo, or download our comparison brochure.
About the author:
Courtney Manning has been active in eCommerce since 2005 and has held roles in both Site Merchandising and Digital Analytics for Macy’s, Bloomingdales, Amazon and Nordstrom. Her passion for eCommerce and desire to arm retail product teams with insights that will reduce analysis time and encourage better, more profitable decisions led her to DynamicAction, where she currently holds the role of Solution Consultant.