Black Friday
It’s here. The turkey has been eaten, the stuffing and mashed potatoes are long gone, and you just know that everyone in the family is going to be eyeing one another each time they head to the refrigerator today: he’s not going to take that last piece of pie, is he? Thanksgiving is gone, Black Friday is here.
Black Friday is traditionally the busiest day of the year for shopping both online and in in stores. As a result, it’s rich with opportunity for analysis. What deals did well? How many big-screen TVs were sold? How big was the interest in this year’s “hot new toy”? Certainly, retail sales data alone could keep analysts busy for weeks.
But one of the reasons it’s important to involve all of your team members in being data fluent and contributing to your discussions about data and analytics is that there’s much more to your business than just the sales on the busiest day of the year.
How long were shoppers waiting in line to check out of the store? How many items were damaged due to mishandling during the chaos? How many phone calls did your team field asking about store hours? How much extra did you pay in wages preparing your store for the big day? Those are just some of the questions that aren’t related to what went across your point of sale. But they’re important questions nonetheless. They speak to processes that drive your business regardless of how many sales you make.
Businesses should be trying to understand how “behind-the-scenes” business processes affect their top and bottom lines - all the time. There should be regular discussions with team members that ask them what sort of trends they’re seeing in their daily workflows - not just on Black Friday but throughout the year. Are there more complaints? Slower response times from vendors? More difficulty with delivery? Increased spoilage? More community-outreach requests?
The responses to these questions should be captured and incorporated into your organization’s data so that it can be used in analysis; and if it seems like there’s a trend, your data professionals should be working closely with the teams reporting the trend to dig into the factors that might affect that trend.
You might ask: why do this? Well, you’re paying these people - theoretically, they’re adding value to your organization, by solving some problem that would otherwise cost you more money than it costs to compensate them. Understanding the events that impact their work means building more insight into your bottom line. And having team members who can speak data when you go to ask those questions makes it that much easier to do so.