Even after spending more than seven years at NRF, I remain mystified by the phrase “business analytics.” I know it’s a powerful tool, but the phrase itself has always felt like one of those vague terms we all know is important but can’t really define. So when today’s business analytics session — featuring 1-800Flowers.com President Chris McCann and analytics expert Tom Davenport — began with a five minute overview of business analytics, I, for one, was a bit relieved. Much of this information may have been old news – but perhaps a good refresher – for almost everyone in the room besides me, but it provided a good starting point for the discussion.
On the one hand, business analytics are reactive. They can answer questions like:
- What happened?
- How many times has it happened?
- Where is a problem and what actions need to be taken?
While reactive analytics can be helpful, however, they’re hardly an end-all, be-all. SAS Institute Executive Advisor Lori Schafer equated business analytics to driving a car. As she put it, “You don’t want to spend too much time looking in the rear view mirror.”
As a result, the most effective analytics can also be predictive, providing information like:
- Why is this happening?
- What’s the best thing that can happen?
- What will happen next?
- What happens if these trends continue?
In addition to using analytics to answer a variety of questions, this data can be used in many different retail areas. For example, merchandising can use analytics to determine the most popular sizes and colors to order while operations can rely upon analytics to help them determine the efficiencies in the warehouse or how to manage store labor to optimize customer service. Analytics about human capital can allow retailers to answer questions about their workforce, everything from which candidates to recruit to employee satisfaction.
With the proliferation of social media, one of the fastest-growing areas of analytics helps retailers understand and engage with their customers. Companies can get a better handle on certain web behaviors and social media or learn what customers feel about store friendliness and cleanliness.
As Schafer said, “Image a world in which you can get inside customers’ heads to predict what they will want to buy, at what price, in which season and in what quantity and frequency? What will be the most popular items? What collections will people want to buy and how you should purchase?”
That’s where the future is going.
And with that introduction, read ten tidbits from today’s business analytics session with 1-800Flowers president Chris McCann and Babson College professor Tom Davenport.