In my book Retail Analytics: The Secret Weapon, I talk about the importance of using all your available data in the decision process, regardless of the area of focus: replenishment, space planning, price optimization, etc.
Blending all of your data together through analytics is where the magic happens, and where the secret weapon is uncovered.
Every business, from small to large industries has data; your competitors may have the same type of data that you have. I guarantee every retailer has some form of basket transaction data. It’s what you do with your particular data that matters, because you are the only one with your data, and that makes it unique. What you do with your data, and how you apply it to business decisions is your secret weapon.
Even today, there are retailers out there, as well as non-retail businesses that don’t do much with their data. Sure, they collect everything because someday they might need it. It’s part of the big data phenomenon. You have everyone telling you the importance of the new big data (especially the software vendors) and that the real magic happens when you blend all this structured and unstructured data together.
Not much has changed in this philosophy over the years, just the volume and complexity of the data. Not so long ago, it was enough to merge sales POS data, replenishment data, and on-hand data together to have a fairly robust sales report. Then adding on shelf-space factors, price-elasticity figures, logistics and ship times, spreads between regular and advertised priced goods, then you were talking about an action report.
Today we look at this as being the bare minimum in any type of report, and barely enough to do accurate propensity or forecast equations. It’s a wonder us old timers made money at all. Sure some of us even used the abacus.
OK, seriously we were successful because we knew how to blend our internal data together to develop our own secret weapon. But in today’s ultra-competitive marketplace, where your biggest competitor doesn’t even own a piece of property, but has the means to ship anything anywhere; you need to avail yourself with as much hard cold fact based data as possible.
In the past, say five or six years most retail problems were two dimensional: “supply and demand”. Look at your inventory flow and compare it to your sales flow, if either one was out of bounds too far you throttled one up or down. Problem fixed. The world was pretty stable, you knew where your competitors were located, you knew their prices and when they had advertising specials. You could prepare and respond appropriately. Today, this is no longer the case.
With the consumer adoption of Internet shopping (How many of you felt this would never take off because consumers want to touch the product?) and the huge variety of products and services available the effect is being felt in almost every industry.
Heck, we bought our last home in Arkansas from Melbourne Australia, 9,000 miles away over the Internet. Sure, we are absolutely an early adopter, but the new generations are growing up with this online availability at their fingertips. How can the traditional brick-and mortar retail shops hope to compete?
The overwhelming adoption of the new retail channels by consumers has aided in the development of new and exciting frontiers of retail analytics. While most still comprise the same base rules as in previous years (the steps are still the same) and the outcome is still your secret weapon, what has changed is the availability of so much more rich and immediate data. The thought that you can still do weekly merchandise reviews is gone. No longer can you compare on-hands to inventory logistics weekly or expect your best competitor to be a block away from your store. Today you can’t base 100% of your sales on brick buildings, and you simply cannot ignore the consumer demand for an on-line presence. Leading retailers today have the ability to review sales trends in near real time, and adjust ship quantities appropriately.
Today, retail analytics is much more like a three-dimensional equation. Today, you blend the same data points as used previously with new digital data. This causes the weighting of importance of each “legacy” data point to be diluted by the emergence of new on-line channels of shopping. It’s more than just big data, but the explosion of supporting big data technologies. We’re seeing the convergence of need for more data, availability of more data, and the new technologies to manage the analytics of this data. In today’s environment it’s not enough to manage your customers face to face. In today’s marketplace you need to manage the relationship across many channels 24x7. The competitive situation today is much more geared towards customer demand and the importance of reducing risk by increasing data driven decisions quickly and efficiently.