The down side of data

“Once upon a time”, as the fairy tale goes, retail was simple and all about the product on the shop floor, the sales team and customer interaction.

Good merchants used the senses of hands, eyes and ears and combined them with some good old common sense brain power in making retail decisions. The shop owner (merchant), was on the spot and had an intimate knowledge on what was happening in his or her store, what was and what was not selling and knew his or her customers by name.

They were very familiar with why their customers visited their store and what they bought.

Fast forward to the times of Buzz Lightyear and we are in the era of “to infinity and beyond”. Probably the greatest change in retail over the past 30 years has been the arrival and advancement of technology. Today a retailer is able to capture, sort, report, study and make decisions using almost every imaginable piece of data assembled top down, bottom up, inside out and outside in.

It seems that hand in hand with the flood of information that technology brought into retail was a proportionate loss of time for the merchant to be on the shop floor, to visit suppliers and to research the market. The merchant became desk bound studying the available data in a myriad of formats, cutting and pasting, charting, graphing, sorting… Desk bound “data merchants” became less and less intimate with the actual retail environment and more and more reliant upon data for each and every decision they needed to make.

Desk bound merchants find themselves with less time available to visit and discuss business with suppliers often insisting the supplier visit them because they are too busy to get out of the office. This attitude generally leads to deterioration in the retailer–supplier relationship. Long term valuable partnerships get replaced with short term deals and this tests loyalty on both sides.

Another consequence of being desk bound is the merchant can justify – well at least in his or her own mind – that there is no time available to visit competitors’ stores. This results in valuable observations of the relative strengths and weaknesses of the competition being lost as an important consideration in the retail decision making process.

Now it is not necessary for retailers to return to the ways of the past, but it is necessary for the data available to be relevant to each specific retail operation, be user friendly and be recognised simply as information to assist in decision making and not the decision in itself.

I watched with interest as a retailer decided to tighten up some nominated ranges where it was considered the offer was too broad. Now this started with the enforcement of the 80–20 rule, you know how it goes, 80 per cent of the sales are generated from 20 per cent of the items. Then to this was added “DDD” (data driven decisions) using the vast lists of statistics available to highlight all items that were outside of nominated parameters e.g. item sells less than a single unit per day or margin achieved was less than the Department average.

The exercise was completed over several days and red highlighters were kept busy crossing out the “to be deleted items”. At the completion of the exercise more data reports were compiled and graphs displayed proving on paper that items ranged could be reduced by 17 per cent and as a consequence stock holding would fall by a whopping 23 per cent.

To this was added increased stock-turn and improved GMROI and it was also argued soiled and damaged markdowns would be reduced because there would be less slow selling merchandise on the shelves. Loud cheers and applause as this was truly amazing and surely would drive the business financials to unprecedented highs.

Beware the “witch offering the rosy red apple”! It all seemed too good to be true and it was.

This retailer went ahead and commenced deleting all of those “red highlighted” items only to find soon after a disastrous drop in sales! You see there are many reasons for having an item on range and it cannot always be simply judged on direct sales. Some items create a level of interest that draws the customer in, some reinforce to the customer you always have what they want, others whilst low in unit sales might be high in profit value and still others can be the catalyst for the sales of other items in the range.

Can you imagine a fashion store that only offered the best selling colors in the highest unit selling styles and in the most wanted sizes? Would you still enter the store if the only colors on show were white, black, grey and taupe? The answer is no because it would be boring and not deliver a fashion image and if you did enter the range offer would not meet your shopping experience expectations.

So what was wrong given the decisions were based on factual data? The answer is the merchants had lost touch with the market reality and did not apply brain power in the decision making process but instead, simply used data as the basis for the “to be deleted” decisions. These were still DDD actions but a better acronym for DDD in this instance would be “Dumb Data Decisions”.

Good, timely, user friendly, logical and sequential data is extremely powerful when harnessed to suit the retailers style of business and operating structure. Data for the sake of data – and perused because it is available – is not the right reason to have it filling computer screens and spewing out in reports in such volume as to destroy an entire forest every day.

Now you might be thinking I am an old school merchant with a resistance to technology and a loathing for data, but I can assure you this is not true. I am actually a data addict and love nothing better than to have spreadsheets, charts and graphs to keep me informed and might I say even entertained. Excellent data availability that is managed with discipline is a must in today’s sophisticated retail world.

Observations when it comes to data in the hands of the merchant:

  • Clearly understand the role of each function and the data that supports each task.
  • Support merchants with quality data that is relevant for analysis and decision making.
  • Use a system that gives flexibility and the ability to apply merchant defined parameters .
  • Train merchants how to read, analyse and use data combined with “retail brainpower”.
  • Be careful that too much data does not hinder good decision making.
  • Demand merchants get away from the desk and spend time in the “real” retail marketplace.

Remember, retail is really all about people. Know yourself (strengths and weakness), know your store team, know your suppliers, know your competitors and – most critical of all – know your customers.

Data is powerful when organised to reflect your business structure and when it is relevant to the decision making processes you undertake. Data is factual but it is the application of brain power to understand the real messages in the data that is the critical step in the decision making process. When data and brain power are combined then it is possible you can “live happily ever after”.

InsideRetail.Asia columnist Darrell Wisbey has 30 years retail experience, living and working in Australia and Asia. He is based in the Philippines and a member of Impact Retailing. Email Darrell.

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