Retail Pro – Let your Data do all the talking!


Retail Pro – Let your Data do all the talking!

Know what you want to measure

The first step in the process of becoming a data-driven organization is to determine what questions you want your data to answer. The questions you’re looking at should have tangible answers; this isn’t where you think about the open ended philosophical questions that drive your company’s overall direction.

But what are the burning questions you’d love answers to that can make your job easier? Every business is different, and the term “retail business” can encompass an incredibly wide variety of organizations, from car dealers to supermarkets to furniture stores and everything in between. We can’t tell you what questions to ask, but we’ve got a few examples of questions that may be useful to your organization.

For example...

  1. Do you know how your chosen vendors and distributors
    affect turnover rates across your locations?
  2. Do you know how each new product introduction affects
    the sales of your existing product lines? Is it the same at
    every location?
  3. Are you keeping more inventory on hand than you need to?
    How could you reduce your inventory requirements?
  4. Where are the hiccups in your supply chain? Can you use
    what you know about one location’s supply chain to correct
    problems in another location?
  5. Is there a way to more efficiently distribute manpower
    among your locations?

Perhaps the best part about the question-asking process is that questions create questions. It’s common for a user of business intelligence to be curious about a particular question, and upon finding the answer, becoming curious about how the numbers got to be where they are. That’s how good Key Performance Indicators (KPIs) are built – asking good questions and always having the answer on hand.

Taking measurements is only the first of several steps in building a data-driven organization, but every step thereafter relies upon these figures for success. Bad decisions result from bad data, so choose your questions and KPIs carefully.

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