Lemonade Stand Data Quality

3 Min Read

My children expressed interest in opening up a lemonade stand this weekend. I’m not sure if it’s done worldwide, but here in America every kid between the age of five and twelve tries their hand at earning extra money during the summer months. Most parents in America indulge this because the whole point of a lemonade stand is really to learn about capitalism. You figure out your costs, how much the lemonade, ice and cups cost, then you charge a little more than what it costs you. At the end of the day, you can hope to show a little profit.

I couldn’t help but think there are lessons we can learn from the lemonade stand that apply to the way we manage our own data quality initiatives.  Data governance programs and data quality projects are still driven by capitalism and lemonade stand fundamentals.

  • Concept – While the lemonade stand requires your audience to have a clear understanding of the product and the price, so does data quality.  In the data world, profiling can help you create an accurate assessment of it and tell the world exactly what it is and how much it’s going to cost.
  • Marketing – My kids proved that more people will come to your lemonade stand if you shout out “Ice Cold Lemonade” and put a few flyers around the neighborhood. Likewise you need to tell management, business people and anyone who will listen about data quality – it’s ice cold and delicious.
  • Pricing – A lemonade stand works by setting the right price. Too little and the profit will be too low, too high and no one will buy. In the data quality world, setting the scope with the proper amount of spend and the right amount of return on investment will be successful.
  • Location – While a busy street and a hot day make a profitable lemonade stand, data quality project managers know that you begin by picking the projects with the least effort and highest potential ROI. In turn, you get to open more lemonade stands and build your data quality projects into a data governance program.

When it comes down to it, data quality projects are a form of capitalism; you need to sell the customers a refreshing glass and keep them coming back for more.

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