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Data Dysfunction: The Undiagnosed Problem

By Amy Chisam

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By the time my hearing was tested as a 5-year-old, I was 85% deaf. The doctor speculated that my hearing had been gradually declining since I was a baby. Prior to the hearing test, neither my parents nor I realized there was a problem. I assumed my situation was normal and coped through lip reading and context clues.

If you heard me talking, my speech sounded fine – it’s just that I occasionally had funny word substitutions. But what toddler doesn’t? My son used to call yogurt “whoa whoa.” So me referring to myself as “Mimio” didn’t seem that odd to my parents.

Soon after the first of my ear surgeries, I was watching Sesame Street. I was amazed that Big Bird and Cookie Monster could talk. Before my operation, I thought only the human characters spoke English. Because I couldn’t read their lips, I had assumed the Muppets were responding with animal sounds or monster gibberish.

Warning Signs

The current state of business intelligence and data analytics is like my childhood experience. At many companies, the approach to producing analytics is inefficient and unscalable. Even worse, most people don’t recognize that this is a problem. Even fewer realize that there’s a simple solution.

Maybe you don’t think there’s a problem because you’re getting by. Your analysts are busy. Ad hoc reports are produced. Some degree of data-driven decision making is done, using scorecards and standardized reporting.

But ask yourself: Is your company producing analytics in an ideal way? If not, are you trying to close the gap with workaround solutions?

Symptom Checklist

Check off which of these symptoms apply to you and your organization:

Processes

Tools

People

If you checked five or more of those symptoms, I have your diagnosis. You’re suffering from data dysfunction.

Treatment

Fortunately, data dysfunction is very treatable:

  1. Assess the situation. Spend time learning where the workload is coming from. Which users are requesting the greatest number of reports, when are they’re requesting them, and what data is needed? But more importantly, find out why these reports are being requested and what business purpose they serve. With a little investigating, you can consolidate or eliminate some of these requests.

  2. Evaluate options for your data. With so many advances in data storage and extraction, learn which solutions can improve your current situation. Focus on improving the structure and management of the data that’s most critical and accessed most often.

  3. Take a look at self-service BI tools. Maybe you tried to go this route in the past, buying enterprise licenses for your analytics platform. But then you realized the business folks didn’t have the time, budget, or interest to attend training. The tool itself was probably very complex – too technical for your marketing, sales, or operations colleagues. And so the time you’d spend training and supporting those users wasn’t worth it.

    But self-service BI has vastly improved. Gartner has declared that we’ve passed “the tipping point” and that most companies are now selecting modern, business-user-centric platforms for their analytics.

    AnswerRocket, for instance, uses an interface anybody with a computer is already familiar with: search. Users type natural language questions and get answers in the form of data visualizations. What currently takes days to compile using traditional BI solutions can display within seconds using AnswerRocket.

  4. Give a low-risk option a try. AnswerRocket offers a free trial using a sample of your data. Set up takes a couple of days at the most. You’ll come out of this feeling more knowledgeable about your options – and possibly with a cure to your data dysfunction.

Request a Demo

See how AnswerRocket can enable your team to make better, faster, data-driven decisions by simply asking questions.