Not Everyone Needs to Be a Data Scientist

Posted by Ben Gawiser on 10/27/15 9:06 PM

Yogi Berra / Credit: Yogi Berra Museum and Learning Center

“It is tough to make predictions, especially about the future” – Yogi Berra

Yogi will probably be remembered more for his quotes than for his baseball playing and managing career. His speech mannerisms endeared him to America at large and ensured his enshrinement as a cultural icon.

Yogi was correct that predicting the future is difficult. For much of the last century, business leaders would make projections about their sales and costs that were nothing more than educated guesses. It could be as simple as: take last year and add 10 percent, or as complex as using models to produce the numbers. Either way, the projections often proved incorrect.

In the last decade or so, there has been reason for stakeholders to have hope – and it comes in the form of big data. Big data evangelists promise it will allow our data scientists to predict with perfect accuracy and specificity. Logically, however, we all know we can never predict every variable or outcome. We know it is possible to use the enterprise data we already have to make better projections, but we need to recognize that even advanced techniques to aggregating and accessing the data have limits. The computer is only as infallible as its programmer and the data entered into it.

3 Options for Data Analytics

When it comes to companies having the capabilities to better predict supply and demand, it comes down to three options:

Hire a Team

In an effort to get the most out of our data, there is a temptation to run out and hire a team of data scientists. After all, our competition is likely doing it and we don’t want to fall hopelessly behind, right?  But finding highly-skilled talent in this area can be challenging, particularly if you are not yourself an expert in the field.  

Outsource

If building your own data science team seems daunting, you could consider looking externally for the expertise. There are a few boutique consulting shops that do this type of analytics work but it still requires significant resources to manage the relationship and provide relevant data they need to build a custom solution. 

Leverage Technology

Fortunately, fantastic tools are emerging to allow us to perform data scientist-level analysis without actually having a data scientist do it. Pre-configured software can do the analytics work for you so you can focus on acting on the data, rather than finding it.

What's Next?

No matter what route you determine is best for your organization, you need to be sure of two things:

  1. The insights are presented in a clear and consumable way, so you know what to focus on
  2. The insights are actionable, so you can easily make better decisions 

While we all need to have access to relevant data and then the ability to distill it into actionable information, it does not require we have a data scientist on staff. There are viable, cost-effective alternatives for organizations of all sizes that can greatly improve the accuracy of business predictions.

Topics: Hive9

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