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Guidance and results for the data-rich, yet information-poor.

Why You Don’t Need to Compete With Google and Facebook for Big Data Talent

HelpWantedData Informed recently put out a report which tells businesses how they can recruit “big data talent,” even if they aren’t Google or Facebook.

The report certainly had many interesting things to say. One was that tech employees don’t always feel valued in consumer goods companies. That insight may well carry over to other types of employees, and may hint at a problem worth solving in the culture of consumer goods companies.

Interesting or not, the report is based on a flawed supposition. Believe it or not, most companies actually have no need to recruit “big data talent” in the first place.

The people described in the report would largely be algorithm builders and software designers. The assumption is that most companies need pros who will build them brand new systems from scratch.

This is the old engine mechanic vs. race car driver problem at work. Right now the narrative around data mining and predictive analytics suggests that people mostly need mechanics.

In truth, however, most companies just need good drivers: business intelligence professionals that can use existing tools to gather actionable insights from business data. Drivers need to be intimately familiar with your business workings, problems, and objectives to be effective but they do not necessarily have to know anything at all about crafting an algorithm.

What they do need to know about data mining and predictive analytics can be seminar trained in a matter of days.

Think about it. Do you need people who can come in and artfully calculate the value of R-squared? Do you really even need someone who can come into your business and build you a software package from the ground up? This would perhaps be appropriate if you were trying to use predictive analytics to offer a sales feature to customers similar to the ones offered by Amazon or Netflix, but it doesn’t touch on the primary good that data mining can do for companies and organizations.

You find that primary good when you realize that data mining and predictive analytics can be used to  help you figure out how to make your marketing more effective, how to reduce waste, how to reduce fraud and how to hire better. And you can usually solve these important business problems with tools and software that your office already owns, and that your employees use on a day-to-day basis.

There are definitely some companies who might need data mechanics. But do some soul searching before assuming you’re one of them.

To explore this issue further, register for TMA’s free webinar: Data Mining: Failure to Launch. This 30 minute online course will help you determine what kind of talent you really need to solve your most pressing business problems.

 

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