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4 Myths About Predictive Analytics

Tuesday, November 01, 2016

If you’re a business owner, having a clear picture of your company’s current state and performance is imperative, but so is knowing where you’re headed. Having this comprehensive understanding is key to determining how to effectively make progressive changes within your organization and gain a competitive advantage.

This is where the field of predictive analytics comes into play. This discipline incorporates advanced analytic techniques such as data mining, statistics, modeling, and machine learning to predict future outcomes based on patterns observed in historical data.

While predictive analytics has been around for quite some time, more and more businesses are now beginning to see and understand just how powerful it can be. The information surrounding predictive analytics is overwhelming, giving rise to all-too-frequent misconceptions and myths.

If you want to use your data wisely, then don't let these myths fool you! For this reason, we’re lending you a hand today by separating fact from fiction and putting your questions to rest.

Myth #1: A PhD is a prerequisite for implementing predictive analytics.

A relic of the past, this is fortunately not required today. You DON’T need a team of data analysts with years of statistical experience and training to put predictive analytics into practice in your organization. Today's tools have made predictive analytics increasingly accessible to business users, empowering them to conduct in-depth analysis and forecasting on their own.

It does, however, require the user to understand the business inside and out, especially its ultimate goals. For example, a marketer should have a solid understanding of consumer behavior in order to successfully take actions toward the desired goal.

Myth #2: The selected algorithm matters most.

While the algorithmic approach that you use is significant (think fancy math), it’s certainly not the most important element. If the resulting model provides little to no value to the business, then why should it carry any weight?

A properly-applied algorithm is a required aspect of building a predictive model, but ultimately, the quality of the data on which that model is built matter most. 

For example, consider two companies that build a model to predict when men of a certain age group will purchase a particular product in store.  While they may both apply the same algorithm in building their predictive model, if one has captured more relevant attributes about their consumer base, over time, and across a diverse mix of consumers, it’s likely to have a more robust outcome. This translates to greater confidence in basing key business decisions on these predictions, and engaging with future customers. 

Myth #3: Predictive analytics is expensive.

You may have heard on more than one occasion that predictive analytics is an expensive venture. As noted earlier, with today's tools, you don’t need to spend money and time on hiring a full-fledged team of expert statisticians and data analysts to execute predictive analytics in your organization. Also, since you can optimize your key business metrics and identify risks, you can save money, spend less, and see significant ROI potential to justify costs. Once you have a better idea of what drives the highest ROI in your business, you can devise and adapt your plan of action accordingly.

Myth #4: Predictions = Prescriptions.

Just because you’ve formulated a set of predictions, it doesn’t mean that your task is complete. The key is to glean insights from those predictions, understand the drivers, and make them prescriptive by conveying actions clearly to stakeholders. Old rules apply—know your audience and deliver these actions in an impactful and consumable manner. 

Keep in mind that with high-quality data, you can devise more accurate predictions and models, but you should always keep a close watch on shifts in the drivers of your model or other events that may have an adverse effect on the forecasts' validity. 

Are you interested in implementing predictive analytics in your business? Visit us today at Big Squid, and we’ll help you discover the answers to your key business questions, forecast future trends, and turn those insights into actions. We also invite you to give our innovative Predictive Toolkit™ a try, a powerful predictive solution for businesses of all sizes. 

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Nick Magnuson

Written by Nick Magnuson

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