August 23, 2017

Using Predictive Analytics? Here’s Why You Should Start Today


If you could predict the future in business, you'd be set. Of course, you can't. But you can use data to try as shown in these predictive analytics examples

The Centers for Medicare and Medicaid (CMS) recently announced that between 2012 and 2014, the organization had saved $42 billion. CMS partnering with law enforcement and vetting health care providers was responsible for part of the savings. But CMS saved much of the amount by implementing predictive analytics, thereby preventing “fraud, waste, and abuse.”

“From October 1, 2012 through September 30, 2014 (Fiscal Year (FY) 2013 and FY 2014), every dollar invested in CMS’ Medicare program integrity efforts saved $12.40 for the Medicare program.”

Simply put, predictive analytics is “computers learning from past behavior about how to do certain business processes better and deliver new insights into how your organization really functions.”

Companies need to learn how to mine actionable strategies from the troves of data they are collecting. Predictive analytics can benefit your business in many ways including determining customer actions, simplifying your processes, and decreasing your level of risk.

Garbage In – Garbage Out (GIGO)

In IT we have a saying: garbage in – garbage out (GIGO). What that means is that the quality of your data is extremely important. Basing business decisions on invalid data could have a severe negative impact on your business.

Predictive Analytics Examples - First, Get Good Data

Make sure that anyone involved in inputting data in your company understands how critical accuracy is to the success of your business.

Predictive Analytics Examples

Predictive Analytics Streamlines Company Operations

The Harvard Business Review reports that big data is extremely helpful for predicting customer demand for products that are not “hits,” but are rather sold to many people in a variety of niches (otherwise known as the “long tail”).

Mining this type of data is more challenging because the products in the long tail are not as popular as hit products and the regions they’re sold in are not as large.

Predictive Analytics Examples - Streamlining Company Operations



Predictive analytics is extremely useful for mining this data and determining what clients in these niches want.

Setting Pricing Using Predictive Analytics

Another way predictive analytics helps companies is with pricing. Businesses can increase sales by targeting particular customers with specific prices, discounts and promotions.

Online retailers can use the tons of data they gather on the behavior of their customers to adjust their prices respective to what will appeal to their clients the most.

Predictive analytics also greatly aids industries that rely on machines for their success because data can be used to evaluate when those machines need maintenance or are likely to fail.

Scientists at Microsoft used data they had gathered on aircraft to determine when flights were likely to be canceled or delayed. Airlines are just one example of organizations that can alleviate an enormous amount of waste by simply being willing to find ways to mine the data that they already have.

Predictive Analytics Decreases Risk

Lowering risk for companies is another advantage of predictive analytics. Businesses have a vested interest in discovering ways to increase their security because it is not a matter of if data breaches will happen, but rather when they will happen.

Gathering information on past attacks and identifying a digital fingerprint to prevent future infiltrations is the conventional way of trying to prevent data breaches.  This method is becoming increasingly ineffective as cyber attacks become more sophisticated.

Predictive analytics, of course, is not guaranteed to prevent every attack that comes along. However, it is a proactive approach to safeguarding information instead of reactive.

Companies can use predictive analytics to identify attacks they have never before seen rather than relying on what they know of past attacks. Combined with artificial intelligence, predictive analytics could grow to be very powerful indeed.

Implementing Predictive Analytics

It’s easy to talk about implementing predictive analytics, but actually doing so can be complicated. Companies should determine the following to get started:

  • the liability to your business if leadership makes poor choices,
  • the types of decisions your company makes,
  • what resources will best help you put your predictive analytics strategy into practice.

Predictive analytics will be an obvious asset to your company if the cost of making a series of bad decisions is going to be high (for example, similar to the $42 billion that would have been spent by the CMS).

Predictive Analytics Examples - Implementing

It’s also helpful to recognize that not all decisions are equal. Operational decisions usually have right or wrong answers, while strategic decisions can have ambiguous answers.

You can use predictive analytics with both types of decisions, but you’ll need to adapt your modeling for either situation. And then you need to select the analytics solution most suited to your needs and with a team that knows what it’s doing.

Management needs to identify:

  • your problems,
  • desired outcomes,
  • internal datasets,
  • the value of the solution you’re considering.

Use this information to determine which vendor is best suited to your company.

Predictive Analytics Is an Effective Asset

Leveraging big data is no longer the province of only large corporations. Even small businesses are now recognizing its value. Fortunately, companies are now able to tap the benefits of big data due to the availability of new cloud solutions.

When it comes to improving in any sphere of life, there are no cure-alls. However, predictive analytics is a valuable resource for helping your business not only to be more efficient but also to lower its risk in a variety of areas.

Predict Photo via Shutterstock

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Gail Gardner


Gail Gardner Gail Gardner is the Small Business Marketing Strategist who founded GrowMap.com and co-founded the Blogger Mastermind Skype group. She mentors small businesses and freelancers, especially writers and social media marketing managers.

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  1. Pingback: Are SMBs Too Quick To Outsource Data Analytics? - Smallbiztechnology.com

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