The Emerging Role of Predictive Analytics in Tech - American Technology Consulting

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The Emerging Role of Predictive Analytics in Tech

Kelsey Davis

Published January 9, 2020

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predictive analytics

Technology and data change every day. Just as you think you grasp the “next big thing” to help you manage your data, another innovation comes along. After a while, playing catch up can seem futile and you’re left treading water, hoping not to drown in the sea of data your business has accumulated.

So how do you make it to shore in a sea of overwhelming information?

Predictive analytics to the rescue. This life preserver dissects and uses your data effectively so you can stay even with the tide and swim with strong currents instead of against them.

What is Predictive Analytics? 

Business intelligence leverages technologies and services to gather, analyze, interpret, and transform data into intelligent decision making using a streamlined approach that synthesizes all the information collected and presents it in easy-to-understand formats. BI tools, often referred to as data analytics, can provide incredibly deep and powerful insights into your business and organization, successfully predict trends and events, and use reporting functionality to serve as a guide for further action.

The predictive analytics portion is the ability to consume and crunch data using machine learning models to heavily steer a data-driven decision for the best possible outcome. 

Predictive Analytics Evolution

This process has a deep history, but its emergence in tech has only occurred over the last 20 years. It has now evolved into a multi-industry best practices approach as it defines the practical outcomes for business objectives.

It has spidered its way into multiple industries and helped them from the inside out. The industries include:

  • Insurance
  • Banking/Financial
  • Technology
  • Retail/E-Commerce 
  • Energy & Manufacturing
  • Government & Public Administration

Predictive Analytics Implementation

One of the biggest hesitancies we see with companies dragging their feet on predictive analytics implementation is a gap in skills. Before you can analyze data, it needs to be prepped first. Businesses need to ensure they have the manpower or can adequately contract out the duties of someone who can efficiently and effectively move between data and strategy as figuring out target definition is essential for outcome interpretation. 

Once this skills gap has been filled and the data reasonably prepped, predictive modeling can start. Advances in technology enable software to do a lot of the grunt work around this area, but it’s beneficial to have a data analyst carry out the modeling tasks to achieve the best results. 

Your IT department should take over the process once the models hit the deployment stage. This is the exciting part as this is where the models work on your data and you see the results of their efforts. Now that your data is being collected, sifted through, and deployed appropriately using your defined analytics approach, it is time for your leadership team and executive decision makers to use the intel intelligently, strategically, and thoughtfully as they dictate the storytelling and direction of your vision.

Predictive Analytics Benefits

How exactly is predictive analytics, working in tandem with business intelligence solutions and RPA, beneficial?

The three main areas that predictive analytics assists businesses with are:

Marketing Optimization: Predictive analytics is used in marketing campaigns to optimize data by analyzing it to find predictive patterns for consumer behavior, letting businesses make intelligent business decisions based on the findings.

Fraud & Risk Reduction: New tech always means wariness among customer as keeping their information safe is a top priority. The combination of up-to-date cybersecurity metrics and predictive analytics serve as a fraud deterrent. On the business end, your company can use predictive analytics to gauge the risk of potential customers so you can mitigate the concern.

Improvement to Operations: Predictive analytics is commonly used by businesses for inventory control and resource management, helping businesses set prices and predict event and marketing outcomes.

Why Predictive Analytics is Important

A Look Into the Future

As big data analytics climbs in popularity, fueled by predictive analytics and nitty gritty details it can etch out for lucrative opportunities, possibilities for its future seem limitless. As time goes forward and other advancements improve, expect more of the predictive analytics functions to be carried out with less human connection.

That doesn’t mean human workers are disregarded completely. As with any big digital disruption, innovative starts and ends with human dreams. As long as your business stays adaptive and flexible, there’s a way to incorporate big tech ideas alongside us regular folk. 

And you don’t have to go about it alone! Let us at ATC serve as your expert navigator. We can handhold and give constructive advice, lead the initiative completely, or just act as a resource for you to bounce ideas off of.

Contact us now and we’ll get started pronto, or at least answer some questions for you.

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