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What is Predictive Analytics, its Benefits and Challenges?

Predictive analytics is a form of advanced analytics that is used to make predictions about uncertain future events. Predictive analytics leverages many data mining, analytical and predictive modeling techniques are used to bring together the information technology, management, and business process to make future predictions. Patterns from historical and transactional data are analyzed, and then the future opportunities and risks are identified that help decision-makers make an optimal decision.

Benefits of Predictive Analytics for Businesses:

Understand Customer Needs:

By leveraging smart analytics, businesses can get an in-depth and precise picture of who their customers are and what they really want. 

Predictive analytics can be used to reduce the number of business risks by getting insights into things like the success of new products, getting an idea of businesses they are dealing with, or assessing the demand of something in the future to identify new opportunities.

 

For instance, you may be launching a new beauty product such as a face mask, by using predictive analytics, you will know how much demand for a similar product like a charcoal mask had in the past and how much demand you can expect for your product in the future.

Mitigate Risk:

If you have a lower risk, then obviously your cost would be lower as well because you will not face failures in the future that lead to financial losses. Furthermore, by analyzing future trends, you will be able to take better steps towards working on an optimal approach and reduce costs.

For instance, if you are buying an asset, you can leverage predictive analytics to determine its maintenance needs beforehand so that you can properly service it and reduce costs that may incur if it stops working.

Cost Reduction:

If you have a lower risk then obviously your cost would be lower as well because you will not face failures in the future that lead to financial losses. Furthermore, by analyzing future trends, you will be able to take better steps towards working on an optimal approach and reduce costs.

For instance if you are buying an asset, you can leverage predictive analytics to determine its maintenance needs beforehand so that you can properly service it and reduce costs that may incur if it stops working.

Challenges with Predictive Analytics:

  • Having Expertise:Having Expertise: This is one of the primary concerns for businesses because predictive analytics solutions are usually designed for people with a deep understanding of statistical modeling, Python, and R like Data Scientists. This limits teams without knowledge of these things to properly leverage predictive analytics solutions.
  • Adoption: Predictive analytics solutions are typically standalone tools which means businesses will have to discard the use of their primary business applications to get this solution. If a company does that and its team doesn’t learn how to use predictive analytics solutions, it can be a big problem.
  • No Actionable Insights: Predictive analytics solutions are usually limited to just providing data about future trends. They do not provide insights to end-users that can help them take action. So, for this, end users have to switch to another tool and may interrupt their workflow.

Final Words:

These are just some of the benefits and challenges that companies face when dealing with predictive analytics solutions. Keep in mind that there are some predictive analytic tools out there that have overcome these challenges that could provide your businesses with an all-in-one solution.