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 techniques from modeling, data mining, machine learning, statistics, and artificial intelligence for analyzing the current data and make predictions about the future.
A number of 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. You can predict future trends related to different niches and then develop a product that will help the audience in that niche solve their problems.
For instance, if you are a marketing firm, then using predictive analytics, you may come to a conclusion that Facebook advertising is going to be widely used in the future, you may start to train your team to become better Facebook advertisers from now.
Predictive analytics can be used to reduce the number of business risks by getting insights into the 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 of similar product like a charcoal mask had in the past and how much demand you can expect for your face mask in the future.
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: 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 properly leverage predictive analytics solutions.
- Adoption: Predictive analytics solutions are typically standalone tools which mean businesses will have to discard the use of their primary business applications to get this solution. If a business 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 that may interrupt their workflow.
So these are some of the benefits and challenges that businesses face when dealing with Predictive Analytics solutions. Keep in mind that there are some predictive analytics tools out there that have overcome these challenges to provide businesses with an all-in-one solution.