What is predictive analytics? With all of the data jargon out there, this blog dissects predictive analytics and explains what it actually means for businesses in real-life. 

What is predictive analytics?

What if you were given the chance to see directly into the future?

Imagine if you were warned about risks years in advance so that you could stop disasters from happening.

And imagine being shown exactly how you could optimise your efforts now to gain even greater success later.

Would you take it?

Well, the truth is, this opportunity already exists, and it’s called predictive analytics.

Predictive analytics can be defined as: “the practice of extracting information from existing data sets in order to determine patterns and predict future outcomes and trends.” – Webopedia

Predictive analytics always starts with a goal in mind. Whether it’s to improve the performance of a campaign, reduce costs around recruiting, or to ensure that product inventory and demand are aligned. 

Once this is in place, it can be used to bridge the knowledge gap between unanswered questions and the desired outcome in order to make these goals a reality.

For example, an organisation wanting to save costs associated with recruiting can use predictive analytics to understand the key traits that make a good employee and the probability of them sticking around for the long-term. Through unveiling these insights, they’ll be able to significantly reduce the amount of time it takes to hire high-quality employees, and equally reduce the risk of having to rehire anytime soon.

Similarly, an organisation hoping to increase sales can use predictive analytics to track customer behaviour and determine what information and sales tactics will result in more completed transactions.

It can even be used to help processes run more efficiently by determining when machinery needs to be serviced in order to prevent time being lost to break-downs.

The list goes on…

How does predictive analytics work?

From ad-hoc statistical analysis, predictive modelling, data mining, to text analytics, optimisation, real-time scoring and machine learning; predictive analytics brings together a number of advanced analytics techniques.

In a way, it works like our own brains. It takes these various advanced analytics techniques (AKA “cognitive processes”) and applies them to historical data (AKA past experiences) to anticipate how what has happened before will determine what happens next.

Through this, businesses can discover patterns that help them to determine which actions will drive the desired outcomes.

This means that organisations are not only able to report on what has already happened – they’re able to have their very own crystal ball at hand to predict what will happen five, ten, even fifteen years from now. And it’s this trait that makes predictive analytics so different from traditional analytics.

What are the benefits of predictive analytics?

There are two organisations – company A and company B. Both are in the same industry, and each are similar in size and resources.

The only difference is that company A uses predictive analytics, whilst company B does not.

What would that difference be?

Well to cut a long story short, company B would react to issues, whilst company A would take the initiative to solve them.

The best decisions are informed decisions, and having the power to anticipate future behaviour and outcomes puts any business strides ahead of the competition.

Predictive analytics gives organisations the edge through a number of different ways. Here are some examples:


  • Increased sales

Being able to predict which product or service will perform better at a certain time of year allows an organisation to create strategic promotions that go beyond gut-feeling and focus on what the data says. 


  • Better understanding of customers

Customer data is valuable, and predictive analytics allows organisations to unlock the potential of this data. By allowing them to understand customers’ previous purchasing history, businesses are able to target customers with personalised offers that resonate with their wants and needs.


  • More efficient processes

Say an organisation has been having issues with their supply chain and want to improve the process… predictive analytics uses demand forecasting to predict the future demand for products and parts. This in turn, prevents any out-of-stock disasters and ensures that customers receive items quickly and smoothly


  • Save time

Streamlining processes helps to save time. For example, through predictive analytics, an organisation may realise that outsourcing a task to an external agency will end up costing them hundreds of unnecessary hours.

Once identified, they could put training programs in place to teach employees how to carry out these tasks on their own. This would not only save money over time, but it would also reduce the number of steps involved to complete the work, and therefore save significant time.


  • Save money

Understanding the areas of your business that hold you back is important. Whether it’s employee absences or money lost to student drop-outs, predictive analytics can be used to identify key factors that indicate risk so that action can be taken to prevent loss of revenue.


  • Effectively manage risk

In the finance industry, predictive analytics is the technology behind the credit approval process. It analyses an applicant’s previous credit history and compares this with the track record of other applicants to assess whether or not they’re likely to be able to meet payments.

Similarly, predictive analytics can be used to safeguard against other risks, like ensuring that budgeting is accurate to prevent going out of pocket, and managing processes more effectively to ensure that the business is best prepared if disaster strikes.


  • Reduce fraud

It’s estimated that 5% of revenue is lost to fraud every year. Predictive analytics detects the patterns related to suspicious activities and stops fraudsters in their tracks.   


  • Identify new opportunities

Predictive analytics works to allow businesses to spot opportunities in real-time so that they can make accurate decisions that will benefit them later down the line. In an IBM study, over 50% of all organisations said that predictive analytics helped them to identify new opportunities.


  • Grow revenue

Through lowering costs, improving efficiency and being better able to detect new opportunities, predictive analytics works to increase revenue in the long-term.


When thinking about how to get started with predictive analytics, it can be confusing.

We’ve teamed with leading author, speaker and advisor, Bernard Marr to bring you a comprehensive guide to embracing predictive analytics. Packed with useful advice and inspirational use-cases it will help you understand how you can start using predictive analytics in your own organisation to reach your goals. Get your free guide to Embracing Predictive Analytics.



Oletta Stewart

Content Writer

Oletta Stewart is a Content Writer for MHR Analytics.


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