Predictive analytics: Perceptions and realities

Director of Offering Management, IBM Analytics, IBM executives, IT managers and business teams are discussing predictive analytics with increasing frequency, but every perspective seems to be different. Various roles can often have diverse perceptions of predictive analytics, and many of them are simply inaccurate.

Some people may think predictive analytics is just too challenging to understand or that it’s just for IT—both of these perspectives are false. Some executives may admit to not having a clear picture of how it works, and assume that rocket science–scale mathematics pulls the data, shakes it up and somehow delivers valuable information. In other words, they kind of look at predictive analytics as if it’s a corporate crystal ball.

And some IT staff may think that predictive analytics requires purchasing a lot of new tools, and that their team will need to become highly skilled to use them. Even more frustrating, some business teams may not fully understand how to actually get the insights they desperately need.

Dispelling inaccuracies

These misconceptions about predictive analytics are all quite common. We need to clarify the realities.

Predictive analytics is actually easier to understand than many may think. It’s a process that uses historical data and existing data to predict what will happen next. And predictive analytics doesn’t necessarily require deep skill sets for in-house staff. Moreover, predictive analytics can bring enormous value to organizations across a wide range of industries—even within departments from marketing and sales to finance and operations.

And predictive analytics is an exciting area because it can quickly move project teams from plain guesswork to prediction that is based on a degree of certainty. It shows organizations or project teams where they are now and where they can go, and it enables them to discover trends, patterns and relationships in structured and unstructured data. In addition, predictive analytics can provide the direction necessary to apply insights and predict future events.

Acting to achieve powerful outcomes

Predictive analytics simply doesn’t require a large team of highly experienced, highly skilled analysts. Getting started with predictive analytics only requires three skill types:

  • A businessperson who understands the business problem and has the ability to formulate this problem in a way that facilitates decision making.
  • An IT leader who can gather the data, automate the process and set up the IT system to enable the analytics execution.
  • An analyst who understands and evaluates the algorithms that ultimately get to the insights the organization is seeking.

Bear in mind that all three roles do not have to be on staff. A trusted partner can complement the staff with the appropriate experts to begin accessing valuable insights that can move the organization forward.

Predictive analytics can have a tremendous impact on a range of outcomes including those that grow profits, reduce fraud and even save lives. Learn more about the rewards of making predictive analytics a part of your business strategy.

If you're interested in getting predictive analytics to work for you, contact an IBM expert or explore our portfolio today.