Businesses today have an enormous amount of data available to them, but figuring out how to use this data to their advantage can seem like an intimidating process. One way that this data can be leveraged is through the use of predictive analytics, which allow companies to not only see trends in their past data, but also to extrapolate possible future trends and better plan for the success of the company.

Beginning to use this technology isn’t as complicated as it may seem if a company is already using Enterprise Performance Management (EPM) solutions, since many aspects of predictive analytics go hand in hand with EPM methods.

One of the most common uses for predictive analytics is determining what companies can do in order to attract and retain customers, along with earning the largest profits from each customer. This goal fits in perfectly with EPM’s tenet of customer profitability analysis, and it can provide businesses with much more accurate answers than older methods.

Another area in which predictive analytics can be applied with great success is Enterprise Risk Management (ERM). Whereas some older methods of determining the most significant risks to a company were as outdated as filling in data on spreadsheets and trying to determine risks based on that data, predictive analytics gives companies a much more concrete, organized method of evaluating risks.

As was demonstrated by Mongolian Mining Corporation (MMC), which made the switch from a spreadsheet system to using ERM solution provider Active Risk’s Active Risk Manager, making the switch to predictive analytics can do a lot for a company. Senior Risk Analyst of MMC Tsevegmed Tserendondov stated that the prior system was “time consuming and required considerable manual effort,” and the new system took only two weeks to implement.