Every business needs the best intelligence it can get to make the right decision at the right time. The best business decisions, whether they’re meant to cut costs, improve efficiency, or find better ways to market products and services, are based on data. Of course, thanks to the constantly growing volume of big data, it’s impossible to gather actionable insights using legacy systems or traditional means.
Modern business intelligence (BI) relies on advanced analytics, and prescriptive analytics is one of the best tools in the kit. To understand how prescriptive analytics can assist you with business process management, however, it’s important to have a grasp on some other analytics techniques.
Descriptive Analytics: This is the process of examining historical data to understand past changes in the business. This gives business leaders a holistic view of business performance during the selected time period to provide greater context to business functions and help guide better decisions in the future.
Diagnostic Analytics: If descriptive analytics tells you what happened in your business, then diagnostic analytics tells you why it happened. This is often done through data mining, which combs through extremely large data sets to find patterns and trends. If customer satisfaction dropped last quarter, for example, your diagnostic analytics might uncover that some of your best customers were displeased when dealing with automated IVR customer support rather than the support agents they’re used to.
Predictive Analytics: This type of analytics is used to make predictions on what will happen based on a combination of historical and current data patterns. An example could be analyzing past and current customer behavior to predict future market trends and gain a competitive advantage.
It might sound like these are all the tools you need, but prescriptive analytics takes things a step further by, not only predicting future outcomes but also presenting the possible consequences of each one. This type of data analytics seeks to draw insights into the best course of action for each business problem. Here’s what you’ll need to know to master a top-rated prescriptive analytics solution.
One thing that business users have to remember about a prescriptive analytics platform is that the possible outcomes and insights it produces are only as accurate as the data that’s entered in the first place. If you’re trying to increase sales for the next quarter, for example, you’ll need to take into account all the things that affect sales. This includes product design, pricing, customer service and support, and even the efficiency of your supply chain.
Breaking each problem down into individual factors and then feeding the most accurate available data into your prescriptive analytics tools will produce better recommendations. Most platforms use computer algorithms empowered by machine learning to create their statistical models at a rate much faster than any data scientist could on their own. By gathering the right information from the appropriate data sources, you can produce actionable insights based on your business rules in near real-time.
There’s no denying that prescriptive analytics can be just what you need to take your business intelligence to the next level, but it’s important to remember that the results are essentially simulations of possible outcomes. Depending on your own business rules and what’s possible for you during a given time period, every suggestion offered may not be possible. For example, if one of the analytics solutions suggested raising prices beyond what you know customers to be comfortable with in order to boost revenue, you’d likely rather pursue a different option that allows for a better customer experience.
No matter how useful technology is, there are always some constraints. With some practice, you’ll learn how to identify and pursue your best possible options and improve decision-making.