Descriptive, Predictive, and Prescriptive Analytics: Which one is best for your business?

Big data and analytics are the latest household names in the business and technology world, and they are here to stay. A recent report by the International Data Corporation projects that this industry will be valued at $41.5 billion by 2018, representing a 26.4 percent annual growth rate. What does this mean for your business?

f your organization is already collecting big data, now is the most opportune time to begin analytics on the data. Analytics will provide great insights into your business (and your customers), but only if you know how exploit the full their potential. There are three main types of business analytics: predictive, prescriptive, and descriptive.

Unfortunately, most business owners are not familiar with these concepts. When you think analytics, you’ll often wonder where to begin, or which type of analytics your business needs. Read further to learn more about the three types of data analytics and which of them is best for your business, and how a technology consulting company can help you make informed decision on which analytics to adopt.

Descriptive Analytics

Does your business generate a lot of data from CRMs, ERPs, POS, and HR systems and it becomes a challenge to organize, tabulate or even define it? Descriptive analytics is the solution your business needs. As the name suggests, this type of analytics "describes" different types of data. Many experts consider this as the first step in the analytics process. It performs otherwise complex summaries on data and simplifies it into something humans will understand easily, and can depend on for decision making. The term is used interchangeably with "reporting".

Descriptive analytics offers insights into past occurrences. It also helps in studying consumer behaviors to determine their most likely influence on future outcomes. This class of analytics is the simplest to perform. Experts estimate that over 80 percent of the analytics done by businesses are descriptive, and are mostly social analytics. It’s no surprise then that your business’s social media page will be summarizing tons of data in the background for instance, total number of likes, views, pins, mentions, posts, fans, and many more metrics that will simplify your analysis work a great deal.

Much of descriptive analytics relies on basic computations, such as sums, averages, and counts, on the data fed into the model. This type of analytics can save your business a lot of time and human resources in tabulating critical statistics such as the total stock in your inventory, the average dollar your business spends on every customer in advertising, and annual changes in sales. If your goal is to obtain timely and reliable summaries of different aspects of your business, descriptive analytics should be your go-to option.

Predictive Analytics

Predictive analysis, which steals most of the attention from the other types of analytics, uses data acquired in the past, to predict future outcomes. Historical data, including trends and patterns, can provide a basis for predicting the future outcome of a given situation.

This is a capability almost all businesses wishes it could possess, and one that has the potential to change how people do business. It’s worth noting that predictive analysis is not your definitive answer to what will happen. Rather, it assigns probabilities to a series of possible outcomes, equipping you with the power to decide which direction your business should take.

Predictive analysis has become increasingly popular because of its high applicability in business processes and more specifically, sales. This type of analytics can influence the type of email communications you send out to your customers, your social media strategy, help in analyzing lead sources, and analyzing customer relationship management data. As an added benefit, predictive analytics will serve as an avenue for performing predictions on other data you did not have beforehand.

Today, one of the prominent forms of predictive analytics is sentiment analysis. This technique has provided very promising results especially when used on social platforms. Also known as opinion mining, sentiment analysis combines tools such as text analysis, natural language processing, and computational linguistics to assign a sentiment score on the data analyzed. The outcome of such analyses can inform business decisions to a great extent. For instance, by analyzing consumers’ spending trends, you can decide whether to upsell or cross-sell your products.

Prescriptive Analytics

Prescriptive analytics is relatively newer, and also operates on a higher level than both descriptive and predictive analytics. Anne Robinson, Verizon’s director of supply chain strategy & analytics, considers this type of analytics as what will tell you what to do in order to maximize the chances of attaining your business goals. It offers a number of possible courses of action, and proceeds to compute the likely outcome of each alternative action.

In order for prescriptive analytics to be effective, it requires a reliable predictive model that contains two additional, but core components: actionable data and system that tracks and receives feedback from entities impacted by the action(s) taken. This type of analytics combines a variety of tools such as machine learning, algorithms, business rules, and computational models to analyze big data, real-time data, and historical data.

Due to the complexity of administering prescriptive analytics, most businesses are yet to incorporate them into their core processes. However, proper implementation of the analytics model can have an immense impact on how you make business decisions. It will not only quantify the potential impacts of future decisions, but also model the possible outcomes of the decisions to your business, even before you actually make them. If you need advice on the most suitable cause of action for your business, predictive analytics will do just that, and much more.

Having learned about the differences between the three types of analytics, you’re better equipped to decide which one best suits your business. When it comes to the actual adoption of analytics, a technology consulting company can help you decide on the most appropriate model to apply in your business. It will advise on the best tools and infrastructure that will support the selected model, the kind of training (if any) that your staff and personnel will require, and the legal considerations you should make when adopting data analytics.