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Three steps to get started with predictive analytics right away

Predict future scenarios based on displayed behaviour. That probably sounds like music to every modern entrepreneur. Anyway, how do you ensure that this does not remain an ideal image, but that it actually becomes reality? We give you three steps, so that you can get started with predictive analytics right away.

The advantages of predictive analytics are obvious. You solve problems before they arise, and you spot opportunities that remain hidden to other, non-data-driven organisations. Sounds good, doesn't it? Then, it is important to get started with predictive analytics within the foreseeable future.

Predictive power of data indispensable

Especially in these economically uncertain times, with an unknown – but most likely large – number of imminent bankruptcies, growing fraud risks and increasingly strict legislation and regulations, it is important to act now. In fact, we believe that the predictive power of data is indispensable when mapping out a successful future.

Anyway, how do you take the first steps with this? With our three steps, you can get started right away and create a work environment in which predictive analytics can flourish.

  1. Bring IT and business together, from the start 

Data-driven entrepreneurship is no party for IT or the business. Do you want to get the most out of the predictive power of data? Then, you will have to ensure that IT and the business work together from the very beginning.

After all, marketing, sales, and the service teams know the business best and know better than anyone which variables are good indicators of success (or the opposite). IT, in turn, has the technical ingenuity and serves as a critical partner. Not by blindly executing what business units request, but by really discussing this with each other.

  1. Break through silos and open up your infrastructure

In order to be able to predict the future as accurately as possible, models need large amounts of data. Focusing on predictive analytics is neither meaningful nor successful when data is unable to flow through the organisation.

The traditional structure of many companies, with separate departments and their own systems, and places to store data, stands in the way of data-driven entrepreneurship. Before IT and the business sit down to take this next step in your digital transformation, you need to take a critical look at your infrastructure.

With the help of APIs, among other things, communication between systems and tools is nowadays quite easily possible. And you are able to break through the existing (data) silos.

  1. Cleaning and keeping data. After all: garbage in = garbage out.

Data sets have a fixed number of variables, while the future is determined by an unlimited number of factors. Predictive analytics therefore do not tell you exactly what will happen but provide you with insights. Insights you can play on. One hundred percent guarantees can never be given, but the result does tell you how great the chance is that 'something' will happen.

Do you want these predictions to be as correct and accurate as possible? Then, it is important that the data on which you base these insights is one hundred percent reliable. No matter how beautiful and sophisticated your predictive models are, if you leave incorrect information in, the results are inherently unreliable. After all: garbage in = garbage out. Therefore, first make sure that your data landscape is and remains clean.

Getting started with predictive analytics?

We are convinced that data-driven entrepreneurship is the future. At the same time, we understand that organisations struggle with this. That is why we are ready to get started with predictive analytics together with you.

Is data-driven entrepreneurship high on your agenda, but you have no idea where exactly to start? Are you looking for high-quality data to support your decisions and/or to enrich your own database? Or are you looking for the right tools to take the next step in your digital transformation? Whatever your challenge, we're here for you.

Leave your details here and we will get back to you as soon as possible.

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