Predictive analytics: what's happening in the business tomorrow?

Reading Time 4 minutes | Written by Michiel Scheepens | September 6, 2018

With predictive analytics, your company predicts what will happen tomorrow. This enables you to anticipate the most promising prospects, market developments, defaults and fraud, for example. Chief data scientist Joris Peeters talks about the latest developments and backgrounds and casts a glance into the crystal ball of predictive analytics.

Cars today can drive themselves, objects can be printed at home, and appliances we can control with our thoughts. Then it's not so strange that we can predict how things will be tomorrow, right?

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The magic formula for this, explains chief data scientist at Altares - Dun & Bradstreet Benelux Joris Peeters, is as follows: an ever-growing mountain of data + data mining + machine learning techniques + statistical algorithms and models.

The formula leads to state of the art predictions, Peeters states. "For example, our models can predict more than three-quarters of the bankruptcies that will take place in the Benelux in the next 12 months."

Prosperity through predictive analytics

The applications of predictive analytics for businesses are many, Peeters knows. "Prospecting, compliance, credit scoring, process automation, accounts receivable management, logistics, customer analytics: basically throughout the business cycle you can apply the data and technology of predictive modeling."

Let's zoom in on prospecting. Peeters: "With a simple command to a database you can already separate the wheat from the chaff, for example by filtering out companies that are too small. But the real power comes from predictive modeling. This tells you which prospects have the best chances of success and therefore who you should approach first. Suppose that normally 2 percent of the companies you call with cold calling eventually buy something from you. With predictive modeling, you can increase this percentage to perhaps 15 or even 20 percent."

Identifying which customers might leave, predicting which suppliers are going to be in trouble, discovering in a timely manner which transactions pose an increased risk of fraud and corruption: there are countless other examples of how predictive analytics helps companies move forward. Would you like to know more about this? Then read our white paper 'From data to insight: predictive analytics'.

Analytics: points of interest for businesses

Joris Peeters observes that companies in the Benelux are rapidly realizing that they need to work with business analytics and predictive analytics. However, in order to gain insights from data, a lot of knowledge is required internally. What do Peeters see as the most important points of attention for companies?

1.   Understand the power of data

Companies do not always realize the possibilities of data. Peeters: "If you don't constantly investigate what is possible, you will fall further and further behind. Companies whose management understands what you can get out of data are the winners of the future. We are already seeing this gap develop in the market."

2.   Invest in knowledge with the right people

Companies need to have a lot of knowledge about data and analytics. But who do you hire to do that? "I've seen companies where they appointed data science teams with only doctors of mathematics. However, the return on investment was lousy. Those people know everything about statistics, but have less feeling for the business," says Peeters. His advice: at C-level one should have sufficient knowledge of - and ideas about - the possibilities of data. And lower down the tree, there must be a strong link between data science and the business side.

3.   Don't invest blindly in hardware and software

Technology, Peeters argues, should be an enabler - not an end in itself. Too many companies stare blindly at certain hardware or software, without asking themselves what they want to do with the data. "First take stock of what the purpose of the data is and only then figure out what technology you need," advises the data scientist. In the end, it's all about an interplay of appropriate technology, good data and capable people.

Doing your bit for evolution

Altares - Dun & Bradstreet, as a leading player in the field of predictive modeling for businesses, will be making a solid contribution to the evolution of predictive analytics over the next decade. According to Peeters, three major developments await him and his colleagues:

  1. How can the ever-exploding mountain of unstructured data in social media, for example, be linked back to the companies that store it? For that, a hefty dose of artificial intelligence is needed. And that is work in progress.
  2. Companies expect - and rightly so - that models and platforms will continue to improve. So that the predictions are more accurate and they can extract ready-to-use (predictive) analytics from, for example D&B CreditD&B Onboard and Market Insight can seamlessly integrate into all their workflows.
  3. There is an increasing emphasis on mobile devices. Customers no longer want to read a 15-page report. Everything has to be simple, fast, easy and efficient. And that can be done with mobile.

The prediction on predictive analytics

Where will we be in 10 years in terms of predictive analytics, according to Peeters? Peeters: "We are going to see spectacular developments in all areas of the business cycle. For example, we are now also collecting data on transport. In the future, transporters who have space available in their trucks can see on their app whether they can also transport some extra cargo from other companies."

Workdays are undergoing a hefty metamorphosis, Peeters sees in his crystal ball. "Suppose you are a sales employee. An intelligent system creates a prospect list for you on your phone. You order a self-driving car, plug in your phone and the car automatically drives the smartest route to all prospects. Once you're at a prospect, you immediately run all kinds of tests through your phone, for example in the area of creditworthiness and compliance. On the way home, you can send a few more invoices fully automatically, for example."

It all sounds very futuristic, doesn't it? Peeters: "That's not so bad. We have already discussed this sales scenario in concrete terms with customers. Believe me: it's closer than you think."

Want to read more about the applications of predictive analytics, areas of concern for businesses, anticipatory analytics, business analytics trends and Altares - Dun & Bradstreet predictive models? Then download our white paper 'From data to insight: predictive analytics’.

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Michiel Scheepens

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