What the future holds is uncertain. Yet we try to gain more control over it, through scenarios, strategies, and increasingly, through data. Predictive analytics, also known as forecasting, gives organizations the opportunity to reduce uncertainty about the future and make better decisions. But what makes forecasting so interesting? And why now, in particular?
We asked this question to Jan Verkade, hydrometeorologist at Deltares.
“Forecasting gives meaning to the near future”
What fascinates him most about predictive analytics is that it goes beyond simply making a prediction.
“Forecasting is very interesting as it allows one to say something meaningful about the near future. To forecast, you have to understand the process that you’re forecasting well enough to base a forecast on. That understanding in itself is very valuable.”
It’s not just about the outcome of the prediction, but also about the insights you gain along the way. Forecasting forces organizations to truly understand their processes. And that in itself provides valuable knowledge, even apart from the forecast.
Why now?
According to Jan Verkade, the timing for forecasting is no coincidence. The science and technology behind forecasting are at a very high level. That makes now the right moment to start with predictive analytics.
“Forecasting is very relevant right now because we are getting very good at it. The science of forecasting is developing, data sets are becoming widely available. That combined allows us to make forecasts that are pretty good. And we measure the quality of those forecasts so this is not something we’re just saying.”
Thanks to the availability of large datasets and the rapid development of models, predictions can now be made more reliably and objectively measured. That makes forecasting more relevant than ever today.
Less uncertainty, better decisions
So what does forecasting actually bring to organizations? In the simplest terms: a foothold in an uncertain world.
“Forecasting is important for organizations as it reduces the uncertainty about the future. Although we cannot eliminate that uncertainty, we can narrow it down and make a good estimate. If you couple that with good decision-making approaches then organizations can realize value.”
Of course, forecasting and predictive analytics never completely eliminate uncertainty, but they significantly narrow the range. That gives companies the ability to base their choices on data and probabilities rather than assumptions or gut feeling.
Risk management as an example
One application where the value of predictive analytics becomes immediately clear is risk management.
“Risk contains two ingredients: a probability and a consequence. Forecasting gives us that probability. Organizations can then estimate and minimize any risk by weighing costs and benefits with their probability of occurrence. This applies to any decision, really, whether it is about weather, hydrology, politics, or the economy.”
By knowing how likely an event is, organizations can make conscious decisions. This ranges from assessing economic scenarios to anticipating extreme weather conditions or political shifts, but also applies in asset monitoring.
Many organizations already have sensor data from machines, installations, or infrastructure, but often underutilize it. By applying forecasting or predictive analytics, it becomes possible not only to detect anomalies but also to predict when an asset will need maintenance or when the risk of failure increases. This shifts monitoring from reactive to proactive.
This approach delivers direct value: fewer unexpected breakdowns, lower maintenance costs, and a longer lifespan for assets. It also provides better insight into the underlying processes that lead to failure or wear. That way, organizations can not only intervene faster but also make structural improvements. Asset monitoring, combined with predictive analytics, thus becomes a strategic instrument that strengthens business continuity and efficiency.
Looking ahead means creating value
Predictive analytics is more than just a technical discipline. It’s a way to help organizations enter the future better prepared. The power lies in the combination of insight and action: understanding how processes work, translating that knowledge into a forecast, and using that forecast to make better decisions.
