Forecasting as a routine: technology forecasting in practice

Every organisation has to trust that it will see new technology coming in time. But most ways of looking ahead share a weak spot: expert panels are prone to bias, data models mostly look backwards, and the big firms' trend report is read by everyone — including your competitor.

In an action research project, published by IEEE, we developed and tested a method that combines two worlds. Text mining works through stacks of technology reports in a fraction of the time it would cost a person, without favouring the loudest voice in the room. Scenario planning then adds the depth: in a half-day workshop, a team builds four future scenarios around one technology and decides what the organisation should do now.

What the participants reported

• Speed. Trend identification no longer takes weeks — just the time needed to collect the reports.
• Depth. Scenarios force you to take uncertainty seriously, instead of predicting one future and betting on it.
• Repeatability. The approach is a playbook, not a one-off trick. A year later, every participant still rated the workshop 7.5 or higher.

The honest lesson

That same one-year look-back also taught us something uncomfortable: the organisation had not repeated the method. Looking ahead only works as a routine — embedded in the organisation's rhythm, with people trained to run it themselves. One good workshop changes your view; a rhythm changes your organisation.

That is exactly how we see it at KabriTO: not yet another trend report, but the capability to look ahead yourself — periodically and with structure.

The full paper was published by IEEE: Technology Forecasting: Action Research on Integrating Scenario Planning and Text Mining.