Home Articles It isn’t disruption; it’s continuum of evolution

It isn’t disruption; it’s continuum of evolution

Disruption is not a word in the technical vocabulary. It has come into being through management jargon. Technology does not disrupt because it is forever evolving. There is always an opportunity to develop a better mousetrap. Technology evolution follows an ‘S’ curve. There is a slow start, which picks up as technology is adopted by more people and then it begins to plateau out. Innovators recognize this process and begin to evaluate new emerging technologies to take over from the older technology as it begins to plateau. Of late, the process has speeded up, which leaves slow adopters behind — hence causing disruption.

For example, consider the evolution of photography. Initially it was a film-based process and names like Kodak and Polaroid ruled for many years. Then came digital imaging, and it was not Kodak and Polaroid but Canon and Nikon that ruled. To slow moving Kodak and Polaroid, digital photography was indeed disruptive, because it destroyed their market. They failed to see what Canon and Nikon saw and capitalized on by moving away from film to digital. The old digital cameras were clunky and low resolution, but as people began to adopt them, the specifications became better and have now unseated professional film cameras. However, in this market, Canon and Nikon still rule because they foresaw the end of film as a medium. That is not disruption, that is innovation. Now, Canon and Nikon are being challenged by iPhone and Samsung. Again, it is not disruption but a continuum of evolution of imaging technology.

Geospatial systems are not unfamiliar to this process and undergo transformations, which may be disruptive for some, but it creates innovative opportunities for the others. Small satellites now enable everyday imaging, which improves the data acquisition cycle. Drones provide versatility that surpasses aerial imaging. Position location has become more accurate through better satellites, instrumentation and processing software. Diverse data sources have become available through technologies like IoT. Social media has become a source of opportunistic geospatial data. The challenge is putting these together to address human needs, in particular the challenges of sustainable development in the face of Climate Change.

Big Data provides a tool for managing data of such variety, volume and velocity. However, there is a need to move away from static, data-centric models of analysis to dynamic analysis-centric models based on diverse data opportunities. Big Data Analytics (BDA) is yet to make a significant mark in geospatial analytics specific to sustainable development and Climate Change. It is to the credit of meteorological scientists that they have a much better handle on Big Data for dynamic modelling of climate and climatic events, though they might not recognize the term BDA. In the same way, Artificial Intelligence has to become the go-to tool for predictive analytics, but here too, geospatial professionals are lagging behind.

Innovation is needed in many areas for innovative technology and applications to flourish. The biggest area where innovation is needed is in capacity building in the fields of BDA and AI for geospatial. The pace of revision and augmentation of geospatial curricula is unable to keep up with rapid changes in technology. This requires a much closer interaction between academia and industry. In the short-term, geospatial courses need to include subjects that are in demand in the industry. However, educational institutions have a long-term goal, and the industry needs to recognize these goals and support long-term research financially and by loaning experts.

Another area is regulatory, and in particular, privacy related. High resolution imagery, in situ data collection and harvesting of social media, lays open sensitive personal data which impacts the privacy of individuals and groups if not suitably anonymized. Laws regarding such issues are in place like GDPR in Europe. There is a need to examine these laws in the context of geospatial data.

Disruption happens when enough attention is not paid to evolving technologies and their possible consequences. Smart professionals, institutions and governments need to be aware of the changes and importantly, the rate of change. Good managements deal with the risk of disruption by devising means of avoiding it.