Big Data’s Potential For Disruptive Innovation

An innovation that creates a new value network and market, and disrupts an existing market and value network by displacing the leading, highly established alliances, products and firms is known asDisruptive Innovation. Clayton M. Christensen and his coworkers defined and analyzed this phenomenon in the year 1995. But, every revolutionary innovation is not disruptive. When a revolution creates a disorder in the current marketplace, then only it is considered as disruptive.

The term ‘disruptive innovation’ has been very popular over the past few years. In spite of many differences in application, many agree on the following.

than their existing counterparts in the market.

The reason why the above characteristics of disruption are important is that when all 3 exist, it is very difficult for an existing business to stay in competition. Whether an organization is saddled with an outmoded distribution system, highly trained specialist employees or a fixed infrastructure, adapting quickly to new environments is challenging when one or all of those things become outdated. Writing off billions of dollars of investment, upsetting the distribution partners of your core business, firing hundreds of employees – these things are difficult for managers to examine, and with good reason.

Every day, new technologies emerge. The vendors in the market get shaken only if the technological innovation is extremely powerful. Big Data technologies such asNoSQL and Hadoop could be seen as catalysts for this type of innovation. We should understand here that big data is just raw data. The disruptive innovation coming from big data arebig data analytics processes and technologies.

In the marketplace, big data is a disruptive force. It means that people require more than new skills, technologies and tools. They need an open mind to rethink about the processes they have followed for a long time and transform the way they operate. However, it is not particularly easy to force this type of change on long-time employees.

This must be viewed differently as many people believe thatbig datais a disruptive opportunity. Instead of the challenges that are stated above, we should consider 2 positive aspects:

In his seminal work,The Innovator’s Dilemma, Clayton M. Christensen states a path forward for disruptive, new innovations in the following 4 steps: 

There are various new market entrants at this stage with a large amount of chaos and the major focus of customers is on the emerging feature sets and functionality. When a technology arrives in the market, the first thing people look for is advanced features and high product performance, while ensuring it is doing the new thing they expect.

When the market reaches this stage, people have accepted the feature set and they now want reliability and stability in the products. There is a shift in focus from ‘does this product do what we expected’ to ‘how reliable is this product.’

Here, the relevance for big data implies making the software accessible on mobile devices in the form of iPhone apps or similar ones.