In big data

In big data, industrialization is innovation

In big data, industrialization is innovation
“We need to innovate” is a common refrain. And in the world of information, there is often a mistaken belief that innovation today is purely about analytics. However, the reality is that sort of fashionista-based innovation rarely delivers sustainable results. Back in 2010, MIT and Capgemini looked at what it really took for companies to be successful with digital. Their report had a very interesting finding: Companies that take a more governed and managed approach to digital deliver more sustained benefits on their journey. Those that pursue technology- and point-driven approaches deliver less value.

This shouldn’t really come as a surprise: History has shown us that some of the greatest innovations in business come from industrializing and standardizing what others had previously done. Henry Ford famously created the first large-scale production line to manufacture his cars, an innovation that enabled him to not only make cars faster, but to make them to a higher and more consistent quality. By enabling certain people to specialize in specific tasks, it meant they could gain higher skill levels and in turn innovate within their new area of expertise.

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The key is that Ford industrialized something that hadn’t been industrialized, and today in big data we find ourselves at a similar place in the journey. We are moving from the building of bespoke smaller-scale solutions to replacing a whole data substrate across an organization. This shift from cottage industry to core capability is why companies need to industrialize to gain advantage over their competition. If we look at the key life cycle stages of ingest, store and distill, all of these are ripe for Industrialization.

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