Businesses looking to make the most of big data analytics must ensure that their initiatives have the support of senior executives, as without this, they will find it much more difficult to overcome obstacles and gain competitive advantage.

This is one of the key findings of a new survey carried out by Forbes Insights and McKinsey, sponsored by Teradata, which revealed that leading-edge organisations have much better buy-in from their C-suite than those where data analytics is less of a priority.

In enterprises where big data is viewed as the number one way of gaining competitive advantage, over half of businesses are led by chief executives who are personally involved in analytics initiatives.

Meanwhile, in organisations where big data is viewed as a top-five issue that gets significant time and attention from top leadership, the key sponsor is typically one level below top leadership.

Overall, around 90 per cent of respondents reported medium to high levels of investment in big data, with a third describing their efforts as very significant.

The three most important use cases for the technology were said to be creating new business models (54 per cent), discovering new product offers (52 per cent) and monetising data to external companies (40 per cent).

However, there remain difficulties for businesses, with the cultural shifts needed to support a big data environment among the biggest issues. Over half of respondents stated that adopting a data-driven culture is the single biggest barrier, while rewarding the use of data and fostering experimentation and creativity with data were also highlighted as significant cultural challenges.
Matt Ariker, chief operating officer of consumer marketing at McKinsey, said that despite the good progress overall, there remains room for improvements, and failing to get to grips with the cultural challenges can especially hinder initiatives.

He added: "The good news is that the reverse is true as well: improving how a company fosters a culture and mindset that rewards the use of data experimentation can help a data and analytics initiative gain momentum and impact."