It’s clear that data and analytics are transforming industry competition, and while some businesses are accelerating at pace, many are yet to implement the necessary changes. In the latest McKinsey Global Survey, respondents believe that the changes data and analytics have created over the last few years have continued to grow. However, they also suggest that many businesses have reacted to this shift with one-off actions rather than implementing a long term plan.

Studies by McKinsey suggest many businesses are being relatively slow to respond to these transformations and potentially could find the gap between them and industry leaders extend further. Based on the report, companies with the most growth in revenue and earnings put a large amount of this increase down to data and analytics. Respondents from these businesses are far more likely to indicate data and analytics plans have supported an increase in earnings over the last few years.

What can other companies do to utilise data and analytics and follow others capitalising on the benefits of data and analytics? The most important factor is that these companies are implementing a long term data and analytics strategy and enforcing this as a core part of their workforce plan and culture. They ensure that high-quality data and modern technologies exist and can support further scaling.

In many industries, professionals believe data and analytics as a priority transforming the competitive landscape. 47% of respondents from the McKinsey survey believe data and analytics have changed the nature of competition in their sector over the last few years. While this may sound relatively low, it represents a 38% increase since the previous survey. When questioned about competitive changes, respondents point towards new analytics-focused businesses and the frequency of new companies emerging in this space. Despite the rise in competition, results suggest that most organisations still respond in an ad-hoc manner toward data and analytics plans.

Many industry professionals recognise that a lack of strategy for these areas will significantly impact future success. Over 20% of respondents believe having a data and analytics strategy is the number one reason for their success, an increase of 14% since the last survey by McKinsey.

While creating a strategy is essential, the survey results suggest that another vital factor driving success is delivering a data culture or creating measures that combine data and decision making. McKinsey interviewed a selection of businesses about their data culture and discovered that having employees use data consistently for decision making is critical for success.

Education is also a key factor, as developing a team with data and analytics skills is a top challenge to reaching a company’s objectives. Businesses have indicated a lack of company-wide education on data as a barrier to implementing new plans. Another aspect of creating a data culture is attracting and retaining the best talent, highlighted as a priority by employees at high-performing businesses. Similar to the previous survey, the biggest talent requirements are business users with analytic skills and a general need for more data professionals. While automation is growing, managing the data needed for these business changes is predominantly human-led.

Creating a data-driven culture requires technology that can support a business in utilising data and analytics. Establishing a solid data architecture enables companies to effectively collect and share data and ensure their employees can access and use information needed. It also allows for efficient delivery of high-level data quality, supporting data-based decision making.

The McKinsey survey suggests high-performing businesses have surpassed others in achieving their data and analytics plans and using both strategy and a solid data culture to extend the gap from other competitors. How can businesses improve the use of data and analytics and reduce the gap?

Improving the availability of data – the survey suggests how important it is to extract data from silos and place it in sophisticated analytics-based tools and allow decision-makers to have easier access to this information.

Recognising data as a product with genuine returns on investment – Business leaders often consider data as something supporting analytics and their decisions. Data should be viewed as an internal product shared across the group and integrated with performance, revenue, quality and other measures.

Be flexible toward data transformation plans – While high performing businesses have enforced a data culture, it’s critical to understand that even the best are yet to implement all of the suggested practices for data culture and have the room to go further. Rather than approaching this by attempting to tackle the gap with large-scale changes, businesses must focus on gradually evolving their data culture over time.