It’s no secret that data and analytics play a key part in every organisation’s digital transformation efforts. Data science has become a rapidly progressing field thanks to the crucial role it plays in understanding big data.
Although data has become a real game-changer harnessing it is not always straightforward and many global corporations are struggling to leverage their data assets. These strategies generate an overabundance of data – and even more questions, requiring more analytics than most can possibly imagine. They also require continuous analytic breakthroughs in order to achieve a true digital transformation.
This pressure to exploit data in new ways and the increased emphasis on digital transformation is also causing a tremendous amount of strain on organisations’ analytics teams. Although many are investing heavily in data technologies to transform their organisations, quick access to information and insights can be impossible – and many are still failing at putting this data in the hands of the business people who must make use of the insights.
A key tactic for improving data access and providing insights involves bringing the two elements of data and data science together. For many organisations unifying these in order to drive digital transformation continues to be a challenge. Every vertical and department has a need for ingesting disparate content and performing complex analytic processes against it to drive value from the massive accumulation of ’dark data’ stored by organisations. Unlocking the value of such data through data analytics is key to guiding leaders make more informed decisions.
One of the principal ways in which organisations can unify data and data science is by changing the status quo and developing an analytics culture across the business. Analytic teams serve as the backbone to digital transformations, but more often than not we find that analytic teams are starting from an insufficient position, attempting to innovate with legacy holdovers of analytics processes, technology and team alignments. Holding on to these relics are the biggest barriers to analytic alignment and innovation.
Leaders focussed on digital transformation should target both cultural and technology strategies that help to create an analytics competency to fuel digital innovation. This is no small task. With data skills in short supply and demand for data-related roles set to continue to rise within the next four to five years, this is either exciting or intimidating depending on what side of the analytic effectiveness spectrum you’re sitting!
Linking up data insight to people with vital business knowledge is paramount to organisations wanting to make the most of data analytics. Not only will it enable the organisation to understand data analytics at every level it will also create an army of ’citizen data scientists’. Uniting departments that otherwise would have been siloed while generating more insightful and valuable analyses. Empowering these burgeoning citizen data scientists is a unique opportunity for organisations to compete in today’s digital economy. These individuals are eager to learn and develop new skills to improve their personal development and contribute to the business, but they can only be harnessed with the right enablement, support and self-service tools. What’s more, according to a survey conducted by Forbes Insights in collaboration with EY organisations which have an analytics strategy central to their overall business strategy are approximately five times more likely to achieve revenue growth and operating margin greater than 15 per cent, as compared to organisations lacking an analytics vision.
With the hyper-focus on digital transformation, it’s important to keep it in perspective. It isn’t always about new ‘things’, it’s about new value. Harnessing the networking effect of data, people and technologies paves the way to creating a sustainable cycle of analytic innovation that drives digital transformation.