It’s a pivotal time for businesses across the Gulf as more organisations look to harness the advantages of data through analytics. With around 2.5 quintillion bytes of data created each day, 90% of the total data in the world has been created in the last two years. Today, we sit at a moment in data history comparable to when e-commerce and payments platforms first took off.
Despite this exponential growth in data generation, the data businesses need usually won’t sit neatly in a predefined database – inside a fully prepared data table – just waiting for you to access it. IDC estimates that 90% of all data created is ‘dark data’ – information that is unstructured, locked away, or generally inaccessible. Furthermore 86% of leaders within the data space report extreme difficulties in hiring people with the specific skills they require to leverage data for insights.
Collecting data is one thing, digesting, understanding, and turning it into an insight is another. The most effective data analysts in previous years required programming knowledge – most commonly using R, or Python – to attain, sort and generate insights from information. Data scientists with these skills, however, are in high demand and can often gravitate towards engineering, cybersecurity, or other higher-level analysis roles.
According to a recent PwC report on the potential impact of AI in the Middle East, data rich AI is expected to contribute over US$135.2 billion to the economy by 2030, equivalent to 12.4% of GDP. Research from The Royal Society found that demand for workers with “specialist data skills” grew by 231% over the last five years. Europe as a whole will also, ultimately, require 346,000 more data scientists to meet growing demands.
In the next few years, the analytic divide between companies that can and cannot harness this data will continue to widen. From oil and gas, to finance, retail and supply chain, there is a huge potential in upskilling every worker in data literacy so they can support the business. A recent report from the Capgemini Research Institute noted that 50% of businesses are already making business decisions based on data, with those harnessing it strategically being 22% more profitable than those which do not.
With 90% of data quantified as ‘dark’, that leaves just 10% for any meaningful insights regardless of intention. A journey cannot be effectively plotted with just 10% of a map. Developing a culture of analytics and this foundational knowledge of analytic literacy, are key to success.
There are a huge number of people in the business world with questions they need to be answered on a day-to-day business, but without the tools to acquire them. As the volume of collected data increases, the sheer quantity will overwhelm the ability of legacy systems to process it and derive the outputs needed for insights. While organisations of all sizes recognise the value in data, it‘s the processes and people surrounding it which are key to digesting, understanding, and turning said data into a breakthrough. But for this level of data analysis to be successful, human-led data science is required. The first step to create and enable this data-driven culture requires identifying team-members with burning questions about data. The second step is giving them a means to do something about it.
To answer these questions, an army of citizen data scientists must bring this data together from different places, analyse it, and create the outcome themselves. Many organisations are seeing growth in this area and are focusing on creating a culture of analytics. With such a shortage of specialists available, the logical conclusion is that line of business workers with the right aptitude for data will begin their own journeys into analytics – many beginning with little more than legacy spreadsheets to help.
Data is one of the greatest equalisers – the greatest democratisers – across business. Making data accessible and ingestible, regardless of technical acumen, means that anybody in the business with unanswered questions can be empowered to uncover insights. Knowledge workers of any discipline can upskill and learn new techniques with ease through self-service analytics platforms to move beyond human decision making and quickly harness the hidden power within thousands of disparate data sources to uncover breakthrough actionable insights.
Over the past year, the pandemic has placed hurdle after hurdle in front of companies trying to go about their business. With digital transformation projects starting much sooner than planned, many are prioritizing the adoption of new business models infused with data-driven actionable insights. Today, upskilling initiatives more important than ever before.
Companies need to be able to rapidly spot and predict changes in their marketplace and business environment; just as customers expect businesses to use data to meet their ever-changing wants and needs. The end goal is not to create a team of expert data scientists – the end goal is to empower teams across the workforce to use data-based tools to make their own work – and the output of the business as a whole – more effective and impactful.
Good analytics is not simply a science – it’s an art. Given access to the right self-service platforms, employees with an aptitude for pattern recognition and a forward focus can complete the exact data-heavy tasks once exclusively in the realm of STEM specialists. With analytics solutions pulling down the barrier between those who do and do not analyse their data, the most challenging aspect of digital transformation will now be teaching staff how to ask better questions.
