Big Data

How technology can be used to address the data analytics skills gap

By Francois Cadillon, Vice President UK & Ireland at MicroStrategy
Big Data
Published: 19 March 2018

Successful, data-driven companies don’t just confine their use of analytics to the IT department and C-suite. Instead, organisations poised for growth open up the power of analytics to everyone across their enterprise – promoting digital transformation and spurring innovations and developments that would not have been previously possible.

This phenomenon, commonly referred to as the democratisation of data, allows employees at all levels of an organisation to connect to relevant sources of data and interact with information in meaningful ways. Whether an employee is working in sales, marketing, HR, accounting, or production, an increasing number of citizen data scientists are able to effectively derive insight to promote growth, increase productivity, and reduce risks. Using self-service tools and intuitive dashboards, any employee can take immediate, informed actions based on data.

Managers in a variety of industries, including healthcare, insurance, government, and financial services, are increasingly called upon to demonstrate their own analytical skills. In fact, according to a recent BHEF and Gallup Data Science and Analytics Business Survey, 59% of employers said data science and analytical skills would be required of all finance and accounting managers by 2020. 51% said these skills would be required by all marketing and sales managers, 49% said it would be required of all executive leaders, and 48% said it would be required of all operations managers.

These findings demonstrate the need for employees to develop analytical skills. But for most organisations, there simply isn’t enough time to train everyone in data science. That’s where user-friendly technology helps to plug the gap; self-service analytics allows users of all different skillsets to quickly create detailed reports.

The insurance industry provides an excellent example of this trend. In this industry, the claims process typically represents the single largest expense for an insurer, which is why it is important to make this process as efficient and effective as possible. Responsibility for this task typically falls to the insurance policy’s underwriter, who conducts necessary research and due diligence to protect the organisation when selling a policy.

Powerful analytics functionality reinforces an underwriter’s ability to confidently act upon data related to customer credit history, risk, and market information. It allows claims adjusters to easily visualise critical data related to policy information, police reports, loss, frequency, and severity. And by mobilising applications, adjusters can access claims information from any location and can write-back and upload critical information such as photos or notes from accident scenes or repair estimates.

Retail is another sector that is embracing self-service analytics. At the start of 2017, leading retailer House of Fraser rolled out its ‘nGenBI’ initiative aimed at completely changing the way employees interact with data and uncover new insights. By democratising their data, the BI team was freed up to focus on higher-value reports and able to eliminate data processing redundancies and bottlenecks. Employees across all departments are now empowered to quickly visualise data to improve stock management, reduce returns, optimise store layouts, and ultimately enhance the overall customer experience.

Organisations that operate call centres are also empowering more employees with the analytical tools needed to improve what can be a stressful process. For these call centres, the handle time, or the time it takes to resolve customer issues, is a critical indicator of performance. Managers need to be able to closely track handle time and other KPIs across the entire operation by applying sophisticated analytics on data from disparate customer systems. By providing key decision-makers with real-time alerts when KPIs begin trending in the wrong direction, the call centre is able to correct its course and continue to operate in high gear.

As analytics continues to grow in importance, it’s critical that organisations embrace technology that empowers all employees with the tools they need to drive performance and productivity. By democratising data companies can create an agile workforce able to take the power of analytics into their own hands while taking an ‘all hands on deck’ approach to solving organisational challenges. Leading companies will therefore be poised to uncover new insights, make more informed decisions, and more effectively drive the digital transformation of the enterprise.