Much has been made of the importance of data in the digital economy. While digital data has been present for decades, it has taken on a greater priority in an age of artificial intelligence, predictive analytics, and customer personalization. Data has been called the “new currency” and the “new oil” of business – an asset so critical that it undergirds the entire operational structure. Yet for all the value being ascribed to data, companies are still in the early stages of building their data discipline and skills.
Why is business data so important?
Simply put, poor data management and insufficient data analysis are impacting the bottom line. Organizations have been collecting data for a long time, but there has typically not been a comprehensive operational approach or a focus on the necessary skills to address this data effectively. Companies are starting to feel the effects of poor data management or insufficient data analysis, with wasted time being a top concern – hunting for data consumes time that could be used to focus on core functions and new innovations. Increased efficiency, another common business goal, comes as a result of well-designed systems and workflow – both of which can be optimised with effective data analysis. Data management and analytics should therefore be treated as a comprehensive program, rather than a collection of point tools for specific purposes.
Focus on data skills
As more companies use data to improve their internal operations and to better understand their customers, the development of new and improved data skills will bring them big success. These skills address a wide range of common business problems, from building a resilient data architecture, to improving the speed of data analysis, to mining data for new insights. In essence, the new currency of business requires new data specialists to extract value for all stakeholders.
Handle data properly
Forming data teams – Job roles and required skills
Whether all data skills are centrally located within an IT department or spread across multiple business units, companies are taking steps toward establishing data teams. The concept of data teams is relatively new, and given that the CISO position was created in the mid-1990s and the CDO position was created in the early 2000s, it makes sense that data teams would be lagging behind security teams. In fact, only 44% of companies say that they have internal employees who are dedicated to data management or data analysis, and even among these companies, there is still high demand to develop more data skills that drives new business value.
For the data function, these four distinct roles can help fill out an organization’s data team:
- Database administrator
- Data analyst
- Data scientist
- Data architect
When considering the areas of the data function where businesses are seeking improvement, there is a clear priority out of the above roles: Companies want to improve their analytics capabilities. Data visualization is an especially interesting task, as it combines technical knowledge with business savvy and communication skills. However, the other roles play a key part in a comprehensive data strategy that ultimately provides high-value data analysis – meaning none of these roles should be neglected.
Is there a data skills shortage?
Given the relative novelty of the data function, one would expect that companies have a particularly strong demand for entry-level positions, but this is not the case. In fact, companies with hiring plans in 2021 are looking for more mid-level data specialists than in any other field. Part of the reason for this is that teams in the emerging fields of data and cybersecurity are often created from existing software and infrastructure teams. However, the high demand for specialized skills indicates a pipeline problem that has no easy solution.
Without well-defined entry-level roles, companies have less ability to rely on historical means of skill development, where they are able to obtain a qualified candidate from a traditional pipeline like a four-year degree program and then give that candidate the job experience and training opportunities that build more advanced skills. The explosion in demand for the advanced skills exacerbates the problem.
In the data field, time is of the essence.
Companies have massive amounts of data—now the question is what to do with it?
The ability to rapidly and effectively analyse data can improve time to market, enhance customer satisfaction and drive growth for the future. As organizations place a priority on speeding up data analysis, they should also place a priority on speeding up skill discovery and development.
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