Data-driven decision making is probably the buzzword of this relatively newborn millennium. If businesses anywhere in the world were reluctant to switch to this new paradigm, the Covid-19 pandemic has rendered the shift inevitable. However, the challenge for most firms starts with recognizing the need to bring people on board who can convey critical business narratives using data. Equally, the existing workforce at many companies doesn’t have the right skills to interpret or work with the enormous volumes of data handled by a business that is even partially global. And this skill gap is felt most keenly in terms of data visualization skills, which have thus far been the preserve of statisticians.
However, businesses looking to hire data visualization experts may find themselves struggling to describe the role precisely, especially if they are still setting up a team to handle their data analytics. In terms of specifying data visualization skills, they could potentially look for someone with experience in using one or more data visualization tools. Alternatively, they could look for someone with an in-depth knowledge of statistics and some programming experience. Ultimately, they may need to hire people who can learn on the job and work with any of the tools or techniques necessary for the business.
The Data Analyst Gap
In 2019, the professional social media service LinkedIn looked at the skills fresh college graduates sought to learn through the service’s LinkedIn Learning platform. The top five skills, per their research, all dealt with data analytics – data visualization, data modeling, Python, web analytics, and databases. While this underscores the career advancement potential offered by the field, it also illustrates the demand for these skills across business sectors. For businesses, hiring younger talent already possessing the necessary data visualization skills can make it easier to build analytics teams with the right mix of data and analytical skills.
Finding the perfect data visualization analyst can effectively translate into finding one person with the skills of four people – one with creativity, one with communication expertise, one with the technical computing skills, and one able to work with data. Businesses may have to compromise on either the creativity or communication skills when hiring data visualization engineers and build a team around them, comprising others who can build the data-based narrative. While businesses may already have storytellers and communicators working for them in marketing and public relations, getting other teams to embrace data-based storytelling can require hands-on engagement by those in upper management.
Creating Data Visualization Through Dashboards
One way of making this exercise more interactive and participative is using data dashboards which can be accessed by different business units based on their needs. These dashboards offer an intuitive approach to data analysis that can be less daunting and more convenient even for those without any programming or statistics training. Data visualization experts can work with different operational teams to customize dashboard views and controls, besides offering guidance on writing back data on key business metrics to derive analytical insights.
Data visualization expertise may need to be supplemented by strong data management since businesses often rely on a variety of sources for business intelligence. Spurious, unverifiable data can throw algorithms off-target, resulting in insights that are not actionable, if not meaningless. A business may therefore need to think of their resources before building their data team. The easier alternative might be leveraging end-to-end analytics solutions like InsightOut that can take care of data management and deriving data intelligence in addition to delivering data visualizations through easy-to-use dashboards. Such solutions can also offer the collaborative impetus and help build critical mass towards transitioning to full-fledged data-driven decision making.
Businesses that choose to build in-house data analytics teams will need an across-the-board understanding that they are about to embark upon an irreversible journey and not conducting an experiment. Even where some management personnel may accept that data visualization skills are necessary, they may find the full-scale transformation to taking data-based business decisions a step too far. For this reason, the data transformation for many firms is a slow process catalyzed solely by visionary leadership. Otherwise, the change may be restricted to a few business units or operational teams at best.
Considering today’s business landscape, it may appear that businesses that haven’t yet decided about moving to a data-based business model are out of time. Nevertheless, data visualization expertise has already found adoption almost globally, even in firms that aren’t otherwise leveraging data for business decisions. It is certainly easy to tell apart firms at different stages in the data transformation journey, even if they all use the same data dashboard.