Data virtualization tools help break down data silos, doing away with the need for duplication and data movement so that anyone can access data at the source.
Data is the new gold. It propels intelligent enterprises across the entire business ecosystem to newer heights. The massive volumes of data currently being produced, collected, stored, and analysed have the potential to fuel a new era of innovation. Today, data analytics is increasingly being used to help stakeholders gain actionable insights and enhance their business agility and efficiency. According to Gartner1, about 30% of organizations will invest in data and analytics governance platforms by 2024, thus increasing the business impact of trusted insights and new efficiencies brought on by data.
However, within most organizations, the power of data largely lies in the hands of a few data science experts who have the requisite technical skills and expertise to effectively glean and interpret data for their organization. A lack of understanding or consensus amongst data leaders on questions like “Which data should drive particular business decisions?” or “How to use data effectively?” can often lead to delayed action and disruptions in operations.
Issues prevalent in mid-size enterprises, like disrupted supply chain operations, sudden decline in demand, or surge of consumer stockpiling, etc., can be dealt with more effectively if there is some advanced notice. According to recent research2, almost two-thirds of surveyed senior leaders from medium-sized organizations state that the shortage of data necessary for analytics-based decision-making is a top internal challenge when meeting their company’s strategic priorities.
Data Analytics Democratization: Boosting Midsized Enterprises
In the last couple of years, there has been an influx of innovative, next-generation technologies that can make data and analytics shareable as well as interpretable for the non-specialist talent force. Access to data insights can expedite decisions, influence sales and customer service, and unearth new growth opportunities.
By democratizing data, everyone in the organization can have access to data without any gatekeepers. This ensures that everyone, from the leadership to the on-ground workforce, is able to leverage the full value of that data and make faster decisions.
Of course, data democratization brings with it the need for appropriate governance3, with well-laid out and clear-cut policies and procedures for data and processes in place, including the data security protocols to avoid any theft, misuse, and loss of vital information.
Thus, data analytics democratization builds a bridge between data and strategic decision-making. This enables better innovations, higher productivity, unification of data access and analytics, and much more.
Roadblocks Restricting Effective Data Democratisation
While one understands the critical role that democratization of data analytics plays in organizational success, there are certain reasons that act as restraints in its smooth layout. Let’s look a few below:
Data silos still exist in many organizations. Data is accessible only by the top management. This means data specialists can impact numerous opportunities of delayed decisions that can emerge if data is shared across all levels and departments in an organization.
Apprehensions about data safety and security: Along with maintaining data integrity by making it accessible to a larger number of people, there is also fear of how the data may be used and interpreted.
Availability of appropriate analytical tools: Another huge barrier to data democratization is the availability of appropriate tools to help analyse the data. They are essential to helping employees without data analysis skills to easily extract meaning from data.
Establishing an Effective Data Democratisation Roadmap
In today’s time, where the pandemic has disrupted the ‘normal course of business’ and given rise to new and unique challenges within the business ecosystem, it is vital that business operations are more agile, efficient, competitive, and resilient than ever before. And this requires expanding the user base for data within the organization. Leaders need to develop clear-cut strategies to spread the data and the insights drawn from it across the hierarchy. Some of the measures that can be adopted include:
Creating a data-literate work culture. Employees need to understand the kind of data getting generated and learn to identify and analyze the useful data. This can help them ask the right questions on data-based insights, enhance overall processes and workflows and build efficiencies. Employers, therefore, need to train employees on the best way to use the available data to achieve organizational goals. Some of the training techniques include up-skilling programs through seminars, self-study guides, and allowing new learners easy access to the experts.
Promoting cross-functional teams for better utilization of data analytics. Midsized businesses often do not have the resources to establish a strong data management team. in such cases, firms can consider setting up a cross-functional team that constitutes both tech/data-centric people as well as representatives of other business functions—such as product development, financing, sales and marketing, etc. where this team acts as a lynchpin between data and other business functions- owning all the data and handling all the data requests that can be further filtered through in a secure and safe manner.
Virtualization of data to share information across the organization near real-time for better outcomes. Data virtualization tools help break down data silos, doing away with the need for duplication and data movement so that anyone can access data at the source. With the help of such tools and software, it no longer matters where the data is stored since these virtualization tools enable users to access data easily and responsibly.
Striking the Balance
In the information age that we operate in today data is, in many ways, the key to business success. However, it is imperative that business leaders strike a perfect balance between data, technology, and individual expertise to understand the needs of every team and process. Doing so would help provide the right resources to the workforce trying to make data-driven decisions. When employees trust their own analytical capabilities, they help build an insights-driven decision-making culture that nurtures growth.
Source: Business World
