In our last blog, we dove into an exploration of data visualizations and their power to bring life to data-driven insights, but the impact of data visualizations relies to a great extent on the organizational culture surrounding them. In this blog, we will dig into the relationship between organizational data culture and effective communication about data. In the process, we’ll look at two organizational pillars, data science training and data governance, that can promote effective, responsible data programs across teams and help organizations maximize the ROI of their data initiatives.
Hurdles en Route to Organizational Data Destinations
It is essential to give employees the tools to work effectively with data, as well as the shared vocabulary to communicate about it. When organizational data capabilities are confined to a single department or select employees, data programs will likely remain stifled and limited. A Deloitte survey supports this notion. Examining progress among select AI- and analytics-driven enterprises, the survey found that 67 percent of respondents in senior management or higher roles expressed discomfort with accessing or using data given the tools and resources available to them. Yet, according to another Deloitte report, 37 percent of survey respondents said their companies had not made significant investments in initiatives to help employees integrate technology into their work, such as change management, training activities, and incentives.
Data Science Training for All
Cultivating data literacy and foundational skills empowers employees to be active contributors to successful data programs. The Deloitte survey found that 88 percent of companies that trained all employees in analytics exceeded their business goals, compared to 61 percent of companies that did not propagate those skills widely.
In addition to nurturing the skills required for using and understanding data, enterprise analytics programs also flourish in cultures with broad ownership of—and trust in—data processes and resources. Creating a cohesive vision for the company’s data strategy and defining use cases helps teams coalesce around the requirements and possibilities that accompany data initiatives. Also, organizational frameworks that ensure the quality, security, and ethical management of data inspire confident and responsible data utilization, innovation, and collaboration across the workforce.
Data Governance for Secure and Reliable Data
Data ethics are crucial to successful data programs because they mitigate the risk of exposing personally identifying information and running afoul of regulations, which can result in both additional costs and reputational damage. Vigorous and agile data governance processes help organizations maintain vigilance over their data through its lifecycle, from collection to storage and destruction, while adapting to evolving ethical concerns.
Effective data governance forms the foundation of workforce trust in data sharing and usage and helps organizations address rising concerns about data ethics. Beyond sound data practices, these outcomes also require compelling messaging. According to Gartner Inc.’s sixth annual Chief Data Officer (CDO) survey, respondents reported that communication is essential to their success in their roles. The report further explains that raising organizational awareness of the business value of data analytics, in addition to advocating effectively for data literacy training across the workforce, are key components of successful data programs.
Clearing the Way Forward
Without broad access to and confidence in data across teams, organizations may fall short of realizing the full potential of their data resources.
While data visualizations can significantly enhance the impact of data programs, for data initiatives to demonstrate the full measure of their promise, organizations must invest in people skills and procedural frameworks as well as technologies. The unifying theme that has emerged in the process is that communication is both a driver and a goal in effective data governance, training, and visualization. By cultivating a shared vocabulary, skills, and solid data standards, organizations will increase their capacity for generative collaboration across the workforce and maximize the ROI of their data initiatives.
