IT’s role in building a Data Culture: Analytics agility, proficiency, and community

Data-leading organizations see benefits like improved customer acquisition and retention, engaged employees, and operational efficiency. While analytics at scale promises many transformative business outcomes , most organizations struggle to build a widespread Data Culture that values and practices data-driven decision-making. Could it be that IT leaders are too focused on implementing technology and not enough on enabling their employees?

The massive acceleration of digital transformation has brought about new ways of working, and you’ve witnessed first-hand the critical impact your people can make when you empower them with trusted data. “Almost two-thirds (64%) of enterprises that have been the most successful with analytics projects in the past two years have increased spending on data management and analytics products and services as a result of the pandemic,” reports 451 Research *, part of S&P Global Market Intelligence.

Your employees are brilliant, creative, and hard-working—and they know exactly the questions to ask for valuable answers that can propel your business forward. As a trusted IT partner to these team members, you can spearhead a deliberate, holistic, and people-focused approach for an enterprise-wide analytics practice. Leading for success across three areas will empower your entire employee base to be more data-driven:
Adopt an agile approach to managing your analytics environment
Support employees in growing their analytics skills

Foster community that builds and celebrates your Data Culture

Let’s take a closer look at each.

1. Adopt agile implementation practices
With modern BI, IT offers a governed model of self-service data for everyone, rather than continuing to gather requirements and design reports. Here are a few ways IT can help lead the business to greater outcomes through the deployment and ongoing management of an organization’s scalable analytics environment:

Accommodate growth with an agile approach to analytics environment support: Analytics is increasingly mission-critical to organizations, particularly as adoption increases across the business. Because of this, you should consider reassessing server utilization more frequently than with other technology solutions—including changing your topology to scale with the organization’s evolving needs. If your analytics solution is flexible, you won’t be restricted to any specific architecture, data sources, or cloud deployments. Adopt agile practices for proactive planning and monitoring; a “set it and forget it” implementation creates the risk of inadequate resources that fail to support enthusiastic data users with their growing data workloads.

Help your teams take action in the context of their business processes: Incorporate data assets into employees’ existing workflows and applications by setting up email subscriptions, chat alerts, and @ mentions , or embedding analytics where employees are already spending their time—like internal portals and your CRM . This not only helps people engage fluidly with contextual analytics, in the moment, but can shorten the time to solve problems with automation and intuitive AI. Consider the impact across your customers’ lifecycles when you help your enterprise employees ask questions of their data in natural language, get accurate responses, and increase cross-functional collaboration, ultimately helping people to act when the data is the most relevant.