Data and analytics leaders face a crucial task: they need to create a flexible and resilient data-driven business strategy. This means enhancing five key IT capabilities: applications, data management, processes, people, and infrastructure. Each of these elements plays a vital role in keeping the business healthy.
A solid data strategy hinges on a broader tech vision that allows companies to swiftly adapt to changing customer and employee needs—emphasizing flexibility and creativity. Sticking to outdated methods for delivering insights just won’t cut it anymore in today’s fast-paced environment.
Let’s talk about data. Digital transformation is producing an overwhelming amount of it, scattered across various sources. More online activities mean more data—both structured and unstructured. This includes internal data from business applications and customer interactions, along with external data from partners, social media, and data marketplaces. The dream of consolidating all this data into one neat analytical repository has faded. Recent evidence suggests that only about 20% of usable enterprise data is actually harnessed for actionable insights. With AI generating even more data, this challenge only intensifies.
New technologies are reshaping responsibilities around data. While a unified analytical repository sounds ideal, the reality is more complex. We’re witnessing a rise in tools like data catalogs and data fabrics that allow us to find and analyze data wherever it lives. This raises questions for data and analytics leaders: Who should manage these new platforms? Business teams? IT? Or specialized groups like data officers? As legacy systems coexist with the cloud and other modern infrastructures, defining these roles will be a complex undertaking.
When it comes to technology platforms, modern insight solutions are becoming multifunctional. Choosing the right tech to support data-driven transformation is increasingly tricky. Emerging technologies often overlap, complicating roles and responsibilities. For instance, many business intelligence (BI) and predictive analytics tools now include data preparation features, blurring lines and confusing ownership. The whole conversation about data democratization hasn’t resolved the communication gap between business and IT. While business teams care about customer insights, IT tends to focus on models and schemas, making it hard for everyone to align on driving value.
Speed is another crucial issue. Forrester highlights that impatience with unused data is rising. Just because a data visualization looks clear doesn’t mean it delivers actionable insights. A graph showing a trend doesn’t clarify whether the trend is positive or negative. Data and analytics leaders need to provide context and narrative to make those visuals meaningful.
The lines between business and IT responsibilities are shifting. Today, business leaders are taking on more data and AI tasks, while centralized functions are focusing on governance. Forrester’s research shows a clear trend: in organizations with advanced data maturity, a greater percentage have a Chief Data Officer (CDO) who often reports directly to the CEO. This reflects a broader shift in how roles and responsibilities are structured below the C-suite, highlighting mixed ownership of insights across IT, business, and analytics teams.
In this data-driven landscape, businesses are encouraged to rethink traditional roles. This transformation isn’t just about newer technologies; it’s about redefining who leads and executes this vision. Data originates in the lines of business (LOB) where professionals across marketing, finance, and HR generate and act on it. Meanwhile, data teams ensure that this information is useful. Close collaboration between business leaders and data analytics teams is essential in identifying new roles and skills that will drive strategic actions.
Despite the push for skills within business teams, the ongoing need for technology-oriented data and analytics professionals remains critical. Leaders are adopting adaptive business processes and technologies, including BI governance and data meshes. It’s essential for data and analytics leaders to align closely with technology-focused mindsets as the landscape rapidly evolves.
Navigating this complex environment requires precise coordination of numerous elements. It’s important not to get too caught up in the allure of new technologies. Promises of simple solutions won’t materialize without the right people, skills, and responsibilities in place.