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4 Insights for Increasing the Value of Your Data Analytics

Organizations need clarity of purpose and strong governance to develop actionable insights.


Many business and IT leaders understand the value that data analytics can provide but struggle to achieve the benefits. In some cases, organizations generate lots of data and create dashboards to visualize it, only to make an unfortunate discovery: They haven’t produced any insights that are actionable.

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Deriving value from analytics requires insights around measuring specific changes or driving a particular action that the organization wants to take. This requires a few key steps:

  • Figuring out your goals and the answers that will help you achieve them
  • Establishing processes that produce usable data
  • Determining how the organization will use insights to make decisions
  • Building a culture that values data analytics

1. Know Where You Want to Go

Without asking the right questions of the data, it’s challenging to generate insights that enable you to take action and generate value.

The first step is to identify your objectives. On its face, this step may seem obvious, but it is often more involved than organizations realize. Depending on the industry, a goal might be to reduce downtime, to improve patient outcomes, to increase student retention or to better meet customers’ needs.

Knowing your goal determines the questions you need to answer, and that in turn reveals more questions. What resources could help you answer these questions? What data sources do we need? What insights will inform your decisions?

2. Establish Processes to Protect Data Integrity

The proliferation of data can be a challenge. Two areas of an organization may be asking the same question but from different perspectives with different data sources. As more organizations adopt self-service analytics, it becomes increasingly important that data be visible and appropriately governed throughout an organization.

Processes and tools can ensure that people access data from a specific point of entry. Data catalogs, for instance, can be immensely helpful because they provide users with the most accurate, up-to-date information. Data catalogs may be department-specific or curated in another way that makes sense for the organization, but they provide visibility and support the governance structure.

3. Determine Decision-Making Processes

If the goal is to make better decisions, the question then becomes how to do that. Once the data is analyzed and actionable, does it lead to an individual decision? A team-based decision? An organization-wide decision?

Typically, the size of the organization and the nature of the questions will inform this process. In some cases, a committee or a centralized decision-making process is responsible for leveraging data-driven insights.

It’s essential to recognize that generating insights is necessary, but taking the time to figure out the best way to utilize those insights — to ensure they lead to valuable outcomes — is equally important.

4. Create a Culture Around Data Analytics

Incorporating data into decision-making is undoubtedly becoming more commonplace, but it is a culture shift. As with any such change, it’s crucial to have leadership reinforcing the message that data-driven insights are valued and that decisions should be driven by data — not just intuition.

There is space for intuition, of course, combined with data, but an organization’s leaders must encourage employees to integrate data analytics for it to take hold. Then, they need to implement processes that make data usable and allow people to take the actions that make data valuable in the first place.