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How to get the most out of your data

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Have you ever just sat and stared at a screen filled with raw data because you’re not sure how to start turning it into actionable insights? 

Well, you’re not alone. Discover how to understand your data and use it to its fullest potential.

Shifting from data-driven to insights-driven

Data itself is useless. Its true value comes in providing actionable insight. That’s why we believe businesses should not be data-driven but insights-driven to become useful when applied in a business setting. Your data should tell you a story or highlight patterns or insights to uncover the “why” to a situation.

An insights-focused strategy allows organizations to plan and anticipate possible needs over time. Additionally, in trying to get ahead of competitors or market shifts, having high-quality insights benefits your organizational agility and ability to act faster.

How to use data effectively to generate insights

So how can you go from raw data to actionable insights? Start by identifying specific questions or business goals you want to explore. While data analytics and machine learning tools help uncover these insights, they don’t always tell you the “why.” Before analyzing any data, ask yourself, “What do I need to know?” Making your research objectives feasible and actionable helps keep your search for knowledge focused, but the type of knowledge you gain can and should be open-ended.

In product development, data must derive from different sources (i.e., operations, product or customer intelligence) to give you a holistic picture of user needs. You don’t have to collect data from ALL sources. Everyone on your team has a role in creating quality data processes. Without the right data collection and organization system, this could create gaps or limit your visibility.

Resources for you
Guide: How to become a data driven organization
Guide: How to become a data driven organization
Your data strategy checklist
Your data strategy checklist
Data-driven vs. data centricity: How to build a data-centric framework
Data-driven vs. data centricity: How to build a data-centric framework

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