Your Introduction to Data Driven Decisions

Overview

The use of facts, metrics, and data to influence strategic business decisions that correspond with your goals, objectives, and projects is called data-driven decision-making. When organizations see the full value of their data, everyone, whether you’re a business analyst, a sales manager, or a human resource professional, is empowered to make better data-driven decisions every day. This, however, cannot be accomplished just by selecting the best analytical tools to uncover the next strategic opportunity.  

Fundamentally, this necessitates a self-service approach in which users may access the desired data while maintaining security and governance. It also necessitates competency, which requires providing staff with training and development opportunities to learn data skills. Finally, having executive advocacy and a culture that supports and makes data-driven decisions will encourage others to do the same.  

FIVE steps to data-driven decisions

Acknowledge that the visual analysis cycle is not linear. One question frequently leads to another, requiring you to return to one of these phases or skip to the next, eventually leading to valuable findings. These five steps will help you in achieving the goal.  

1. Organizational goals:  

This stage will involve understanding your organization’s executive and downstream goals. This could be anything as specific as increasing sales and website traffic or as broad as raising brand awareness.  

This will assist you later in selecting key performance indicators and metrics that affect data-driven decisions. These will assist you in determining which data to study and which questions to ask so that your analysis supports key business objectives. If a marketing strategy aims to increase website traffic, a KPI could be linked to the number of contact submissions received, allowing sales to follow up with leads.  

2. Survey key sources of data:  

Collecting input from employees across the organization is essential to comprehend short- and long-term goals. These inputs influence the questions people ask in their studies and how verified data sources are prioritized.  

Valuable input from the organization will aid in the direction of the analytical deployment, including the roles, responsibilities, and processes and the success metrics to analyze progress.  

3. Data Compilation:  

Accessing high-quality, accurate data may be challenging if your company’s data is scattered across multiple sources. Once you identify the scope of your company’s data sources, you may begin data preparation.  

Begin with preparing high-impact, low-complexity data sources. Prioritize data sources with the most people to have an immediate impact. Begin with these resources to construct a powerful dashboard.    

4. Data Exploration:  

Data visualization is essential for data-driven decision-making. You will have a better chance of influencing the decisions of senior leadership and others if you visually represent your opinions.  

Data visualization, with its various visual features such as charts, graphs, and maps, is an easy way to observe and analyze trends, outliers, and patterns in data. There are numerous popular visualization types for successfully displaying information, including a bar chart for comparison, a map for spatial data, and more.  

5. Develop insights:  

Critical thinking with data entails finding insights and expressing them in a useful, engaging manner. Visual analytics is a straightforward approach to asking and answering data queries. Assess the opportunities and threats to success or problem-solving.  

Summary

Data-driven decisions are game changers. When everyone in a business embraces visual analytics, data becomes a crucial enterprise asset. Data-driven decisions become a company mission rather than a headache with a modern business intelligence solution. This benefits smoother, more accurate choices. These decisions will lead to a stronger bottom line, increased creative and commercial success, and increased staff involvement and collaboration. 

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