5 steps to start Data-Driven Decision Making in your business

Data Science & Analytics
Thiago Loureiro and Yasmim RestumThiago Loureiro and Yasmim Restum - 22 de September de 2021.

The famous engineer W. Edwards Deming once said: "Without data, you're just another person with an opinion.”

That is, without insights from data, people make decisions based on instinct, speculation, or prevailing theories. The risk of acting on assumptions and even prejudices is great. The result? Needless to say, right?


Data-driven decision making (DDDM) involves collecting data, performing data analysis, and making decisions based on the insights derived from that analysis. Basing decisions on data also allows the logic behind the determinations to be transparent and provides stronger evidence to support those decisions. 


How, then, do you ensure you are making data-driven decisions that are free of bias and focused on clear issues that empower your organization?


Data-driven decision making process is defined as the use of facts, metrics and data to guide strategic business decisions that align with your goals, objectives and initiatives. 


When organizations realize the full value of their data, it means that everyone-whether you are a business analyst, sales manager, or human resources specialist-is empowered to make better decisions with data, every day. However, this is not achieved simply by choosing the appropriate analytics technology to identify the next strategic opportunity. It goes much further. 


Your company needs to make data-driven decision as the norm - creating a culture that encourages critical thinking and curiosity. Employees at all levels need to develop data skills through practice and application. Fundamentally, this requires a self-service model, where people access the data they need, balanced with security and governance. It also requires proficiency, creation of development and data training in order to make employees skilled when it comes to data. Finally, it takes a community that supports and makes decisions based on data to encourage others to do the same.


Establishing these basic capabilities will help encourage data-driven decision making at all levels of work, so that business groups regularly question and investigate information to uncover powerful insights that lead to action. 


Why is data-driven decision making process so important?


The amount of information collected has never been larger, but it is also more complex. This makes it difficult for organizations to manage and analyze their data. And if data driven business decisions make or break companies, it becomes mandatory to leverage data to make more powerful decisions in a steady growth direction.

A 2020 IDC research with predictions concerning tech trends for the next years has shown that, by 2024, over 50% of all IT spending will be directly for digital transformation and innovation. However, only investing in technology and innovation is not enough.


Another IDC research conducted in 2019 concluded that amongst the organizations which have invested trillions of dollars to modernize their businesses, 70% of these initiatives failed because they prioritized technology investments rather than building a data driven culture to support them.

This context exemplifies how competitiveness is now determined by how data is transformed into insight and knowledge for products, clients, predictions, and actions to improve the customer experience and business decisions.


But in this quest to be data-driven, many companies are facing how hard this task is. Incorporating data and analytics into decision-making cycles requires a dedicated approach to developing and refining the analytics program.


Thanks to more modern business intelligence, organizations are getting closer to understanding the value of data-driven decision making across all departments and functions. To help you, we've put together some suggestions that, if put into practice, can unleash great potential from data and your people. 


5 steps to start Data-Driven Decision Making in your business


These steps can help you find the "who, what, where, when, and why" to make the most of the data for the business. 


But keep in mind that the analysis cycle is not linear. One question usually leads to another, which may mean that you need to go back to one of these steps or move on to another, thus having multiple insights at the same time. 


  • Step 1 - Identify business objectives


This step requires an understanding of your organization's executive and downstream goals, and can be as specific as increasing the number of sales and website traffic, or as ambiguous as increasing brand awareness. 


This will help later in the process of choosing the key performance indicators (KPIs) and metrics that influence the decisions made from the data - and this will help you determine what data to analyze and what questions to ask so that your analysis supports key business goals.


For example, if a marketing campaign focuses on driving website traffic, a KPI might be tied to the amount of leads captured so that sales can follow up on leads.


  • Step 2 - Survey business teams for key data sources


To ensure the success of data-driven decision making, it is crucial to get input from people across the organization to understand the short - and long - term goals. 


Input from across the organization helps guide your analytics deployment and future state - including roles, responsibilities, architecture, and processes, as well as measures of success to understand progress.


  • Step 3 - Collect and prepare the necessary data


Accessing reliable, quality data can be an obstacle if your company's information is in disconnected sources. Once you have an idea of the breadth of data sources in your organization, it is essential to begin data preparation.


The tip is to start by preparing data sources with high impact and low complexity. Prioritize data sources with the largest audience so that you can have an immediate effect. Later, with the process properly organized, medium and long-term results tend to appear. 


Read more: Data Lake and Data Warehouse: What is the difference and which one is best for your business?


  • Step 4 - Visualize and explore the data


Visualizing your data is also fundamental to DDDM. Representing your insights in a visually impactful way means that you will have a greater chance of influencing the decisions of leadership and other employees.


Starting with visual elements such as tables, graphs, and maps, data visualization is an accessible way to see and understand trends, discrepant values, and patterns in the data.


There are many popular visualization types to effectively display information: a bar chart for comparison, a map for spatial data, a line graph for temporal data, a scatter plot to compare two measures, and others.


  • Step 5 - Develop insights


Critical thinking with data means finding insights and communicating them in a useful and engaging way. Visual analysis is an intuitive approach to asking and answering questions about your data. Discover opportunities or risks that affect success or problem solving.


Seek to gain a comprehensive view of the customer journey by reviewing line-of-business relationships (i.e. product, marketing, and service touchpoints) with customer data.

For example, the Marketing team, one of the most in-demand areas in a data-driven culture, can provide analytics that influence design decisions for the website, promotional materials, and products such as apps. 






Is your company prepared to put this information into practice and have a data-driven culture?


Going back to the beginning of the text, when we mentioned W. Edwards Deming's quote, it is important to emphasize that companies that aim to grow at a fast pace cannot dispense with the use of data, obviously, but data is useless without a creative and professional team with good ideas behind these processes. It is a two-way street.


Data-driven decision making is transformative, and when adopted by everyone in an organization, data becomes an essential asset. With a modern business intelligence solution, this decision-making model tends to raise the bar for your company, with faster and more effective decisions. And these decisions lead to stronger financial results, greater creativity and business success, and more employee engagement and collaboration.


To take the first steps for your company become a data-driven business, we have created a complete eBook with several tips. Download it here.


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