As technology plays an ever-increasing role in both business and everyday life, the volume of digital information is constantly expanding. Studies estimate that 90% of the global data currently in existence has been generated in the last two years. Modern businesses have access to unprecedented quantities of data. However, this information is only beneficial if it’s used effectively.  

Data-driven decision-making is the process of leveraging data to guide organizational practices and procedures. Everything from website traffic and social media metrics to sales records and customer reviews can provide invaluable insights into a business’s strengths and weaknesses. By analyzing data and using it to inform business decisions, companies can streamline operations, increase customer satisfaction, mitigate risks, and achieve other strategic goals. Continue reading to discover the benefits of data-driven decision-making and explore how high-performing businesses harness data to make strategic choices.

Benefits of Data-Driven Decision Making 

According to Forbes, businesses that make decisions based on data are 19 times more likely to remain profitable and 23 times more likely to outperform competitors in customer acquisition. Gone are the days of relying on speculation to guide business practices. In today’s technological world, companies can ground their approaches in verifiable evidence, enhancing decision-making accuracy and precision. 

Data-driven decision making (DDDM) can positively influence nearly every aspect of a business, including: 

• Strategic planning. Government agencies, nonprofits, corporations, and small businesses alike draft strategic plans to articulate their short- and long-term goals. By aligning proposed methods with reliable data, these organizations ensure that their plans are informed, achievable, and measurable. 
• Operational efficiency. Through data analysis, organizations can identify delays, errors, and wasted resources that reduce productivity and profitability. They can track operational key performance indicators (KPIs) such as warehousing costs and downtime rates to find areas for improvement, enabling them to address these problems and optimize workflows. 
• Transparency and accountability. When decisions are based on objective data, internal and external stakeholders can see the rationale behind business practices. Data-driven decision-making ensures that personal biases or other irrelevant factors don’t influence policies and procedures.
• Resource allocation. In an era marked by supply chain disruptions, inflation, and staffing shortages, effective resource utilization is crucial. Organizations can use data to make informed decisions regarding task prioritization, resource allocation, and human capital management.
• Marketing. Website analytics, social media interactions, and customer relationship management (CRM) platforms are goldmines of information about customers’ needs and preferences. By aligning marketing strategies with data-derived conclusions, companies can ensure that their methods are as effective as possible. 
• Financial management. Through data-driven decision-making, organizations can identify financial risks, optimize budgeting, and improve cash flow management. 
• Forecasting. Statistical modeling and machine learning algorithms use historical data to forecast future events, allowing organizations to predict everything from financial trends to customer behavior. Forecasting empowers businesses to take a proactive approach that anticipates problems before they arise. 

 Steps in Data-Driven Decision Making 

• Identify objectives. To get the most out of the data analysis process, decision-makers should begin by establishing clear, measurable goals that align with the organization’s primary targets. For example, a company experiencing a revenue decline may set a goal to increase conversion rates on its e-commerce platform by 10%. Similarly, an organization struggling with inventory management may seek to determine the ideal inventory levels for its top-selling products.
• Collect data. Point-of-sale (POS) systems, financial reports, website traffic, and enterprise resource planning systems (ERPs) are just some of the many data sources that can lay the foundation for DDDM. Many organizations use business intelligence reporting tools that automatically gather and organize data in preparation for analysis. However, it's up to each business to understand the significance and applications of this information.
• Analyze data. Once the data is collected, businesses can use various digital tools and techniques to explore the relationships between variables, find correlations and patterns, and make predictions. Power BI, Tableau, and Apache Spark are examples of software programs that can manipulate and visualize data, enabling stakeholders to gain insights and extract actionable conclusions.
• Interpret results. The next step is to interpret the findings and understand their implications. For example, a marketing company may find that a particular advertising campaign had low engagement. Or a retail chain may notice a spike in sales during certain months of the year. By scrutinizing the patterns and trends illuminated during the data analysis process, companies can determine the best way to achieve their strategic goals.
• Make decisions. Finally, businesses use data-derived conclusions and insights to guide critical decisions. This may involve implementing new products and services, changing how they allocate resources, pivoting to a new marketing plan, or adjusting their pricing strategies. The applications for data-driven decision-making are nearly endless. 

Challenges in the Implementation of Data-Driven Decision-Making  

Using data to steer business strategies can yield incredible results. However, many organizations encounter obstacles during the data-driven decision-making process, including: 

• Inaccurate or inconsistent data. When data is flawed or incomplete, businesses can draw inaccurate conclusions. Data cleaning techniques can help fill in the missing information, account for outliers, remove duplicate data points, and correct inconsistencies so that data is ready for analysis. 
• Resistance to change. Sometimes called “organizational inertia,” businesses and their employees often favor the status quo— even when data-driven decision-making offers a better alternative. When a company changes how it handles important decisions, there can be significant backlash. One of the best ways to combat resistance to change is to foster a culture of transparency and collaboration. When people understand the reasons behind a change and can participate in the transformation, they’re more willing to embrace it.  
• Difficulty integrating data tools. Incorporating new technologies into existing workflows can also present challenges when adopting DDDM. Companies implementing data collection and analysis tools must ensure that the new technologies are compatible with the current infrastructure and will scale to accommodate fluctuating needs. Choosing programs with intuitive, user-friendly interfaces can also minimize the learning curve and ease the transition. 
• Concerns about data privacy. When collecting and storing data, companies have both an ethical and a legal obligation to ensure confidentiality. This is especially true in the finance and healthcare industry. DDDM initiatives must adhere to data protection laws such as the Health Insurance Portability and Accountability Act (HIPPA) and Gramm-Leach-Billey Act (GLBA).

Staying Competitive 

Data-driven decision-making allows organizations to make strategic choices, adapt to evolving conditions, and maintain a competitive edge. As a result, professionals who can gather, evaluate, and interpret data are in high demand. If you’re interested in elevating your skills and getting ahead in your career, earning a master’s degree in data analytics can be a great way to do so. 

At WGU, our M.S. Data Analytics degree is designed with input from industry leaders, so students are equipped with the knowledge and skills employers seek in candidates. Our programs are competency-based, meaning students can advance to the next course as soon as they demonstrate knowledge of the course material. Whether you’re a working professional fitting college into your busy schedule or just beginning your career journey, a degree from WGU can help you achieve your goals. Apply today!