6 Steps & 4 Accelerators to Data Utilization & Maturity

Let’s talk about data utilization and maturity — companies that effectively collect, analyze, and derive insights from their business data set themselves on a trajectory for success. To harness their data’s potential, companies naturally progress along a “data utilization journey.” We’ve identified six stages or steps in that journey. At each step, your company’s data utilization maturity increases, thereby delivering greater value to the organization. Through our work guiding hundreds of companies on their data journeys, we’ve found that the pace at which a company moves through the stages depends on four factors. That’s right—six steps to the top and four accelerators to help you climb higher and faster.

Let’s look at those six steps in the data utilization journey and the four factors that dictate your journey’s pace and overall success.

The Six Stages In the Data Utilization Journey

Data utilization involves more than just collecting or accessing data—it encompasses how your business and its employees actively use, analyze, and apply data to make informed decisions, derive insights, and drive actions.

In terms of complexity and the progression of data maturity, the journey often goes from descriptive analytics (what happened) to diagnostic analytics (why it happened), then to predictive analytics (what is likely to happen), and finally to prescriptive analytics (what actions should be taken).

It’s helpful to think of a data utilization journey as a series of six progressive steps or stages, evolving from basic reporting to the pinnacle of prescriptive insights.

1. Reporting: The foundational stage where you gather and present data.
2. Analysis: Where you dissect your data to identify and understand trends and patterns.
3. Monitoring: You continuously track data metrics to maintain performance standards.
4. Forecasting: You begin using your data to predict future trends.
5. Predictive Insights: You’re able to proactively identify future outcomes based on historical data.
6. Prescriptive Insights: You can offer solutions or actions based on predictive analytics.

The more quickly you advance along your data journey, the sooner you’ll begin realizing the benefits.

Four Critical Factors for Data Utilization 

As businesses navigate their data journey, four pivotal factors determine how quickly they move and how successful the results are. In our work helping businesses advance and mature their data usage, we’ve identified four critical factors that significantly influence the speed and effectiveness of your organization’s data journey:

Data Infrastructure: Laying the Groundwork

Here, organizations embrace modern data storage solutions, including big data platforms. This includes creating storage solutions, establishing data pipelines, and ensuring data can be accessed and processed efficiently. You begin seamlessly integrating data from different sources, and there’s a heavy reliance on advanced analytics, forecasting, and prescriptive insights. You’re tapping into machine learning and AI tools to process and analyze data.

• Storage Solutions: Whether opting for on-premises databases or cloud-based solutions, choosing a storage method that scales with the organization’s growth is crucial. Considerations include data volume, velocity, and variety.
• Data Pipelines: These are essential for transporting data from various sources to its destined storage or processing unit. Effective data pipelines help automate the data flow, preparing it for analysis.
• Access and Processing: Ensure that tools and platforms can handle the organization’s data processing needs, whether it’s simple querying or complex data modeling.

Data Quality—Ensuring Reliability

Once the infrastructure is in place, when looking at your data utilization, your focus shifts to the data quality. Your governance structures are well-defined, ensuring standardized data collection, storage, and usage practices across the organization.

• Data Cleaning: This involves removing duplicates, correcting errors, and handling missing values. Regular data audits help in identifying and rectifying inconsistencies.
• Data Integration: With data coming from multiple sources, integration ensures a unified view. This might involve data normalization and the use of unique identifiers for matching records across datasets.
• Data Validation: Implementing validation checks at the point of data entry or ingestion can prevent poor-quality data from entering the system in the first place.

Data Literacy—Building Capacity for Data Utilization 

With a strong infrastructure and quality data, your focus shifts to the users. Data literacy is about empowering every member of the organization to make data-driven decisions. Employees across all levels understand the value of data, and there’s a strong emphasis on continuous learning and upskilling. Data-driven decision-making becomes the norm rather than the exception.

• Training Programs: From basic data awareness to advanced analytics, provide training tailored to different organizational roles.
• Tools and Dashboards: Offer intuitive tools that allow users to extract insights without needing advanced technical skills. Dashboards can visualize data in an understandable format, aiding in decision-making.
• Support Systems: Establish a helpdesk or a team of data champions to assist users when they face challenges, ensuring continuous learning.

Data Culture—Fostering a Data-Driven Mindset

The ultimate stage in the data journey is when the entire organization embraces a data-driven culture. Data is central to all strategic decisions. Your organization relies on advanced analytics, predictive modeling, and AI to derive deep insights, identify trends, and stay ahead of the competition. Data is not just an operational tool but a critical strategic asset.

• Leadership Buy-In: It starts at the top. Leaders must lead by example, basing their decisions on data and encouraging their teams to do the same.
• Openness and Transparency: Foster an environment where data is readily available and shared. This encourages collaboration and innovative use of data across departments.
• Incentivizing Data Use: Reward teams and individuals who effectively use data in their roles. This could be through recognition, promotions, or bonuses.

Take the First Steps

The data journey is a transformative process that requires attention and action at every step. From the tangible aspects like infrastructure and data quality to the intangible elements like literacy and culture, each factor plays a pivotal role in maturing your organization’s use of data. By recognizing the journey’s progressive steps and investing in these four factors to advance through those steps, your organization can not only navigate the data journey effectively but also unlock the true value of its data assets.

Velosio works with small and mid-sized organizations across industries, helping them make smart, strategic use of their data. We’re here to support you every step of the way. Reach out to our consulting team to start a conversation.