The Pragmatic Data Insights Model
Our courses are built around the Pragmatic Data Insights Model, a proven, optimized and repeatable approach to data projects. Aligning data teams and business leaders around this approach will enable them to define a question of tangible impact to the business and solve it with the data at hand.
Focus on the specific business problem you want to solve with data
Data practitioners should avoid disconnects and make the most of initial meetings by establishing clear goals from the outset with their stakeholders.
- Ask key questions
- Ensure it’s solvable
- Confirm your understanding
- Provide options
They should get to the crux of the problem by finding answers to the basics: who, what, when, where, why and how. This will head off any misunderstandings and build consensus with stakeholders. Setting the right parameters and expectations with those who will need to act on the findings will help ensure a successful project.
Explore the available data and the most useful methods
Once a data practitioner has defined the objective, they should review the data they have and consider the resources needed to complete the project. The “Prepare” phase is the due diligence around framing what’s possible with the data at hand and identifying issues from the start.
Here are the just first few questions in our checklist:
- Does the data you need exist?
- Do you know how the data was generated and collected?
- Is the data enough to reach reliable conclusions?
- Are you missing variables, values or entire datasets?
- Are you aware of the relevant policies and laws associated with the data?
Revise questions and expectations as necessary
Data practitioners must decide if their initial plans are feasible and likely to provide the desired return on investment. Going back to the stakeholder to refine and adjust the parameters of the project is a crucial phase. Skipping this step is a major reason many data projects fail or experience “scope creep.” The “Refine” phase kicks off with broader concerns to keep in mind:
- Organizational policies
- Legal responsibilities
- Vendors and business partners
- Public interest
Build models to find actionable insights
With clear questions, the data at hand and refined parameters, data practitioners are now ready to analyze the data. The goal: provide actionable insights to stakeholders, with a good return on investment. There is no one right way to analyze data—it might look like a machine learning algorithm or a simple pivot table. For findings to be translated into business strategy, data practitioners need to simplify them into something that can be easily interpreted and put into action.
The high-level steps of the “Analyze” phase are as follows:
- Know your context
- Choose the tools that fit your goals
- Interpret for actionable insights
- Highlight applications
Communicate actionable insights and next steps to stakeholders
This phase is about communicating—as clearly as possible—the business problem, the data used to answer it and the business solution that can be justified by that data. Data practitioners have a story to tell, and they shouldn’t let the data overwhelm their stakeholders. They can follow these guidelines to ensure they avoid the most common mistakes as they begin to visualize their insights.
- Keep it simple
- Label your axes
- Consider scales
- Direct attention
- Notate as needed
- Beware of unwanted interference
For more on the Pragmatic Data Insights Model, watch the below webinar.
Learn How to Harness the Power of Data to Solve Business Problems
All Pragmatic Data courses are built around the Pragmatic Data Insights Model to ensure both data teams and their stakeholders can embrace a single, optimized approach to data projects. The Insight course within Pragmatic Product leverages the model as well.
Master the Pragmatic Data Insights Model by completing five case studies (from representative business problems) and a final project that implements these skills within your own organization using real-world data.
Understand how business leaders and data practitioners contribute at each phase of the Pragmatic Data Insights Model to drive results that have real impact on your own organization.