7 Steps to Successful Analytics

by | Jan 30, 2025 | General BI

Reading Time: 6 minutes

One of the hardest parts of instituting a data-driven culture is the initial transition period following implementation. How can organizations put into place the processes that will enable them to be self-sufficient in gaining and acting on insights from their data?

At Dimensional Insight, we help organizations with that transition, not only guaranteeing the successful implementation of high-quality dashboards and reports, but also the high-quality data that fuels those dashboards and reports, matching the specific goals of the organization.

By actively involving users and ensuring a continuous focus on quality, we deliver sustainable data solutions that provide deep insights and enable organizations to make informed decisions. By doing all of this, we proudly contribute to the success and growth of our partners.

Here in our Dutch office, we follow a seven-step implementation process. It is based on years of experience working with our customers and brings together our best practices. The process is divided into three phases – startup, delivery, and support. Let’s take a closer look at these steps and how they can help you successfully start your analytics projects.

Phase One: Startup

Step 1: Define goals and scope

The first part of any analytics project is to clearly define the objectives and scope of the project. This is an iterative process, as the scope is typically not immediately fully defined. As the project progresses and more insights are gained, the scope can be adjusted to better meet the needs of the organization.

We identify the stakeholders involved and analyze the key business processes to develop a solution that contributes to the goals for the organization. This kind of a start helps to reduce risk and ensures effective project execution.

Step 2: Data discovery and planning

Next, we perform a thorough assessment of the available data, paying particular attention to the data quality assessment. We also analyze the structures already in place. This forms an essential basis for the data modeling and allows us to develop a clear roadmap for the next steps. By evaluating the quality of the data early, we can proactively address any issues and ensure a solid foundation for everything to come.

Step 3: Define roles, responsibilities, and information security

A successful implementation requires a clear allocation of roles and responsibilities within the project team. As the project grows, this allocation of roles may evolve, with some responsibilities needing to be re-examined and adapted to the changing complexity and scale of the project.

It is also essential to establish robust information security procedures from the start that can be continuously evaluated and refined to ensure the protection of data. Every project starts with a security risk assessment. As the project progresses, certain security decisions may be re-evaluated to ensure they continue to meet the needs of the project. It’s also equally important to establish effective communication processes that help manage expectations and ensure cooperation.

 

 

Phase Two: Delivery

Step 4: Agile delivery and collaboration

We use the AgileLight methodology, a flexible approach specifically designed to respond to changing project requirements. Within this methodology, we perform customer value prioritization, where we work with the client to determine which features add the most value to their business goals. This helps us focus on the areas that have the greatest impact.

We use feedback loops at every stage of the project so we can quickly pivot and continuously improve based on customer feedback. This allows us to deliver results quickly without compromising quality. Collaboration tools such as GitLab and version control via DTAP (design, testing, acceptance, and production) ensure streamlined collaboration and quality assurance, with every change closely monitored and tested for consistent delivery.

Step 5: Quality assurance and user involvement

Quality is at the heart of every solution we deliver. Early documentation of decisions plays a key role, not only providing a clear overview of the choices and steps taken, but also promoting user acceptance, which can significantly simplify onboarding. This documentation also serves as a guarantee for consistency and quality throughout the project lifecycle.

In addition to strict coding standards and peer reviews, detailed documentation ensures that all stakeholders, including users, are informed at the right time. The importance of user feedback during sprints cannot be underestimated; it allows us to continuously align progress with the wishes and requirements of the users, resulting in solutions that are reliable, sustainable, and seamlessly aligned with the needs of the organization.

 

 

Phase Three: Support

Step 6: Continuous improvement and feedback

With continuous feedback loops we ensure that our solutions remain relevant and up-to-date. Collecting feedback from both core and occasional users plays an important role in this step, so that we gain insight into how the solution is experienced and used by different groups.

We use a wide range of workshops to both implement operational improvements and increase the involvement of a broader user base. One example is DAKI (Drop, Add, Keep, Improve) workshops, which are specifically aimed at optimizing functionality. By collecting input from both frequent and occasional users, we can better tailor the solution to the diverse needs within the organization. This ensures that not only the technical aspects are adapted to the changing requirements, but also that the entire organization actively contributes to the continuous improvement of the solution.

Step 7: Long-term support and optimization

After implementation, we provide ongoing support to ensure the solution continues to perform optimally and adapts to changing circumstances. Our State of the Union (SOTU) workshops, ideally held once a year, provide an opportunity to explore the latest developments from Dimensional Insight while ensuring that the solution remains aligned with the strategic goals of the organization. We also place extra emphasis on extensive training and detailed usage analysis.

Training not only helps users get the most out of the solution, but also enables them to identify and report issues early. In larger organizations, this, combined with monitoring usage patterns, can help identify potential bottlenecks or inefficiencies before they become a bigger problem. This proactive management ensures that the solution continues to meet both operational and strategic needs, while users are better able to get the most out of the technology.

 

 

Conclusion

By following these seven steps, organizations can effectively implement analytics solutions that are tailored to their unique needs. Throughout this journey, a focus on stakeholder engagement, data quality, and iterative refinement ensures that solutions remain both relevant and impactful. The result is a sustainable data-driven culture that empowers users, drives informed decision-making, and ultimately propels organizational success.

 

Lieven Schellevis
Latest posts by Lieven Schellevis (see all)

You may also like