3 Key Stages for Effective Data Modernization | 7wData

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Don't get stuck in a room going nowhere. Follow the Plan-Build-Execute model, and your data modernization initiative will lead to success.

San Jose’s Winchester Mystery House is a spectacle. Stairs going nowhere. Doors opening into walls. Windows overlooking other rooms. There’s no blueprint for how the house was supposed to look --merely a set of ideas.

That kind of chaos is an all-too-common sight for organizations that haven’t realized the power of their data. Silos form and teams aren’t sure how their data impacts the whole business. You’ll see multiple tools, different processes, and inconsistencies across the company, which can lead to decreased revenue and customer trust.

While the Winchester is fun to visit, you don’t want to model your organizational structure after it. Luckily, your data modernization initiative can thrive by following three key stages: plan, build, and execute.

Think of your stack like a home. Add more rooms onto a house, and you need more electricity to power them. Everything must work together, or the entire system could shut down. 

Similarly, when you’re modernizing your stack, look at how to bring everything together in one environment. By leveraging the power of the cloud, you can create scalable analytics, effectively Data-as-a-Service. You’ve got this information at your fingertips and can begin planning how to use it across the organization.

The first part of that planning stage? Identify your problem. Any data modernization initiative will fail if you can’t clearly define the problem you’re trying to solve.

The next step: Establish a clear goal or objective. This is your team’s North Star. If you’ve ever gotten lost outdoors, find the North Star and it will guide you home. Your objective should be the same --something clear and tangible to work towards. You’ll likely need a centralized data analytics lake here, so everything can run through the same system and processes, creating consistent data to measure against.

The third step is defining success. You know you may want to reduce churn or improve a net promoter score. But what does achieving that goal look like? By putting metrics or KPIs in place, you’ll have a clearer understanding of your data modernization initiative.

Finally, before you can begin building, you need to get buy-in across your teams. It’s sometimes difficult to clearly articulate the value of data modernization. It’s a disruptive process and can impact the entire organization when things start shifting around. Your first stop should be the company’s C-suite or board of directors. Getting that top-level buy-in is critical.

Once the planning phase is complete, move onto the build stage. It’s easy to say you want to move to the cloud and be data driven. It’s a lot harder to do it.