Build a business case for prototyping

Better to validate needs from the outset than impede the progress of your project with a challenging requirements review process.

“Prototyping helps organizations begin to see business results in the earlier stages of a project—reaping value sooner in a data project’s lifecycle.”

—Peter Johnson, vice president of Enterprise Applications and Information Services at MetLife

The traditional requirements process is at once predictable and unpredictable. Invariably, your staff will spend hours struggling to decipher what their business counterparts really want. They most likely will be challenged to provide a complete picture of business goals. But once they start the project, they can’t predict the scope without a thorough review of business requirements.

What if you could equip key business analysts with innovative tools that give them greater control? What if these tools help them accelerate development cycles and increase productivity? Peter Johnson, vice president of Enterprise Applications and Information Services at MetLife, believes it’s an attainable goal.

By using prototyping tools to explore data and create compelling prototypes, Johnson says, business leaders can better communicate and demonstrate their needs. In turn, you can better influence and guide data-driven decision making as a result of your increased agility, fidelity, and governance.

How can prototyping take agility to the next level?

Peter Johnson: Coding used to be a huge part of determining what a particular system can and cannot do. But that’s all changing. Now, the up-front processes of setting a system’s specifications and back-end processes, and testing these systems, are a larger portion of the development cycle. As a result, agile methods of development and prototyping using visualization tools can really help validate business requirements. They do this by demonstrating what the end result will actually look like.

By simulating data warehouse changes and additions, virtualization can show how standardizing a particular variable will impact the outcome. It’s these concrete examples that accelerate the IT development cycle and eliminate misunderstandings.

What role does fidelity play in the long development process?

Johnson: Prototyping is about more than speeding up the development cycle. If done correctly, it can also build confidence in the development process. For instance, ensuring quality data and knowing its lineage can encourage business leaders to trust that the resulting data will be accurate.

In addition, prototyping creates greater clarity for a project’s stakeholders, in terms of what various hardware and software combinations will produce. And finally, prototyping helps organizations begin to see business results in the earlier stages of a project—reaping value sooner in a data project’s lifecycle.

How can governance drive greater business intelligence?

Johnson: Whether you’re looking to secure project funding or validate data, prototyping requirements can help organizations understand the prize at the end of a long development cycle.

Consider, for example, a predictive model built to identify fraudulent or suspicious insurance claims. With the help of data quality reports and prototyping, an organization can closely examine the data that’s driving that model and its effectiveness. That’s because these reports can highlight key variables, such as income level or location. These are some of the best indicators of fraud—information that may be missing from a predictive model.

Armed with this higher-quality data, an organization can then introduce the metrics needed to generate better business results.


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