Perhaps you want to reduce the mean time to resolution (MTTR) for your call center. Narrowing the scope of your project to that specific goal will make it much simpler to identify the data that's most pertinent to success.
"You should really walk before you run," Keep says. "Start with a specific business problem which has a defined set of data you can pull from and a defined set of goals so you can measure success."
This will also help you identify the key stakeholders who stand to benefit. They won't run the project day-to-day, but they can help get the necessary resources in place to ensure the project is successful.
Step 2: Identify data consumers
Once you've identified the business problem you're trying to solve, the next step is to understand the consumers of the single view of data that you're going to create. To get the right requirements, you need to understand who they are, how they work and ultimately how you can make their jobs simpler.
"You have to block some time out with them," Keep says. "Observe. How do they actually query the data? Is it a text search? A lookup by customer ID? You can't overengineer this and you can't get enough data."
For example, Keep says, MongoDB has helped insurance company MetLife get a single view up and running for its call center reps. Observation revealed that the company's call center reps had to navigate across as many as 15 different screens to answer common customer questions. By watching precisely what they were doing day-to-day — the questions they were answering for customers and what it took to reach those answers — MetLife and MongoDB were able to build something much simpler.
Step 3: Identify data producers
The third step, often symbiotic with Step 2, is to identify the data sources that generate the data you need for your project.
"This could potentially mean creating new data sources, but very often the data exists," Keep says. "It's a matter of knowing where it is and how to get it. It might mean modifying an existing application to catch a new attribute, or digitizing something that was previously manual."
Like step 2, this step will help you identify the correct requirements.
Step 4: Appoint data stewards
The previous steps of the methodology encompassed the discovery phase of your single-view project. They were all about creating a framework of requirements. With step 4, you enter the development phase by appointing the data stewards responsible for the data in the source systems. Your data stewards will be the key players in both the creation of your single-view project and its ongoing maintenance.
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