Simply getting data is not good enough. You must get it to the right people at the right time while it is still fresh enough to be useful.
Data is critical to a company’s success—data about customers, data about products, data about revenue, data about every aspect of the business. You can use it to work better, faster, and smarter. The trick is figuring out how to deliver the right data to the right people in a timely manner. If data is not fresh, it loses value and relevancy.
“We put a tremendous amount of effort into trying to get data from various sources and into people’s hands. The focus tends to be on just getting the info, and timeliness is not the top priority it should be,” says Kristin Kokie, vice president of IT enterprise strategic services at Informatica.
“The value of data has a direct correlation with time. You must get it out at the right time so it can be consumed in time to make a business impact,” she says.
Of all the ways good data can turn bad, loss of relevance due to age is one of the most challenging and most frequently overlooked. It may have been perfectly accurate and useful when you captured it, but aspects are almost certain to change over time. This can happen to any type of data point, such as:
- Customer contact information: Postal addresses, phone numbers, and email addresses can all change frequently.
- Customer age: The only way to reliably track a person’s age is if you capture a date of birth.
- Company revenue: Because total revenue changes every year, you must also capture the financial reporting date to maintain its relevance.
- Company headcount: The number of employees at any company is a fluid number, so an associated date is also necessary.
- Hierarchy/relationship data: Changes such as discontinued product bundles or the spin-off of a subsidiary alter data relationships.
Because timeliness is so important, you may feel pressured to deliver all data in realtime, but that is impractical—if not impossible. Instead, develop with your business partners the right-time requirements for each set of data you manage, and build them into the service level agreement (SLA).
“Many business users feel they need real-time streaming data. But it is expensive, and in reality, those who truly need real-time data are a significantly small percentage relative to the masses,” says Kokie. “Part of the information manager’s job is to push back and challenge latency requirements. Challenge your business users to give you right-time requirements, not real-time requirements.”
To determine right-time requirements, question the variety of business usage scenarios for each data set. Ask what the latency and freshness requirements are because it directly affects the perception of quality in your data. It may be accurate, but if you do not deliver it fast enough and it is not fresh enough, it is simply a waste of time.