4 Steps to Achieve Data Agility

To achieve data agility—how quickly you can derive value from the piles of data and how fast you can turn that data in actionable insight to meet the changing needs of your customers—you have to be sure that your data is in “top shape.”

…So says H.O. Maycotte in an article in Forbes. There are a number of steps you can take to enhance your company’s data agility, according to Maycotte. Here are four of them:

1. Assess the Condition of Your Data

First, determine how your data is currently doing so you can establish a baseline. Is your data sluggish? Or can you access it quickly so you can use it to make better business decisions? Are there tons of duplications? Is it updated often enough? Is it clean and fit? “Take an honest look and see where your data could use a workout,” Maycotte says.

2. Foster an Environment of Agility

Agile is as agile does. Maycotte says that you should encourage the teams throughout your organization to consider the business benefits of thinking and responding in real time to changing market conditions and/or customer behaviors. “That’s the agile culture businesses that excel today constantly strive for, and agile data is part of it,” he notes.

3. The Time Is Now

Data agility means you have to respond to things as they’re happening so that you’ll get the biggest bang for your buck from whatever actions you take, according to Maycotte. That means doing away with the old data warehouse model because if you want to remain competitive you can’t wait weeks or months to collect and normalize the data into a traditional data warehouse, according to Maycotte. Rather, you have to make decisions on your data in real time and reevaluate them whenever necessary.

4. Agile Data Is Clean Data

Every day vast amounts of information are flowing into companies from a variety of sources, including wearable devices, sensors, and Internet of Things devices. Because that data is being stored on various platforms it’s often duplicated, inaccurate, and incomplete.

To eliminate these obstacles to agility, you can’t just capture data, you have to clean it and keep it as useful as possible, Maycotte says.

If you want to achieve data agility, you first have to recognize its value to your organization, he says. Then you can figure out exactly how you’re going to attain it. “Data agility is as much about an organizational attitude as it is about the tools and technology that help achieve it,” Maycotte says.