- Most Fortune 1000 companies get low marks in data intelligence
- New study proves direct link between effective data and profitability drivers
- Improved data use increases a company's ability to introduce new products
- Executives should treat data as a strategic issue rather than technology overhead
Data Quality Model
“Peer inside any Fortune 1000 company and you’ll see data everywhere, most of it quite timely and accurate,” says IT researcher Anitesh Barua. “But data doesn’t give you competitive advantage. For that you need other attributes like intelligence, usability, accessibility and mobility, and we now have the research results to convince CEOs and CFOs of that.”
His latest study (together with Deepa Mani and Rajiv Mukherjee) gives low marks for data intelligence to most of the corporate world. Viewed positively, there’s plenty of opportunity to improve. “We show that in the median Fortune 1000 business, increasing the usability of data by just 10 percent translates to an increase in $2.01 billion in total revenue every year,” he says.
Barua is both a researcher and a cheerleader regarding the smart use of data to drive financial performance, and he grows impatient with what he sees as cultural and operational barriers within large organizations.
Moving beyond data fundamentals
“Companies have gotten very good at the data fundamentals, but a trainload of data can be extremely accurate and still be meaningless or even detrimental,” he explains. He partially blames a corporate culture which equates intelligence as a technology issue rather than a financial performance driver.
“Previous studies have shown that where CIOs actually report to CEOs, companies are more innovative, have more patents, more new products and more new customers,” he says.
He encourages executives to think of data quality as a pyramid in which basic attributes like accuracy and timeliness provide the foundation, and where attributes like intelligence make up the tip.
One factor is the portability of data, the ability to get it into the hands of a sales team, for example, in real-time and directly where they interact with a customer. “That allows a sales person to customize a product or service plan right at the point of the transaction,” he says. “We can show portability directly improves sales per employee, which is a widely used indicator of employee productivity within a company.”
Tying business intelligence to financials
By linking better data use directly to financial performance factors, Barua hopes he can influence better strategic use of data within organizations. “We’ve long known that data quality and access positively impact financial performance, but now we can actually show how it drives better financials.”
Besides sales per employee, another area that responds well to improved data use is new product introduction. “We see increased revenue from new products ranging from $17 million to $150 million per year with just a 10 percent increase in data effectiveness,” he says. “That translates to increased revenue from new customers, revenue coming from new products, and improved efficiency in getting products to market. This touches accuracy of schedules, accuracy of forecasting, on-time delivery, on-time provisioning of services, all the way down the line.”
Changing the executive mindset
Barua says that intelligence success stories such as Walmart result from a corporate philosophy that sees effective data as a strategic business factor, not technology overhead. “If the CIO is always focused on efficiency, it is difficult to demonstrate the strategic value of attributes like data portability and usability,” he insists. “If I can show that information technology can directly drive profitability, who cares whether the IT budget is three percent of the revenues? We can actually spend more.”
Armed with his study, Barua is now on a mission to sell the financial power of business intelligence to top decision makers. "This requires C-level support, and not just the CIO," he says. "My message is for CXOs, in which X does not equal I.”