Even more than a lack of money or time, corporate culture can sometimes be the largest barrier to change within an organization — and that rings true when it comes to adopting new and better technologies. Analysis recently released by data analytics software company SAS found that internal leadership plays a key role in a company’s ability to integrate new technologies.
According to SAS, while hurdles including data preparation capabilities are key to facilitating the adoption of new data tools, other factors are at play that are less easily addressed.
“Even organizations that are strong in these areas say that they see significant challenges with things like innovation, creativity and leadership,” the company found in a survey conducted in conjunction with IIA for their 2016 IIA and SAS Business Intelligence and Analytics Capabilities Report. “Without a strong vision and buy-in at the executive level, resulting initiatives will naturally fail or underperform.”
Inciting a change in corporate culture to an environment that embraces innovative technology is certainly no easy feat, but the latest analysis from SAS is urging companies to push forward with these efforts, because while there is a cost to integrating disruptive technologies, the cost of remaining stagnant could be higher.
In a new paper authored by Thomas H. Davenport, a data analytics industry advisor and educator, SAS and Deloitte warn against “preserving the status quo.” When it comes to data analytics technologies, failure to upgrade and update systems can hit a company hard.
“Not taking advantage of these analytics modernization opportunities has some substantial implications,” Davenport wrote. “If you don’t modernize your analytics, they’re likely taking too long to run, are not sufficiently visual, they cost too much to operate, require too much expertise to use and so forth.”
He highlighted several case studies that show what he described as “dramatic benefits” these companies realized through data technology modernization. One telecommunications company, he said, saw revenue collections increase by $2 million a month as a result of updating various analytics solutions around collections and customer billing management.
In another case, noted Davenport, one bank in the U.S. deployed data analytics technologies that could aid with faster credit decision-making.
Earlier SAS research found that companies are well aware that updating data technology will be beneficial. In its survey, the majority of mid-market and enterprise firms surveyed (57 percent) said business intelligence is critical to their companies and that their use of sophisticated technologies will increase this year. Sixty percent said they have already experienced benefits from their data analytics and business intelligence tools.
Modernizing existing systems no doubt has its benefits, but taking the first steps of the process are some of the most difficult. Davenport outlined five steps the enterprise can take to begin: assess technical and human capabilities, generate a proof of concept for new technologies, redesign the work press, address relationships between the enterprise and IT and measure outcomes.
SAS isn’t the first to draw conclusions about the difficulty companies face when trying to upgrade technologies. Research released last month from Forbes and EY Global similarly found that corporate culture often stands in the way of adopting better analytics tools, with executives’ intuition often trumping cold, hard data when a company explores whether to adopt a new tool. Just 35 percent of respondents to their survey said their company has “well established” data and analytics groups within the enterprise.
According to Davenport, though, businesses must work to overcome the hurdle of its own inability to enact change.
“There is little doubt that we are in the age of analytics, and strong analytical capabilities demand modern analytics technologies,” Davenport concluded. “Those companies that have invested in new technologies have achieved great results. I know of few types of investments that will yield greater returns than well-targeted analytical modernization programs.”