The Biggest Barrier for Companies That Want to Leverage Their Own Data
According to the Society for Information Management’s IT Trends Study, which surveys thousands of IT leaders every year, analytics and business intelligence are among the largest investments IT departments are making this year. In an interview about the SIM study’s findings, Russell R. Torres, one of its co-authors, stated that many companies have embraced applications that “give them the ability to extract value that’s been sitting dormant in the data they collected.” When leveraged effectively, this data can allow them to gain customer insights, increase efficiency, and reduce costs.
But companies that rush headlong into capitalizing on their digital data streams without first ensuring they have the appropriate infrastructure and culture in place could end up wasting money on inaccurate insights. This according to a new report titled “Selecting Digital Data Stream Winners.” A joint collaboration between two leading researchers and SIM’s Advanced Practices Council, a program for CIOs, “Selecting Digital Data Stream Winners” puts forward several frameworks that, if adopted, would increase the likelihood that a company would produce significant ROI out of its data efforts.
Federico Pigni, an associate professor in information systems at the Grenoble Ecole de Management, and co-author Gabriele Piccoli, an information systems professor at Louisiana State University, empirically developed the study’s frameworks through an in-depth analysis of digital data stream (DDS) initiatives and the organizations leveraging them. “We mainly gathered information through secondary sources, but we also conducted interviews in several cases,” said Pigni in an interview. “We employed an inductive case study approach to gather the data and followed established literature to build the proposed classification.” The researchers also conducted surveys with more than 200 US and European companies to study which processes were being exploited and assess firms’ DDS readiness.
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So how can companies assess their preparedness for harvesting their own digital data streams? The study created a framework with four dimensions, all of which are necessary prior to any data harvesting:
Mindset: According to the study, a company’s mindset is its “willingness to invest in new data-driven initiatives and assume the associated risks.” Without a data-driven mindset instilled in the company culture, those charged with leveraging DDS can easily get mired in a bureaucratic minefield that makes their job impossible.
Skillset: Skillset refers to the “ability of a company to manage DDS initiatives by acquiring and orchestrating all the resources necessary to deliver value with a DDS.” Without the trained personnel who are knowledgeable of best practices, a company’s use of data is prone to error.
Dataset: This refers to whether the company actually has access to a quality data stream. If the data being collected are incomplete or poor in quality, then any business insights that are derived from them should be suspect.
Toolset: Does the company have the appropriate software and hardware to intercept a DDS and harvest its content? “The most technical of the four DDS capabilities,” wrote the study’s authors, “it encompasses both technical competencies and resources necessary to tap into streaming data.”
As the study notes, all four dimensions are necessary for a company to move forward with harvesting digital data streams, but which dimension provides the biggest barrier and is the hardest to overcome? “I believe the mindset is the largest barrier,” said Pigni. “The world has changed but organizations are often still lagging behind. In Europe, I still see companies struggling when it comes to the relationship between business and IT. Data initiatives require domain-knowledge to interpret data and match them to business requirements and … organizations not wired for an agile allocation (and reallocation) of the resources (financial, human, knowledge) needed for a DDS strategic initiative will be, in my opinion, slow movers in their respective industries.”
Pigni explained that he often sees companies making pitfalls in the allocation of resources. In fact, when the researchers asked survey participants to list their greatest challenges, they cited a lack of access to resources such as partners, financial means, and technical skills.
Pigni referenced the scene in Alice in Wonderland in which Alice is lost in the woods and asks the Cheshire Cat which way she should go. The cat asks her where she wants to get to, and when she replies that it doesn’t really matter, he retorts “then it doesn’t really matter which way you go.” Similarly, without a clear direction that is predicated on a firm cultural mindset, it’s impossible to draw a direct line between the origin of your digital data stream and the desired outcome. “While you may in the end get there,” said Pigni, “your journey will require much more resources and energy. At the end of the day, a lack of mindset will result in a lack of vision and a consequently bad resource allocation.”