Top 6 roadblocks derailing data-driven projects
Data is what drives digital business. Consider how strategically important it has become for companies to leverage advanced analytics to uncover trends that can help them gain decisive insights they might not otherwise possess.
But data-driven projects are not always easy to launch, let alone complete. In fact, enterprises face several challenges as they look to leverage their information resources to gain a competitive advantage.
Foundry’s recent Data & Analytics Study looked into why organizations have difficulty making good on the promise of data-driven projects, and revealed several key roadblocks to success. Here are the top six reasons data initiatives fail to materialize and deliver, as revealed by the research, along with tips from IT leaders and data experts on how to overcome them.
Funding can be hard to come by for any technology initiatives, particularly in an uncertain economy. This certainly applies to data projects. These undertakings might be competing with a host of other initiatives in need of financing, so it’s important for IT leaders and their data teams to present a strong business case for each project, and to not make them overly complex.
“While budget is always tricky, this is a question of priorities and right-sizing the body of work,” says Craig Susen, CTO and technology enablement lead at management consulting firm Unify Consulting. “Looking for obvious outcomes [does not] always require reworking the entire infrastructure.”
Being data-driven is as much a cultural pursuit as it is anything else, Susen says. “It requires designing/rethinking key performance indicators, capturing data in a smart timely manner, landing it in common areas quickly,” he says. “Then it can be evaluated and aggregated, either applying advanced visualization technologies or working it against machine learning algorithms. It’s all a complicated bit of science. Having said that, many companies overcomplicate this process by trying to do too much all at once or over-indexing in places that don’t drive true value to their businesses and customers.”
CIOs and other technology leaders need to develop strong working relationships with fellow C-suite members, particularly CFOs. In many cases it’s the finance executive who makes the decision on budget approvals, so to improve the likelihood of getting the needing funding technology chiefs need to be able to demonstrate why data-driven projects are important to the bottom line.
Lacking a complete data strategy to guide data-driven projects “is like not having an outline to guide a thesis,” says Charles Link, senior director of data and analytics at Covanta, a provider of sustainable materials management and environmental solutions.
“Every project should contribute some paving stones to the road leading to the desired destination,” Link says. “A data strategy identifies how to align information and technology to help you get there. Your business should be able to travel down the road as you deliver value.”
To be successful, a data strategy should have both a data management component — generally IT tools, technologies, and methods — and a data use strategy, Link says.
Oftentimes there isn’t a clear understanding within enterprises of what data is available, how the data is defined, how frequently it changes, and how it is being used, says Mike Clifton, executive vice president and chief information and digital officer at Alorica, a global customer service outsourcing firm.
Companies need to create a common language among stakeholders in advance of establishing any data-driven projects, Clifton says. “If you don’t have a solid foundation, budget and funding are too unpredictable and often get cut first due to a lack of clear scope and achievable outcome,” he says.
Making the challenge of getting sufficient funding for data projects even more daunting is the fact that they can be expensive endeavors.
