Gartner outlines the strategies and technologies that will shape great data analytics and AI initiatives.
Today’s successful data analytics or artificial intelligence (AI) initiative doesn’t start with buying a tool or gathering up every gigabyte of online data that your organization has generated in hope of finding efficiencies or a competitive edge. Rather, leaders need to start by stepping back to look at the big picture and ask the right questions.
That was the underlying message in Tuesday’s keynote address opening the annual Gartner Data and Analytics Summit.
In the virtual conference, Gartner Research Director Gareth Herschel said, “Data analytics is essential for enabling organizations to respond to change. As enterprises look to recover from the profound disruptions of the last year, D&A can help with tasks such as enabling business model transformation, optimizing resource allocation, or figuring out new ways to connect employees, customers and other stakeholders.”
Herschel noted that Gartner research shows C-level executives and corporate directors already recognize data analytics and AI as having the most potential as disruptive technologies. Those leaders are counting on analytics and AI to drive the change that enterprises need.
He added, “We [D&A professionals] need to the things the CEO cares about, like helping enable a transformation of our business model; identify the changes sweeping our industry before anyone else; optimize the way we manage our resources; and figure out new ways to connect employees, customers and other stakeholders.”
Three things to know
To address such questions, Herschel said D&A leaders have to take a step back and recognize three key factors: That analytics pros can’t work in isolation, needing to partner with the “agents of change” in their organization, that they need to build automated systems that keep pace with “continual change”, and data initiatives have to scale across the enterprise with analytics embedded in business processes.
Where analytics and AI teams are likely to fail is if they implement applications that aren’t tied to real business needs in the “hope that someone uses it.”
That advice isn’t new. Those who have been around the analytics field for a few years have heard plenty of stories about analytics or AI initiatives failing because they didn’t address corporate goals or business leaders’ questions. In some cases, the data team developed what is derisively called “technology for technology’s sake.”
Today, D&A professionals can avoid that problem by identifying and partnering with executives or business leaders who know their own challenges and are likely open to a data-driven solution, said Herschel. That type of partnership has the potential to overcome the issues of a few years ago when applications seemingly were dumped on users without solid business input.
Applications designed for continual change rather than what could be viewed as “one-off” systems in the past have to rely on automation, according to Herschel.
More specifically, he said those adaptive systems require a data fabric for data integration, use of graph technology to identify connections between data types, utilize generative adversarial networks (GANS) to simulate solutions, and use natural language generation to help machines “tell data stories”.
“The new imperative is to build adaptive systems so that we can rely on technology to help keep pace with our changing world,” said Herschel.
So, the bottom line to all of this is that D&A teams have an opportunity to change the way key decisions are made. “D&A leaders must identify opportunities to change the way people think, until using data and analytics becomes a habit.”
The Gartner event continues Wednesday and Thursday.