Leonard Maganza, Chief Customer Officer at Syniti, sits down with Head of Data Science and Analytics at Gap, Inc., Vimal Kohli, to discuss the changing roles of the CDO and the challenges facing them today.
The Role of the Global CDO
In today’s fast-paced world, “data is rich but insights are poor” as Kohli puts it. Before the advent of Big Data, the biggest complaint within the business was, ‘We don’t have enough data’. These days, it’s the reverse; companies feel they have too much data and struggle to manage it. And with the volume and variety of that data, it's a bit like drinking from a firehose.
The role of the CDO has become critical and is now abundantly clear. “Our job is to make sure the organization has the ability, the eco-system, and the processes to turn data into insights and insights into action and strategy,” Kohli states. “Because otherwise it just becomes this ‘nice to have’ and there isn’t really any ROI from your data.”
The Challenges of Scale
The problem of scale is not a situation unique to any one country or industry – it's across the board. The trouble is that when any new technology comes to market, it becomes the hot new item. “It’s easy to do a lot of POCs,” says Kohli, “but it’s really, really difficult to scale. It’s difficult to go into production. To do that at scale and at the velocity that modern business needs, and that’s been some of the biggest challenges.”
For Kohli, part of the reason companies have had difficulty with scaling data and analytics is because they’re not focused on process-driven change.
“If data and analytics have to be the engine of growth for running the business into the future, we have to pivot the mindset,” Kohli says. Data quality and strategy have to be a part of the way everyone in the company does business, from the marketing organization to business users throughout the business.
Using Data to Drive Value
As Maganza notes, data is often considered the ‘new oil’. “But it's only going to achieve that status if we prove that these efforts of gaining insights actually has an impact on the business,” Maganza says. To do this, Kohli recommends taking an investment perspective on data is key.
“If you really want the oil to be flowing through the pipeline, we need to be talking about investment. Otherwise, it’s not possible to scale. There’s no value capture going on,” Kohli explains. “It’s not about doing those flashy cool things that you read about in a magazine, it’s about driving action for the business.
Democratization of Data
People are still in the mindset that you need to go to someone within a central analytics team to get data and analysis to do your job. The pivot will be when everyone can use it.
We used to say, ‘If you want to build better quality cars, don’t make it the problem of the quality assurance department’,” Kohli recalls. When it comes to data, this could never be more true. Democratization of data throughout the business is critical. If anything, global workforces and customer marketplaces are demanding it at a rapid pace.
The roles of employees are also changing across functions, just as the role of the IT professional has matured a lot since its inception decades ago. Employees perform complex tasks as a part of their daily workflow. For a truly “AI-version” of the company, one of the tenants is providing employees access to data across the business.
As Kohli sums up, “If we truly want our company to be data-driven, and have an analytics and AI-centric company, this has to be everyone’s jobs, not just the people who have 'Data' in their titles.”