Analytics Everywhere: Building a Business-Led Data and Analytics Strategy

Data Science Innovators Conference 2023Analytics Everywhere - Building a Business-Led Analytics StrategyWatch the full session · 18 min

In a session at the Data Science Innovators Conference 2023, Selma Dogic, senior manager of the Analytics Center of Excellence at Carter's, laid out recommendations for building a business-led data and analytics strategy. Her talk, "Analytics Everywhere," covered how to win champions, tie analytics to corporate goals, democratize data and embed machine learning into daily workflows. Dogic said her point of view comes from time in public research and academia, followed by corporate work on both the business side and as a liaison to IT.

Why does data and analytics strategy matter now?

Dogic said organizations are producing and consuming more data than ever, and that shifts in consumer, business and human behavior are moving quickly. In her view, every leader is "data inspired" to some degree because of disruptions such as COVID and labor market swings, but the ones who build data and analytics into their business strategy are set to take market share.

She pointed to the release of ChatGPT as the biggest recent disruptor, because it put generative AI in the hands of the masses and induced competition among technology providers. She noted that she used a new content-generation feature in Canva to build her own slide deck, which she said gave her time back and ended the writer's block. She called the moment "the space race of our generation." She also cited market projections for e-commerce, cloud and generative AI, though the captions for some figures were unclear.

How do you drive adoption of an analytics strategy?

Dogic said there is no data and analytics transformation without a cultural shift, and that people need to be bought in. Her first recommendation is to find champions: cross-functional leaders with high influence who are already adopting the change. Teams then incorporate analytics into their workflows and use those champions to engage users at every level.

That, she said, is the idea of analytics everywhere: incorporating analytics into every part of somebody's daily workflow, at every level of user.

Why must analytics benefits be quantified?

Dogic warned about a fallacy she said data leaders often fall for. "Data is not the strategy and analytics is not the benefit," she said. The strategy has to be tied to the corporate strategy, with benefits that are clear, measurable and actionable.

Her example: if a company wants to improve revenue by adding more products to a customer's profile and builds machine learning models for product recommendations, the recommendations must be actionable by people in the organization. Without quantifying the benefit, she said, teams fall short on outcomes.

What does democratizing data and analytics look like at Carter's?

Dogic said most organizations run on a few key data sets grouped into a few domains. At Carter's, a retailer, those are sales, customers, inventory and supply chain. It "boggles my mind," she said, when they are not easily accessible to employees making daily decisions.

She said results should be repeatable and certifiable so analysts can tie their analysis back to certified numbers. Carter's uses federated governance, with business teams empowered to own analytics and reporting, supported by the BI team and a data engineering team in her center of excellence. The key data sets are certified for business users through what she called golden bucket certified views.

What are embedded and augmented analytics?

Embedded analytics, Dogic said, means integrating analytics into business applications and decision tools. At Carter's that mostly happens through dashboards, and it is also how leaders consume machine learning predictions and forecasts. She said it should not be "dashboards for dashboarding's sake," and that the aim is for leaders to consume insights as routinely as they read email. She listed better visibility, faster decisions, higher productivity and better adoption as benefits.

Augmented analytics, she said, uses AI and machine learning to enhance traditional tools so average business users get advanced capabilities without data science or statistics skills. Examples included automated data preparation, predictive analytics inside the tool, and visualization recommendations in Tableau, which Carter's uses. She closed by saying that in a new era, teams should not spend 80 percent of their time sourcing and transforming data.

What is next from AI Connect?

AI Connect hosts sessions on analytics strategy and data leadership year-round. The 2027 schedule includes 24 free live webinars, listed on the webinars page, and COLLIDE 2027 takes place Wednesday, October 13, 2027, at the Sandy Springs Performing Arts Center in Atlanta; see COLLIDE. Registration is coming soon.

Frequently asked questions

What is analytics everywhere?

Dogic described it as incorporating analytics into every part of a person's daily workflow, at every level of user.

Why isn't analytics a strategy by itself?

She said data and analytics must be tied to the corporate strategy with benefits that are measurable and actionable.

What is embedded analytics?

Integrating analytics into business applications and decision tools, which at Carter's mostly means dashboards that carry machine learning predictions and forecasts.

What is augmented analytics?

Using AI and machine learning to enhance traditional analytics tools, for example automated data prep and predictive features, so average business users get advanced capabilities.

This article is based on remarks by Selma Dogic, Sr. Manager, Analytics COE, Carter's at Data Science Innovators Conference 2023 on April 12, 2023. More coverage: More AI Connect Events.

Filed under: AI Strategy & ROI, People, Culture & Leadership