Amid rabid competition in the retail space, businesses turn to machines for insights that let them one-up other competitors. Data, not emotion or instinct, steers the most effective decisions for supply chain, marketing or IT operations.
For organizations hoping to absorb the advantages of data analytics, Matthew Hartwig, associate director of product management, data infrastructure at Wayfair, proposes one counterintuitive change: saying goodbye to the standalone data analyst role.
"Every corporate employee at Wayfair is a data analyst," said Hartwig, speaking Thursday at NRF 2021. Wayfair embeds data analysis requirements in the job description for its corporate employees, and expects new hires to have skills or familiarity with tools such as Looker for data analytics.
Wayfair does hire data analysts, said John Costello, senior manager, corporate communications at Wayfair, in an email. "Matt’s intention in framing his answer this way was to emphasize the fact that data analytics is part of nearly every role at Wayfair," Costello said.
Spreading data analysis tasks beyond the traditional role of a data analyst signifies a desire to fuel data literacy throughout the company. But for businesses contending with how to most effectively leverage data analytics, the ideal model partners subject matter experts with tech-savvy employees.
"If you're not with the times and if you are not capable of analyzing a dataset, drawing conclusions and making a business decision on the other side, you're not a great fit for Wayfair," said Hartwig.
Under a hybrid data analytics model, advanced analytical solutions are owned by the business side, but implemented "by somebody who has specific technical training," said Igor Ikonnikov, research director at Info-Tech Research Group.
"If you don't understand business properly, you won't solve the problem," said Ikonnikov.
Modeling data skills
Businesses already know how critical a data analytics strategy is to their business, but often find challenges in implementing these capabilities throughout the company.
Organizations that make investments in building reusable platforms for data analytics will see their reliance on more traditional roles such as data developers or analysts fall, said Joe Antelmi, senior principal analyst at Gartner.
"Business users can focus on extracting insights from data, IT can specialize in building data platforms," said Antelmi.
As organizations gain business users who are capable of data analysis, they must mind the data silos and data quality issues that could arise, according to Antelmi.
"On the flip side, this is a novel and welcome change for many organizations where they have a desire to use analytics but they're facing analytics scarcity," such as an excess of data but a shortage of insight into that data, said Antelmi.
Organizations grappling with analytics scarcity face a choice: do they train subject matter experts in technical platforms or do they take an expert in statistical or probabilistic modeling and then teach them the business context? The fastest way to meet company needs in the analytics department is to pair together experts from both sides of the aisle, according to Ikonnikov.
But the maturation of data analytics tools does not herald an expansion of standalone data analyst roles. "I would expect that technology will become more business user friendly," said Ikonnikov.
Despite the lowered barrier of access to data tools, demand for roles in the data science family, such as data analyst, grew nearly 46% since 2019, according to a report from LinkedIn.
There's a compelling case for a data-driven approach to business decisions: Companies that are data-driven are 58% more likely to beat their revenue goals, though 41% of organizations struggle to turn their data into decisions.
Wayfair's move to pepper data analytics functions throughout the organization reflects a desire to "shake off the dust on these traditional data analytics offering processes and saying, what new way of delivering the platform can we deliver?" said Antelmi.
To enable a healthy data culture within an organization, companies must embrace trust in data, rely on advanced technology and make their business and technology decisions as tightly coupled as possible, said Ikonnikov.