Why Retailers Struggle to Embrace Data Science

Retailers Struggle To Embrace Data Science

Meet the Team Cognira Series

It’s no secret that advanced science technologies are becoming critical for business success (yep, even for retail). With the power of data science, retailers have the opportunity to enhance marketing strategies, operations, financial performance, and of course, stay ahead of the competition. However, despite all of these benefits, many retailers still struggle to operate as a data-driven organization.

In our fourth installment of the Meet the Team series, Linda Whitaker, VP of Science Delivery at Cognira, shares 3 reasons why retailers struggle to fully embrace data science into their business.

Meet Linda

Linda Whitaker
Linda’s journey with data science started at Eckerd College, a liberal arts school, where she received her undergraduate degree in mathematics. She later went on to get her PhD in operations research at The Georgia Institute of Technology. Though a career in data science research was on the table, she wanted to step away from theory, and apply her knowledge in the working world.

Since that decision, Linda has been involved in many different startups. One of her first was Retek, a company that gave her the opportunity to focus her time in science development and product management (and also where Linda met many of Cognira’s employees today). She then moved on to becoming Co-Founder of Quantum Retail, where she served as Chief Science Officer. Finally, Linda joined forces with Hatem Sellami and other former Retek coworkers and made it to Cognira as VP of Science Delivery.

 

Despite Linda’s already impressive academic and professional background, she is also a writer of techno-thrillers (Check out her first novel, The Crucible of Steele!!!). As Linda puts it, by day she plays with numbers, by night, with words.

3 reasons why retailers struggle to fully embrace data science

1. Data science and analytics is not part of their culture

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To successfully adopt big data and advanced science technologies, businesses need to have a data-driven culture. This means having sustained support from executives, laid out objectives with strategic goals, and a dedicated, multi-faceted team (Check out our blog on creating a data science team in retail here).

Today, many retailers struggle to make analytics part of their culture because they are just looking for quick data fixes, gatekeep data from employees out of fear of sharing sensitive information, and switch from system to system each time leadership is shuffled.

If you really want to excel in data science, it has to become part of your company DNA!

2. Retailers struggle with bad past experiences

retailers struggle
Bad experiences can leave sour tastes in our mouths. When it comes to data science, bad past experiences typically happen when companies don’t ensure the new data science aligns with their people, processes, and systems. For example, retailers may:

Data, science, technologies and business processes need to align. Solutions that do not adhere to operational constraints or account for downstream systems usage can be suboptimal at best, downright harmful at worst.

If the system is a black box, gives confusing results and/or throws many exceptions that users have to override, they will quickly lose confidence. The system must make life easier for users, not harder.

It can be hard to measure benefit, and this cannot be an afterthought. Good data science can get thrown out and bad can stay in without consistent and continual performance measurement.

3. Finding data science experts you can trust and rely on

retailer experts
It’s hard to keep up with new science and technologies and especially difficult to find a crew of experts to help you along the way. Here are a few reasons why:

Typically, there is no consistent language or definitions around analytics/data science/big data.

Vendors are anxious to boot out competition, not always forthright. Additionally, they typically do not speak retail and may not solve a problem as the business wants it solved.

Technology is a moving target, making technology and data science expertise hard to find, and even harder to retain. (To learn more about technology advancing, check out one of our blogs on the analytics evolution and its impact on retailers).

Takeaway

Investing in data science allows retailers to better plan and operate their business and connect with customers. However, without making analytics part of your company’s culture and investing proper time and resources into the adoption process, it can be extremely challenging to have a successful experience.
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About Cognira

About Cognira

Cognira is the leading artificial intelligence solutions provider for retailers. Cognira is passionate about helping retailers unlock valuable, transformative business insights from their data.

We know retail. We love data.

To learn more, check out our website at cognira.com or contact us today to get started. 

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