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Retail Store Automation: Embracing Machines and Humans Alike

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Operations and retail teams are proving that you don’t have to sacrifice human interaction in order adopt retail store automation. Machine learning tools (like that of CB4) use computer algorithms to advance performance. In reality, automation is empowering human retail operations teams to connect more deeply than ever before with the people purchasing their goods. Through artificial intelligence, sales teams have unprecedented access to customer data, while operations teams can now target specific challenges affecting items with high local demand, creating additional revenue by focusing on what matters most.

A 2017 Pew Research Center Survey reports that Americans are about twice as likely to express worry about automation than enthusiasm for it. In fact 72% of the adult Americans Pew Research Center surveyed describe feelings of concern over technological advances in automation, rather than the 33% who report feeling optimistic about it. Nonetheless, a closer look at automation technology reveals that automation, by and large, bolsters human workers rather than competes with them.

 

Know that Most Jobs Are Becoming Only Partly Automated

Machine learning cannot be effective in a vacuum. In other words, machine learning tools perform best in the hands of human beings. In a July 2018 article for The New York Times, Noam Scheiber describes a trend in which most of the jobs affected by machine learning would become “partly automated rather than disappear altogether,” providing reassurance that retail store automation doesn’t mean neglecting human workers.

One example of a job becoming only partially automated is that of a retail buyer. Scheiber highlights the story of Nathan Cates, buyer at Bombfell, an online styling service offering boxed clothing delivery. While Bombfell relies heavily on algorithmic tools and an extensive digital data repository to guide buying decisions, there are simply parts of a buyer’s job that only a human can do. It’s Mr. Cates who must feel and examine fabric swatches and try on garments to ensure customer satisfaction.

But it’s not only the human touch that computers can’t replicate. Among most conventional retailers, employees are using automation to bolster human intuition, rather than replace it. Specifically, Scheiber mentions Arti Zeighami, head of advanced analytics and artificial intelligence for H&M. Zeighami describes how machine learning tools are “enhancing and empowering” human buyers and planners, backing up their gut feelings with data and additional insight.

Beyond the need for humans to use and enact change based on machine learning insights, there are certain things that machines just can’t do (for now). For example, negotiations with suppliers is something that only humans can finesse. Additionally, there are limitations to how many supplier relationships current machine learning tools can analyze.

 

Remember that Retail Store Automation Also Creates New Jobs

Although some jobs will be lost (or become less important and therefore compensated at a lower rate) as certain tasks become automated, it’s important to remember that the insights automation provides will also create new jobs. For instance, Scheiber reports that brands like Bombfell and Stitchfix are hiring “a growing army of human stylists” to receive recommendations from algorithms about items that may work for customers.

As such, additional human workers are needed to act to check and balance machine learning tools. Humans can ask customers what they want and make notes of it, serving a crucial role as interpreter between human customers and machines. These stylists ultimately decide for themselves what to ship out, given their more nuanced understanding of what their customers are looking for.

 

Set Employees Up for Machine Learning Success

Apparel brands like Stitchfix have adopted machine learning tools to boost sales and make better, more informed decisions quickly. In order to utilize the tools, you’ll want to learn how to effectively on-board employees and overcome any concerns they have regarding automation in the workplace.

According to Rebecca Knight’s article for Harvard Business Review, the process of helping your team successfully adopt new technology begins far earlier than you might think. Knight suggests selecting new technology wisely by asking your retail and operations teams what tools they need to boost their functionality. Make sure you’ve selected the most intuitive system you can, i.e. one with a user-friendly dashboard. You can even have team members do trials of various technologies before selecting one (most technologies, like CB4’s, offer demos for this purpose).

Once you’ve honed in on the right tool for your business, plan out a few different training sessions customized to meet the unique needs of people on your team. For example, a tech-savvy employee might be happy with an online training session, while other team members might benefit more from personal coaching.

You’ll want to lead by example, showing your team how you’re using the technology to improve your performance. It also makes sense to get team influencers, those who have the most sway and visibility in your organization, to do the same. If you can show why machine learning is an improvement to what they had before, your team will be well-poised for success.

Teaching employees how to use the technology and lauding its capabilities may not be enough. Make technology routine by asking for weekly updates on numbers, raising the cost of not using the technology. Simultaneously, draw attention to those employees seeing technology-related successes.

 

The Takeaways for Your Business

In determining whether retail store automation and machine learning is right for your business, you’ll want to look the most pressing obstacles your business is facing (with feedback from your team) and focus on technology that rises to those specific challenges. Be bolstered by knowing that the technology is seeking to help, not replace human workers. In fact, with the aid of automated tools, you will probably find that your employees are better poised than ever before to serve your customers.

Finally, be deliberate in your plan for implementing new technologies in your workplace. Strive to cater to the unique needs of each employee, and set in place a plan not only for the initial training, but for long term success. Adopting a positive outlook toward retail store automation and machine learning tools will allow your team to flourish as adoption becomes prevalent.

Explore our blog to read more about things like Blockchain in Retail and How to Sell Absurd Amounts of Designer Denim. If you’re curious about how machine learning can help improve store operations, read more here and here.

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