Could Hardware Accelerate Software Adoption In Retail?

Strategic advisor at Blue Yonder.

Software in the form of artificial intelligence (AI) and machine learning (ML) solutions is about to become a whole lot more attractive to the retail space. Ironically, it may just be hardware that secures this smart future.

When people look at their iPhone, do they see a piece of hardware or software? The answer is probably the former, despite it being the software that makes our lives more connected, seamless, manageable and tech-driven.

What the iPhone really represents is the perfect harmony of hardware and software. One element is a marketable object—a physical, tangible unit that so many people can’t live without. The other element (the software) is what makes that unit so in-demand and so successful. In essence, it is the software that provides the value but the hardware that seals the deal.

This blend of hardware and software has become more pronounced in recent years, with the iPhone a perfect example of how the two worlds can manifest in a single object. However, there are countless examples in industry of how this symbiotic relationship can also work across separate but connected devices to elevate digital transformations.

Much is made of the role of big data, for example, and the conversion of insight into actionable strategy. But more and more often, that data is being generated by physical pieces of equipment. Especially coming out of the Covid-19 pandemic, we see a lot of physical workspaces relying on sensors, cameras and security devices to help generate data on peak times, workplace management or health and safety.

Critically, this development could prove to be of huge benefit to software developers in the coming months and years. All too often, decision-makers are resistant to applications and algorithms that could improve their operations and risk management processes. This is often because it’s not a visible concept. They have to rely on physics, mathematics and expertise beyond their own remit. However, hardware is much more conceivable. In a lot of cases, C-suite members are more likely to trust a connection between hardware and software systems than they are a SaaS provider simply integrating a piece of a software kit.

They know hardware—they’ve used it and trust it.

For AI and ML, the role of hardware is critical. By connecting these two dots, IT decision-makers are realizing the true strength of digital connectivity. In this vein, despite all of the focus on software as an operational game changer, it could be hardware that ignites the transition to smart companies, factories and stores of the future.

End-To-End Visibility

The relationship between hardware and software may be best epitomized by the retail sector over the coming years.

Across the supply chain, in and out of distribution centers, and either to stores or straight to people’s homes, inventory management has never been more complex amid the rise of e-commerce and omnichannel fulfillment.

Retailers not only need to know the volume and whereabouts of stock at any one time, but they then have to be flexible enough to respond to consumer demand in real time as well. Visibility is key, and manual guesswork around optimum procurement levels simply doesn’t cut it anymore.

ML has therefore become critical to establishing a more accurate forecast of what items are needed, where and when. This calculation derives from data to make the latter stages of that procurement process more seamless, less labor-intensive, more efficient in terms of prospective waste, and customer-serving in terms of stock availability and fulfillment choice.

However, picking up on the labor and accuracy strands of that benefit rundown, there is still an element of risk when that data is being manually inputted to begin with.

The role of automatic cameras in warehouses, for instance, can facilitate the monitoring of volumes automatically and in continuous real time. The development of smart shelves to gauge weights and monitor stock levels in that way have also come a long way over the past year. Again, the resultant data can then feed into the AI software to ensure complete accuracy, end to end.

Smarter Than Ever

You can almost hear the cries of “robots taking over” at the thought of another manual task being digitized. But yet again, this is an opportunity for retailers to make better use of personnel rather than to release them entirely.

And to be blunt, the benefits of a completely connected procurement function are too significant to ignore. AI feeds off data and is therefore only working to its optimum capacity if that data is accurate. As experienced as they may be, humans will always be more liable to make mistakes when it comes to this data entry. By taking that pressure away from them, both employees and employers will come out the other side knowing that neither products nor money is being wasted when it comes to audit time.

What this notion of a smart store or smart factory has done, as a result, is elevate the AI proposition as a whole. Decision-makers may still be adjusting to the idea of algorithms top-trumping their experience. But they do respond positively to upshots of saved time, improved labor efficiency or better cost-effectiveness.

Hardware in the form of cameras, sensors or even reimagined stalwarts such as factory shelves are comprehendible. They’re familiar.

By showcasing how these recognizable units are a facilitator of AI solutions, the latter become more attractive by association. SaaS providers are no longer just trying to sell a solution. They’re selling a complete transformation of customers’ supply chains, with outcomes they’d always be attracted to and with the help of equipment they already know.

Inadvertently, the conclusion that providers and retail as an industry are working toward is a completely digitally connected supply chain.

As a result, the retail sector is about to become smarter than ever. And software may just have hardware to thank.


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