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What is “Microvation” in B2B Ecommerce?

In a recent post on LinkedIn, I shared an article discussing Amazon’s recent patent for an “airborne fulfillment center” and how the culture at Amazon promotes innovation in a way that makes outsiders assume Amazon can make things like blimp-based warehouses actually happen. While the “big idea” innovations are the ones that grab headlines, an innovation culture makes companies equally as passionate about finding smaller, more focused ways to work faster, more efficiently, or with higher quality than before – even if it’s just incremental improvement.

These small, incremental innovations, or “microvations”, are key in product data work, which includes organizational structure, product attribution, images, descriptions – all information shown on a screen that helps explain and sell a product online. Design, implementation, and maintenance of product data has historically been a time-consuming and error-prone process due to the work’s manual nature. To better explain, I’ll discuss a few examples.

Examples of Microvation in B2B Ecommerce

Earlier in my career I ran a team responsible for ingesting large numbers of new products as they were added to our selection. With so many SKUs coming in, it was difficult to identify relationships (e.g. different sizes of a particular type of fastener that were all designed for the same application). At the time relationships between SKUs were identified and created manually, but I realized that it would be faster, easier, and more scalable to automate that process using product attribute data submitted by suppliers at the time the SKUs were loaded. Once we realized the value this could create to the company we filed for a patent on the process which was granted last year. Even though implementing new processes and tools to take advantage of will take time, we had to protect the idea quickly before someone else made it their own.

Another example of a microvation success stemmed from working with clients on ways to manage data for manufacturer part numbers (MPNs) in their databases. MPNs are notorious for being complex and in many cases involving atypical characters (e.g. hyphens, spaces, symbols) in addition to more conventional characters. Because humans tend to be inconsistent in how they work with data, MPNs often suffer from information degradation over time and they are often entered into databases inconsistently, increasing the chances of product redundancy. By leveraging research originally done on identifying duplicate records for people in databases, we used pattern recognition to identify the ways people typically modified MPNs to identify duplicate records in an automated way – speeding time to market for new SKUs.

An Innovation Culture that Celebrates Small Improvements

Both these examples highlight the key role microvations can have when working with product information. As most technologies that support product information are mature, using them lends itself to targeted and incremental improvements. Finding new ways to organize, classify, maintain, and optimize product data using algorithms and technology has led to new service offerings, tools that improve client results, and ways of doing more work faster.

The takeaway for businesses considering ways to promote innovation is to communicate with your teams that innovation doesn’t always need to be the next “big idea”. Valuable innovations can come from smaller, microvation improvements to existing processes or tools. By fostering a culture that values, rewards, and promotes small changes with as much support as the big ones, companies can find reduced costs, provide superior customer experience, and drive revenue that keeps them a step ahead of competitors (even if the competition’s warehouses are airborne).