ML can help SMEs gain efficiency, operational visibility and trust

RECENTLY, machine learning (ML) has transitioned from a technology to a solution, and can help small- and medium-sized enterprises (SMEs) decipher data right out of the box.

Companies that capture enormous data about customers and users in physical and digital environments can finally tap into those repositories to create intelligent insights using ML-powered solutions.

Since a lot of these solutions are offered as a service (SaaS), they’re affordable and provide SMEs with a fighting chance against larger organizations that are investing heavily in customized digital-first solutions to beat the competition.

For example, despite lacking the scale of some of the larger competitors, small-scale manufacturers using ML might be able to fine-tune their processes and drive efficiencies to provide great production value to customers — at competitive prices.

Why machine learning is a game changer

In the digital world, efficiency, operational visibility, and trust are incredibly important. Organizations that fail to provide these tend to lose out to competitors.

ML levels the playing field for small and large organizations because it not only helps achieve efficiency as we’ve seen previously, but also helps provide operational visibility and earn the customer’s trust.

Most organizations collect gigabytes of data every day but don’t really put it to good use. According to a survey cited by a recent Harvard Business Review article, 72 percent of organizations have yet to forge a data culture, 69 percent report that they have not created a data-driven organization, and 53 percent state that they are not yet treating data as a business asset.

What this means is that a large number of businesses in the world are not using data to predict the future state of their operations.

As a result, SMEs that use ML to gain visibility into their future will find it incredibly rewarding — now is the time for them to make the most of this opportunity.

Once organizations gain visibility into their operations, they can provide customers with accurate answers about delivery schedules and pricing — because they now have an in-depth understanding of their business which translates into insights that can support customer’s questions about pricing and supply.

At the end of the day, the reality is that ML provides incredible opportunities to all kinds of businesses, and with ML-powered solutions becoming more affordable as a service, the technology can provide significant advantages to CX managers and operations professionals.

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