msme

By Soumendra Mohanty 

Technology for MSMEs: Accounting for 70 per cent of all employment, 99 per cent of companies, and nearly 50 per cent of global GDP, MSMEs are a key economic artery for almost every nation on the planet. However, the small size and limited resources of most MSMEs have traditionally made it difficult for them to access enterprise technology and implement digital transformation at scale. In fact, less than 20 per cent of MSME digital transformation initiatives are successful. But all that is quickly changing. 

MSME digital transformation landscape 

In the past, digital transformation for MSMEs has largely been viewed as a customer acquisition tool that helped them scale faster and access new markets. But now the rapid acceleration towards digital during the pandemic has helped even the smallest retailers transform their businesses. They can access analytics dashboards for critical insights into customer behaviour, inventory management, supply chain metrics, and more, via new offerings in AI and predictive algorithms by digital service aggregators. The real-time insights they offer have allowed MSMEs to deliver increased personalization and tailor their portfolios to the needs of the quickly evolving consumer.  

Lest they be left out, IT vendors are also showing renewed interest in the MSME market, launching low-cost service and product tiers tailored to the needs of emerging businesses. But I believe that the mass-market adoption of SaaS services will be the tipping point.  

Pay-as-you-go is the game-changer 

Having cut its teeth on enterprise customers over the last two decades, the SaaS model is now being rapidly rolled out and optimized for MSMEs. Shared environments and API-based microservices architecture have reduced the overall IT spend, and MSMEs now have on-demand access to business software without the expensive licensing costs. Launching a new customer acquisition channel, integrating a digital payment gateway, implementing a fraud detection system, or adopting a CRM has become a matter of a few clicks and a relatively minimal monthly investment.  

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The result? Small businesses can now unlock new operational efficiencies, evolve new stakeholder experiences, and accelerate go-to-market cycles. AI and data science tools have been exceptionally useful in enabling firms to quickly derive insights from previously cluttered and unstructured customer data pools. Unshackled by legacy systems and business rules, technologically savvy MSMEs are increasingly being viewed as innovation pioneers, pushing the experimental edge ahead of larger enterprises.

Adopting AI while avoiding pitfalls 

For many MSMEs, existing ML models should be sufficient to meet their initial needs as they partner with specialized AI or data science vendors to outsource data processing. But as data collection and analytics tools grow, MSMEs will need to create in-house data models and data science teams that are customized for their business. One cost-effective option is to upskill and repurpose existing IT talent toward the challenge of data processing, while strategically filling larger skill gaps with new hires.  

Developing a holistic approach to AI adoption is also vital. In my experience, most MSMEs tend to be consumer-focused when it comes to technology adoption, at the expense of the larger business ecosystem. Without creating visibility across the value chain for the service providers and partnerships that support their business model of being uniquely B2B2C, MSMEs run the risk of repercussions to the customer experience. And in a world where CX benchmarks are high, a slew of irate customers can rapidly break a small business. 

Another challenge is data availability. With a small customer base and operational footprint, MSMEs and startups need to have a clear agenda for acquiring the right data to fuel their AI modules. The complexity occurs when businesses have to dig deeper to understand the context behind their data and ensure they are establishing the right kind of Ops practices around them. Most SaaS models come with in-built AI/ML Ops services but deploying one that is tailor-made for your business will ensure it is generating the insights you need. 

The future of AI adoption across MSMEs 

From sentiment analysis, customer onboarding, and smarter chatbots to automated cybersecurity, content management, and credit and risk assessments – the number of use cases for AI in MSMEs is growing. 

Across industries ranging from retail and banking to healthcare and insurance, AI and ML technologies are rapidly driving up efficiency, productivity, and customer satisfaction. In FinTech, for example, AI and alternative data are being used to create new credit models and deliver personalized financial products.

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From every vantage point, it’s clear that AI is truly the great leveller of this decade, enabling smaller businesses to successfully compete with global enterprises. And as the infrastructure for digital ecosystems continues to expand, MSMEs that have a clear AI and data science strategy are likely to thrive and drive better outcomes with their innovation initiatives.  

With AI becoming all-pervasive in the rapidly growing and competitive MSME market, the future of AI adoption seems promising. MSMEs will have to think deeper about what AI can offer them and their customers in a saturated world. The real differentiator will be in making AI human-centric in design across touchpoints. Factoring in explainability and bias will help MSMEs build hyper-personalized offerings and gain the trust of the customer, now and in the future. 

Soumendra Mohanty is the Chief Strategy Officer & Chief Innovation Officer of Tredence. Views expressed are the author’s own.

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