Technology for MSMEs
Over the last few decades, the corporate world has witnessed challenges with many industry giants. This includes Reliance Group spearheaded by Anil Ambani, Jaypee Group, the debt of Essar, the Binani dynasty, the Bhushan’s, and Alok Industries, to name a few. It is difficult to fathom that such well-known business groups could go into such deep distress. When there are failures in such well-known and established businesses there are ripple effects across the entire ecosystem.
Such corporate giants hardly ever face total destruction and financial losses alone since many stakeholders also face the heat. Small and Medium Enterprises (SMEs) that conduct business with prominent industry players without thorough due diligence experience severe impacts when these companies go through financial troubles. A successful business is all about gaining steady profits. If an SME is caught off guard while a large partner company is about to come under colossal distress, the result would be catastrophic. However, with the advent of advanced digital technologies like predictive analytics, such dangers can be significantly mitigated or avoided completely.
What is predictive analytics?
Under the aegis of predictive analytics, machine learning and data modelling techniques forecast future trends and outcomes based on the currently available and historical data. These alternate sources of information can be evaluated in real-time with the help of AI/ML platforms to provide predictive analytics for businesses. Internalization of complex functions such as market research and technology innovation drains resources for small businesses. This is where SaaS-based analytics products come into the picture and democratize access for smaller businesses. With these technologies, SMEs only need to pay for what they consume without establishing separate infrastructure for generating insights.
Most SMEs depend on their conventional network system and relationships to make even the most complex business decisions. The lack of an adequate data system and the absence of appropriate technology to analyze can do more harm than good. However, by leveraging proprietary algorithms and risk detection tools, SMEs can assess potential risk intelligence. These insights equip SMEs to safeguard against possible distress and strategize reasonable steps to avoid socio-economical losses.
How predictive analytics help SMEs, other businesses
Swift data analysis: Maintaining data is not an easy task. SMEs that deal with huge piles of records, for them, data prepping, cleansing, identifying the right columns to segregate, and recognizing correlations are burdensome. While the self-generated data by SMEs is relatively small compared to big industry giants, it still enables them to gain notable insights to tailor products aligned with customers’ penchant and forecast sales by analyzing current market trends.
Regular business evaluation: Conventionally, trade is conducted by extending invoice credit for 30-60 days typically. Without a means to measure the payment capability of the buyer, businesses lose out on capital by conducting business with counterparties that take a long time to pay up or do not pay at all. Predictive analytics enable SMEs to make mindful decisions instead of simply relying on instincts or suggestions given by past relationships. A thorough business evaluation of the counterparty will help identify the right parties to do business with.
Comprehensive risk monitoring: Staying aware of your counterparty’s functionality can give you the power to predict looming issues. Even after the business association is done, it is vital to keep track of your partners. With the help of predictive analytics, SMEs can easily get oversight of their counterparts and forecasted information on how they may fare in the upcoming months in real-time.
Modern-age business discovery: Unlike large businesses, SMEs have limited resources, but predictive analytics can help them discover potential customers, vendors, and partners. On the back of these advanced tools, these players can own the narrative of their unique business journey. It will help them streamline prospective stakeholders to engage with. For instance, Walmart leveraged predictive analytics to forecast consumers’ buying behaviour. Similarly, OTT giant Netflix uses predictive algorithms to recommend content based on users’ digital footprint.
Moving forward
There are certain business segments such as customer prospecting, sales forecasting, and customer retention, where predictive analytics is thriving today. The wider area SMEs apply, the greater and more impactful is the result. Even before the pandemic, the world was already moving forward by leaps and bounds through the many possibilities of digital adoption and automation tools. Remember, the right technology can make or break a business, and predictive analytics has the potential to save their business against possible financial turmoil.
To know more about how ENIQUE can help your enterprise, drop us a mail at info@eniquesolutions.com for a free consultation.