Technology for MSMEs: The internalization of complex functions such as market research and technological innovation drains the resources of small businesses. This is where SaaS-based analytics products come in and democratize access for small businesses.
By Meghna Suryakumar
Technology for MSMEs: Over the past few decades, the corporate world has faced challenges with many industry giants. This includes Reliance Group led by Anil Ambani, Jaypee Group, Essar Debt, Binani Dynasty, Bhushans and Alok Industries to name a few. It is hard to imagine that such well-known business groups could fall into such distress. When there are failures in such well-known and established businesses, there are ripple effects throughout the entire ecosystem.
These corporate giants almost never face utter destruction and financial loss alone, as many stakeholders also face the heat. Small and medium-sized enterprises (SMEs) that do business with leading industry players without thorough due diligence face severe repercussions when those companies experience financial difficulties. A successful business is all about making regular profits. If an SME is caught off guard while a large corporate partner is about to suffer colossal distress, the result would be catastrophic. However, with the advent of advanced digital technologies such as predictive analytics, these dangers can be significantly mitigated or avoided altogether.
What is Predictive Analytics?
Under the umbrella of predictive analytics, machine learning and data modeling techniques predict future trends and outcomes based on currently available and historical data. These alternative sources of information can be evaluated in real time using AI/ML platforms to provide predictive analytics to businesses. Insourcing complex functions such as market research and technology innovation strains the resources of small businesses. This is where SaaS-based analytics products come in and democratize access for small businesses. With these technologies, SMBs only have to pay for what they consume without establishing a separate infrastructure to generate information.
Most SMBs depend on their conventional network system and relationships to make the most complex business decisions. The lack of an adequate data system and the lack of appropriate technology to analyze can do more harm than good. However, by leveraging proprietary algorithms and risk detection tools, SMBs can assess information about potential risks. This information enables SMEs to protect themselves against possible difficulties and to develop reasonable strategies to avoid socio-economic losses.
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How Predictive Analytics Helps SMBs and Other Businesses
Quick data analysis: Data management is not an easy task. SMBs who deal with huge stacks of records, for them, preparing data, cleaning, identifying the right columns to separate and recognizing correlations is tedious. Although the data self-generated by SMBs is relatively small compared to the big giants in the industry, it still allows them to obtain notable insights to tailor products to customer inclinations and forecast sales by analyzing current market trends.
Regular business review: Traditionally, the trade is made by extending the invoice credit for 30 to 60 days generally. Without a way to measure the buyer’s ability to pay, businesses lose capital by dealing with counterparties that take a long time to pay or don’t pay at all. Predictive analytics enables SMBs to make informed decisions instead of simply relying on instinct or suggestions given by past relationships. A thorough business assessment of the counterparty will help identify the right parties to do business with.
Full risk monitoring: Staying on top of your counterparty’s features can give you the power to foresee impending issues. Even after the business association is over, it is essential to keep track of your partners. With the help of predictive analytics, SMBs can easily get peer monitoring and forecast information on how they might fare in the coming months in real time.
Enterprise Discovery in the Modern Era: Unlike large enterprises, SMBs have limited resources, but predictive analytics can help them discover potential customers, suppliers, and partners. Thanks to these advanced tools, these actors can appropriate the story of their unique professional journey. This will help them rationalize potential stakeholders to engage with. For example, Walmart has used predictive analytics to forecast consumer buying behavior. Similarly, OTT giant Netflix uses predictive algorithms to recommend content based on users’ digital footprints.
There are certain business segments such as customer prospecting, sales forecasting, and customer retention, where predictive analytics is booming today. The more SMEs in the region apply, the more important and impactful the result. Even before the pandemic, the world was already moving forward in leaps and bounds with the many opportunities for 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 from possible financial turmoil.
Meghna Suryakumar is the founder and CEO of Crediwatch. The opinions expressed are those of the author.
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