An estimated ~2 crores or ~20% of all workers employed by Micro, Small and Medium Enterprises (MSMEs) are at risk due to the COVID-19 pandemic and our response to the pandemic. MSMEs in 8 states / union territories are especially vulnerable. Why? How? Let’s break it down.


On the 13th of May, the central government announced 6 sweeping reforms / stimuli for MSMEs in India worth Rs. 3.7 lakh crores (~US$ 50 billion). Only 15% of that was additional cash, but all in all, it was still staggering. And exciting.

But, only 7% of all MSMEs (as defined before these set of reforms) are covered directly by these reforms. To be fair, all MSMEs are eligible for the 50k crore fund of funds (~US$7 billion). But, there will be a screening process based on “potential” and “viability.”

All in all, it is essential that we isolate, address and track those states and areas in which MSMEs are the most vulnerable, and ensure they are getting all the support they need to first survive, and then thrive.

This is an attempt at a macro-level analysis to do just that.

Sizing Up The MSME World

Firstly, there 6.3 crore (63 million) MSMEs in India. For perspective, that is pretty much the population of the UK. We have that many small businesses. And this reform might not be covering a significant piece of the pie. But, as mentioned earlier, this only directly address 47 lakh MSMEs — that is just 7% of all MSMEs.

Secondly, MSMEs contribute ~30% of India’s GDP and employ about 11 crore workers (110 million). That is the population of Mexico, again, for perspective. MSMEs are over represented in urban areas with 49% of all MSMEs located there as compared to an overall urban population of 31%.

And lastly, only about 15%-20% of these MSMEs are formally registered with the government. Not great, but the new registration program was launched in 2015 so it is still generally new.

Which States Are Highly Vulnerable? Rural Areas Or Urban Areas?

Based on the MSME Vulnerability Score*, urban areas of Delhi are the most vulnerable for MSMEs. This is mainly because Delhi is in its entirety a COVID-19 red zone. This has brought the entire economy there to a halt. Almost 90% of all workers work either in fully closed or partially closed sectors, and 38% of all workers are employed by MSMEs, above the national average of 30%. Chandigarh is also in a similar predicament.

West Bengal MSMEs are also at risk. Only ~3% of them are registered (versus the 15% national average). Unemployment there increased from 6% in January to 17% in April. Tamil Nadu should also be tracked carefully — not only are COVID-19 cases there skyrocketing, but unemployment has also skyrocketed there from 2% in January to 50% in April.

Uttar Pradesh and Kerala could also be at risk. They both have a high number of informal MSMES with increasing unemployment.

Despite not having any COVID-19 red zones, Puducherry is highly dependent on MSMEs. ~44% of the all employees work for MSMEs there and unemployment catapulted 75 percentage points from ~1% to ~76%.

Urban areas are more vulnerable than rural areas mainly because of the concentration of COVID-19 related red zones brining the economy to a halt.

~33% of India’s population live in COVID-19 red zones. The economy is barely functioning in those areas. About 50% of all workers in India are working in fully or partially closed sectors. Taking that into consideration, about 20% of all MSME employees (~2 crores) are at economic risk. This means that there is a high chance they might get laid off, furloughed, or have to take pay cuts because of the sheer inability of MSMEs to function at any sustainable scale.

These new reforms are a ray of hope. Execution is going to be vital. And execution without measurement is like putting a patient on a ventilator without tracking any of their vitals.

Let’s be as intelligent as we can as we try and mitigate the pain.


How did we calculate the MSME Vulnerability Score?

We devoured a ton of economic data from many sources and isolated the most important factors based on how COVID-19 was unfolding. 

This is how we calculated the score:

  • We isolated 6 of the the most pertinent indicators based on availability and prevailing stream of research / thinking.
  • We bucketed them into four overarching buckets and weighted each metric on perceived importance towards economic vulnerability. Importance was based on prevailing evidence, logic and reason (“Importance”).
  • We assigned a confidence level (1% to 100%) to each metric based on how good and recent the data was (“Confidence”).
  • Multiplying Importance and Confidence gave us our metric multiplier, or effective weight (“Multiplier”).
  • We then assigned a “least vulnerable” and “most vulnerable” value to each metric based on evidence, logic and reason, using minimum and maximum values as a basis.
  • We normalized (range-scaled) the metrics to remove any differences in the size of the metrics.
  • We then multiplied the normalized metrics with the multiplier to give us an independent score for each state.
  • We then calculated the worst possible score and took that as the denominator to calculate the vulnerability score as a %.
These are the metrics we identified and the weights associated with them (sources further down):


We scoured the world wide web for information and were lucky to happen upon good sources (each source is linked):

For any questions / concerns, please do not hesitate to contact us.