## Friday, September 11, 2020

### Introduction

A critical element of organisational planning is the ability to anticipate and manage risks. Many organisations worry about the risk of disruptions to their operations. They spend time and resources to anticipate such events, and put in place mechanisms to mitigate their impact. This is known as business continuity planning (BCP). It can range from keeping standby suppliers for raw materials, finding alternate delivery channels to reach customers, building redundancies along networks and so on. The objective of BCP is to ensure that business operations do not get disrupted.

Courts are an important part of the institutional eco-system of business. In times of general distress, like the one posed by the pandemic, courts are an essential service. As the state uses all the powers at its disposal to deal with the pandemic, judicial checks and balances are likely to be most needed. As businesses try to minimise their losses, disputes between economic actors are likely to increase. The role of courts to adjudicate disputes becomes more important in these times. An important question in this context is: are key institutions such as courts able to ensure business continuity?

In this article, we analyse this question in the context of the functioning of one of India's largest commercial tribunals, the National Company Law Tribunal (NCLT), in the post-Covid world. The NCLT's jurisdiction extends to matters under the Companies Act, 2013 (CA2013), the Insolvency and Bankruptcy Code, 2016 (IBC), and the Limited Liability and Partnership Act, 2008 (LLP Act). It hears a wide range of matters such as disputes between shareholders, enforcement actions against companies and their management, schemes of corporate restructuring, and insolvency proceedings. It would not be unfair to say that the NCLT's functioning likely affects the functioning of firms in the country.

India implemented one of the most stringent lockdowns in response to the pandemic. A near complete closure of all activities that were deemed non-essential commenced on 25th March and lasted till nearly the end of May. From June onwards, a phase-wise unlocking process commenced. In order to study the impact of the lockdown on the functioning of the NCLT, we constructed a novel data-set, drawing upon the daily cause-lists published by the NCLT.

### Data and methodology

Data

We use a novel data-set derived from the daily cause-lists published by the NCLT. A causelist is a list of cases that are scheduled to be heard in a courtroom. While causelists suffer from lack from standardisation, both in the template and in the manner in which data fields are populated, they are a rich source of information about court functioning. Table 1 provides the list of the fields that we used in our analysis. Some of these are original, that is verbatim from the causelist, while others are derived by cleaning up and organising the original information available.

Table 1: Causelist data

Field name Description

Date Causelist date
Bench/Court Bench name and court room number
CP/CA Unique case identifier
Case purpose Purpose of hearing
Remarks Post hearing remarks

We use causelists for the period from 1st February to 30th June for our analysis. In India, the lockdown started from 25th March and was subsequently extended till the end of May. However, from 20th April, a range of conditional relaxations began to be introduced. On 30th May, 2020, the Central Government effectively allowed a phasewise opening of economic activity outside containment zones with effect from 1st June, 2020. In line with this timeline, we divide our analysis period into three phases: pre-lockdown, lockdown and unlock (Table 2). The pre-lockdown phase allows us to observe the regular functioning of the NCLT. The lockdown and the unlock phases allow us to observe court functioning in the post-Covid world.

Table 2: Study period

Phase Dates Days of data

Pre-lockdown 1st February to 24th March 34
Lockdown 25th March to 31st May 31
Unlock 1st June to 30th June 22

The NCLT Registry issued several circulars and practice directions with regard to its functioning during the lockdown period. The first of such circulars, issued on 23rd March, 2020, suspended the functioning of the NCLT with effect from 23rd March, 2020 until 31st March, 2020. The suspension was subsequently extended until the end of the lockdown. During this time, all the benches of the NCLT were directed to schedule hearings for 'urgent matters' through video-conferencing on designated days of the week.

For our analysis period, from the NCLT website, we get data for 22 bench-court combinations. We use 18 of these, namely 6 courtrooms of the NCLT bench in New Delhi (including the Principal Bench), 5 courtrooms of the NCLT bench in Mumbai, 2 courtrooms for the bench in Kolkata, and one each for the benches in Bengaluru, Chandigarh, Cuttack, Guwahati and Jaipur. We exclude 4 bench-court combinations, 2 for Chennai, and one each for Allahabad and Kochi due to sparse causelist availability. Ahmedabad bench is excluded as no data is available.

Methodology

We use the input-output approach to analyse court functioning, where scheduled hearings are treated as inputs and outcomes of hearings as outputs. Matters that come to the NCLT often go through a cycle of multiple hearings before they are finally completed. The input-output approach assumes that the NCLT's objective is to hold hearings on substantive questions that arise before it in respect of a matter and dispose them of. In doing so, the court seeks to move the matter forward towards a timely completion. A hearing that results in disposal as an outcome enables this. Hearings that result in a next date being given, for whatever reason, extend the completion timeline. Regy and Roy 2017 have previously used the idea of 'failed hearings'(adjourned hearings) to estimate judicial delays in debt recovery tribunals. We apply this concept to estimate the productivity of the court in the aftermath of the pandemic.

The input-output approach allows us to measure effective court capacity as:

$Effective court capacity = Hearings scheduled x Disposal rate$

A limitation of this approach is that it does not take into account the quality of the order passed by the NCLT. Our analysis is restricted to the volume of hearings and the number of disposals.

### Input: volume of hearings scheduled

We find a sharp drop in the average number of daily hearings conducted by the NCLT during the lockdown period (Figure 1). In the pre-lockdown world, across all benches in our study, an average of 588 hearings were scheduled per day. This declined to 30 hearings per day during the lockdown period, a 95% decline. In the unlock period, the total hearings per day marginally increased from 30 to 41 per day. However, even this was a 93% decline from the pre-lockdown levels.

Figure 2 shows the location wise variation in the number of hearings scheduled. For each location graph, the red dotted line indicates the start of the lockdown period and the green dotted line indicates the start of the unlock period. The numbers on the top indicate the average daily hearings scheduled in each period.

Several interesting findings emerge. First, the bulk of the hearings during the lockdown period were conducted by benches in three locations, namely Mumbai, New Delhi and Chandigarh. Second, there is time variation in when courts started functioning during the lockdown. We observe that while courtrooms in Mumbai started scheduling hearings from 22nd April, the courtrooms in New Delhi started from 5th May onwards. Third, Mumbai, New Delhi and Chandigarh benches are also the ones that managed to ramp up capacity during the unlock period. Other benches have not, even till 30th June, built up a steady pattern of scheduling hearings.

The reason for the variation in the volume of hearings across locations remains a puzzle. We note that while the e-filing facility was available across some of the benches, with time, the litigants before the other benches were instructed to file their proceedings through an e-mail to the Registrar. The availibility of the e-filing facility does not explain the volume of hearings post lockdown. For instance, the Chandigarh bench, which was hearing cases all through this period, implemented e-filing only towards the later half of June. With Mumbai and New Delhi being the worst affected by the pandemic, the variation in volumes also cannot be attributed to the severity of the pandemic at a location. It is unclear then as to what has caused this location level variation and why some benches were able to resume functioning as early as mid-April while others could not do so even towards the end of June.

### Output: disposal rates

Table 3 gives us an overview of the outcome of hearings during the pre-lockdown, lockdown and unlock period. In the pre-lockdown period, while a large number of hearings were getting scheduled, nearly 82% of these resulted in a next hearing date being given. During the lockdown period, this changed. The disposal rate improved significantly, from 17.9% to 54.5%.

Several factors might explain the improvement in disposal rates in the post lockdown period. One possibility is that during the lockdown, since the NCLT was hearing urgent matters only, they had to be disposed of. The second is that the pre-lockdown scheduling of nearly 40-50 cases per courtroom per day, was unrealistic. It resulted in a few matters getting actually heard and a next date being given in the remaining. Since the number of hearings getting scheduled during the lockdown period were low, these matters were actually getting the attention of the court which resulted in an improved disposal rate. Finally, it is also possible that the manner in which courts have dealt with hearings in the lockdown period changed. They were less amenable to allowing re-scheduling.

The pattern of a higher disposal rate during the lockdown period continued in the unlock period. However, there was some decline in the disposal rates compared to the lockdown period (from 54.5% to 48.4%).

Table 3: Outcome of hearings (as % of period totals)

Next date For order Disposed Total

Pre-lockdown
Number of hearings 15,813 968 2,489 19,270
% of hearings 82.1 5.0 12.9 100.0

Lockdown
Number of hearings 373 26 420 819
% of hearings 45.5 3.2 51.3 100.0

Unlock
Number of hearings 432 52 354 838
% of hearings 51.6 6.2 42.2 100.0

* Disposal rate = percentage of hearings with outcome "disposed, dismissed, admitted or allowed" + percentage of hearings with outcome "For order"

### Estimating effective court capacity in the lockdown period

Table 4 brings together the input (hearings scheduled) and output (disposal rate) to give us a sense of the effective court capacity in the three phases. It shows that court capacity even in the unlock period is around 19% of pre-lockdown capacity. Table 4 suggests that the NCLT can adopt a very different mix of hearings and disposal from its pre-lockdown period to increase its overall output. For instance, at a disposal rate of 50%, even scheduling half of the pre-lockdown hearings will result in a higher effective capacity. However, this will require courts to analyse the process learnings from the post-lockdown period which resulted in higher disposal rates and apply them on an ongoing basis.

Table 4: Effective court capacity across the three periods

Phase Hearings (daily avg.) Disposal (%) Output (daily avg.)
($A$) ($B$) ($A*B\right)$

Pre-lockdown 588 17.9 105
Lockdown 30 54.5 16
Unlock 41 48.4 20

### Conclusion

The lockdown has reduced the output of an already overburdened justice delivery system. Our analysis of the NCLT output is one case-study that demonstrates this. The functioning of courts during the pandemic is in contrast with the functioning of the overall economy during the same time. By June, most sectors of the economy had resumed operations to a large extent. The manufacturing sector IIP had returned to 80% of its February levels. Railway freight traffic, cargo traffic at ports and air cargo traffic had come back to 88%, 86% and 61% of their February levels respectively. Even a hard hit sector, like airlines, had resumed aircraft traffic to 26% of February levels. By June, the employment rate had come back to 95% of its February levels.

Courts have been reasonably quick in transitioning to virtual hearings. The relatively higher disposal rate at the NCLT demonstrates that a combination of the electronic filing system and virtual hearings, is workable. Despite this, we find that the NCLT has not reverted to even 20% of its output in the pre-lockdown period. The output is much lower for a majority of the benches. This is likely to substantially increase the pendency at the tribunal.

An extended disruption in court functioning can adversely affect the enforcement of civil liberties, property rights and contracts. This can have a debilitating effect on the rule of law. While most of the discourse on court capacity in India focuses on the inadequacy of judges, significant gains can be made by process improvements at the NCLT. Several scholars and policymakers have highlighted the need for a deeper focus on the management and business process planning for courts and tribunals in India (for example, see Datta 2016; Datta and Shah 2015). The courts too have recognised this need time and again (example). A BCP is an integral part of the business proceess engineering of courts.

A silver lining to the devastation caused by the pandemic is that it has accelerated some important reforms. Renewed focus on process management at courts is likely to give us maximum bang for the buck.

### References

Regy, Prasanth, and Shubho Roy (2017), Understanding Judicial Delays in Debt Tribunals, NIPFP Working Paper Series, National Institute of Public Finance and Policy, New Delhi, India.

Datta, Pratik, and Ajay Shah. "How to Make Courts Work?" The LEAP Blog, 22 Feb. 2015.

Datta, Pratik, (2016), Towards a Tribunal Services Agency, Indira Gandhi Institute of Development Research, Mumbai Working Papers, Indira Gandhi Institute of Development Research, Mumbai, India.

The authors are researchers with the Finance Research Group. They would like to thank Ajay Shah for discussions and inputs on this article and Rahul Somani for developing the code for constructing the data-set.

#### 1 comment:

1. Interesting work, I think comparing within year changes might not be able to account for seasonal nature of such filings. I don't know if there is a seasonality in such filings but would be curious to find out and see trends from previous years. This obviously doesn't reduce the message being delivered through the blog about need of reform and lost productivity due to the pandemic.

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