Having data on number of pending cases does not tell anything about what caused the delays in the first place. If the delays in Indian judicial process have to be addressed, a ‘delay’ must be defined and measured.
The present system of measuring judicial statistics in India may highlight the magnitude of the problem of judicial delays; it lacks information which may inform court management on the ways to deal with it. In India, we only measure pendency: The total number of unfinished cases left at the end of the year. It is arrived at by adding the total number of new cases (in a year) to last year's pendency and subtracting the cases which have been closed. For example, the annual report of the Supreme Court notes that total pending cases rose from 59,272 to 60,938 between 2015 and 2016. While this gives some idea about the magnitude of the problem, it does not tell us how to solve it. When we see pendency go up, we can only conclude that the courts have been unable to keep up with their workload. This system has three shortcomings:
1. There is no definition of what constitutes delay in a case as opposed to total number of pending cases. Therefore, there is no actual measure of delay in the Indian court system.
2. There is no identification of the cause of the delay. We do not know what delay was caused due to the litigants asking for adjournments, the lawyers being absent, the court administration being slow, etc.
3. There is no attribution of delay to a party. It ignores the fact that there are multiple parties to every judicial proceeding: the plaintiff, the defendant and the judge. Any of the three parties may cause delays.
An ideal system to measure judicial delays would provide extremely granular data about the court. We would have all information about judicial processes and capture video of proceedings in a court. Such information would allow us to carry out time-motion studies of court functioning. Detailed statistics like that require a dedicated management system for courts which records every step in a judicial proceeding. Dedicated court management entities like the Her Majesty's Courts and Tribunal Service or the Administrative Office of the United States Courts produce detailed statistics of court functioning in their countries. We do not have such systems in India. This creates the problem of: How to measure judicial delays in a manner which helps policy analysis on judicial reforms?
A new approach to measurement
What we have in India, are case files. These are the official records of a judicial proceeding, kept in the court and with the litigants. Case files include all documents filed before the court/tribunal by all parties to the litigation, and all documents generated by the court/tribunal. One important class of documents in a case file are the interim orders. Interim orders are generated every time a case comes before a judicial officer. This gives us a glimpse into what happened in the judicial proceeding (called hearings) on the days it was presented before a judicial officer. Even if the hearing did not result in any judicial work being done, an interim order is generated.
In a recent working paper (Regy and Roy, 2017) we study individual case files, with attention to each interim order, to reconstruct what happened in each hearing of a case. We use the interim orders to determine if the hearings were failure or not. We define a hearing to be a failure if no judicial work was done at that hearing and no penalty was imposed on any party. If a hearing is determined to be a failure we try to determine two additional facts from the interim order for the hearing:
1. The party was responsible for the hearing failure.
2. A standardised reason for failure.
This system of measurement has advantages over the present system of measuring pendency. It determines the delay in individual cases without any need to imagine what time a case ought to take. Delays are calculated by the number of failed hearings and the time each such hearing added to the total time of the case. The system also provides the reason for delay and the party causing delays. This information can inform court managers and policy makers on strategies to reduce judicial delays.
One dataset
We deploy this measurement system to orders of the Debt Recovery Tribunal - III, New Delhi (DRT). A research team went through the case file of 22 decided cases of the DRT. For each case the following information was recorded:
1. The case name, type, and the party who had filed the case (lender or borrower)
2. Date of filing and final order (finishing the case)
3. Decision of the tribunal, which was standardised into: dismissed (withdrawn or otherwise), disposed, closed (as fully satisfied or with liberty to revive later)
4. Date for each hearing of the case.
5. Brief subject for the hearing and the next date of the hearing
6. If the hearing was a failure, then: which party was responsible for it, and a standardised reason for failure
This gave us granular data about a total of 474 hearings.
Preliminary findings
Of the 474 hearings, 274 hearings (about 58 per cent) were hearing failures. These failures accounted for more than half the time taken by the cases. We could reduce the duration of the average case by half if we were able to avoid hearing failures. The majority of delays are due to requests from the parties for more time to submit documents. Other common reasons include the absence of lawyers or of tribunal officers. Figure 1 highlights the standardised reasons for delays.
The other interesting finding is the person causing the delay. One would expect that borrowers would be interested in delaying cases to delay eventual recovery of dues through coercive means like auctioning off collateral. On the other hand, lenders would be interested in quickly finishing cases to recover dues. However, the data does not bear this out. Figures 2 and 3 identify the party causing hearing failure in the cases. Figure 2 identifies parties when the borrower has filed the case (borrower is plaintiff). Figure 3 identifies parties when the lender has filed the case (lender is plaintiff).
Surprisingly even when the plaintiff is the lender, the plaintiff is the party responsible for most number of hearing failures. Lenders here are financial institutions who are expected to have processes and systems to pursue defaulting borrowers in court, yet they seem to ask for adjournments at rates similar to borrowers who may not have experience in litigation.
Conclusion
Computerisation is seen as a panacea for judicial delays. The Supreme Court plans to move to a paperless system soon. The government had started a process of computerising DRTs in 1997. The National Institute of Smart Governance has been running a project on this since 2011. Yet, there is little information about the functioning of DRTs in the public domain or what are the reasons for delays in them. Computerisation, by itself, will not lead to better management of courts. We need a complete loop, which: Collects granular data of court functioning; analyses the information to identify causes of delays; changes court processes and legal rules (process re-engineering) to reduce delays; and goes back to collecting granular data to check for effects. In this, computerisation will play an important role in gathering information. But computers have no idea about which information is relevant and how to use it. This still requires human intervention and scientific enquiry.
Source: Understanding judicial delays in debt tribunals, Prasanth Regy and Shubho Roy. Ajay Shah’s blog. 22 May, 2017.