What you measure is what you can manage. In thinking about public goods in India, achieving a sound public policy framework in India, and appropriate checks and balances for providers, critically requires sound measurement of outcomes.
In the area of telecom, TRAI has started working on measurement of quality of service (QOS). As an example, look at the PDF file that they are putting out. I find it interesting, but not yet designed in a way that facilitates customer choice. When you're picking a mobile phone vendor in Delhi or Bombay, it is hard to read this file and understand which vendors are strong on QOS. In the area of electricity, a think tank named Prayas has embarked on measurement of the quality of service at a few locations in Pune. They have setup a few data loggers which generate realtime data for the mains voltage, and measure supply interruptions. They have released documentation, and a lovely google maps mashup which locates their data loggers and gives access to the information being captured (click on any of the balloons). Their email says:
For the first time in India, the ESMI captures supply interruptions data as well as voltage levels at the ordinary consumer location.
Poor supply quality (i.e. frequent supply interruptions and low voltage levels), is the most common complaint by electricity consumers and often results in consumers unwillingness to pay. Poor supply quality forces consumers to either invest in back-up devices such as stabilisers, inverters and generators or they suffer loss of productivity and inconvenience. Though recently efforts are being made to capture supply quality parameters, (e.g. CEA compilation of interruptions at 11 kV feeders in urban areas) there is still a long way to go for availability of reliable and comprehensive indicators of supply quality.
The Electricity Supply Monitoring Initiative (ESMI), by Prayas, is developed as a complement to such ongoing efforts to monitor electricity supply quality. This is a tool for consumers and regulators to get an idea of the ground reality and to increase the accountability of electricity utilities. For example, this will allow consumers to verify if load shedding is being carried out as per the regulatory commission's directive. Similarly ESMI data could be used to assess the impact of large capital expenditure (under projects such as APDRP or MSEDCL's infrastructure plan) on supply quality.
Currently data loggers are installed at three locations in Pune, and supply interruptions and voltage profile of these locations is available at http://prayas.icantrack.com. This site will be updated periodically and many more locations will be added in the next few weeks.
As an example, their Pune results reveal interesting and new facts:
Pune does not face any scheduled load shedding due to implementation of `Pune Model'. Under this arrangement local industries give the required relief to the grid by generating power through their captive power plants (using liquid fuel such as diesel). In spite of this as shown in the tables, Pune consumers fact ten to twenty sustained interruptions (i.e. interruptions of 4 minutes and more) every month and do not have supply for about eleven hours every month. As per Maharashtra Electricity Regulatory Commission (MERC) regulations, voltage for low-tension consumers should be between 225 volts to 255 volts. But as shown in the following tables, voltage levels in Pune are significantly below MERC norms. For example, even in central Pune (Deccan Gymkhana) voltage is often below MERC norms and for about 7% to 9% of the time is very low (i.e. below 195 Volts). This indicates that, apart from sufficient availability of power, proper maintenance and strengthening of local distribution network is essential to ensure good quality of supply. The electricity supply quality in rural areas is expected to be still worse. In the next few weeks ESMI will focus on capturing status of electricity supply quality in rural areas.
I'm a great believer in the importance of information in closing the loop and enabling superior public goods. What is not easy to figure out is the incentive structure for this information. This information has public goods characteristics, so what would work best is for a government agency to contract-out its production and public dissemination with tight integration between the public goods outcomes data and google earth. However, this would require sensible decision making and procurement on the part of the government agency. There is a bit of a chicken-and-egg problem here. A dysfunctional and non-responsive government agency would not even make this first step correctly - it might do nothing, or it might muck up the contract, or the contract might get awarded to the wrong team. Without a feedback loop from outcomes to citizens to policy, these mistakes might not get corrected.