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November 25, 2020

Over the last several months of the COVID-19 pandemic, industries globally have been severely impacted both in terms of revenue and operational efficiency. The utilities industry, however, has remained relatively untouched by the effect of this force majeure facing mankind. Clearly, we have become far too accustomed to the comforts of 24/7 power, running tap water, and clean sewage systems, considering them to be necessities and reluctant to give them up easily. However, while utility service providers themselves have not suffered from the global economic downturn— as evidenced in their balance sheets—end users have had to often bear the brunt of service disruptions and inflated bills. While utility services have improved significantly in recent years with better service assurance, incidents that are beyond our control, such as the pandemic, invariably bring with them major setbacks.

One such utility service that has been heavily shaken by the pandemic is electricity billing. The transaction between a utility, such as electricity, and its consumers revolves around the meter which monitors consumed units. Under normal circumstances, the modus operandi is for monthly electricity bills to be raised based on actuals. A large part, at least 80%, of utilities’ billing globally for low voltage (domestic) meter reading is carried out manually by the field workforce. In the event of non-availability of meter reading, such as during the enforced lockdown, utility services have had to resort to raising bills based on estimations. The methodology used to estimate could more accurately be termed as ‘guesstimating’ and is another story in itself.

Understanding utilities billing during the pandemic

In some instances, estimation rules were clearly put in place by regulators. In others, utility services relied on their own billing engine and business experience to raise estimated bills. Some of the provisions guiding estimation included — reflecting the billed units of the same month in the previous year or an average of the last three to six months or summer/winter averages, and so on. A few advanced utilities resorted to artificial intelligence (AI) and machine learning (ML) algorithms to arrive at a consumer-specific estimation rule. But how far can a machine estimate human behavior and consumption patterns, especially in a situation that has had no precedents, like the ongoing pandemic? How can machines that work by studying patterns, account for consumers staying at home 24/7?

Electromechanical meter readings are cumulative in nature. So, when utility services were able to resume meter reading after a couple of months, the generated bills included the undercharges of all previously estimated bills. This resulted in consumers receiving inflated bills after the lockdown period. Very few utility services were able to make accurate estimations during the lockdown period. Most missed the mark by a wide margin by undercharging consumers in units or slabs corresponding to those units in the event of no readings being taken during that time.

The fallout? A large hue and cry among consumers and an exorbitant rise in billing complaints, apart from outbursts in the press and social media. Some utilities had to withdraw their bills while others declared indefinite abeyance of payments. In a majority of these cases, however, the bills had been correctly tendered. In retrospect, what could utility services have done to avoid such a situation? Should they have billed consumers or refrained from it?

Two possibilities emerge: Utility companies could have stopped generating estimated bills. The immediate impact of this would have been a complete halt in cash flow. Consumer satisfaction, however, would have been higher, and concerns would have been limited to issuing clarifications and availing instalments. The other option would have been to increase the number of available channels for addressing consumer complaints. By proactively anticipating an influx of complaints, utility services could have put adequate mechanisms in place to better support consumers.

Is a win-win situation possible?

Irrespective of the route taken, however, it stands to reason that the consumer would still have been impacted. The truth remains that the pandemic only exacerbated an existing challenge, not created it. In fact, no billing system dependent on a human workforce would be capable of completely circumventing its associated challenges.

Ultimately, it is up to the utility service to decide what its main objectives are and act in accordance. If the aim is to reduce instances of non-billing, estimations and customer complaints would be inevitable. On the other hand, if end-user satisfaction is the goal, cash flow will be negatively impacted. The million-dollar question facing utility billing services today is – what is the way out of this conundrum? Can we not aim for optimizing both?

The answer is ‘Yes’! To find out more, keep watching this space for my next blog, which will delve into the foundation of automatic meter reading (AMR) and advanced metering infrastructure (AMI) for utilities.

Anupam Chakraborty is an Industry Advisor and Domain Consultant in the Utilities Business Unit at TCS. In his capacity as an advisor, he leads grid modernization and strategic initiatives of machine vision in the Utilities Business Unit. Anupam has over 26 years of operational, management, and consultancy experience spanning IT and electricity utility environment, electricity distribution, transmission, generation (including renewables and alternate sources), customer relationship management, commercial and financial functionalities and business enterprise development. He has worked in multiple USAID projects and smart initiatives in his earlier assignments.


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