Recent research and experiences from utilities all across the U.S. reveal that water demand per account is generally declining. For many utilities, this leads to a total demand decline despite an increase in the number of customers. Lower water sales equates to lower revenues.
Exasperating the issue is the fact that while the vast majority of utilities’ costs are short-term fixed, the majority of utilities’ revenues are variable, obtained from the volumetric commodity charges that are based solely on the volume of water sold to the customers. For example, in three medium sized utilities in North Carolina, revenues from variable charges accounted for 70-90% of all customers’ charges. As customers cut back their consumption – which is generally what they are doing now – utilities’ revenues decline significantly but the costs do not, risking net revenue shortfalls.
A utility’s revenues are therefore inextricably linked and vulnerable to customer demand fluctuations. Yet, the level of risk for any given utility’s revenues to demand fluctuations is unknown. Even if a utility can determine that, for example, 80% of its revenues are collected from variable rates, not all of that 80% is equally vulnerable to demand fluctuations. How much demand (and under which tiers?) may realistically be reduced under different scenarios and how much of the total utility revenue does that translate to under a given rate structure? Is 20% of your utility’s expected revenues “at risk of loss” due to significant and unplanned demand reductions? 50%? 70%?
The Environmental Finance Center at the University of North Carolina is developing a simple, ready-to-use revenue vulnerability risk assessment tool for water utilities, funded by the Water Research Foundation. This Excel-based tool allows a utility to relatively quickly assess its level of revenue vulnerability in terms of the proportions of expected revenues that are at risk of “loss” due to sudden and unplanned reductions in customer demand in the coming year. This risk assessment is based on the utility’s own current rate structure, current customer demand distribution, and susceptibility to changes in the demand distribution due to events such as drought, economic downturn, increased precipitation, etc. Historic customer demand data from hundreds of thousands of customers are used to simulate realistic changes to demand.
While utilities have several options to mitigate revenue vulnerability risk, the focus of this presentation will be on using the rate structure itself to reduce revenue risk. This tool will allow a utility to compare its projected revenue risk under different proposed rate structures, allowing the utility managers to make informed decisions about their rate structure design while incorporating revenue risk assessment into their analysis. Utility management will be able to set an “acceptable” target of revenue risk based on their bond covenants, financial policies and level of risk aversion.