Some innovators in the electric industry recently began offering financial hedging products that absorb risk from large customers. Why not offer this kind of protection to customers with small electric loads?
Flat pricing is not flat rates per kilowatt-hour, nor is it a budget bill program. Such common products help customers to levelize monthly bill variance, but do not actually protect customers from price and billing risk. Protecting customers from price risk is the essence of flat pricing, and it is where a company can step in and capitalize.
The flat pricing concept is not rocket science. In fact, it isn't even considered innovative. Many industries, including some that are similar to the electric industry, use it as their pricing strategy of choice. Capacity-constrained Internet service providers quickly moved from volumetric pricing to flat bills early in that industry's history. Another industry with capacity constraints, the cellular phone service market, has evolved from pure volumetric pricing to a more customized menu of flat offerings. Even the volatile retail gas market has been experimenting with its version of residential flat bills.
Sure, you might say, it's fine for other industries, but not for the complex and dynamic electric industry. System capacity would become inefficient and unmanageable; peak loads would skyrocket, requiring new investments in existing plants; or it might even damage system reliability. The absorbed financial risk would be too great. Regulators won't approve it. Customers won't pay for it.
If that's your reaction, you are not alone. These are what we consider the "myths." Once we challenged them, we found the reality often didn't match.
At Georgia Power, we decided specifically to challenge the stereotypes about flat pricing for small customers, both residential and small business. The result was a flat pricing pilot program rolled out June 1, 2000, which involved 500 customers. The goal of the program was to understand the myths about flat pricing.
On the surface, the idea of pure flat pricing in the electric market is frightening, posing potential threats in terms of capacity constraints, the price premium, revenue risk, and regulations. But under the microscope of market research, load shape modeling, and product testing, we found an exciting new pricing opportunity. Let's examine each of these perceived threats and the realities we came to understand.
The biggest hurdle to flat pricing in the energy industry is the fear that customers will change their behavior, which then will lead to a dramatic increase in their load demand. Although this worry is deeply held, we have been unable to find quantitative research to support it.
We used a three-prong approach to challenge this belief. First, customers were surveyed to learn how they would behave on such a pure flat program. Then those results were put through a modeling program that analyzed and projected the impact of these customers' behavior change on their load shape. Finally, we conducted a pilot that metered the participants' actual energy and peak consumption. This information was normalized to account for weather and compared to the previously measured behavior for these customers. The results were measured empirically using test and control groups.
The Reality: With the pilot flat pricing program, there was an increase in both energy and demand consumption. But, the increase was minimal and occurred mostly during off-peak periods. The majority of the growth resulted from customers lowering their thermostat setting during the summer months. The effect of this action was minimal during peak hours because the electric cooling system was running full speed regardless of whether the thermostat was set at 76 degrees or lowered to 74 degrees. But during the off-peak times, when the weather had cooled, the threshold of the thermostat setting had a greater impact of the running time of the cooling system.
Despite the minimal increase in energy consumption exhibited during the pilot, it can be energy-efficient. This program is the only one for residential customers that can accurately measure participants' change in behavior in terms of the financial impact on their annual bills. Typical volumetric pricing used by weather-sensitive residential or small business customers reveals a change in behavior from month to month, or month to the same month of the previous year, but that is less accurate, since weather conditions always will blur the results. Because a flat bill is based on weather-normalized behavior, any change in demand will be accurately quantified in the customers' next-year, flat-price offer. In addition, improved efficiency will be rewarded by a lower offer, regardless of the weather. If the program is marketed correctly to inform customers of how they could be more efficient, and how the program can measure and reward them, it could provide the means for customers to become more energy-efficient.
Risk is frightening, and it exists everywhere. But risk also is transferable. With flat pricing, financial risk can be deflected from the customer to the supplier. For flat pricing to work, the key question is whether this risk could be dissected and managed.
The major risk is the weather impact. If the summer is hotter than normal, and the winter is colder than normal, the result is that the amount collected from the flat pricing would be less than the amount otherwise paid by the customer. Conversely, if mild weather occurs, then the amount collected by flat pricing would be greater than the amount otherwise paid by the customer.
In some industries this risk might not be manageable. In the electric industry, however, it acts as a natural hedge. In hot weather years, when flat pricing is under-recovering, the company is generating unusually high returns from its other weather-sensitive customers not on the flat pricing schedule. In mild weather years, at the same time flat pricing is over-recovering, the company is generating unusually low returns from its other weather-sensitive customers. Thus, flat pricing can provide for free a hedge that some energy companies pay for, in the form of weather insurance or weather derivatives.
Another financial risk is the change in individual customer behavior. During the first year it is impossible to predict how an individual customer may respond to flat pricing. But the overall average response can be anticipated and distributed evenly into all customers' flat pricing during the first year. When customers renew their offer, however, their actual usage with their demonstrated behavior change could be built into the renewal offer, rather than simply offering a flat price for the average customer. This practice in itself can be expected to reduce inefficient consumption changes.
An additional risk is that a customer might use more electricity during the first year than predicted, and then decide not to renew. This "free-ridership risk" can be measured and forecasted. The predicted impact can then be built evenly into all future customers' flat pricing offerings. Even if participants return to the traditional pricing tariff, they will retain some residual behavioral changes that will generate further profitable sales.
Finally, there is risk associated with the accuracy of the cost variable going into the flat pricing model. That variable includes the predicted base energy price and fuel price, customer usage history, predicted customer behavior, and the accuracy of the weather-normalization model. A risk adder can compensate the supplier for these financial risks. Customers are willing to pay a premium to have this risk transferred to the supplier, so if customer sensitivity to the risk adder is equal to, or greater than, the acceptable risk of these components, then this portion of the risk can be managed.
To manage the portfolio of financial risks, we created a spectrum of potential outcomes based on all risk variables. We tested the severity of these risks by creating a range of worst-case, expected, and best-case scenarios, where the risks can be quantified and therefore managed through the flat price.
The Reality: The financial results of the pilot during the 12-month period supported the hypothesis that the risk could be managed. The actual outcome fell within the risk spectrum and very close to what was predicted, given the actual outcome of each risk variable. That does not mean that the financial results were positive. In fact, during the 12-month period, there was a hot summer, a mild winter, and a fuel price increase. Though that caused Georgia Power to see a negative financial impact for the flat bill customers, it supported the natural hedge theory because the company earned a higher than normal return from weather-sensitive customers not taking the flat pricing option.
Flat pricing programs are not designed to win every year. Rather, they are designed to earn a given return over multiple years. The scenario is similar to the bet a casino wagers. On any given roll, a customer can beat the house, but over a course of multiple rolls, the odds are set so that the house comes out ahead. Most casinos "bet" that few winners will walk away from the table immediately after winning, or act as free riders. The analogy with flat pricing is that even those few who leave the program will maintain higher consumption habits, which have become embedded in their behavior and will be captured in normal tariffs. The trick is managing the risk.
Even if the potential load growth is manageable, even customers want it, and if the risks can be managed, many suppliers believe that commissioners in regulated regions will be opposed to the program's innovation and risk.
It's easy to understand why regulators would scrutinize this product. The industry norms suggest that there are established opinions against such a product. But we believed that by challenging each of these norms through market research, modeling and risk analysis, this product could be approved and introduced into the regulated electric market. After all, IPALCO's regulated subsidiary, Indianapolis Power & Light, had received regulatory approval for a similar product in 1998, and has offered it ever since. In addition, regulatory concerns could be addressed through standard regulatory accounting to shelter regulated non-participants of the program from flat pricing risk, exposing only utility stockholders.
The Reality: In June 2000, Georgia Power received regulatory approval for a one-year pilot with a maximum number of 500 participants. The utility recently earned approval to expand the offering to 100,000 customers with no cap on participation.
The commonly held belief is that electricity is a true commodity and consumers will always choose the lowest-cost option. But flat pricing should not be the cheapest pricing package for the customer in the long run, due to the significant cost and quantity risk the programs place on energy retailers.
But would customers recognize the value of an electric service package that provides convenience and "peace of mind," and if so, would they be willing to pay a premium for it?
Reality Check: Survey results showed that many customers valued predictability and convenience, and were willing to pay a premium for that. Because our previous market research predicted that pilot participants would use more energy, the forecasted additional energy was built into the price of the flat pricing offer.
Surveys, however, did not prepare us for the extremely high public interest in the pilot. The day after the pilot was filed, news of it made the front page of the business section. Soon, it was reported favorably on both national radio and television-all for a 500-customer pilot, which hadn't even mailed promotions about the product yet. The mailed offers gained a high penetration rate, indicating that customers opted for the flat pricing option to meet their budgeting needs. In a follow-up survey of pilot participants, 95 percent reported that flat pricing either met or exceeded their expectations.
Energy companies can manage the financial return of a flat pricing program based on its appetite for risk. There are two simple methods to control risk and return.
The first method is managing the number of participants (). The program can be phased in by offering a small pilot, then slowly expanding eligibility to larger markets. A phased approach can give time to assess risks and returns and make small adjustments to the pricing model, as well as to the program's terms and conditions.
The second method is to manage risk through a risk adder (). The risk adder is the premium charged to compensate the company for the additional risk it assumes. In any given year, the program could take in more or less money than what customers would have paid under the tariff-based, volumetric-pricing plan. Increasing the amount of the risk adder increases the likelihood that in any given year, the revenue outcome for the company will be a gain. Of course, the larger the risk adder, the smaller the participation rate.
In an industry built on the bricks and mortar of unit price efficiency, some will continue to scoff at this pricing innovation, dismissing flat pricing due to its perceived inefficiency. We suggest those skeptics carefully examine the many industries offering flat bills. Consider the Internet service providers offering unlimited use for $19.95 per month; the mobile phone firms hawking unlimited use at $50 a month; and auto rental companies with unlimited miles for $40 per day.
There is a market niche yearning for such a product, and it can be constructed safely and profitably. It simply requires that you clearly define the norm and logically address it. If you don't, someone else will.
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