Utility companies continue to face considerable margin pressures that stem from a number of challenges. An overall weakness in the commercial market, a flat and fragile residential market, modernization costs with limited availability of capital, and a higher level of volatility in energy costs all continue to affect profitability. Although the impact of these factors might be magnified by the recession, they are likely to persist throughout a recovery. Also, rate changes that might lessen these impacts are available in some cases, but regulators’ biases to limit further economic pressure on ratepayers is reducing the overall opportunity and size of any rate relief.
In response, most utility companies have established some form of margin improvement program that includes a portfolio of cost optimization, process optimization, and revenue-management efforts. Given the challenging market conditions, these efforts are mostly focusing on internal programs that can deliver predictable results, limit the need for significant operational changes, and have a proven track record of success. However, each program lever has its advantages and limitations. Executives must balance maximizing cost reduction without eroding operational performance; and maximizing operational efficiency without taking on unexpected change, costs, and risks. This portfolio approach often uses expected returns as a way to decide what to do and which efforts are most important.
At the highest level, levers that can affect the entire revenue line have the potential to create a greater impact than cost initiatives. For example, if a utility operates its business with variable costs at 15 percent to 20 percent of revenue, one point of revenue gain would equate to five points of cost reduction. To match this return, cost-optimization programs eventually would cut into operational muscle. Using the example above, revenue-management programs that can improve revenue performance by one point would give business leaders both significant financial value and extraordinary flexibility to attack costs in a highly targeted way and avoid risk or forcing operational changes.
Because utility companies have a limited ability to affect the external market, the best option is to maximize revenue from current operations. To address this opportunity, most utility companies have made efforts to address credit and collections, bad debt risk, and provide sampled-based billing analytics to reduce billing errors. These revenue-assurance efforts have, in the majority of cases, helped to reduce revenue leakage to approximately 3 percent. But is reducing revenue leakage to 3 percent good enough? What would an additional 1 or 2 points of revenue recovery mean to financial performance?
Using a simple model, a one billion dollar revenue stream realizes $30 million of leakage at 3 percent. Recognizing that zero-percent leakage is practically impossible—what should the target be? In complex telecom operations, most providers have been able to reduce leakage from 3 percent or more down to 1 to 2 percent in mature operations. If achievable in the utility order-to-cash environment, every one-percentage point of gain produces $10 million of annuity value, and a 50-percent reduction produces $15 million of annuity value (see Figure 1).
Telecommunication providers faced similar challenges in the 1990s. Three specific changes drove severe risk to revenue management: changes in the market structure that accelerated wholesale services and trading partners, the introduction of more multifaceted offerings that greatly expanded the enterprise product catalogue, and the introduction of more complex price packages based on time of day, usage, and other cross-discounting factors. Based on these changes, average revenue leakage grew dramatically from 1 to 2 percent to 5 to 10 percent. The risk escalation was based on the straightforward premise that external and internal changes overwhelmed the order-to- cash systems and processes, and rendered existing controls obsolete.
In response, telecommunication providers significantly increased their investment in revenue-assurance capabilities; shelving the prior manual and reactive approaches in favor of a more proactive, systematic approach. The investment has had significant payback that reduced revenue leakage from 5 percent to 10 percent down to 2 percent to 3 percent, and enabled telecommunication providers to aggressively introduce a broader set of products and more complex pricing while managing revenue risk.
The question is whether the analytic approach used for telecommunications can deliver a 1 to 2 percentage point gain for utility revenue operations? At a high level, the relationship between telecommunications and utilities makes sense in that they are both infrastructure-based, usage-based, regulated with different rate classes, have different wholesale and retail relationships, and operate relatively similar order-to-cash operations. The possible revenue gains are tantalizing—but certainly require a different analytic model for most utilities. How do utilities embrace the new model while appropriately kicking the tires on the approach itself?
If one stipulates that these types of gains are feasible—albeit, currently elusive—what are the characteristics of the technologies and practices that are relevant? Efforts in the utility sector suggest there are a set of critical capabilities needed to build and execute a highly productive revenue-assurance capability. There also are a set of practical concerns that need to be addressed to make an informed decision.
These critical capabilities and concerns help shape the investments. To build the business case, utilities also need to answer key questions that, in part, directly address revenue-management needs, revenue-recovery expectations, and the belief that tools built in a different sector have sufficient relevance to utility operations. These include:
• Are existing tools and practices sufficient to deliver an additional 1 to 2 points of revenue recovery?
• Can the utility benefit from a more proactive, systematic capability—and can it produce 1 to 2 points of revenue recovery?
• Will tools and practices proven in the telecom sector have sufficient relevance to the utility business such that their applicability and productivity can be tested?
In some cases, enterprises need to make substantial investments with the expectation, but not the proof, that the investment will pay off. This is not the case for revenue assurance, as this capability will directly influence revenue performance, regulatory relationships, rate cases, and customer relationships. Utilities should expect more from proven revenue-assurance capabilities and demand that providers execute both a Proof of Concept (PoC) and a Proof of Value (PoV) that prove technical feasibility (i.e., relative to working with operational data, capturing and working with the actual logic that governs order-to-cash, etc.), and produce indicative results that directly inform the business case. Using a PoC/PoV approach, utilities can validate the benefits of a rigorous process analytic capability without taking on the risk that these tools and practices would not fit or produce in the order-to-cash environment (see Figure 2).
The financial pressure on margins might abate, but are not likely to stop altogether. As a result, utility companies are actively engaged in a range of activities with the goals of reducing the effects of weak demand, a higher uncertainty in energy costs, increased capital costs, and stagnant rate cases. Among these efforts, a rigorous revenue-assurance capability is likely to produce the greatest immediate and long-term return, as it can produce 1 to 2 points of revenue recovery through a single, unified investment. Further, the PoC/PoV approach enables utilities to pursue the revenue opportunity using a sensible, efficient, low-risk method that is available now. More important, it provides a low-risk opportunity to reduce and possibly even reverse margin loss, while protecting current operations. It also reduces any risk associated with the business model shift that will be required with the expansion of smart metering and the implementation of the smart grid.