(September 2011) Walgreens to install eVgo charging stations at 800 sites; Siemens and eMeter team up in Maryland; Glasgow muni installs Elster meters; ABB...
Rethinking Revenue Assurance
Reducing leakage to improve the bottom line.
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