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Weekly UpdatesA white paper from Compass and UtiliPoint International, Inc.
Most utilities and energy companies are not operating as efficiently as possible. Facing extraordinary pressure to optimize operational efficiency, reduce costs, and demonstrate transparency in management practices, utilities are turning to benchmarking to facilitate performance improvement.
The fundamental challenge of utility operations is to deliver service at an ever lower cost at ever higher levels of quality. This challenge is complicated by decades of continuing deficient public investment in infrastructure, lack of consistent regulatory framework, and, at times, a lack of institutional accountability.
Regulatory commissions, boards of directors, and consumer interest groups consistently demand that utility rate increases are justified by market conditions, through schemes such as Cost-Plus and Performance-Based rates. In response, utilities are undertaking rigorous analyses of business operations to identify opportunities to drive performance improvement, and to demonstrate that management practices are in line with--and ideally ahead of--industry standards.
Benchmarking and comparative analysis are highly effective methods to gauge operational performance, identify gaps, reduce costs, increase quality and productivity, and define and implement leading practices. An effective benchmark initiative drills down into sub-process performance drivers and yields insights into root causes of performance gaps and helps define strategies to address them.
Another benefit of benchmarking is to provide an objective, quantifiable, and auditable analysis of operational performance. By ensuring transparency among all parties involved, such a perspective is particularly critical to regulatory reviews of utility operations.
This article examines the role of measurement and comparative analysis in a comprehensive performance improvement strategy that utilities and energy companies can apply to IT systems as well as to business process and operations such as customer care and billing, finance and accounting, human resources, and supply chain management.
A specific focus explores how detailed analysis of cost and productivity drivers makes it possible to identify root causes of performance issues and to define actions to address them. The article also discusses how this approach can be applied to various IT service towers and to core utility and energy company business.
Benefits of Utility and Energy Company Benchmarking
Benchmarking of utilities and energy companies should be driven by in-house interest to improve performance and satisfy customers. Internally motivated benchmarks are not only an effective diagnostic managerial tool, but also a process by which the organization gains critical knowledge and experience.
Rather than targeting any one discrete business unit, utilities and energy companies with the most aggressive approach to improvement are pursuing a portfolio approach. This involves changing business practices as well as organizational culture. By focusing improvement efforts on processes with the largest potential for improvement, and on those that are most critical to meeting future business requirements, successful utilities and energy companies are effectively turning business processes into a "best practices."
Measurements of improvement are also critical. Utilities that quantify performance gaps and measure improvements before, during, and after transformation reap significant rewards. Benchmarking defines key measurement inputs and, more importantly, the process measures needed to successfully implement a change strategy.
Benchmarking & Root Cause Analysis
Performance analysis and improvement involves collecting data (quantitative and qualitative) in the target areas, and establishing a hierarchy of metrics to represent the operations or processes. A high-level analysis is useful to an extent, as it can show how an organization performs, and, in a comparative context, show how it performs relative to its peers.
[FIGURE 1 OMITTED]
In an IT-focused example, the chart in Figure 1 compares network hardware unit costs for "Acme" (top number) against network hardware costs achieved by top-performing companies (lower number). At first glance, Acme seems to be performing well, since costs are comparable for the high-level measure of network hardware costs ($74 vs. $73).
However, an anomaly appears at the sub-process level, specifically in the area of Acme's voice network hardware costs. But the impact of this anomaly on overall performance is obscured by lower-than-average costs in data network hardware. Moreover, at this level, while the differences in voice and data network hardware costs are indicated, the reasons behind those cost differences are not apparent.
Drilling down further, analysis shows PBX costs are somewhat higher for Acme. But to understand the real source of the issue, it's necessary to go even further down the metrics hierarchy--to large PBX maintenance costs, where Acme's costs are more than double the Reference Group's.
Once this root cause of Acme's high voice network hardware costs is identified, corrective action--and a significant improvement in operational efficiency--becomes possible. But what specific actions should be taken to lower Acme's high costs in this area?
Compass analyses indicate that high PBX maintenance costs commonly result from one (or more) of the following factors:
* Non-competitive service procurement--in this case, the client organization should renegotiate its maintenance services contract, either through a formal RFP process or through an informal multi-vendor approach.
* Unnecessary maintenance of non-operating PBX components--unused port and trunk cards should be removed from the PBXs and consolidated to minimize the number of card shelves; cards which have been removed can then be used as maintenance spares or to support growth in other locations using similar PBXs.
* Unnecessary maintenance of spare PBXs--leading practices indicate that maintenance services are not necessary for spare PBX components.
* Inappropriate service coverage or response time environments--user organizations should review PBX service coverage needs (24x7 vs. 12x6 vs. business day, etc.) and buy the level of coverage necessary. Similarly, response time for outage coverage should meet business requirements: Is a one-hour response necessary for a port outage? Or is same-day coverage adequate?
Similar analyses can be applied to sub-process activities in other IT infrastructure towers to formulate specific actions to improve cost efficiency, productivity, and quality. In a desktop environment, for example, the high-level metric of cost per desktop may not reveal potential improvement opportunities that exist further down the metrics hierarchy, in an area such as support personnel per desktop. In a mainframe environment, the root causes of performance gaps in the high-level measure of cost per MIPS might be found in areas such as storage utilization or acquisition practices. In an application development environment, low productivity might reflect an inadequate system of activity reporting, resulting in limited knowledge sharing.
Cost reduction is not necessarily the goal of a detailed performance analysis, in many cases, the analysis can reveal that a lack of investment in technology, personnel, or processes relative to top performers results in sub-par performance.
Analyzing Business Processes
Comparative analysis methodologies and models can also be applied to business processes within utility and energy company business processes and operations. The hierarchy of metrics that deconstructs the cost drivers of a particular business process tower can similarly measure, for example, how efficiently a utility or energy company manages customer contacts relative to industry standards and top performers.
Figure 2 provides an example. At a high level, the call center might appear to have an efficient Interactive Voice Recognition (IVR) system because it handles 20 percent of incoming calls. Yet that same call center has difficulty reaching service level targets at industry acceptable staffing levels. A high-level analysis may conclude that agents need more training on how to handle calls efficiently.
[FIGURE 2 OMITTED]
However, further drill down shows that the IVR has a high percentage of calls that opt out of the system and choose a live agent. This means the IVR only handles 15 percent the calls and causes 5 percent to opt out to live agents. The reason for the opt out is that the system provides the option to inquire about high bills but was not programmed to fully address all high bill inquiries. This causes customers to opt out of the system for a live agent when their concerns are not resolved by the IVR.
Initially, it appears that further programming of the IVR will resolve the gap. Upon further analysis, we find that the high bill opt out sends customers to live agents not trained to handle high bill inquires. The call center maintains a special group to handle high bill inquires. This causes agents to take the calls, and then transfer them to the special group. Therefore, the gap requires two steps for resolution. First, the IVR must have additional programming, and, second, opt out calls for high bill inquires must go to the special group queue.
[FIGURE 3 OMITTED]
Resolving the gap with both solutions flees up the agents to reach service levels at industry standards and the IVR to perform at higher than industry standards.
Breadth of Operations
A benchmarking initiative can be applied to a narrow focus on a discretely defined area (an IT tower or a specific utility or energy company business process) as well as to a broad review of operational performance. The latter--an analysis that combines an assessment of IT operational performance and utility or energy company business process efficiency--can be particularly valuable, for several reasons.
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