In many countries, government entities can be the lowest-paying customers. For example in the Republic of Congo, the bill collection rate for the state was only 33 percent, against 89 percent for nonstate consumers. Reasons for large payment arrears by government agencies and state-owned companies vary—the utility’s limited influence over such customers as the military; an informal agreement where government agencies withhold payments to compensate for subsidies provided to the utility (direct transfers, tax breaks, exemption from import duties), or financially weak state-owned enterprises not paying bills to the state-owned utility; and the inability of the utility to cut off electricity for street lighting and other services considered public service obligations, for which the utility is rarely if ever paid by the government in some countries, including The Gambia.

Against a benchmark of 100 percent collection efficiency, a total loss of revenue to the utilities amounted to 0.2 percent of current GDP. Bill collection inefficiencies are the highest as a share of GDP in Comoros, The Gambia, São Tomé and Príncipe, and Zimbabwe where the losses represent more than one percent of GDP. Although Nigeria has a relatively low bill collection rate, the losses were equivalent to 0.17 percent of GDP.

Collection rates in some countries have improved significantly in the past few years. For example, since Umeme took the private concessionaire in Uganda, bill collection rates increase from 94 percent in 2009 to 99 percent in 2014. The main reason in many other countries is the increased use of pre-paid meters, which secure the revenues to the utilities in advance of consumption. At approximately US$100 per meter, pre-paid meters improve collection efficiency significantly at relative low costs. More than 80 percent of residential customers in South Africa are on pre-paid meters. Malawi has been engaged for several years in rollout programs for prepaid meters, having achieved enrollment of 47 percent of customers by 2014, which helped to achieve a 93 percent bill collection rate in 2014.

There is a strongly statistically significant correlation between T&D losses and bill collection losses. The correlation coefficient of 0.68 is significant using a 1-percent test. This may suggest that operational inefficiencies tend to be pervasive rather than found in isolated pockets.

# 6.3 Utility staffing

Staffing data were available in 36 countries. There are at least several important dimensions to consider with respect to utility staffing, including staff numbers, staff skills, attendance (reporting to work), and salaries and benefits. A utility may appear overstaffed, but if many staff members on the payroll are not showing up for work—a known problem in several utilities—the utility may actually be chronically understaffed with large and unproductive overhead costs that have a strong political dimension. Staff skills may also be a concern, with many utilities suffering from lack of appropriately trained and experienced staff.

Figure 11 summarizes utility staff costs, which include employee salaries and associated costs such as health benefits and pensions. Staff costs can represent a significant portion of operating costs for a utility: on average US$27,000 per employee per year in constant 2014 US dollars, although this result is heavily skewed by South Africa where the staff costs average US$61,000 per employee. Excluding South Africa, staff costs are on average US$13,000 per employee. Staff costs represent a median of 14 percent of operating costs. Staff costs represent the lowest share of opex in Tanzania (5 percent). At the 46