Abstract

Water utilities in Egypt are facing difficulties in managing the numerous indicators generated from the different departments. The increasing number of indicators and factors cause distraction and difficulties to interpreting the causes of problems, time wasting in analyzing redundant and unnecessary information, and delays in taking effective decisions. The BSC (Balanced Score Cards) technique has been utilized by many international utilities as the most influential multidimensional performance management system worldwide. This paper developed a new BSC model in cooperation with experts and managers to help decision makers managing water utilities' performance efficiently. The proposed model is based on the Egyptian Water and Wastewater Regulatory Agency performance indicators. In addition, new indicators have been developed to integrate all indicators that might affect overall utility performance. The proposed model will provide the utilities' managers with a fast but comprehensive view of the utility's performance. It also can be used by the regulatory agency as an evaluation and ranking tool for different water providers on the national level.

INTRODUCTION

The EWRA (Egyptian Water and Wastewater Regulatory Agency) has a performance indicator management system called AIR (annual information return), where all Egyptian utilities are obligated to send the data annually to EWRA for assessment (Soulie 2013). AIR is well developed to capture the utility indicators. However, the huge number of tables and indicators make interpreting utility performance difficult and causes delays in applying the optimum corrective actions. The Balanced Scorecard (BSC) developed by Kaplan and Norton is an effective tool and can be used by water utilities to help managers effectively managing their utilities' performance (Kaplan & Norton 2001). The BSC has been applied in several utilities for both public and private sectors all over the world (Mendes et al. 2012). In Egypt, the BSC was introduced in the banking sector (Hamdy 2018; Mobarez & Elfar 2016) and in the hospitality industry (El-Deep & Halim 2011). However, as yet BSC has not been applied to water and wastewater utilities in Egypt. This paper proposes a new BSC model for the Egyptian water utilities to provide decision makers with a comprehensive view about specific utility performance in order to improve the overall utility management system.

LITERATURE REVIEW

Balanced scorecards (BSC)

The BSC contains a diverse set of performance indicators addressing the following four perspectives: financial, customers, internal business, and innovation and learning (Kaplan & Norton 2001). The financial perspective includes items that measure how the company will be viewed by its shareholders (Liyai 2014). The second perspective (customer) identifies how the company manages the relationship with its customers (Strategic Management Group 2015). The internal business perspective highlights critical processes under each utility's objectives such as production and quality (Kaplan & Norton 2001). This perspective focuses on the internal processes the organization must undertake to gain customer satisfaction and maximize financial returns to shareholders (Venanzi 2012). Finally, the innovation and learning perspective considers how an organization learns and makes changes and improvements so that long-term value formation can be recognized. This perspective mainly focuses on the competences of employees, systems, and procedures applied to improve the performance of internal processes (Strategic Management Group 2015). Figure 1 illustrates these four perspectives.

Figure 1

Typical BSC. (based on Kaplan & Norton 1996).

Figure 1

Typical BSC. (based on Kaplan & Norton 1996).

BSC success heavily relies on the way of linking the measures (performance indicators) of the four perspectives in a causal chain to obtain the desired outcomes (Chen et al. 2012). BSC can be adapted and applied in public sector organization (Kaplan 2010). This can be done by integrating the customer perspective on the top of hierarchy (Kaplan & Norton 2001; Kaplan 2010; Northcott & Taulapapa 2012).

However, public sector organizations have always been affected by economic stability, political change, the involvement of external agencies and demands for public services (Arnaboldi et al. 2015). Accordingly, the different nature and challenges related to public sector made developing and applying new system to integrate and manage the huge amount of data is a must to any organization to get full overview about their utilities performance. Previous efforts have been done to apply BSC models to the healthcare (Behrouzi et al. 2014; Al-Hosaini & Sofian 2015), banking and hospitality sectors (El-Deep & Halim 2011; Hamdy 2018). However, no effort has been done to apply the BSC model to manage the performance of water and wastewater utilities in Egypt.

EWRA performance indicators

EWRA developed a framework to assess technical, financial, and economic performance for water and wastewater service providers. EWRA cooperated with experts from the UK Drinking Water Inspectorate (DWI) and the UK Office of Water Services (OFWAT) to prepare the AIR spreadsheets to be submitted by the companies to EWRA for measuring performance indicators and level of service (Soulie 2013).

The AIR is an excel workbook consisting of 25 sheets each sheet contains number of indicators related to the scope of its category. For example, first sheet ‘Coverage and subscribers in the water service’ includes 17 indicators (such as, total population, served population, number of subscribers, etc.). Table 1 shows different categories arranged into separate sheets and related performance indicators under each category.

Table 1

Annual information return (AIR) spreadsheets (EWRA 2013, annual information report)

Table No. Category Name No. Indicators 
T01 Coverage and subscribers in the water service 17 
T02 Number of force mains and networks samples complying with the Egyptian standard 14 
T03 Number of force mains samples complying with the Egyptian standard (branches level) 28 
T04 Number of network samples complying with the Egyptian standard (branches level) 22 
T05 Performance and purification 36 
T06 Water balance 18 
T07 Design and actual capacities of purification plants (branches level) 14 
T08 Costs and expenses according to type of activity 33 
T09 Costs and expenses, according to the stages of operation 18 
T10 Costs and expenses, according to the stages of operation 18 
T11 Revenues 25 
T12 Grants and subsidies 
T13 Employees cost and number 27 
T14 Amount of water sold and number of subscribers and connections 25 
T15 Customers and bills collections 19 
T16 Classification of employment, according to the phases of operation 14 
T17 Electricity consumption and costs 15 
T18 Fixed assets and the replacement and renewal 24 
T19 Coverage and subscriber's sewer service 
T20 The number of samples and their conformity with the specifications and standards 
T21 The number of samples and their conformity with the specifications and standards (branches level) 
T22 Performance and treatment 22 
T23 Design and actual capacities of treatment plants (branches level) 
T24 Classification of customer complaints 27 
T25 Sources of complaints, customer inquiries and resolve complaints 29 
Table No. Category Name No. Indicators 
T01 Coverage and subscribers in the water service 17 
T02 Number of force mains and networks samples complying with the Egyptian standard 14 
T03 Number of force mains samples complying with the Egyptian standard (branches level) 28 
T04 Number of network samples complying with the Egyptian standard (branches level) 22 
T05 Performance and purification 36 
T06 Water balance 18 
T07 Design and actual capacities of purification plants (branches level) 14 
T08 Costs and expenses according to type of activity 33 
T09 Costs and expenses, according to the stages of operation 18 
T10 Costs and expenses, according to the stages of operation 18 
T11 Revenues 25 
T12 Grants and subsidies 
T13 Employees cost and number 27 
T14 Amount of water sold and number of subscribers and connections 25 
T15 Customers and bills collections 19 
T16 Classification of employment, according to the phases of operation 14 
T17 Electricity consumption and costs 15 
T18 Fixed assets and the replacement and renewal 24 
T19 Coverage and subscriber's sewer service 
T20 The number of samples and their conformity with the specifications and standards 
T21 The number of samples and their conformity with the specifications and standards (branches level) 
T22 Performance and treatment 22 
T23 Design and actual capacities of treatment plants (branches level) 
T24 Classification of customer complaints 27 
T25 Sources of complaints, customer inquiries and resolve complaints 29 

Problem identification

To assess a particular water utility, data for a huge number of indicators should be collected on a yearly basis from all Egyptian water utilities through the AIR (Soulie 2013). However, although the data collected captures every aspect of utility management, it fails to provide a clear and comprehensive image for the utility's overall performance. Furthermore, the huge number of indicators confuse the utilities' managers and keep them busy with incorrect information, leading to late decisions in applying corrective actions. Accordingly, the performance of most of Egyptian water utilities is low and in need of improvement (Hassanein & Khalifa 2007). So, this research is proposing a BSC model to help decision makers improve the overall performance of water utilities in Egypt. The following sections will discuss the BSC model building process.

METHODOLOGY

Comprehensive evaluation for the water utilities' performance requires a simple and easy to apply model considering all indicators affecting water utility performance. The proposed BSC model methodology has been summarized as shown in Figure 2. In order to develop the proposed BSC model, first the EWRA indicators have been thoroughly studied, and a process map was designed to plan the model development. The process starts with developing the main BSC model perspectives. The second process is to link the BSC perspectives with the utility strategic goals. The third process is to select the most critical performance indicators from the AIR, in addition to developing some new indicators based on experts' opinions. Finally, the analytical hierarchy process (AHP) will be applied for the final list of indicators under each perspective to get their weights and ensure their consistency. The weighted BSC then can be used to develop a performance measurement tool to help decision makers manage their water utilities. Figure 2 shows the process map used to build the proposed BSC model.

Figure 2

Water utilities BSC model methodology.

Figure 2

Water utilities BSC model methodology.

PROPOSED BSC MODEL DEVELOPMENT PROCESS

BSC perspectives

Face to face interviews have been held with water utilities' experts to investigate their opinion on the proposed BSC perspectives. A total of 15 experts were interviewed over two rounds. The first round was to explain the BSC perspectives and get their feedbacks and recommendations. Then, round two was held to discuss the final BSC perspectives intended to be used in the BSC model. The experts were chosen from different organizations working in the water and wastewater utilities sectors (i.e., Cairo Water Company, Sharqia Water Company, Ministry of Housing, Utilities & Urban Communities, National Organization for Potable Water and Sanitary Drainage, Holding Company for Water and Wastewater, water and wastewater consultants).

Based on data analysis, most of interviewed experts have the same idea about the sector challenges and accordingly their feedback was very similar. Figure 3 shows the final proposed BSC model perspectives after experts' interviews in round two. The final four BSC perspectives are Customer, Technical, Financial, and Employees which will be used to develop the proposed BSC model. The final BSC perspectives comply with the recommended perspectives by (Kaplan & Norton 2001). The only difference is that the ‘innovation and learning’ perspective has been changed to the ‘Employees’ perspective, which is commonly known as employee's problems in different water utilities in Egypt.

Figure 3

Proposed BSC model perspectives.

Figure 3

Proposed BSC model perspectives.

Strategic goals

Strategic goals have been selected based on different water utilities' business plans in Egypt (e.g., Behiera Governorate, Cairo Governorate, and Sharqia Governate). The business plans were developed by a private consultant as a part of technical assistance program funded by the European Union in 2014. Figure 4 provides a schematic overview of the conducted business planning process.

Figure 4

Utility business plan process.

Figure 4

Utility business plan process.

According to utility business plan process, the private consultant held different workshops to determine the company's vision, mission, and strategic goals/objectives. The analysis resulted in 23 potential strategic choices, in which six strategies have been chosen as they are the most critical and directly reflect the performance of each water utility, so it will be used by the proposed model. The chosen strategic goals are:

  • Increase customer satisfaction

  • Increase service sustainability

  • Increase service efficiency

  • Increase employee satisfaction

  • Achieve cost recovery

  • Increase collection efficiency

The business plan report was then discussed with the same 15 experts (who selected the BSC perspectives) to link them with their associated perspectives. The discussion concluded the following strategic goals under the four BSC perspectives:

  • Customer perspective:

    • o Increase customer satisfaction

  • Technical perspective:

    • o Increase service sustainability

    • o Increase service efficiency

  • Employees perspective:

    • o Increase employee satisfaction

  • Financial perspective:

    • o Achieve cost recovery

    • o Increase collection efficiency

Performance indicators

Twenty performance indicators were selected from the indicators list used by EWRA and extracted from the AIR tables. Five more indicators were newly developed based on AIR indicators. The indicators were then identified under each strategic goal according to the scope similarity between them.

The urge for creating new indicators has been determined from the deep discussion with the experts. All the newly developed indicators are under the ‘Employees’ perspective. New indicators reflect ignorance of the employees' condition and needs by the utilities' managers as they are an important aspect to effectively managing the utility.

An example of one of the new indicators that was developed, the ‘Employees to Customers’ indicator, was not listed in the AIR indicators. This indicator is crucial for the Employees' satisfaction perspective. It reflects the employees' work load and accordingly their satisfaction. The ‘Employees to Customers’ was calculated by dividing the number of employees by the number of customers. Real data have been collected from the AIR sheets and used to calculate the ‘Employees to Customers’ indicator.

The indicators were then distributed into the four perspectives according to the experts' opinions. Table 2 shows the BSC model structure without any weight for the different indicators within each perspective.

Table 2

BSC model strategic goals and their performance indicators

BSC Strategic goals Indicators 
Customer Increase customer satisfaction Complaints by customers (customer satisfaction) 
Complaints solved to total complaints 
Calls answered within 30 s to total calls 
Population served to total population 
Unserved population to total population 
Service complaints 
Administrative complaints 
Technical Increase service sustainability Unplanned service interruptions 
Connections with pressure <2.5 bar 
Number of bursts 
Working meters to total meters 
Increase service efficiency Non-revenue water 
Physical & chemical samples within limits 
Bacteriological samples within limits 
Employees Increase employee satisfaction Employees to customers 
Average water employee salary 
Average wastewater employee salary 
Employees to WTP 
Employees to WWTP 
Wastewater to water employees 
Financial Achieve cost recovery % cost recovery 
Total revenue per m3 
Total cost per m3 
Increase collection efficiency Revenue collected per m3 
% Bills collection 
BSC Strategic goals Indicators 
Customer Increase customer satisfaction Complaints by customers (customer satisfaction) 
Complaints solved to total complaints 
Calls answered within 30 s to total calls 
Population served to total population 
Unserved population to total population 
Service complaints 
Administrative complaints 
Technical Increase service sustainability Unplanned service interruptions 
Connections with pressure <2.5 bar 
Number of bursts 
Working meters to total meters 
Increase service efficiency Non-revenue water 
Physical & chemical samples within limits 
Bacteriological samples within limits 
Employees Increase employee satisfaction Employees to customers 
Average water employee salary 
Average wastewater employee salary 
Employees to WTP 
Employees to WWTP 
Wastewater to water employees 
Financial Achieve cost recovery % cost recovery 
Total revenue per m3 
Total cost per m3 
Increase collection efficiency Revenue collected per m3 
% Bills collection 

AHP analysis

The Analytic Hierarchy Process (AHP), introduced by Thomas Saaty (Saaty 2008) has been used to assign relative weights for indicators and prioritise them to help decision makers focus on the critical ones. AHP incorporates a useful technique for checking the consistency of decision makers' evaluation, thus reducing the bias in the decision-making process.

The model perspectives and their indicators shown in Table 2 were presented to the same 15 experts who were involved in the BSC perspectives selection. The experts were asked to score each indicator under each perspective. The scores were based on the definitions listed in Table 3.

Table 3

The fundamental scale for indicators scoring

Number Definition 
The selected attribute is significantly more important than the compared attribute 
The selected attribute is more important than the compared attribute 
Attributes are equal in importance 
1/3 The selected is slightly less important than the compared attribute 
1/5 The selected is significantly less important than the compared attribute 
Number Definition 
The selected attribute is significantly more important than the compared attribute 
The selected attribute is more important than the compared attribute 
Attributes are equal in importance 
1/3 The selected is slightly less important than the compared attribute 
1/5 The selected is significantly less important than the compared attribute 

After collecting all evaluations, the final average score was calculated for each indicator. Table 4 shows an example for the final scores collected from all experts for the financial perspective indicators.

Table 4

Financial perspective indicators relative scores

Financial Indicators % Cost recovery Total revenue per m3 Revenue collected per m3 Total cost per m3 % Bills collection 
% Cost recovery 1.0 5.0 3.0 3.0 1.0 
Total revenue per m3 1/5 1.0 1/3 1/3 1/5 
Revenue collected per m3 1/3 3.0 1.0 1.0 1/3 
Total cost per m3 1/3 3.0 1.0 1.0 1/3 
% Bills collection 1.0 5.0 3.0 3.0 1.0 
Financial Indicators % Cost recovery Total revenue per m3 Revenue collected per m3 Total cost per m3 % Bills collection 
% Cost recovery 1.0 5.0 3.0 3.0 1.0 
Total revenue per m3 1/5 1.0 1/3 1/3 1/5 
Revenue collected per m3 1/3 3.0 1.0 1.0 1/3 
Total cost per m3 1/3 3.0 1.0 1.0 1/3 
% Bills collection 1.0 5.0 3.0 3.0 1.0 

Accordingly, the normalized matrix has been developed to insure the consistency of each perspective. Since the numeric values of indicators' weights are derived from subjective preferences of individuals, it is impossible to avoid some inconsistencies. AHP calculates different ratios such as the consistency ratio (CR) and consistency index (CI) of the matrix, then CI should be divided by CI of a random-like matrix (RI). Table 5 shows the weighted indicators and consistency check for the four perspectives using the AHP technique.

Table 5

Four perspective indicators weights and consistency check

Financial % Cost recovery Total revenue per m3 Revenue collected per m3 Total cost per m3 % Bills collection Weight         
% Cost recovery 1.000 5.000 3.000 3.000 1.000 34%     
Total revenue per m3 0.200 1.000 0.333 0.333 0.200 6%     
Revenue collected per m3 0.333 3.000 1.000 1.000 0.333 13%     
Total cost per m3 0.333 3.000 1.000 1.000 0.333 13%     
% Bills collection 1.000 5.000 3.000 3.000 1.000 34%     
Normalized matrix     Weights Products Ratio    
0.3488 0.2941 0.3600 0.3600 0.3488 34.2% 1.7419 5.087972    
0.0698 0.0588 0.0400 0.0400 0.0698 5.6% 0.2792 5.014259    
0.1163 0.1765 0.1200 0.1200 0.1163 13.0% 0.6549 5.044966    
0.1163 0.1765 0.1200 0.1200 0.1163 13.0% 0.6549 5.044966    
0.3488 0.2941 0.3600 0.3600 0.3488 34.2% 1.7419 5.087972    
      CI = 0.014007 CI/RI = 0.01 consistent 
Technical Unplanned services cut % connections with pressure <2.5 bar Number of Bursts % working meters % Non revenue water % Physical & Chemical samples within limits % Bacteriological samples within limits Weight   
Unplanned service interruptions 1.000 3.000 1.000 3.000 0.200 0.333 0.333 10%   
% connections with pressure <2.5 bar 0.333 1.000 0.300 1.000 0.200 0.200 0.200 4%   
Number of bursts 1.000 3.333 1.000 3.000 0.333 1.000 1.000 13%   
% working meters 0.333 1.000 0.333 1.000 0.333 0.333 0.333 6%   
% Non Revenue Water 5.000 5.000 3.000 3.000 1.000 3.000 3.000 34%   
% Physical & chemical samples within limits 3.000 5.000 1.000 3.000 0.333 1.000 1.000 16%   
% Bacteriological samples within limits 3.000 5.000 1.000 3.000 0.333 1.000 1.000 16%   
Customer Number of complaints % Telephone complaints solved the same day Calls answered within 30 sec % population served water 247 % unserved population Quality complaints Bills complaints Weight   
Number of complaints 1.000 3.000 3.000 1.000 0.333 1.000 1.000 13%   
% Telephone complaints solved the same day 0.333 1.000 1.000 0.200 0.143 1.000 1.000 6%   
Calls answered within 30 sec 0.333 1.000 1.000 0.200 0.143 0.300 0.300 4%   
% population served water 247 1.000 5.000 5.000 1.000 0.333 3.000 3.000 21%   
% unserved population 3.000 7.000 7.000 3.000 1.000 3.000 3.000 36%   
Quality complaints 1.000 1.000 3.333 0.333 0.333 1.000 1.000 10%   
Bills complaints 1.000 1.000 3.333 0.333 0.333 1.000 1.000 10%   
Employees Employees to customers Average water employee salary Average wastewater employee salary Employees to WTP Employees to WWTP Wastewater to water employees Weight    
Employees to customers 1.000 0.333 0.333 0.333 0.333 1.000 7%    
Average water employee salary 3.000 1.000 1.000 1.000 1.000 3.000 21%    
Average wastewater employee salary 3.000 1.000 1.000 1.000 1.000 3.000 21%    
Employees to WTP 3.000 1.000 1.000 1.000 1.000 3.000 21%    
Employees to WWTP 3.000 1.000 1.000 1.000 1.000 3.000 21%    
Wastewater to water employees 1.000 0.333 0.333 0.333 0.333 1.000 7%    
Financial % Cost recovery Total revenue per m3 Revenue collected per m3 Total cost per m3 % Bills collection Weight         
% Cost recovery 1.000 5.000 3.000 3.000 1.000 34%     
Total revenue per m3 0.200 1.000 0.333 0.333 0.200 6%     
Revenue collected per m3 0.333 3.000 1.000 1.000 0.333 13%     
Total cost per m3 0.333 3.000 1.000 1.000 0.333 13%     
% Bills collection 1.000 5.000 3.000 3.000 1.000 34%     
Normalized matrix     Weights Products Ratio    
0.3488 0.2941 0.3600 0.3600 0.3488 34.2% 1.7419 5.087972    
0.0698 0.0588 0.0400 0.0400 0.0698 5.6% 0.2792 5.014259    
0.1163 0.1765 0.1200 0.1200 0.1163 13.0% 0.6549 5.044966    
0.1163 0.1765 0.1200 0.1200 0.1163 13.0% 0.6549 5.044966    
0.3488 0.2941 0.3600 0.3600 0.3488 34.2% 1.7419 5.087972    
      CI = 0.014007 CI/RI = 0.01 consistent 
Technical Unplanned services cut % connections with pressure <2.5 bar Number of Bursts % working meters % Non revenue water % Physical & Chemical samples within limits % Bacteriological samples within limits Weight   
Unplanned service interruptions 1.000 3.000 1.000 3.000 0.200 0.333 0.333 10%   
% connections with pressure <2.5 bar 0.333 1.000 0.300 1.000 0.200 0.200 0.200 4%   
Number of bursts 1.000 3.333 1.000 3.000 0.333 1.000 1.000 13%   
% working meters 0.333 1.000 0.333 1.000 0.333 0.333 0.333 6%   
% Non Revenue Water 5.000 5.000 3.000 3.000 1.000 3.000 3.000 34%   
% Physical & chemical samples within limits 3.000 5.000 1.000 3.000 0.333 1.000 1.000 16%   
% Bacteriological samples within limits 3.000 5.000 1.000 3.000 0.333 1.000 1.000 16%   
Customer Number of complaints % Telephone complaints solved the same day Calls answered within 30 sec % population served water 247 % unserved population Quality complaints Bills complaints Weight   
Number of complaints 1.000 3.000 3.000 1.000 0.333 1.000 1.000 13%   
% Telephone complaints solved the same day 0.333 1.000 1.000 0.200 0.143 1.000 1.000 6%   
Calls answered within 30 sec 0.333 1.000 1.000 0.200 0.143 0.300 0.300 4%   
% population served water 247 1.000 5.000 5.000 1.000 0.333 3.000 3.000 21%   
% unserved population 3.000 7.000 7.000 3.000 1.000 3.000 3.000 36%   
Quality complaints 1.000 1.000 3.333 0.333 0.333 1.000 1.000 10%   
Bills complaints 1.000 1.000 3.333 0.333 0.333 1.000 1.000 10%   
Employees Employees to customers Average water employee salary Average wastewater employee salary Employees to WTP Employees to WWTP Wastewater to water employees Weight    
Employees to customers 1.000 0.333 0.333 0.333 0.333 1.000 7%    
Average water employee salary 3.000 1.000 1.000 1.000 1.000 3.000 21%    
Average wastewater employee salary 3.000 1.000 1.000 1.000 1.000 3.000 21%    
Employees to WTP 3.000 1.000 1.000 1.000 1.000 3.000 21%    
Employees to WWTP 3.000 1.000 1.000 1.000 1.000 3.000 21%    
Wastewater to water employees 1.000 0.333 0.333 0.333 0.333 1.000 7%    

CASE STUDY APPLICATION

The BSC model developed has been applied to real data from a selected case study to calculate the performance of each perspective and to evaluate the overall performance for this utility, as well as to test its applicability and its limitation. Based on the BSC model, weighted indicators calculation sheet was developed. Table 6 presents the proposed BSC model calculation sheet.

Table 6

Proposed balanced scorecard model calculation sheet

Overall BSC Weight Status Strategic goals Indicators Unit Value Target weight Status 
75% Customer 25% 67.4% Increase customer satisfaction Number of complaints (customer satisfaction) Complaint/connection (i) 0.09915 0.01 13% 10% 
Complaints solved to total complaints 100 100 6% 100% 
Calls answered within 30 s to total calls 100 4% 0% 
Population served to total population 100 100 21% 100% 
Unserved population to total population %(i) 36% 100.0% 
Service complaints Complaint/connection (i) 9.86521 10% 10% 
Administrative complaints Complaint/connection (i) 0.04985 0.01 10% 20% 
Technical 25% 81.8% Increase service sustainability Unplanned services cut # (i) 680 4,000 10% 100% 
Connections with pressure <2.5 bar per water connection (i) 4% 100% 
Number of bursts # (i) 10 13% 10% 
Working meters to total meters 55.0719 100 6% 55% 
Increase service efficiency Non revenue water %(i) 26.1628 25 34% 96% 
Physical & chemical samples within limits 94.2909 100 16% 94% 
Bacteriological samples within limits 92.5639 100 16% 93% 
Employees 25% 59.8% Increase employees' satisfaction Employees to customers %(i) 83.1865 140 7% 100% 
Average water employee salary EGP/month 3,360.65 5,000 21% 67% 
Average wastewater employee salary EGP/month 3,150.56 5,000 21% 63% 
Employees to WTP %(i) 193.333 25 21% 13% 
Employees to WWTP %(i) 28.5714 20 21% 70% 
Wastewater to water employees 35.7453 35 7% 98% 
Financial 25% 89% Achieve cost recovery % cost recovery 81.3121 100 34% 81% 
Total revenue per m3 EGP/m3 1.23654 1.5 6% 82% 
Total cost per m3 EGP/m3 (i) 1.18832 13% 84% 
Increase collection efficiency Revenue collected per m3 EGP/m3 1.64565 1.2 13% 100% 
% Bills collection 96.1002 100 34% 96% 
Overall BSC Weight Status Strategic goals Indicators Unit Value Target weight Status 
75% Customer 25% 67.4% Increase customer satisfaction Number of complaints (customer satisfaction) Complaint/connection (i) 0.09915 0.01 13% 10% 
Complaints solved to total complaints 100 100 6% 100% 
Calls answered within 30 s to total calls 100 4% 0% 
Population served to total population 100 100 21% 100% 
Unserved population to total population %(i) 36% 100.0% 
Service complaints Complaint/connection (i) 9.86521 10% 10% 
Administrative complaints Complaint/connection (i) 0.04985 0.01 10% 20% 
Technical 25% 81.8% Increase service sustainability Unplanned services cut # (i) 680 4,000 10% 100% 
Connections with pressure <2.5 bar per water connection (i) 4% 100% 
Number of bursts # (i) 10 13% 10% 
Working meters to total meters 55.0719 100 6% 55% 
Increase service efficiency Non revenue water %(i) 26.1628 25 34% 96% 
Physical & chemical samples within limits 94.2909 100 16% 94% 
Bacteriological samples within limits 92.5639 100 16% 93% 
Employees 25% 59.8% Increase employees' satisfaction Employees to customers %(i) 83.1865 140 7% 100% 
Average water employee salary EGP/month 3,360.65 5,000 21% 67% 
Average wastewater employee salary EGP/month 3,150.56 5,000 21% 63% 
Employees to WTP %(i) 193.333 25 21% 13% 
Employees to WWTP %(i) 28.5714 20 21% 70% 
Wastewater to water employees 35.7453 35 7% 98% 
Financial 25% 89% Achieve cost recovery % cost recovery 81.3121 100 34% 81% 
Total revenue per m3 EGP/m3 1.23654 1.5 6% 82% 
Total cost per m3 EGP/m3 (i) 1.18832 13% 84% 
Increase collection efficiency Revenue collected per m3 EGP/m3 1.64565 1.2 13% 100% 
% Bills collection 96.1002 100 34% 96% 

The BSC model sheet is divided into three main parts as shown in Table 6. The last six columns are designated to evaluate each indicator and to calculate its performance. Columns from 2 to 5 are associated with four perspectives where performance is calculated by aggregating the performance for all indicators under each category. The first column presents the overall utility performance by aggregating the performance of the four-perspectives. The BSC Model Calculation sheet consists of the following columns for indicators: Unit, Value, Target, Weight and Status to evaluate each indicator. The ‘Unit’ column is to identify the measurement unit for each indicator. Some units have the (i) at the end, this indicates that the relationship between the indicator and the strategic goal is inversely proportional.

Indicator performance

The ‘Value’ column of indicators represents the value of each indicator that have been obtained from the AIR of the utility. The values used in this table is for demonstration, however it was obtained from real data from one of the water utilities in Egypt based on their AIR. The equations used to calculate each indicator are presented in the Table 7.

Table 7

Proposed balanced scorecard model indicators' equations

Indicator Equation 
Customer perspective 
 Number of complaints (customer satisfaction) Number of complaints/Number of water connections 
 Complaints solved to total complaints Complaints solved/Number of complaints*100 
 Calls answered within 30 s to total calls Calls answered within 30 s/total calls received *100 
 Population served to total population Number of population served 247/Total population*100 
 Unserved population to total population Number of unserved population/Total population*100 
 Service complaints Number of service complaints/Number of water connections*100 
 Administrative complaints Number of administrative complaints/Number of water connections*100 
Technical perspective 
 Unplanned services cut (+12 h unplanned service interruptions) + (−12 h unplanned service interruptions) 
 Connections with pressure <2.5 bar −2.5 bar connections/Total number of water connections*100 
 Number of bursts Number of bursts 
 Working meters to total meters Total number of water meters - Non-working meters/Total number of water meters*100 
 Non-revenue water Total produced water - Total number of water meters/Total produced water *100 
 Physical & chemical samples within limits Physical and chemical samples within limits/total number of physical and chemical samples tested*100 
 Bacteriological passed samples Bacteriological samples within limits/total number of bacteriological samples tested*100 
Employees' perspective 
 Employees to customers Total number of customers/Total number of employees 
 Average water employee salary Water employees cost/Water employees/12 
 Average wastewater employee salary Wastewater employees cost/Wastewater employees/12 
 Employees to WTP WTP employees/Number of WTP 
 Employees to WWTP WWTP employees/Number of WWTP 
 Wastewater to water employees Wastewater employees/Water employees*100 
Employees perspective 
 Cost recovery Total revenue/Total cost*100 
 Total revenue Total exported revenue/Total water sold 
 Total cost Total collected revenue/Total water sold 
 Revenue collected Total cost-Depreciation cost/Total water sold 
 Bills collection Total collected revenue/Total exported revenue*100 
Indicator Equation 
Customer perspective 
 Number of complaints (customer satisfaction) Number of complaints/Number of water connections 
 Complaints solved to total complaints Complaints solved/Number of complaints*100 
 Calls answered within 30 s to total calls Calls answered within 30 s/total calls received *100 
 Population served to total population Number of population served 247/Total population*100 
 Unserved population to total population Number of unserved population/Total population*100 
 Service complaints Number of service complaints/Number of water connections*100 
 Administrative complaints Number of administrative complaints/Number of water connections*100 
Technical perspective 
 Unplanned services cut (+12 h unplanned service interruptions) + (−12 h unplanned service interruptions) 
 Connections with pressure <2.5 bar −2.5 bar connections/Total number of water connections*100 
 Number of bursts Number of bursts 
 Working meters to total meters Total number of water meters - Non-working meters/Total number of water meters*100 
 Non-revenue water Total produced water - Total number of water meters/Total produced water *100 
 Physical & chemical samples within limits Physical and chemical samples within limits/total number of physical and chemical samples tested*100 
 Bacteriological passed samples Bacteriological samples within limits/total number of bacteriological samples tested*100 
Employees' perspective 
 Employees to customers Total number of customers/Total number of employees 
 Average water employee salary Water employees cost/Water employees/12 
 Average wastewater employee salary Wastewater employees cost/Wastewater employees/12 
 Employees to WTP WTP employees/Number of WTP 
 Employees to WWTP WWTP employees/Number of WWTP 
 Wastewater to water employees Wastewater employees/Water employees*100 
Employees perspective 
 Cost recovery Total revenue/Total cost*100 
 Total revenue Total exported revenue/Total water sold 
 Total cost Total collected revenue/Total water sold 
 Revenue collected Total cost-Depreciation cost/Total water sold 
 Bills collection Total collected revenue/Total exported revenue*100 

The ‘Target’ column is the desired value of the indicator that the utility managers would like to achieve. The target for each indicator will be set by the utility manager/decision-maker based on current status reports and the desired goals. There are different methods to set the target; one of them is by taking a national sector average. The target values used in this case study are proposed by changing the original indicator value slightly to a higher desired value to be achieved according to utility preference. These target values have been set to demonstrate the model's capabilities.

The ‘Status’ column of indicators is calculated by two methods based on the relationship between the indicator and the perspective. If the indicator is inversely proportional to the perspective, then the equation is dividing the indicator ‘Target’ by the indicator ‘Value’ as shown in Equation (1). If the indicator is directly proportional to the perspective, then the equation is dividing the indicator ‘Value’ by the indicator ‘Target’ as shown in Equation (2). The indicators' ‘Weight’ column values are obtained from the AHP analysis discussed earlier. 
formula
(1)
 
formula
(2)

Perspective performance

Each perspective's performance is shown in Table 6. The perspective weight shown in column 3 is according to the results of AHP analysis and can be modified by users. The weights are distributed evenly between the four perspectives; 25% each. The perspective ‘Status’ column values have been calculated by summation of the indicator's weights and status as shown in Equation (3). 
formula
(3)
where:
  • n = number of indicators within the perspective

  • Wi = Indicator Weight

  • Si = Indicator Status

The overall performance shown in column 1 ‘Overall’ has been calculated by averaging the summation of weights and status of four perspectives.

DISCUSSION AND FUTURE EXTENSION

The BSC model developed has been presented to some of the experts involved in the development process. The interviews concluded the following points: (1) The weights of the perspectives could be changing depending on the utility priorities; (2) Before implementing BSC model in Egyptian utilities, the model should be developed in a more user-friendly application; (3) The model lacks the ability to link the indicators in a feedback loop, for example, how the improvement in ‘Number of bursts’ could affect the service complaints. This was one of major limitations and should be resolved before real implementation.

The experts discussed some of challenges that could face the implementation of the proposed model in the Egyptian water utilities and how to overcome these challenges. Their valuable comments and recommendations are currently being addressed and will be integrated before applying the final BSC model in several real case studies. According to discussion with experts Table 8 summarizes some challenges and proposed solutions to be taken when implementing the BSC model in reality.

Table 8

Challenges associated with BSC model implementation

Challenge Challenge Description Mitigation Action 
Change resistance Employees will not easily use the new BSC system Involve all employees in an open discussion and get their feedback on the model. Let them know that the model will make the work load less and organize the overall work process 
BSC model needs training and requires more work load Not all the employees are familiar with the BSC Training on the BSC model should be plan during the preparatory phase before implementation 
Financial resources The implementation might be accompanied with some costs Software development costs worth the benefits gained from applying such system 
Challenge Challenge Description Mitigation Action 
Change resistance Employees will not easily use the new BSC system Involve all employees in an open discussion and get their feedback on the model. Let them know that the model will make the work load less and organize the overall work process 
BSC model needs training and requires more work load Not all the employees are familiar with the BSC Training on the BSC model should be plan during the preparatory phase before implementation 
Financial resources The implementation might be accompanied with some costs Software development costs worth the benefits gained from applying such system 

CONCLUSION

This paper developed a new BSC model that includes the necessary attributes and adoption levels to be used as an efficient management tool for water utilities in Egypt. The BSC model can be used by all water and waste utilities in Egypt to assess their service performance. The indicators were chosen and formulated to allow benchmarking between different utilities at the national level and to enable EWRA to rank/evaluate them together. The developed model includes four main perspectives that reflects the water utility management aspects. Twenty-five indicators have been identified under strategic goals of each perspective. The AHP method was used as a prioritization tool to calculate the weight for each performance indicator. During the development of the BSC model and according to experts' discussions, new indicators were developed such as ‘Average water employee salary’. This indicator is very important to compare the employees' salary on the national level. This new indicator also draws the managers' attention to the importance of measuring the employees' satisfaction and to resolve the overstaffing issues.

The proposed BSC model can measure the overall utility performance considering different perspectives to help decision makers get early warnings about perspectives that need improvement. The developed model was applied in real case studies, so currently the authors are working to extend the developed model to integrate experts' recommendations and to develop the final model as a separate software. Later it will be applied in several real case studies for validation before implementation by the utility. The future implementation process will definitely provide feedback that will strengthen the model and/or validate the model capability.

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