Human resources are one of the most important assets of water utilities (WUs), being responsible for assuring systems management and playing an important role in the tacit forms of organizational knowledge. In organizations with responsibility for managing extensive, diverse infrastructure with long life-cycles, with adequate service and acceptable risk levels, knowledge transfer between peers should be assured to maintain a stable human resources framework. In WUs, strategic asset management should include the long-term planning of human resources alongside urban water infrastructure assets, to ensure service sustainability. Based on these assumptions and driven by the legal obligations in developing infrastructure asset management plans, Administração e Gestão de Sistemas de Salubridade, S.A. (AGS) created and implemented a novel personnel aging index (PAI) with the main goal of evaluating the human resources framework, including employee ages and professional categories, and the remaining time needed to transfer knowledge to new members of staff. This paper describes AGS' approach to human resources management under the asset management policy and PAI's formulation. A case study with 10 AGS WUs is presented, aiming to evaluate their teams' maturity level and allowing comparison between WUs.

INTRODUCTION

Strategic asset management in water utilities (WUs) implies the challenge of managing extensive infrastructure assets while meeting a required service level in the most cost-effective way. In Portugal, asset management policies have been assuming an increasingly important role as it is now mandatory to develop infrastructure asset management (IAM) plans. For this reason, national utilities' concerns are focused on long-term infrastructure planning. In this process, human resources and the existing fund of knowledge within organizations need to be seen as an ‘asset’ that should be properly managed alongside the infrastructure.

Administração e Gestão de Sistemas de Salubridade, S.A. (AGS) is a Portuguese multi-operator owned by Marubeni and Innovation Network Corporation of Japan that manages 13 WUs in Portugal and Brazil under long-term concession agreements. IAM has always played an important role in AGS due to its contractual obligations and more recently because of legal planning requirements. On this basis, AGS has participated in European research and innovation projects, like CARE-W, AWARE-P and iWIDGET, enabling the establishment of an asset management policy in the group and the implementation of a collaborative program to support WUs in developing IAM plans (Feliciano et al. 2014).

The program's first edition followed the AWARE-P approach, focusing mainly on urban water system assets. The second was implemented to monitor and improve IAM plans to closer alignment with ISO 55 001 requirements. In the current edition, the human resources dimension has been introduced to enlarge the plans' scope. In this it is clear that teams should be of suitable size and include appropriate professional skills. Team balance, taking the previous concerns into account, should be determined to try to ensure service sustainability in the longer-term.

HUMAN ASSETS AS AN AXIS OF ANALYSIS IN STRATEGIC ASSET MANAGEMENT

Organizational value and competitiveness depend mostly on the development, use and distribution of knowledge-based competences. As knowledge increasingly becomes a key strategic resource, the need for organizations to develop a comprehensive understanding of knowledge strategies, processes and tools for the creation, transfer and deployment of this unique asset is becoming critical (Mentzas et al. 2003).

Within an organization, knowledge can be passed on by apprenticeship, through observation and the guidance of a ‘mentor’ (tacit knowledge), or by books, manuals or other procedures that clearly express information through language, images or other means of communication (explicit knowledge). Nonaka & Takeuchi (1995) argue that conversion from tacit to explicit knowledge is the most crucial knowledge creation method in organizations.

In this context, human resources are a valuable asset as they act as a knowledge vehicle within an organization. In order to ensure proper knowledge transfer, it is important to adopt a long-term perspective on human resources management and to guarantee that human resources renewal processes are planned in advance, allowing enough time for junior employees to learn, and more senior staff to transfer their know-how and experience to younger employees.

HUMAN RESOURCES RENOVATION NEEDS

To ensure service sustainability, human resources asset management is as important as that of infrastructure. Both are valuable assets, performing their activities during a given lifetime, and requiring careful management and renewal after their useful life has come to an end. However, while physical assets such as pipes, meters or valves can be replaced instantly without significant effect on service quality, personnel renovation typically requires adaptation and a learning period for new staff to be able to perform adequately.

When replacing an employee who has reached his/her retirement age with someone new, performance is not the only issue. Tacit knowledge acquired by the older employee during a lifetime career might be lost to the organization, if not transferred in advance. As this type of knowledge is not easily documented, it must be passed from person to person within the working environment. This is particularly relevant in water utility technical departments, where specific knowledge of specific activities is required but is not easily obtained outside the organization.

To minimize such losses, it is necessary to assess the aging level within the organization, identifying teams with high or low maturity levels, and detecting situations where low maturity teams can yield lower performance levels, or high maturity teams where renovation can be compromised due to potential gaps between the time to retirement and the availability of experienced employees to replace them.

PERSONNEL AGING INDEX DEFINITION

The assessment systems of the Portuguese Water Regulator (ERSAR 2014) and International Water Association (Alegre et al. 2006) include performance indicators to evaluate the adequacy of human resources and the training frequency (explicit knowledge). However, these were not thought to describe teams' maturity levels, which is important in organizations like WUs where systems operation management is highly dependent on personal knowledge.

To respond to this gap, AGS developed a Personnel Aging Index (PAI) which describes peoples' average working career as the ratio between the sum of the remaining useful professional life for every employee and their total lifetime career: 
formula
where t= reference time (years); PAI (t)= personnel aging index at time t (dimensionless); n = total number of employees; RUpli,t = remaining useful professional life of employee i at time t (years); and Cli = career length of employee i (years).

The PAI can be computed for the entire organization or a single department. It can also be determined by professional category, since each implies a different useful professional life according to graduation level and/or the period needed to acquire specific skills through working experience and/or training in the organization. For example, graduate employees begin their careers later than undergraduates and coordination responsibilities should only be assumed by technicians with some level of work experience. These differences are translated into different useful professional lives and total lifetime careers.

ASSESSING PAI IN WUs

It is recommended that several issues are taken into account in producing a PAI. These can be customized case by case or according to the organization's practices, legal framework, human resources policies, and so on.

It is suggested that PAIs are calculated in WUs for the professional categories directly responsible for ensuring water service quality at technical level, e.g.:

  • a) unskilled technician (UT), employees with secondary level education;

  • b) skilled technician (ST), employees with secondary level education and certified skills;

  • c) undergraduate coordinator (UC), coordinators with secondary level education and coordination responsibilities;

  • d) graduate technician (GT), employees with university degrees;

  • e) graduate coordinator (GC), employees with university degrees and coordination responsibilities.

For each category, the useful professional lifetime should be defined according to the graduation levels and work experience required by the company.

While all of these careers are essential for a water utility's activities, their paths are quite different. An employee working as a UT during his/her lifetime career typically starts working after completing secondary level education, without specific training, and continues until retirement age. This category includes unskilled plumbers, pumping station operators, water meter readers, etc.

An ST, on the other hand, starts working later as, after completing secondary education, he/she will need one year's training, according to AGS practices, to achieve the initial level of technical skill needed, which is acquired through formal education, practical training or other means, and leads to a certificate or legal permit. Electricians, mechanics and heavy machinery drivers are examples of STs.

UC is a professional category that requires some level of knowledge and experience in the operation of water or wastewater systems. Therefore, these employees need some time to acquire the relevant degree of tacit knowledge and experience within the water utility, usually as a UT or an ST. Within AGS, in Portugal, this period should not be less than 10 years, so, UCs like foremen have shorter professional lifetime careers than UTs or STs.

There are substantial differences when approaching the GT category. Typically, secondary education is followed by a 5-year period of university education, which implies starting the activity later and having a shorter professional lifetime career, compared to UTs or STs. Engineers are included in this category.

GC is a professional category requiring a university education and some level of tacit knowledge in coordination activities. This type of knowledge is usually acquired by performing GT activities within the water utility for some time, usually not less than 8 years in AGS. For these reasons, GCs, as chief operating officers or general managers, have the shortest professional lifetime careers.

To calculate the PAI for each category, the useful professional lifetime, based on graduation levels and working experience as required by the company, should be defined. Figure 1 shows the professional useful life – the period from starting work to retiring – by category and illustrates possible employee flows within the organization (dashed arrows). The categories (UT, ST and GT) in which employees should be recruited from the external labor market are identified by filled arrows.
Figure 1

Professional useful life, by category.

Figure 1

Professional useful life, by category.

Reference values were defined for the coordination categories (UC and GC) as these are especially relevant in terms of tacit knowledge level. They typically correspond to job functions that are more difficult to replace, and therefore more critical for the organization. The reference values were established taking into account legal working age, retirement age and graduation periods, according to Portuguese legislation and learning periods within the WUs.

The learning periods in which employees acquire specific knowledge and capture an organization's culture are crucial in a water utility. Failure to ensure proper knowledge transfer may have consequences that are not easily overcome. Based on AGS' experience the UC category requires a minimum learning period of 10 years, while GC requires a minimum of 8 years. For these categories, poor PAI levels have two ranges. PAI values above 1 represent teams that did not accomplish the minimum learning period, while PAI values below 0.26 (UC) or 0.23 (GC) represent older teams that might not be able to transfer knowledge in the defined minimum learning period. Fair values transmit alerts for teams which represent young coordinators or for identifying employees to be prepared for the receiving category.

Table 1 summarizes the PAI reference values for UC and GC categories, and their corresponding results interpretation.

Table 1

PAI reference values for the UC and GC categories

Category Reference values Interpretation 
UC [0.00; 0.26] Poor  Teams without the required period to transfer knowledge 
[0.26; 0.32] Fair  Alert for identification of UT or ST to start learning – the minimum learning period 
[0.32; 0.95] Good  Stabilized teams 
[0.95; 1.00] Fair  Younger teams with coordination responsibilities 
[1.00; 1.26] Poor  Teams that have not accomplished the minimum learning period 
GC [0.00; 0.23] Poor  Teams without the required period to transfer knowledge 
[0.23; 0.29] Fair  Alert for identification of GT to initiate the minimum learning period 
[0.29; 0.94] Good  Stabilized teams 
[0.94; 1.00] Fair  Younger teams with coordination responsibilities 
[1.00; 1.23] Poor  Teams that have not accomplished the minimum learning period 
Category Reference values Interpretation 
UC [0.00; 0.26] Poor  Teams without the required period to transfer knowledge 
[0.26; 0.32] Fair  Alert for identification of UT or ST to start learning – the minimum learning period 
[0.32; 0.95] Good  Stabilized teams 
[0.95; 1.00] Fair  Younger teams with coordination responsibilities 
[1.00; 1.26] Poor  Teams that have not accomplished the minimum learning period 
GC [0.00; 0.23] Poor  Teams without the required period to transfer knowledge 
[0.23; 0.29] Fair  Alert for identification of GT to initiate the minimum learning period 
[0.29; 0.94] Good  Stabilized teams 
[0.94; 1.00] Fair  Younger teams with coordination responsibilities 
[1.00; 1.23] Poor  Teams that have not accomplished the minimum learning period 

Figure 2 presents the reference values for the coordination categories and the qualitative relationship in terms of good (green), fair (yellow) or poor (red) index levels. Retirement age was taken as 66 years.
Figure 2

PAI reference values for the UC and GC categories.

Figure 2

PAI reference values for the UC and GC categories.

CASE STUDY

The main goal of this case study was to assess the maturity level of the technical department teams, for which working experience and knowledge transfer between peers is more critical for the systems' sustainability operation and management from a long-term perspective.

The study was focused on the analysis of 10 AGS WUs employing 1,233 people in total. The utilities have different sizes and organizational structures, with between 16 and 207 employees in different departments. Table 2 is an overview of the WUs' dimensions and organizational characteristics.

Table 2

Overview of the AGS utilities used in the case study

  Network length (km)
 
Households with effective service (No.)
 
  
Variable Water service Wastewater service Water service Wastewater service Departments (No.) Employees (No.) 
Minimum 404 17 18,278 16,593 16 
Median 706 388 33,208 34,412 133 
Maximum 1,376 767 102,733 102,719 10 211 
Total 6,216 3,690 357,589 434,443 – 1,233 
  Network length (km)
 
Households with effective service (No.)
 
  
Variable Water service Wastewater service Water service Wastewater service Departments (No.) Employees (No.) 
Minimum 404 17 18,278 16,593 16 
Median 706 388 33,208 34,412 133 
Maximum 1,376 767 102,733 102,719 10 211 
Total 6,216 3,690 357,589 434,443 – 1,233 

PAI was calculated for all of the WUs and for the UT, ST, UC, GT and GC categories. The assumptions used took into account the legal working and retirement ages, and graduation periods according to Portuguese legislation. At global level, PAI for all companies is 0.45. The PAIs for the individual WUs are presented in Table 3. A qualitative analysis of the UC and GC categories, using the reference values in Table 1, is included.

Table 3

PAI by category for all case study WUs

Water utility UT ST UC GT GC 
0.67 0.47  0.53 0.88  0.78 
0.37 0.41  0.34 0.63  0.68 
0.32 0.31  0.25 0.53  0.45 
0.40 0.51  0.44 0.60  0.60 
0.36 0.29  0.21 0.55  0.56 
0.46 0.45  0.42 0.70  0.72 
0.38 0.41  0.19 0.65  0.56 
0.54 0.79  0.67 0.88  0.74 
0.61 0.38  0.16 0.66  0.31 
10 0.56 0.57  0.62 0.71  0.66 
Water utility UT ST UC GT GC 
0.67 0.47  0.53 0.88  0.78 
0.37 0.41  0.34 0.63  0.68 
0.32 0.31  0.25 0.53  0.45 
0.40 0.51  0.44 0.60  0.60 
0.36 0.29  0.21 0.55  0.56 
0.46 0.45  0.42 0.70  0.72 
0.38 0.41  0.19 0.65  0.56 
0.54 0.79  0.67 0.88  0.74 
0.61 0.38  0.16 0.66  0.31 
10 0.56 0.57  0.62 0.71  0.66 

On the basis of the definitions used, the PAI of a stabilized team should be between 0.40 and 0.60. Younger teams (lacking senior members and with a concentrated age profile) yield PAI values between 0 and 0.40, while values between 0.60 and 1 represent older teams (lacking younger members who are being trained, and willing to accept novel approaches and technologies, as well as having a concentrated age profile).

In relation to categories UT, ST and UC – i.e., those staff who did not go to university – the PAI results are very different. In the UT category there are four WUs with stabilized teams, two with younger teams (PAI above 0.6) and four with older teams (PAI below 0.40), which can indicate a need for renewal in the medium term. The ST category also presents PAI values below 0.40 but most WUs have stabilized teams. Five WUs have UC groups with low values, representing older teams. Analysis of the graduate categories (GT and GC) shows that most WUs have young teams. Most department managers are at average maturity level.

When analyzing the technical departments, alone, there are slight differences. Table 4 shows the PAI results for the AGS technical departments, a sample of 608 employees.

Table 4

PAI by category for the technical departments

Water utility UT ST UC GT GC 
0.69 0.40  0.53 0.85  0.77 
0.34 0.54  0.36 0.64  0.79 
0.28 0.32  0.27 0.57  0.66 
0.38 0.49  0.47 0.59  0.54 
0.35 0.30  0.14 0.54  0.33 
0.49 0.43  0.43 0.75  0.69 
0.36 0.40  0.19 0.68  0.41 
0.54 0.79  0.67 0.88  0.74 
0.58 0.38  0.16 0.55  0.27 
10 0.56 0.56  0.55 0.70  0.61 
Water utility UT ST UC GT GC 
0.69 0.40  0.53 0.85  0.77 
0.34 0.54  0.36 0.64  0.79 
0.28 0.32  0.27 0.57  0.66 
0.38 0.49  0.47 0.59  0.54 
0.35 0.30  0.14 0.54  0.33 
0.49 0.43  0.43 0.75  0.69 
0.36 0.40  0.19 0.68  0.41 
0.54 0.79  0.67 0.88  0.74 
0.58 0.38  0.16 0.55  0.27 
10 0.56 0.56  0.55 0.70  0.61 

WUs 5, 7 and 9 present low values in the UC category, indicating that it is important to identify potential substitutes in the medium term. The average UC team age is 59, and the retirement age in Portugal is 66.

Another important outcome concerns category GC in WU 9, where a PAI value of 0.27 represents an alert for identification of employees in the GT category who can potentially replace these team members in the future and, for that reason, should initiate learning in the short-term.

WU 3 is an example of how PAI results can contribute to identify renovation needs as it presents the lowest index of all (0.32) in the UT category. The high maturity level in the WU is confirmed by its age pyramid (Figure 3).
Figure 3

Age pyramid for WU 3.

Figure 3

Age pyramid for WU 3.

When WU 3's technical department is analyzed (Table 4), the results indicate that the UT category presents an even lower value (0.28) and that it is closer to retirement than any other group there. This reflects the need to renew the UT group by hiring new employees in the local labor market (Figure 4), as most WU employees are recruited in the municipality.
Figure 4

Age pyramid in the municipality where WU 3 operates.

Figure 4

Age pyramid in the municipality where WU 3 operates.

CONCLUSIONS

In organizations responsible for managing extensive, diverse assets with long life-cycles, with an adequate service and acceptable risk levels, such as urban WUs, knowledge transfer between peers should be assured to maintain a stable human resources framework. This is particularly relevant in undocumented forms of knowledge, when this transfer is made from person to person – tacit knowledge.

Human assets are critical for water service sustainability and a sound performance assessment system is needed to support WUs management to address this issue. In the authors' view, the pre-existing regulatory (e.g. ERSAR PI system) and standardized assessment systems (e.g. IWA PI systems) do not respond to these needs. To overcome this situation, AGS has developed an index that quantifies average working careers in an organization or department. This enables assessment of team maturity levels, and identification of situations where appropriate forms of tacit knowledge transfer are at risk or situations where learning periods are lower than ideal in coordination categories, indicating the need for renewal and for long-term planning of human resource management.

The application of PAI within AGS group enabled identification of WUs in which human resource renovation is required in the short–term, reducing the operational risk and improving service sustainability in these respects.

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