Among the factors affecting FSL growth, development and competitiveness, is the human resource management. The human capital within the FSL has two main components which are individual staff or employees and the FSL as an organization. Human capital have four key attributes [1] , that is, 1) flexibility and adaptability (improved via longevity and training), 2) enhancement of individual competencies (acquired through training and experience), 3) the development of the organizational competencies (including innovation, networking, facilities availability, other resources), and 4) individual employability (which may involve engagement and loyalty). Literature shows that, these attributes in turn, generate or add values to individual and organizational outcomes. There are various findings associating human capital with higher performance and sustainable competitive advantage [2] [3] , higher organizational commitment [4] , and enhanced organizational retention [5] .

From the individual level, the importance of human capital depends on the degree to which it contributes to the creation of a competitive advantage [6] . From an economic point of view, firms gain competitive advantages when they own firm-specific resources that cannot be copied by rivals. Thus, as the uniqueness of human capital increases, firms have incentives to invest resources into its management aiming at reducing risks and capitalizing on productive potentials. Hence, individuals need to enhance their competency skills in order to be competitive in their organizations, which stresses on academic and professional development.

During human capital theory development, greater attention has been paid to training related aspects (denoted in this paper as academic development). Human capital investment is any activity which improves the quality (productivity) of the worker. Therefore, training is still an important component of human capital investment. This refers to the knowledge and training required and undergone by a person that increases own capabilities in performing activities of economic value. However, training required is that which focuses on the FSL specific activities, for which such colleges to provide training are lacking within the country and also in the region. On the other hand, research on longevity issues has not been reported compared to training and academic development.

Literature shows the importance of training on employee’s productivity and firm’s competitiveness, indicating that the workforce’s lack of training is related to low competitiveness [7] . In turn, a greater human capital stock is associated with greater productivity and higher salaries [8] . Likewise, training is linked to the longevity of companies [9] and greater tendency to business and economic growth [10] . In addition, human capital is a source not only to motivate workers and boost up their commitment but also as expenditure in R&D which is a difficult expense in publically owned facilities like FSL due to competing resources [6] [11] . However, investment in training is desirable from both a personal and social perspective.

Thus, FSL’s human capital can add value if it contributes to lowering costs and providing increased performances. The human capital indicators such as training attended and team-work practices have a positive association with organizational performances [12] [13] . In this study, FSL employees who attended training were used as a sample in order to assess the capital investment in terms of training at work (academic development), delays in professional development (stagnation) and professional development challenges among staff of different professions [14] . Human capital enhancement paves a way for greater innovativeness and this in turn offers positive implications on firm performance and return of investment (ROI) of firms [15] [16] [17] . Firm performance is positively impacted by the presence of human capital practices [18] [19] , while human capital development is also a prerequisite to good financial performance [2] [15] [17] [20] .

Longevity is a measure of how long an employee has been working in the FSL (measured in years). This study differentiates between simple longevity (years worked in a given organization) and the newly introduced concept of complex longevity (by considering the initiatives made to improve the academic levels of the staff while building their longevity in the FSL). This paper presents the mathematical formulation for quantifying workplace complex longevity and tries to answer the question: how much of a competitive advantage is employee longevity? Employee longevity (simple and complex) is a signal of a strong company that has established some competitive advantages. Employee longevity suggests they have a lot of experience and therefore likely to be very efficient and effective. Longevity shows that the company is growing and improving over time. A growing company keeps things interesting for good employees by providing them new challenges and professional growth opportunities. Moreover, longevity suggests that the company continues to provide value to its customers and is able to raise prices or improve margins or both. A company cannot keep employees over the long-term without steady compensation increases and therefore the company needs to be creating and capturing value to be able to keep those employees.

Organizational stability stimulates longevity, because good employees stick around. High employee longevity in FSL shows that the organization has found a rhythm of work that is balanced. Employee longevity suggests that the workload (normal and the heavy bursts in FSL) is sustainable by the employees over the long term.

However, arguments against longevity exist and there are some logical reasons why longevity may not be the best tool for all organizations. For companies that need to change and adapt to new conditions, doing that with legacy staff can be difficult. Employees with experience outside the company (and who has dealt with such changes), are required to initiate major change initiatives without help of outside consultants. Having a mix of legacy and newer staff will help in moving forward, while making necessary adjustments.

Workplace learning is conceptualized in broad and diverse ways, and essentially covers a mix of the issues pertaining to both organizations and workers [21] . It can refer to learning to enable work (including entry into professions and continued professional development) and, learning at work (through structured courses, training, workshops, and so on as well as “informally”). This paper focuses on academic development for staff while at work, that is, embarking on further studies during their life at FSL and attaining different certificates as shown in Figure 1.

This diversity of theories is problematic because: “[m]any researchers construct their model, conceptualization or theory of learning, with the explicit claim or by implication that it might adequately cover all aspects of workplace learning, in all contexts” [22] . This has created a potentially very confusing picture of learning associated with work. Thus, there was a need during development of this research, to clearly identify the type of learning, i.e., academic development of FSL staff. Delimiters of informal learning include problem framing capacity and intellectual ability, although informal learning can be enhanced by critical reflectivity, proactivity and creativity.

The study was conducted using GCLA as a study area, details of which are shown in Table 1. The key components included employment trends, academic

certificates, attendance in short courses and simple and complex longevity. The forensic chemistry and toxicology laboratories were combined in this analysis due to lower number of staff.

In this study, it was assumed that a strong relationship exists between longevity and academic development and that certificates attained while at work are relevant to the performance and competitiveness of the FSL. Moreover, only existing employees were considered in this analysis to assist human resource management team to decide on placement of staff in different areas. It was further assumed in this study that employees may enter the FSL at any point in time with any certificate indicated by circles or boxes in Figure 1.

This objective was accomplished through the assessment of staff experience and longevity in FSL as part of the laboratory’s staff credentials or certificates which reflect broad, in-depth knowledge, sufficient expertise within the organization. Staff experience was expressed using simple and complex longevity. Simple longevity or experience, L_s, is defined as the period in years from first employment with FSL to date, given as per Equation (1):

L s = Y t d − Y e (1)

where Y_td = year to date, (Y2015 for this case), and Y_e = year of first employment.

For a given laboratory, unit or zonal operations, the total staff simple longevity is determined as per Equation (2):

L s t = ∑ i = 1 N s ( L s , i ) (2)

Let N_s be the number of staff in a given laboratory or unit, the average simple longevity can be determined using Equation (3):

L s ¯ = 1 N s ∑ i = 1 N s ( L s , i ) (3)

Depending on the qualification during the first employment in the FSL, that is, BSc, MSc or PhD, the corresponding arbitrary points, denoted as P_i, was assigned to each qualification, that is, P_i = 5, 10, or 20, respectively. The values of P_i were arbitrarily selected in that order to differentiate the weights of BSc, MSc and PhD certificates. Any other values could be selected in that increasing order. Each staff score, S_c, is thus defined as per Equation (4):

S c = P i × Y i (4)

where Y_i is equal to years the degree has been used in FSL or L_s for the specific degree.

Given that an employee can only have a maximum simple longevity of 40 years (employed at the age of 20 years and retiring at the age of 60 years) then the maximum score is obtained when employed with PhD on the first day, as per Equation (5):

max ( P i Y i ) = P i ( = 20 ) × Y i ( = 40 ) = 800 (5)

If at employment date in 2000 an employee had a BSc, then this BSc will have a value of Y_i of 15 years at a reference year, Y2015 (denoted as to date). Moreover, if such an employee acquires an MSc degree in Y2010, then, the value of Y_i for MSc will be 5 years in Y2015. All staff will have a specific score value, P_iY_i less than 800, based on which, a normalized score for each staff can be defined as per Equation (6):

N s c = P i Y i max ( P i Y i ) = P i Y i 800 (6)

The maximum of 3 certificates for each staff were considered in this study, that is, at BSc, MSc, and PhD levels, defined as j = 1, 2, 3. The total normalized score, N_sct is defined as complex longevity for each staff, given as per Equation (7):

L c k = N s c t = L j = ∑ j = 1 3 ( P i Y i 800 ) (7)

For each value of j, a different degree is considered, and the time since it was received is multiplied by the degree score, P_i. Each staff will be represented by a single value of N_sct or L_c which is the measure of how useful the academic qualification of the specific staff has been in the FSL, and also indicates a measure of staff’ experience. The quantity, L_c, is thus a compound measure taking care of both time elapsed since a given degree was obtained and academic credentials possessed thereafter. For comparison between different laboratories or FSL units, the total values of L_c for all staff in the laboratory can be used. Assuming that a laboratory has N_s staff members, then the staff members will vary as k = 1, 2, 3, …, N_s, then total complex longevity for that laboratory will be determined as per Equation (8):

L c t = ∑ k = 1 N s [ ∑ j = 1 3 ( P i Y i 800 ) ] (8)

For a laboratory or unit with Ns staff, the average complex longevity can be determined as per Equation (9):

L c ¯ = 1 N s ∑ k = 1 N s ( L c , k ) (9)

Table 2 shows the sample calculations for L_c and L_ct for laboratory staff based on Equations (1) to (9).

Higher value of L_c implies that a specific employee has worked in the laboratory for many years with those years supported by degrees or certificates obtained while working in the FSL.

Another measure of staff experience was established through academic development index where courses relevant to the job requirements are taken. Academic

development is a factor of skills gained during the studies, as well as a demonstration of effective ways to study and manage time. Given the year of employment, Y_e, with a starting qualification (Certificate, Advanced Diploma, BSc, MSc or PhD), any added degree or certificate, Y_t years later, adds to staff academic development. The academic development index, denoted as A_d, quantifies the delay time for a specific staff from one degree or certificate to another, determined as per Equation (10):

A d = 1 + [ ∑ i = 1 n ( 1 Y t ) ] + 1 L s f d (10)

where Y_t = years from the first graduation, to the next graduation, while working within the FSL, and L_sfd = simple longevity of last degree or certificate in years, and n = number of degrees or certificates. The base value of A_d = 1, corresponds to the value of A_d for the certificate leading to employment in the FSL and n is the number of degrees or certificates attained. When L_sfd = L_s, a condition satisfied when an employee did not attain any other degree or certificate from first employment, then adding 1/L_s to A_d signifies that an employee who had worked longer in the laboratory should have made efforts in attaining a next certificate, provided that the last certificate was not a PhD. A measure of delay is given by the reciprocal of L_sfd or L_s. Higher value of A_d signifies that a given staff has gained additional certificates faster or in short time intervals, while working within the FSL. For a laboratory with N_s staff, the average academic development index was determined as per Equation (11):

A d ¯ = 1 N s ∑ i = 1 N s A d , i (11)

Higher values of A_d signify staff who acquired the degrees in short time intervals (shorter Y_t and hence high reciprocal values). Lower value of A_d indicates that the corresponding staff attained the degree after a longer time interval (high Y_t and hence lower reciprocal values) or none of certificates were attained after employment (routes J, K, L, N, Q, D in Figure 1). Figure 3 shows the conceptual model used for determination of academic development index. Table 3 shows sample calculations for A_d from a sample laboratory with 6 staff members. After computing the A_d for each employee in FSL, comparison of staff academic development index will be used for comparing the different laboratories or units.

Figure 2 shows the time variations of percentage staff with FTC, BSc, and MSc (out of N = 171 employees) from the Y2000 to Y2015. This comprise of laboratory carders which can perform analysis and maintain laboratory equipment and facilities. The percentage of employees with BSc rose starting from 3% to 18% between Y2004 and Y2015, respectively, being the highest throughout the study period. The number and hence the fraction of employees with MSc increased in the same period from about 3.8% in Y2014 to 9% in Y2015 due to increased training opportunities for MSc. This increase of employees with science degrees is a result of human resource planning during employment and internal FSL carrier development program for employees and their personal efforts by staff embarking into MSc programs with most of such carrier development sponsored by the FSL led to improved number of MSc holders.

The decrease in BSc percentage from 5% to 3% between Y2000 and Y2004, respectively, can be attributed to the need for business competitiveness which necessitated introduction of additional skills or professions and disciplines such as certificates, to complement the core carder for new functions such as accounting and procurement management which slightly diluted the BSc. Chemists with BSc have been given great opportunities and support to acquire MSc in order to improve the FSL analysis capability but also as a carrier or professional development requirement from a senior chemist level to a principal chemist (as per Figure 1). This is depicted by the increase in percentage of staff with MSc, shown in Figure 2.

Figure 3 shows the trends in percentage of different certificate holders in the FSL laboratory carders for the three consecutive five-year terms from 1999 to 2015. While the percentage of BSc increased from 26.7% to 37% in 15 years, MSc fraction dropped slightly from 23.6% to 22.5%. The percentage of FTC holders has been decreasing from 17.4% before 2005 to 7.9% by 2015. While the actual number of BSc holders has been on a rise from 2005 to 2010 and also from 2010 to 2015, the percentage increase observed was small, attributable to the similar increase in the number of degrees or certificates from social sciences, that is, diploma and certificate holders for support cadres.

Figure 4 shows the overall distribution of the academic levels from Y2000 to Y2015, together with a snapshot of the distribution for the Y2015 for BSc, FTC, and MSc. It is interesting to note that BSc and MSc comprise of largest parts of 28.6% and 14.3%, respectively, on an overall basis. The functional requirements for BSc and MSc are complemented by FTC holders and in some cases by diploma holders (laboratory assistant), keeping the FSL at its competitive edge. The snapshot for the year 2015 alone shows that the core laboratory cadre comprise of 46.7% of the whole workforce, which is still low. The proportion of MSc at 31% of the laboratory cadre is encouraging as it indicates higher leadership and succession potential within the FSL [23] .

Figure 4 shows also that there is an increase in the number of diploma holders compared to the past, mainly due to the need for improvements in laboratory attendants’ duties, accounts and financial management, and library services to monitor sensitive documentation for confidentiality and staff records management. In the past, such cadres were inexistence, leading to staff complaints in the records, remunerations, and pension funds management. However, the number of diploma holders need to be minimized while increasing the scientific workforce for the competitiveness improvement of the FSL, especially in delivery of its core functionalities.

Figure 5 shows the time series of percentage of support carders with different certificates from Y2000 to Y2015. The fraction of staff with diplomas also increased from Y2004 to 2015, reaching a maximum of about 20%. This can be attributed to the increased demand for secretarial services, assistant accountants, librarians, laboratory attendants, and registry. With exception of certificate holders, most of the academic certificates for support cadres are emerging or new to the FSL portfolio. For example, CPAs emerged in 2009, advanced diploma in Y2008, MBA in Y2008, while CPSP certificates were first presented in 2011. Up to Y2004, the support cadre comprised workforce with diplomas and certificate holders only, while between Y2004 and Y2008, advanced diplomas were added to the workforce portfolio. Such an emerging carrier growth development for support carders is necessary for keeping the competitive edge of the FSL.

Results in Figure 5 show the diversification of workforce from Y2004 onwards from financial management and procurement management to human resource management a move supported by researchers in human resource management [23] [24] . Thus, academic skills expansion was an inevitable move for FSL. Most of employees took evening studies to sharpen their carriers, but also to attain promotions. Investment in training has improved the FSL’s financial standing. Moreover, attending customer needs require academic and professional competence. The FSL employees are currently capable of re-orienting in different

ways of working depending on situation. Training can help solve these performance problems by explaining the details of the job aiming at reducing duplication of effort in the workplace. The time spent correcting mistakes and the problem solving necessary to correct poor performances is reduced by training. Improved performance from employee training and diversification can reduce staff turnover, lower maintenance costs by reducing unnecessary equipment breakdowns and result in fewer customer complaints. Better performance from employees typically creates less need for supervision and brings increase work output.