Question One (40 Marks) Dangote commenced a Cement manufacturing business in Zambia earmarked to last five years starting 1st January 2015 and ending 31st December 2020. As at 1st January 2015 the Dangote Company had a total of 6,797 and 10,283 female and male employees respectively broken down according to the provinces of operation as follows: • Luapula – Females 500, Males 3000; Western – Females 1798, Males 3452; • Eastern – Females 903, Males 2212; Central – Females 1002, Males 1203; • Muchinga – Females 1400, Males 140; Southern – Females 1194, Males 276. By the end of the period (i.e., 31st December 2020) each department had lost the following number of employees: • Central – Females 117, Males 152; Muchinga – Females 134, Males 121; • Southern – Females 94, Males 124; Eastern – Females 194, Males 138; • Western – Females 215, Males 501; Luapula – Females 187, Males 353. Required: (a) With the aid of a table compute the Wastage and Survival rate in percentage for each department for the period 2015 – 2020. (24 Marks) (b) Calculate the total labour turnover for the period 2015 – 2020 in percentage. (4 Marks) (c) What was the total survival rate in percentage for the period 2015 – 2020? (4 Marks) (d) Explain the meaning of “Wastage” and “Survival” in this context. (8 Marks)

Introduction

Human resource planning (HRP) is a critical aspect of organisational management, particularly in industries like manufacturing where workforce stability directly impacts productivity and operational efficiency. As a student studying human resource management, I recognise that HRP involves forecasting future staffing needs, analysing current resources, and addressing gaps through strategies such as recruitment, training, and retention (Armstrong, 2014). In the context of Dangote’s cement manufacturing business in Zambia, which operated from 1 January 2015 to 31 December 2020, understanding employee attrition through metrics like wastage and survival rates is essential. These metrics help evaluate workforce stability over the five-year period, highlighting potential issues in retention and informing future planning. This essay addresses the given requirements by first computing wastage and survival rates for each department using a table, then calculating total labour turnover and survival rates, and finally explaining the key terms. The analysis draws on established HR theories to provide a sound understanding, while acknowledging limitations such as the absence of data on hires or external factors influencing attrition. The structure ensures logical progression, supported by evidence from academic sources.

Calculation of Wastage and Survival Rates by Department

In human resource planning, wastage and survival rates are fundamental tools for cohort analysis, which tracks a group of employees over time to assess retention patterns (Torrington et al., 2017). For Dangote’s operations, the provinces are treated as departments, with initial employee numbers provided by gender as of 1 January 2015 and losses recorded by 31 December 2020. Assuming no new hires during the period—as the data does not indicate otherwise—the wastage rate for each department is calculated as the percentage of employees lost relative to the initial cohort: (Number lost / Initial number) × 100. Correspondingly, the survival rate is (Initial number – Number lost) / Initial number × 100, or simply 100 minus the wastage rate. This approach aligns with standard HRP practices for evaluating long-term workforce dynamics, though it may oversimplify if external variables like economic conditions in Zambia affected attrition (Armstrong, 2014).

To provide a comprehensive view, the calculations are presented in the table below, incorporating totals for each department. While the data is broken down by gender, the question focuses on departmental rates, so totals are prioritised; however, gender-specific figures are included for deeper analysis, as gender disparities in attrition can reveal underlying issues such as workplace inequality (CIPD, 2020). The rates are rounded to two decimal places for clarity.

The table reveals variations across departments. For instance, Muchinga shows the highest total wastage at 16.56%, driven largely by an exceptionally high male wastage rate of 86.43%, which might indicate gender-specific retention challenges, such as job dissatisfaction or external opportunities (Torrington et al., 2017). Conversely, Eastern has the lowest wastage at 10.66%, suggesting stronger retention mechanisms. These differences could stem from regional factors in Zambia, like economic disparities between provinces, though further research would be needed to confirm this. Critically, while these calculations provide a snapshot, they assume a static workforce, which may not fully capture dynamic HRP elements like voluntary versus involuntary leavers (Armstrong, 2014). Nevertheless, they offer valuable insights for planning future operations.

Total Labour Turnover for the Period

Labour turnover, often used interchangeably with wastage in HRP contexts, measures the rate at which employees leave an organisation over a specified period (CIPD, 2020). For Dangote’s entire operation, the total initial workforce was 17,080 (6,797 females and 10,283 males), with 2,330 losses (941 females and 1,389 males) by the end of 2020. Using the standard formula for turnover rate over the period—(Total leavers / Initial workforce) × 100—the calculation yields 2,330 / 17,080 × 100 = 13.64%. Some sources advocate using average workforce for more accuracy, especially in longer periods: average = (17,080 + 14,750) / 2 = 15,915, giving 2,330 / 15,915 × 100 ≈ 14.64% (Torrington et al., 2017). However, given the question’s focus on the period without specifying averages, the simpler initial-based rate of 13.64% is appropriate. This figure indicates moderate turnover, potentially influenced by industry norms in manufacturing, where rates around 10-15% are common, though higher in developing economies like Zambia due to migration or economic pressures (Armstrong, 2014). Evaluating this, the rate suggests reasonable stability but highlights the need for targeted retention strategies to mitigate costs associated with turnover, such as recruitment expenses.

Total Survival Rate for the Period

The total survival rate complements turnover by focusing on retention, calculated as (Surviving employees / Initial workforce) × 100. With 14,750 employees remaining (17,080 initial minus 2,330 lost), the rate is 14,750 / 17,080 × 100 ≈ 86.36%. This aligns with 100% minus the turnover rate of 13.64%. In HRP terms, a survival rate above 80% over five years is generally positive, indicating effective manpower planning despite challenges (Torrington et al., 2017). However, slight gender differences—86.16% for females and 86.49% for males—suggest nuanced dynamics, possibly reflecting better male retention in male-dominated roles. Critically, this metric has limitations; it does not account for the timing of losses or external factors like Zambia’s economic growth in the cement sector during 2015-2020, which might have encouraged stays (World Bank, 2021). Overall, it underscores the importance of survival analysis in forecasting future staffing needs.

Explanation of Wastage and Survival in Context

In the context of human resource planning for Dangote’s Zambian operations, “wastage” refers to the proportion of the workforce that leaves the organisation over a defined period, expressed as a percentage of the initial cohort. It encompasses various forms of attrition, including voluntary resignations, retirements, dismissals, or deaths, and is crucial for identifying leakage in manpower supply (Armstrong, 2014). For example, high wastage in Muchinga (16.56%) might signal issues like poor working conditions or inadequate compensation, leading to hidden costs such as lost productivity and training investments. Conversely, “survival” denotes the percentage of employees who remain with the organisation throughout the period, highlighting retention success. In this case, Eastern’s 89.34% survival rate exemplifies strong endurance, possibly due to better engagement strategies. These concepts are integral to cohort or life-table analysis in HRP, enabling organisations to predict future vacancies and plan accordingly (Torrington et al., 2017). However, they are not without limitations; wastage does not differentiate between avoidable and unavoidable losses, and survival may mask underlying dissatisfaction if employees stay due to limited alternatives (CIPD, 2020). In a manufacturing context like Dangote’s, understanding these metrics can inform policies to reduce wastage, such as improved training or incentives, ultimately enhancing organisational resilience. Arguably, integrating them with qualitative data would provide a more holistic view, though the quantitative focus here aligns with basic HRP techniques.

Conclusion

This essay has demonstrated the application of key human resource planning concepts to Dangote’s cement business in Zambia, computing departmental wastage and survival rates, total labour turnover at 13.64%, and total survival at 86.36%. These calculations reveal departmental variations, with implications for targeted interventions to improve retention. Furthermore, explaining wastage and survival underscores their role in manpower forecasting, though limitations like data gaps highlight the need for broader analysis. In studying HRP, such exercises illustrate how metrics can address complex workforce challenges, potentially reducing costs and enhancing efficiency in similar operations. Future research could explore causal factors in Zambia’s context to refine these strategies.

References

• Armstrong, M. (2014) Armstrong’s Handbook of Human Resource Management Practice. 13th edn. London: Kogan Page.
• CIPD (2020) Labour turnover and retention. Chartered Institute of Personnel and Development.
• Torrington, D., Hall, L., Taylor, S. and Atkinson, C. (2017) Human Resource Management. 10th edn. Harlow: Pearson.
• World Bank (2021) Zambia Economic Brief: Raising Revenues for Economic Recovery. World Bank Group.