Economic assessment of SSE s human capital Summary Report

Transcription

1 Economic assessment of SSE s human capital Summary Report February 2015 Final

2 Contents Executive summary [03] 1 Introduction [04] 2 Economic value of SSE s human capital [09] 3 Economic impact of SSE s training programmes [14] 4 Concluding remarks [20] Appendices [22] PwC 2

3 Executive summary About this report: Following from the estimation of SSE s economic footprint in the UK and Ireland, SSE asked us to assess the value of its human capital the skills and capabilities of its employees. Human capital is a key driver of economic and business growth and our analysis aims to provide a new perspective on the strategic importance of SSE s employees to its business model. In this report we look at SSE s human capital from two perspectives. Firstly, we estimate the economic value of the human capital employed by SSE as per 1 April 2014, at the beginning of SSE s 2015 employee performance year. Our analysis covers all of SSE s employees. Secondly, we estimate the net impact on expected future employee productivity of participants in two of SSE s training programmes who started in the financial year 2013/2014 (FY14). Participants from all business segments in both the UK and Republic of Ireland are considered. For both types of analysis we built on existing methodologies from human capital and economic accounting to develop a methodology for valuing the human capital employed by SSE. The methodologies used estimates of future expected earnings for valuing SSE s human capital and the economic benefits of its investment in training programmes. Key findings: SSE economic value of human capital As of 1 April 2014 the economic value of SSE s human capital the skills and capabilities of its employees is estimated to be 3.40bn.* On average this corresponds to 173,000 per head for a total of 19,631 SSE employees included in our analysis. Economic impact of SSE s training programmes The total expected net economic impact of SSE s Technical Staff Trainee (TST) and Apprenticeship programmes that started in FY14 is estimated to be 17m. The net economic impact of SSE s Technical Staff Trainee (TST) programme was 7.65 per 1 invested, while this was 4.29 for its Apprenticeship programmes. * This value does not constitute a fair valuation of SSE s workforce, as it does not represent the market price of SSE s employees. PwC 3

4 Introduction

5 Section 1 Introduction Purpose, scope and limitations of our analysis Purpose and contents Over the past year we have been working with SSE to estimate the company s footprint on the UK and Irish economies. In the most recent report for the UK, we estimated that SSE contributed 8.9bn to UK Gross Domestic Product (GDP) and supported over 113,000 jobs in the UK in financial year 2013/2014 (FY14). 1 Following from this work SSE asked us to assess the value of the human capital the skills and capabilities of its employees employed by the company, as well as the economic impact of two of its main training programmes. SSE s purpose in doing this was to understand further the value drivers of human capital and ways in which the investment in training programmes can add value to the employees, the business and the wider economy. In Section 2 of this report, we take an economic look at the human capital embodied in SSE s workforce. The skills and capabilities of an organisation s workforce have long been thought of as a form of capital a company uses in its value creation process. There are few examples of companies that have measured and reported the value of the human capital contained in their organisations, reflecting the lack of consensus as to how to measure it. 2 For SSE, we have developed a customised approach based on economic and business literature in this field. In Section 3 of this report, we present our analysis of the economic impact of two key training programmes that SSE offers. These are SSE s Technical Staff Trainee (TST) programme and its Apprenticeship programme. 1 SSE s Economic contribution to the UK Financial year 2013/14, PwC, 2014, 2 See for example: Abeysekera and Guthrie, In accounting, and economics fair value is a rational and unbiased estimate of the potential market price of a good, service or asset. Scope Business segments: All of SSE s business segments are covered, including Networks, Wholesale and Retail. Our analysis doesn t cover employees in SSE jointly held companies. Geography: Our analysis covers the United Kingdom and the Republic of Ireland, which are the two countries where SSE has a presence. Time period: The total economic value of SSE s human capital is based on SSE s workforce as per 1 April 2014, which is the start date of SSE s 2015 employee performance year. The economic impact analysis corresponds to the lifetime impact created through the TSTs and Apprentices that joined SSE in FY14. Economic impact: Our valuation of the economic impact of SSE s training programmes is a net analysis as it takes into account a counterfactual scenario. We only look at the direct impact and do not consider indirect and induced economic impacts. Limitations The methodology developed to measure the economic value of SSE s human capital is informed by literature in the field of human capital and national accounting. The monetary values presented do not constitute a fair valuation of SSE s workforce, as they do not represent the market price of SSE s employees. 3 Furthermore, as human capital is not an asset owned by SSE, the results of our analysis are not meant to be incorporated in SSE s financial accounts. Our analysis of the economic impact of SSE s training programmes uses a combination of primary SSE data and supporting data from the literature. The projected outcome is based on an average TST and Apprentice and cannot be interpreted as the expected career progression for every single programme participant. Data used for both analyses were provided by SSE and have not been audited by PwC. PwC 5

6 Section 1 Introduction About SSE SSE plc ( SSE or the company ) is one of the largest companies in the UK, part of the FTSE100, and the only major energy provider which is both UK headquartered and operates exclusively in the UK and Republic of Ireland. Its core purpose is to provide the energy people need in a reliable and sustainable way 4 through its involvement in the production, generation, storage, transmission, distribution and supply of energy and related services. SSE s business is organised into three segments: Networks, Wholesale and Retail. In FY14, SSE s reported profit before tax was 611m and it employed a total of 19,749 people across the UK and Republic of Ireland as of 1 April Table 1.1: SSE s business in FY14 Revenue: 30,585m Operating profit: 611m Employment: 19,749 employees (1 April 2014) (19,631 included in our analysis) Networks Transmission and distribution of electricity: Covers 130,000km of overhead lines and underground cables in the UK Connects to 3.7m homes and businesses in the UK Wholesale Production and storage of gas, generation of electricity and energy portfolio management: Total electricity generation capacity of nearly 11.7 GW 28% of total capacity is from renewable sources (wind, biomass and hydro) Retail Supply of electricity and gas and other services such as electrical contracting to business and household customers: 9.1m household and business customers Three UK brands: SSE Southern Electric, SSE SWALEC and SSE Scottish Hydro One single brand in Ireland: SSE Airtricity Source: SSE Picture source: SSE 4 SSE website. PwC 6

7 Section 1 Introduction What is human capital and why do we measure it? What is human capital? A business relies on a number of different capitals for its value creation process (see Figure 1.1). The International Integrated Reporting Council (IIRC) defines capital as stores of value that, in one form or another, become inputs to the organisation's business model. ( ) Not all capitals an organisation uses or affects are owned by the organisation. 5 The Organisation for Economic Co-operation and Development (OECD) defines human capital as the knowledge, skills, competencies and other attributes embodied in individuals or groups of individuals acquired during their life and used to produce goods, services or ideas in market circumstances. 6 Figure 1.1: Six types of capital according to the IIRC Intellectual capital Financial capital Manufactured capital Social and relationship capital Human capital = Capitals that are well documented and reported = Capitals that are not well documented and/or reported Financial and manufactured capital are well documented and accounted for in a company s financial statements. However, human capital can only be partially found in financial statements, for example indirectly in the valuation of a company s goodwill, and there is no consensus in the literature on how to account for it. 7 Why measure human capital? From both an economic and business perspective, there has been increased interest in measuring the human capital embodied in individuals. From a national perspective, the interest in human capital measurement has grown as it is found to be an increasingly important driver of economic growth. The OECD s Human Capital Project researches methods for including human capital in national accounting. 8 The UK Office for National Statistics (ONS) has measured the value of the UK s human capital since Equally businesses recognise that human capital is an important driver of business value creation. Creating a better understanding of the strategic significance of employees to a business may give insights into the drivers of future business growth. In the business literature, a number of methods have been developed to provide a quantitative measure of the human capital of an organisation. 10 There are, however, few examples of companies that have actually done such analysis. Natural capital Source: Adapted from IIRC, IIRC, See for example OECD, See for example: Dean, McKenna and Krishan, See for example Liu, See for example ONS, See for example: Andrade and Sotomayor, PwC 7

8 Section 1 Introduction Measuring capital stocks and flows Two types of analysis measuring stocks and flows At SSE s request we have developed two methodologies to gain an insight into the importance of human capital for its business. In line with other forms of capital, human capital can be thought of as a stock that can be drawn from. People are endowed with human capital, which they can add to over time. The stock value of human capital can be thought of as the balance sheet value of assets. A change in stock is referred to as flow in economics. A positive flow in human capital could result from investment in human capital. The payment on wages is a negative flow, as human capital is used. The flow can be considered to correspond to a profit & loss account. Figure 1.2 illustrates the interaction between human capital stocks and flows at a company level. The flows are examples of factors that could affect the overall value of human capital between two points in time. Some of these factors can be partially controlled by the company, e.g. retention rate or training, whereas others less so, e.g. early retirement. In this example, the net flow is positive, but the economic value of human capital can also decrease between two years. Figure 1.2: Illustrative example of the relation between capital stocks and flows In our analysis we measure the economic value of SSE s human capital at a specific point in time, which in this case is 1 April The estimated value is a snapshot that is based on the characteristics of all of SSE s employees on the valuation date. The results of this analysis are presented in Section 2 of this report. To complement the analysis of the economic value of human capital, we also performed an assessment of the economic impact of SSE s investment in formal staff training. This can be interpreted as the benefits of the flow in human capital, expressed in terms of the expected uplift in lifetime earnings and productivity. The results of this analysis are presented in Section 3 of this report. Both approaches build on and add to the field of human capital accounting, by adapting already established methodologies to a company level and context. These approaches should be refined over time as insights and data quality evolve. Stock in year t Leavers New joiners Lower than expected productivity growth Higher than expected impact of training Increase in discount rate Higher average retirement age Stock in year t+1 Key: Negative flow Positive flow Change in number of people Change in human capital value per person Source: PwC PwC 8

9 Economic value of SSE s human capital

10 Section 2 Economic value of SSE s human capital Methodology summary (1/2) Methodologies for measuring human capital A wide range of methods have been developed in the field of human capital accounting since the 1960s. 11 Some of these approaches aim to place a monetary value on human capital to fit in with the measurement of other forms of economic capital and to be incorporated in existing accounting structures. At a high level, the OECD distinguishes between three approaches to measuring human capital: Indicator-based approach. This approach does not intend to monetise the value of human capital and instead focuses on education indicators, such as qualifications obtained. 2. Cost-based approach. This approach stipulates that the economic value of human capital is approximated by the investment into the accumulation of human capital. For example, the financial costs and time invested in obtaining a university degree. 3. Income-based approach. This approach equates the value of capital to the present value of the expected future income streams. In the case of human capital these are expected future labour earnings. Our approach In order to measure the human capital employed by SSE, we opted for an approach that allows for monetary valuation of human capital. We used the income-based approach as it is consistent with the approach taken by the ONS. According to the income-based approach, the economic value of human capital employed by SSE is the sum of the discounted expected future earnings of each individual that works for the company. We have adapted the approach to a company level by making adjustments for the fact that employees are likely to leave the company at some point in time. The adjustments we make are for retirement, turnover and other leaving reasons including health issues and premature mortality. We use SSE s Weighted Average Cost of Capital (WACC) to discount expected future earnings. This valuation does not account for new employees after 1 April Figure 2.1: Key steps of our approach Economic value of human capital Sum of expected future labour earnings = x x Adjustments for time spent with SSE Discount factor Source: PwC 11 See for example Lev and Schwartz, 1971 and ONS, See for example Kwon, 2009 PwC 10

11 Section 2 Economic value of SSE s human capital Methodology summary (2/2) Key principles A number of key assumptions underlie the income-based approach, including: Labour is paid according to its marginal productivity, hence earnings are reflective of the skills and competences of employees. We use actual SSE data on employee compensation. The method is reliant on the use of age-earnings profiles from SSE to project expected future earnings. Expected future earnings are dependent on age, as this is a proxy for the increase in the skillset of an individual. The estimation of an individual s expected future earnings is determined by her or his characteristics on the valuation date. For example, we do not factor in the probability of an individual changing job roles. We use SSE s WACC to discount the expected future earnings. The WACC is higher than the discount rate used if the analysis was done from a national labour force perspective, as it accounts for additional company-level risks. Refer to Appendix A for additional explanation of the methodology and key assumptions and Appendix C for the sensitivity analysis. Table 2.1 summarises some of the key statistics for SSE s workforce. Of these, remuneration, age and retention rate are variables in our analysis. The other data are included for information purposes. Table 2.1: SSE s workforce statistics of 1 April 2014: Figures Total number of employees included in the analysis 19,631 Average remuneration ~ 30,000 Average age ~ 40 years Gender distribution Female: 30%, Male: 70% Average retention rate ~ 91% Geographical distribution UK: 96%, Republic of Ireland: 4% Source: SSE PwC 11

12 Section 2 Economic value of SSE s human capital Results: key findings Figure 2.2: The total economic value of human capital employed by SSE SSE 3.40bn We estimate that the total economic value of SSE human capital was 3.40bn as of 1 April This is a monetary measurement of the amount of human capital embodied in SSE employees adjusted for the period of time that they are expected to work for SSE. Note that this value is lower than the total human capital value embodied in SSE s employees during their entire working life, as we adjust for leaving reasons. In the theoretical scenario that employees would never leave SSE, the economic value of employed human capital would be much higher as SSE is able to access it over the individual s full working life. 3.40bn is our central estimate, based on the best available assumptions. Appendix C includes a sensitivity analysis of key factors that impact this value, including the employee retention rate and WACC. In Table 2.2 below we place the value of SSE s human capital in the context of a number of key financial indicators from its FY14 financial accounts. Such indicators could potentially be tracked over time, to inform the extent to which human capital is efficiently employed. Table 2.2: Key financial ratios Revenue/Human capital 9.00 Operating profit/human capital 0.25 Human capital/property, plant and equipment 33 % Human capital/total assets 16 % On average this corresponds to 173,000 of human capital Source: SSE, PwC analysis Human capital/net assets 66% Source: SSE, PwC analysis per head for a total of 19,631 employees. PwC 12

13 Section 2 Economic value of SSE s human capital Results: breakdown by geography Figure 2.3: Geographical breakdown of SSE s human capital value Scotland: 1.12bn 6,241 employees 180,000 of human capital per head Northern Ireland: 0.02bn 106 employees 165,000 of human capital per head Republic of Ireland: 0.17bn 801 employees 213,000 of human capital per head Figure 2.3 shows a breakdown of the total human capital value by geography in which SSE operates. We estimate that most of the economic value of SSE s human capital is contained within the workforce in England and Scotland. This is predominantly driven by the high proportion of total SSE staff based in these geographies. The average human capital per head is the highest in the Republic of Ireland. Employees here have higher than average wages, reflective of the high-skilled job positions at SSE Airtricity. Additionally, the workforce is younger than the SSE average, which means the expected time these employees are expected to spend with the company is longer than in other geographies. Northern Ireland and Wales have a comparatively lower average human capital per head, which is largely due to a concentration of jobs with lower qualification requirements. As England and Scotland both employ people with a wide range of skills, the average human capital values per head in these geographies are close to the SSE average. Wales: 0.27bn 1,798 employees 148,000 of human capital per head England: 1.82bn 10,685 employees 170,000 of human capital per head Source: SSE, PwC analysis PwC 13

14 The economic impact of SSE s training programmes

15 Section 3 The economic impact of SSE s training programmes Methodology summary (1/3) Assessing economic impact from human capital investment In addition to the economic valuation of the human capital employed by SSE, we analysed the economic impact of two of SSE s training programmes. As training increases the skills and capabilities of individuals, it is expected to increase an individual s productivity and associated earnings. This, in turn, increases the value of the human capital. In the UK, there is a wide body of research that assesses the earnings premium individuals can expect to experience after completing education and professional training. 13 In addition to increasing labour earnings, there is evidence from the literature that supports the notion that there are additional benefits for the companies that employ these individuals, as some of the increased productivity monetises as business profit. 14 In line with the literature, our approach assumes that Gross Value Added (GVA, see box 3.1) per head increases at the same rate as the expected increase in earnings. This GVA premium is therefore assumed to be equivalent to the earnings premium. For the purpose of our analysis, we define the benefits of training in terms of economic impact. While training can provide other benefits to the individual and the company, such as increased motivation and self confidence, we did not explicitly assess these in our analysis presented here. 13 See for example McIntosh, 2002; Patrignani and Conlon, 2011; London Economics, 2011a; London Economics, 2011b. 14 See for example Dearden et al., After adjusting for taxes and subsidies on products, a component of GDP which is not generally included in the calculation of GVA. Box 3.1: Defining economic impact GVA is a measure of the value generated in the economy and represents the difference between the value of goods and services sold by a company and the bought goods and services used as an input to production. Hence, it is the company-level equivalent of GDP: adding up the GVA of all individual companies in the economy gets you to a country s GDP. 15 GVA is distributed as profits (defined as Earnings Before Interest, Tax, Depreciation and Amortisation [EBITDA]) and wages. The increased productivity is split into three elements of value, each accruing to a different stakeholder group: Components of economic impact: Source: PwC Corporate (Profit) Individual (Wages) Fiscal (Taxes) 1. Increased earnings for the individual employees: corresponds to the increase in wages net of income tax and National Insurance Contributions. 2. Increased profits for companies: corresponds to the increase in profits as a result of a more productive workforce. (Note: the profits estimated are not only expected to accrue to SSE, as employees will leave and contribute to other companies in the future). 3. Increased tax revenue for the Exchequer: corresponds to the increase in tax revenue to the Exchequer as a result of higher wages to the individual. An increase in profits can also result in increased tax revenue because of higher corporate taxes, but this is out of the scope of our analysis. PwC 15

16 Section 3 The economic impact of SSE s training programmes Methodology summary (2/3) SSE training programmes included in the analysis Our analysis covers two of SSE s major training programmes: the Technical Staff Trainee (TST) programme and the Apprenticeship programme. The TST programme is unique to SSE and is fully funded by the company. The Apprenticeship programme can lead to a range of qualifications and receives part external funding support (see Table 3.1). Our approach We estimate the expected economic impact over the full working life of the TSTs and Apprentices that joined SSE in FY14. We use two indicators to summarise the economic impact of this investment: Net Present Value (NPV) of expected future benefits and costs. The benefits are defined as the increase in GVA while the costs are defined as the training costs associated with the programme. NPV is our preferred estimate of the total economic impact of the training programmes. Economic Return on Investment. The value of the benefits obtained for every 1 of total investment in SSE s training programmes, both by SSE itself and from external funding support (if applicable). We used data from the literature to project the expected earnings premium associated with the various qualifications that SSE s training programmes offer. The earnings premiums from the literature are considered to be a reasonable proxy as they correspond to the entry requirements and expected qualifications of SSE s training programmes. Combining these premiums with data on labour productivity in the UK electricity sector and earnings data of SSE employees, we estimated the absolute value of the expected uplift in GVA per head over an individual s working life. Table 3.1: description of SSE s training programmes Number of individuals that joined in FY14 Technical Staff Trainees (TSTs) Apprentices Entry requirements Minimum of A2 levels Minimum of 4 GCSEs at C Qualification expected Foundation Degree National Vocational Qualification level 2 or 3 Programme length 3 years 3 to 4 years Relevant productivity premium 13.8% 7.9% (level 2) 13.3% (level 3) SSE funding Around 15,000 per year Between 4,000 and 12,000 average annual funding per Apprentice (depending on the programme) External funding N/A Between 2,100 and 2,400 average annual funding per Apprentice (depending on the programme) External funders N/A Skills Development Scotland Skills Funding Agency Engineering Construction Industry Training Board Scottish Electrical Charitable Training Trust Source: SSE PwC 16

17 GVA ( ) Section 3 The economic impact of SSE s training programmes Methodology summary (3/3) Establishing net impact attributable to SSE The earnings premium is represented by the difference between the expected earnings curve of qualified individuals and what these individuals would have earned if they hadn t obtained this qualification (the counterfactual). In our analysis, the counterfactual is the GVA generated by an individual with the same level of qualification as the entry requirement for the programmes. In this scenario, the individual is not estimated to obtain any further qualifications, but is expected to increase GVA over time with more work experience. Figure 3.1 illustrates how expected GVA increases after qualification. We estimated the counterfactual by deducting the annual GVA premium from the expected future GVA curves for TSTs and Apprentices. In addition, to more accurately establish the net impact of SSE s investment in training programmes, we estimated and adjusted the likelihood that individuals would have achieved the same qualification via other opportunities with similar qualities also available to them. We refer to this adjustment as deadweight, which we assumed to be 50%. As indicated in Table 3.1 (on previous page), several external entities provide funding for SSE s Apprenticeship programmes. Due to this external funding, we cannot attribute the entire economic impact of human capital investment to SSE. In the presentation of our results, we differentiate between the overall impact of the training programmes and the impact which is attributable to SSE based on its proportion of total funding. Refer to Appendix B for additional explanation of the methodology and key assumptions and Appendix C for the sensitivity analysis. Figure 3.1: Estimating qualification impact on expected future earnings Source: PwC Training period Employee expected GVA Counterfactual expected GVA Time GVA premium PwC 17

18 Section 3 The economic impact of SSE s training programmes Results: key findings The economic impact of SSE s training programmes Figures 3.2 and 3.3 show the results of our analysis for the TST and Apprenticeship programmes. Although the economic return per 1 invested is higher for the TST programme, the overall impact of the Apprenticeship programme is higher as there are more participants. As SSE fully funds its TST programme, we attribute the full impact to SSE whereas this is 73% for the Apprenticeship programme. For both programmes, the corporate share of impact is highest, followed by individual and fiscal impact. This is due to the high GVA to earnings ratio in the electricity sector, which means that a proportional increase in profits and earnings leads to a higher absolute increase in profits. Figure 3.2: TST programme economic impact Total economic impact 1.2m 4.6m 1.2m 7.0m. Note that not all this benefit accrues to SSE, as programme participants are likely to change employer over the course of their working life. The extent to which this profit increase is expected to accrue to SSE is dependent on the retention rates for each group. These values represent our central estimate of the economic impact of SSE s training programmes. Refer to Appendix C for a sensitivity analysis of the TST results to our key assumptions, including the earnings premium and the discount rate. Figure 3.3: Apprenticeship programme economic impact Total economic impact 2.4m 6.1m 1.6m 10.1m Attributable to SSE Attributable to SSE 1.2m 4.6m 1.2m 7.0m 1.7m 4.4m 1.2m 7.3m Individual Corporate Fiscal (25 individuals included) Individual Corporate Fiscal (109 individuals included) Economic Return on Investment For each 1 invested in SSE s TST programme it is estimated to generate a return of 7.65 to the economy. Economic Return on Investment For each 1 invested in SSE s Apprenticeship programme it is estimated to generate a return of 4.29 to the economy. Source: SSE, PwC analysis Source: SSE, PwC analysis PwC 18

19 Section 3 The economic impact of SSE s training programmes Results: individual economic impact The impact on programme participant expected future earnings As part of the overall economic impact, our analysis includes the estimation of the expected increase in future lifetime earnings of programme participants. In addition to presenting the aggregate results at programme level, we present the individual impact. Figure 3.4 shows the expected increase in total lifetime earnings for an average TST and average Apprentice. For Apprentices, the result represents the weighted average across the various Apprenticeship programmes. Note that these are expressed in 2014 prices and are discounted to their Present Value in The results assume that the individual continues to work in the electricity sector and that there is continued demand for her or his skillset. Figure 3.4: Expected increase in total lifetime earnings 49,200 21,7oo TSTs An average SSE TST is estimated to experience an increase of 49,200 in their projected net lifetime earnings. Apprentices An average SSE Apprentice is expected to experience an increase of 21,700 in their projected net lifetime earnings. Source: SSE, PwC analysis PwC 19

20 Concluding remarks

21 Section 4 Concluding remarks Concluding remarks This report introduced an approach to assessing one of the main types of capital that a business relies on to create value: human capital. The first part of our analysis illustrates how human capital relates to other forms of capital and provides insight into the factors that drive the accumulation of human capital over time. We found that the economic value of the human capital embodied as of 1 April 2014 in SSE s staff amounts to 3.4 billion. This shows its strategic value relative to manufactured and financial capital as reported in SSE s financial accounts. The second type of analysis shows the value of investing in human capital accumulation. SSE s ongoing investment in training programmes contributes to building human capital for the benefit of employees, the Exchequer, SSE and the wider economy. We estimated that SSE s TST programme is expected to provide future benefits with a Net Present Value of 7 million, while the Apprenticeship programme has expected benefits of over 10.1 million. For new joiners these programmes mean a significant increase in lifetime earnings, and for SSE and the wider economy a positive return on investment. The findings summarised in this report provide SSE with a new perspective on its business and its employees. It shows the strategic importance of human capital in generating future business value and an understanding of how business actions and policies generate wider economic value. In addition, it has also made the point that human capital, similar to other less accounted for forms of capital, doesn t belong to the company but can be nurtured and developed by it; and investing in human capital can generate an attractive return for employees but also for the company that has made such an investment. This report is a summary of PwC s overall analysis on the human capital employed by SSE and its training programmes. Our overall work equips SSE with a more in-depth understanding of the drivers of human capital value, including those that can be directly influenced by SSE to create both wider societal as well as business returns. Human capital accounting is constantly evolving. Substantial effort has been invested at country level, including by the ONS in the UK but there are very few examples of companies that have done this. We have relied on existing economic and business literature to inform our approach, as well as a number of key assumptions which we have aimed to make transparent in this report, which should be refined over time. Additionally, as the quality of the input data improves, so will the robustness of the results. Building on other forms of impact analysis that have been carried out by SSE, this analysis is part of a journey of improving the understanding of the business and the way it interacts, relies on, and changes the society around it. In this case: its employees and the societal impact of investing in them. SSE continues to demonstrate leadership by pioneering approaches in some of the most difficult and less traditional areas to measure. By piloting new approaches to measuring and valuing human capital, SSE is contributing to the debate of how human capital accounting could evolve in the future. PwC 21

22 Appendices

23 Section 5 Appendices Appendix A: Economic value of human capital employed by SSE (1/3) Our approach We apply an income-based approach to estimating the economic value of human capital employed by SSE. This approach uses discounted expected future earnings of SSE s employees as of 1 April 2014 based on their characteristics. Our approach to measuring and valuing human capital is based on literature that has researched this, as well as tested methods used by other organisations including the ONS. It should be noted though that the measurement of capital is open to discussion. The valuation of human capital in particular is highly debated and there is no consensus on how to value it. Capital is defined as an entity functioning as store of value and over which ownership rights are enforced by institutional units, individually or collectively, and from which economic benefits may be derived by their owners by holding it, or using it, over a period of time. 16 Box A.1: Market value of capital T f t+τ-1 V t = τ= 1 (1+δ) τ Where V t = the real market value of an asset at the beginning of year t f = the real rental income earned in each period T = the service life of an asset in years T takes values of 1, 2, 3.T δ = the discount rate Under competitive market conditions capital accountants measure capital assets by discounting future income streams. This is expressed in the equation in Box A.1. The fundamental principle of our approach is the notion that the value of capital is equivalent to the discounted earnings generated by that capital over its working life. The implication for valuing human capital is that we estimate this using the expected future labour earnings over an individual s working life. The core of our methodology, therefore, consists of two elements: Estimate the expected future earnings profile for every individual in an organisation. Determine the length of the individual s working life. The working life in this case is determined from a company perspective. It is the expected length of service of the individual with SSE. The relevant adjustment factors used in our analysis are detailed in step 6 of Table A.1 overleaf. Please note this differs from estimating the capital from an individual or national perspective as retention is not a factor that influences the value in such cases. As we value human capital at the level of an individual employee, we then estimate this for the company as a whole. From a company perspective, the total value of its human capital is simply the human capital embodied in the individuals that make up its workforce. It is calculated as the sum of these individual values adjusted for the time individuals remain as SSE employees. Source: Adapted from the ONS 16 Definition of an asset according to the OECD Glossary of Statistical Terms. Note that we use the word capital throughout this report. PwC 23

24 Section 5 Appendices Appendix A: Economic value of human capital employed by SSE (2/3) Table A.1: Key steps in analysis Step Description 1 Group employees into homogenous groups (i.e. with similar expected future earnings pathways) 2 Estimate relationship between age and earnings for each group 3 Match average age-earnings profiles to individual employees 4 Apply estimated (relative) increase in earnings over time to individual s current earnings 5 Adjust expected future earnings for real productivity growth 6 Make adjustments for the length of time employees are expected to spend with SSE: 1. Retirement age 2. Contract length 3. Health reasons for leaving 4. Mortality 5. Other reasons for turnover (voluntary and involuntary) 7 Discount individual expected future earnings to 2014 values 8 Sum discounted individual expected future earnings of all employees Source: PwC Key notes and assumptions All financial data presented are in FY14 prices, unless indicated otherwise. Where we have used data directly provided by SSE, we have not audited the data. We define labour earnings as gross wages including benefits. Human capital is only calculated for the period that an individual spends with the company. Adjustments are therefore not only made for retirement but also for retention. Human capital is also only calculated for individuals who were part of SSE s workforce on 1 April 2014 and not their replacements. Expected future earnings are discounted using SSE s Weighted Average Cost of Capital (WACC) to account for SSE s business risk. We did not explicitly account for the possibility that an employee may develop new skills through formal education or other development, which would affect her or his future earnings. Rather, age acts as a proxy for someone s development. As an employee grows older, her or his abilities are expected to increase and this is reflected in earnings. Please note that education and all the on-the-job training is therefore captured indirectly through the ageearnings profile, to the extent that the individuals that make up the sample to estimate this profile have particular skills. Our analysis does not cover jointly controlled entities in which SSE has a stake of 50% or less (e.g. Scottish Gas Networks). Jointly controlled entities in which SSE has a majority stake (e.g. SSE Contracting) are included. PwC 24

25 Section 5 Appendices Appendix A: Economic value of human capital employed by SSE (3/3) Table A.2: Main data sources Data point Comments Source Expected future earnings Expected lifetime earnings for new joiners SSE Contract length Probability of leaving SSE due to termination of temporary or fixed-term contract Working hours Employee-specific working hours SSE Voluntary turnover (resignation) Probability of leaving SSE due to resignation SSE Involuntary turnover (dismissal) Probability of leaving SSE due to dismissal SSE Discount rate SSE Weighted Average Cost of Capital (WACC) SSE Real productivity growth Long-term forecast UK: Office for Budget Responsibility (OBR), 2013; Datastream, 2014 ROI: Central Statistics Office (CSO); Datastream, 2014 Retirement age Country and gender-specific UK: Labour Force Survey, ONS; OECD, 2012 ROI: Labour Force Survey, CSO; OECD, 2012 Health leavers Probability of leaving SSE due to health reasons UK used as proxy for Ireland Mortality Mortality rates specific to country and age group UK: ONS, 2013 ROI: CSO, 2013 SSE UK and ROI: Annual Population Survey, ONS, 2011 PwC 25

26 Section 5 Appendices Appendix B: Economic impact of training (1/3) Our approach Our approach is based on the notion that qualifications lead to an uplift in expected future earnings and productivity. Our analysis focuses on the 134 joiners of SSE s training programmes in FY14. We estimate the annual uplift in earnings and productivity over their entire working life, whether with SSE or elsewhere in the economy. Other, non-economic, benefits of training, such as an increase in self-confidence, are not in scope of our analysis. Our starting point is a relation between expected future earnings and age of SSE employees. For the initial training years, we use standard trainee and Apprentice wages. For the years after qualification, we use the age-earnings profiles created for the human capital valuation to estimate wage progression (see Appendix A). To estimate the counterfactual curve, we use evidence from the literature on the uplift in earnings experienced by individuals obtaining similar qualifications to those obtained by SSE trainees and Apprentices. This is illustrated in Figure 3.1 in section three of the report. The premiums are defined as the difference between the qualification required for entry to the training programmes and the qualification that participants obtain upon completion. In addition to increasing earnings, it is assumed that some of the increased productivity will also benefit the company by increasing its profit. The increase in profit is estimated using the electricity sector Gross Value Added (GVA) to earnings ratio (see page 15 for an explanation of GVA). This ratio is assumed to be constant irrespective of whether the individual works for SSE or another company in the UK electricity sector. As both profits and gross labour earnings will generate tax payments we also estimate these using standard UK tax rates. In this instance, we have only calculated employment taxes borne by the employee. The lifetime uplift in expected future earnings, tax and profits is discounted back to FY14 the UK government s discount rate. 17 The cost element is estimated using SSE data on training costs, which include trainer salary costs, college fees and administrative fees, among others. Having estimated both the qualification benefits and costs, we then estimate Net Present Value (economic impact) and Economic Return on Investment in the following way: NPV = sum of discounted future benefits sum of discounted future costs Economic Return on Investment = sum of discounted future benefits/sum of discounted future costs We apply a deadweight factor of 50%, which assumes that half of the individuals would have received training if they hadn t received it through SSE. This is a conservative adjustment informed by SSE s staff working in managing these types of programmes on the basis of their knowledge of participants and other training programmes available in the market. Finally, we attribute the economic impact to SSE on the basis of the funding costs borne by SSE. The overall funding by SSE for its Apprenticeship programme is approximately 73% while this is 100% for the TST programme. The table B.1 overleaf summarises the seven key steps in our analysis. 17 The HMRC long-term discount rate is 3.5% for the first 30 years and changes to 3.0% after. PwC 26

27 Section 5 Appendices Appendix B: Economic impact of training (2/3) Table B.1: Key steps in analysis Step Description 1 Estimate gross earnings curves (real and counterfactual) and associated taxes and net earnings 2 Extrapolate gross earnings to Gross Value Added 3 Calculate difference between the estimated and counterfactual series 4 Estimate external funding available 5 Calculate Present Value of benefits and costs 6 Calculate Net Present Value and Economic Return on Investment from different perspectives 7 Establish SSE attribution and deadweight for total economic impact Source: PwC Key notes and assumptions All financial data presented are in FY14 prices, unless indicated otherwise. Where we have used data directly provided by SSE, we have not audited the data. We have used data from the literature to estimate the difference between expected future earnings with and without the qualification attained through SSE s training. The analysis can be further developed by using more primary data on expected future earnings for individuals without qualifications. We assume that GVA per head is the same, irrespective of whether an individual works for SSE or elsewhere in the UK electricity sector. While our analysis does not involve employee retention rates, it should be noted that the profits these individuals generate over their lifetime will not only accrue to SSE but will be shared with other companies if SSE employees decide to change employer. We have estimated the Income Tax and National Insurance contributions paid by employees only. We do not estimate other tax contributions, such as employer s contributions and Value Added Tax (VAT) and sales tax payments. We also do not estimate corporate tax payments. In terms of costs, we do not assume any foregone earnings, taxes or profits, as we assume that individuals would have earned the same amount during the initial years, had they gone into immediate employment. Our analysis does not cover jointly controlled entities in which SSE has a stake of 50% or less (e.g. Scottish Gas Networks). Jointly controlled entities in which SSE has a majority stake (e.g. SSE Contracting) are included. PwC 27

28 Section 5 Appendices Appendix B: Economic impact of training (3/3) Table B.2: Main data sources Data point Comments Source Expected future earnings Expected lifetime earnings for new joiners SSE Real productivity growth Long-term forecast UK: Office for Budget Responsibility (OBR), 2013; Datastream, 2014 ROI: Central Statistics Office (CSO); Datastream, 2014 Electricity sector GVA to earnings ratio Ratio of Gross Value Added to compensation of employees Office for National Statistics (ONS), 2014 Training costs External funding support Total costs (fixed and variable) of SSE s training programmes Total funding available from external sources for each training programme SSE SSE Qualification earnings premium Expected annual earnings premium after qualification Department for Business, Innovation and Skills (BIS), 2012 Income tax rates and bands Income tax rates and bands for estimating employee tax contributions Her Majesty s Revenue & Customs (HMRC) FY14 rates Discount rate Discount rate used for expected future earnings HMRC Green Book PwC 28

29 Section 5 Appendices Appendix C: Sensitivity analysis Table C.1: Economic value of SSE s human capital Variable Change Economic value of human capital Change in economic value of human capital % Central estimate N/A 3.40bn N/A N/A Discount Rate Attrition Rate Retirement Age Real productivity growth Source: SSE, PwC analysis +20% 3.21bn bn -5.4% +40 % 3.05bn bn -10.2% -20 % 3.61bn bn +6.1% -40% 3.84bn bn +13.2% -20% 3.83bn bn +12.8% -40% 4.36bn bn +28.5% -60% 5.02bn + 1,63bn +47.9% +1 year 3.44bn bn +1.3% + 2 years 3.46bn bn +1.8% + 20% 3.41bn bn +0.3% - 20% 3.38bn bn -0.3% None 3.34bn bn -1.7% Table C.1 shows the sensitivity of the human capital value results to a change in key assumptions. The attrition rate in particular has a large impact on the final result, followed by the discount rate. Table C.2: Economic impact of SSE s TST programme Variable Change NPV (total) Central estimate Discount rate Earnings premium Real productivity growth Source: SSE, PwC analysis Change in NPV % Change in EROI N/A 7.0m N/A N/A N/A +20% 5.9m - 1.1m -16% % 4.9m - 2.1m -30% % 8.5m + 1.5m +21% % 10.3m + 3.3m +47% % 8.5m + 1.5m +21% % 9.8m + 2.8m +40% % 5.6m - 1.4m -20% % 4.1m - 2.9m -41% % 7.6m + 0.6m +8.6% % 6.6m - 0.4m -5.7% 7.17 None 4.9m - 2.1m -30% 5.65 Table C.2 shows the sensitivity of the TST programme results to a change in the key assumptions relevant to this analysis. It also shows the accompanying change in our estimate of the Economic Return on Investment (EROI). As the Apprenticeship programme is based on the same model, the sensitivity of the results of this analysis to the key assumptions is very similar. PwC 29

30 Section 5 Appendices Appendix D: Literature references Abeysekera and Guthrie, Human capital reporting in a developing nation. British Accounting Review, Vol. 36 No. 3. Andrade and Sotomayor, Human capital accounting measurement models. International Journal of Economics and Management Sciences, Vol. 1 No. 3. Dean, McKenna and Krishan, Accounting for human capital: is the balance sheet missing something? International Journal of Business and Social Science, Vol. 3 No. 12. Dearden et al., The impact of training on productivity and wages: evidence from British panel data. Centre for Economic Performance Discussion Paper No 674. Available from: International Integrated Reporting Council (IIRC), Capitals: background paper for <IR>. Available from: Capitals.pdf Kwon, Human capital and its measurement. 3rd OECD World Forum on Statistics, Knowledge and Policy. Available from: Lev and Schwartz, On the use of the economic concept of human capital in financial statements. The Accounting Review, Vol. 46 No.1. Liu, 2011, Measuring the Stock of Human Capital for Comparative Analysis: An Application of the Lifetime Income Approach to Selected Countries. OECD Working Paper No. 41. London Economics, 2011a. The Returns to Higher Education Qualifications. BIS Research Paper No. 45. Available from: ile/32419/ returns-to-higher-education-qualifications.pdf London Economics, 2011b. Returns to Intermediate and Low Level Vocational Qualifications. BIS Research Paper No. 53. Available from: McIntosh, Further Analysis of the Returns to Academic and Vocational Qualifications. Department for Education and Skills Research Report RR370. Available from: OECD, The well-being of nations: the role of human and social capital. Available from: ONS, Measuring the UK s human capital stock: methodology guidance. ile/32354/ returns-intermediate-and-low-level-vocationalqualifications.pdf --human-capital-estimates html#tab-what-is-human-capital- Patrignani and Conlon, The Long Term Effect of Vocational Qualifications on Labour Market Outcomes. BIS Research Paper No. 47. Available from: ile/32326/ long-term-effect-of-vocational-qualifications.pdf PwC 30