Unum Report 22 10 15 - Cebr ·...

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© Centre for Economics and Business Research

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Disclaimer

Whilst every effort has been made to ensure the accuracy of the material in this document, neither Centre for Economics and Business Research Ltd nor the report’s authors will be liable for any loss or damages incurred through the use of the report.

Authorship and acknowledgements

This report has been produced by Cebr, an independent economics and business research consultancy established in 1992. The views expressed herein are those of the authors only and are based upon independent research by them.

The report does not necessarily reflect the views of Unum

London, September 2015

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Contents

1 Introduction 9

1.1 About Group Income Protection (GIP) insurance 9

1.2 Policy context 10

1.3 Background: The cost to business of employee absence 10

1.4 Long-‐term vs. short-‐term absence 11

1.5 Structure of the report 12

2 The 'GIP dividend' 14

2.1 The macroeconomic appraisal model 14

2.2 Underlying assumptions 15

2.3 The GIP ‘dividend’: Updated findings 19

2.4 The benefits to employees 22

3 The impact on the GIP dividend of rehabilitation and early intervention services 24

3.1 Background and underlying assumptions 24

3.2 The impact on long-‐term absence 24

3.3 Mental health conditions 26

3.4 Musculoskeletal conditions 28

3.5 Including early intervention for both mental illness and musculoskeletal conditions 30

4 The cost of long-‐term sickness absence by 2030 33

4.1 Forecasts of the UK population and workforce 33

4.2 Forecast of long-‐term sickness absence rate 34

5 Conclusions 36

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Key Findings

This report presents Cebr’s analysis carried out for Unum that explores the financial implications for UK businesses of widespread adoption of employer-‐sponsored Group Income Protection (GIP) cover for their employees. This report builds and expands upon our previous study completed in 2012.

Annual cost of long-‐term sickness absence • The objective of this study is to estimate the annual cost of long-‐term sickness absence1 to the UK

economy in 2014. This represents an update to Cebr’s previous 2012 study. In estimating the cost of long-‐term sickness absence, the study incorporates the cost burden faced by employers from a number of areas including occupational and statutory sick pay, absence management costs and the costs associated with staff retention.

• The study found that the annual cost of long-‐term sickness absence to the UK economy amounts to £6.71 billion, equivalent to £208 per employee in 2014. This represents a 3.7% increase on the estimate produced as part of Cebr’s 2012 study, in which costs to the UK economy were calculated at £6.47 billion. This increase can be attributed to the rise in statutory sick pay entitlement (an 8% increase) and the overall number of people employed (which has risen by 6%) during the same period.

• The private sector is expected to shoulder the majority of the overall cost of long-‐term sickness absence. Cebr’s analysis estimated that the annual cost to the private sector was £4.17 billion in 2014, increasing from the £3.13 billion cost estimated in our previous 2012 study. The remaining £2.54 billion in 2014 is incurred by the public sector.

• Focusing on private sector businesses, Table 1 below presents our estimates for the total and average annual cost of long-‐term sickness absence by company size. The high overall cost faced by larger organisations reflects their greater numbers of employees, as well as the more generous occupational sick-‐pay arrangements that tend to be in place in these firms, compared with smaller businesses.

Table 1: Breakdown of total annual cost of long-‐term sickness absence across the private sector, by company size bands

Company size band (no. of employees)

Breakdown of total annual cost of LT absence (£ billions)

5-‐249 1.42 250-‐499 0.21 500+ 2.54

Total private sector 4.17

Total economy, incl. public sector 6.71 Source: Cebr analysis

• Mental illness (including stress-‐related) and musculoskeletal problems (including back pain) are both listed in the top five most common causes of long-‐term sickness absence (CIPD 2014). Our findings suggest that the annual cost of long-‐term sickness absence due to mental illness amounts to £1.88

1 Long-‐term sickness absence, in the context of this study, is defined as a period of absence of six months or more.

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billion. Nearly two-‐thirds (£1.17 billion) of this total annual cost is estimated to fall upon the private sector each year.

• The report also presents projections for the costs of long-‐term sickness absence to the UK private sector in 2030. As the workforce continues to grow and to age, there is an increased likelihood of illness. This can, in turn, be expected to impact on rates of long-‐term absence amongst the working population, anticipated to rise by 4% over the period 2015 to 2030.

• We estimate that the total annual cost of long-‐term absence to the UK private sector in 2030 could rise by 15% to about £4.81 billion from today’s estimate of £4.17 billion. When the public sector is included, the total cost of long-‐term absence is expected to increase from £6.71 billion today to £7.60 billion by 2030.

Motivation for using Group Income Protection and the ‘GIP dividend’ Investment by employers in Group Income Protection (GIP) is one option in their contingency planning and can offer strategic benefits to employers by:

• enhancing, as an attractive non-‐salary benefit for employees, a company’s ability to attract and retain key staff because it provides stable and ongoing replacement of salary to employees if a health condition prevents them from working; and

• allowing regular and certain payments of GIP premiums to be built into forward budgets more easily than a forecast of what can be an inherently volatile resource cost associated with long-‐term absence.

Certainty about budgets and ability to retain key staff are important for business sustainability, especially when the broader economic environment is challenging.

Employers tend not to expect any return of monies invested in other types of insurance as non-‐salary employee benefits. But GIP actually gives something tangible back. It is this tangible return – what we have termed the ‘GIP dividend’ – that our previous study was the first to quantify. This report provides a refresh of our estimates of the GIP dividend using the most up-‐to-‐date national statistical data and updated data from GIP provider Unum. Our key findings on the GIP dividend are:

• Under widespread GIP adoption (a scenario in which all private sector employers insure all their employees under a GIP scheme), we estimate the private sector GIP dividend at £3.68 billion, equivalent to 60.9% of the total expenditure on GIP premiums (Table 2).

• Firms employing 500+ employees are expected to see the largest dividend per annum, with the average firm in this size band estimated to yield a GIP dividend ratio of 76.1%.

• The similarity between the results for firms employing 5-‐249 and 250-‐499 is a function of the assumption of a single average GIP premium per employee insured regardless of firm size. In practice, the average premium per head would tend to fall as more and more employees are included in the policy in larger firms.

• This suggests that the GIP dividends presented in Table 2 for companies employing 250-‐499 and 500+ employees are probably underestimates.

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Table 2: Annual expenditure on GIP premiums and the annual GIP dividend for all private sector companies in each size band


Total spend on GIP premiums (£'s

billions)

GIP dividend (all sources; £'s billions)

GIP dividend (all sources, %)

5-‐249 2.62 1.24 46.2

250-‐499 0.38 0.17 45.0

500+ 2.94 2.27 76.1

Total private sector 5.93 3.68 60.9

Source: Cebr analysis

Assessing the benefits of early intervention and rehabilitation services Insurers offering GIP policies usually offer a range of associated services that can assist an employee on sickness absence to return to work in a shorter period of time. For example, GIP providers can offer rehabilitation and other early intervention services that can help in tackling health issues before they become more serious. This can help minimise the incidence and duration of long-‐term sickness absences and some of these services can be activated in the first or second week of an employees’ absence.

This study analyses the impact of early intervention and rehabilitation services under a number of scenarios, which are compared to the baseline GIP dividend ratio of 60.9% (or, in monetary terms, an absolute GIP dividend of £3.68 billion, as in Table 2 above). These scenarios assess early intervention and rehabilitation services under the following alternative assumptions:

• A proportion (69%2) of employees in all firms having access to these services across all types of illness.

• 100% of employees having access to these services across all types of illness.

• Only those employees on long-‐term absence caused by mental illness having access to the services.

• Only those employees on long-‐term absence caused by musculoskeletal health problems.

• Those individuals on long-‐term absence caused by either mental or musculoskeletal health problems.

Our findings suggest that:

• Employees with access to these services and who utilise them have on average an absence period that is 16.6% shorter compared to those that do not. This translates to a reduction of more than a year (60 weeks) in the average 7-‐year duration of a long-‐term absence assumed in this report.

• In such a scenario, the average private sector firm could see the GIP dividend rise to 65.6% (from the baseline value of 60.9%). In monetary terms this is estimated at £3.95 billion out of a total £5.93 billion invested in GIP premiums being returned to private sector employers across the UK economy.

• Furthermore, if we assume that early intervention and rehabilitation services are accessible to all employees, this figure increases to £4.24 billion, equivalent to a GIP dividend of 70.3%.

• This reduction in absence duration translates into an additional GIP dividend of £85 million, increasing the total for the private sector to £3.76 billion per year. This translates into a 2.5%

2 This is the proportion of employees in Unum’s claims data that have access to early intervention services.

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increase in the overall GIP dividend from 60.9% to 63.4%.

• Almost a fifth (17%) of all fit-‐notes issued for long-‐term sickness absence are for musculoskeletal problems3. This is estimated to cost the economy £1.14 billion per year. The average absence duration is assumed to be 12.3%4 lower for those employees with access to early intervention and rehabilitation services relative to those that do not. This reduction in the duration of claims directly impacts upon the GIP dividend, increasing it from £3.68 billion to £3.71 billion. This is equivalent to a 1.6% increase in the overall GIP dividend ratio from 60.9% to 62.6%.

• Examining the effect of early intervention and rehabilitation services under widespread5 GIP adoption on both mental health and musculoskeletal long-‐term absence claims, this is estimated to provide a £120 million increase to the GIP dividend annually. This translates into a 3.1% increase in the GIP dividend ratio from 60.9% to 64.0% for the UK private sector. In monetary terms, this is equivalent to a rise from £3.68 billion to £3.80 billion per annum.

Summary of early intervention and rehabilitation impact on the GIP dividend • Our findings suggest that a more widespread application of early intervention and rehabilitation

services to the medical conditions that cause long-‐term absenteeism can increase the GIP dividend. This is illustrated in Table 3 below.

• The largest GIP dividend is estimated at 65.6% which could be expected under a scenario where these services are provided for employee use for all causes of long-‐term absence. The GIP dividend with no early intervention services is 60.9%.

• Applying early intervention to specific illnesses only (mental illness and musculoskeletal conditions) produces values for the GIP dividend that sit between the minimum and maximum.

Table 3: Comparison of the GIP dividend ratio under various early intervention scenarios, by company size band


Baseline GIP dividend -‐ no early intervention services

Early intervention services mental health

Early intervention services musculoskeletal health

Early intervention services for mental and musculoskeletal health

Early intervention services for all conditions

5-‐249 46.2% 48.7% 47.9% 49.3% 50.9% 250-‐499 45.0% 47.6% 46.7% 48.2% 49.8% 500+ 76.1% 78.6% 77.7% 79.2% 80.7% Total private sector

60.9% 63.4% 62.6% 64.0% 65.6%


3 Cebr analysis of Fit-‐Note dataset 4 Based on Cebr analysis of Unum claims data. 5 A widespread GIP adoption refers to a scenario in which all private sector employers insure all their employers under a GIP scheme, but this does not necessarily mean they have access early intervention and rehabilitation services.

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1 Introduction This report by Centre for Economics and Business Research (Cebr) examines the financial implications for UK businesses of widespread adoption of employer-‐sponsored Group Income Protection (GIP) cover for their employees. It builds and expands upon work first completed in 2012, which, like this report, was commissioned by Unum, a leading GIP policy provider.

1.1 About Group Income Protection (GIP) insurance Income Protection is an insurance product that, in the event of a claim, provides stable and ongoing replacement of salary to employees whose health condition continues to prevent them from returning to work. The price of this cover is an annual premium. The main strategic benefits for a company are twofold: (i) it enhances, as an attractive benefit for employees, a company’s ability to attract and retain key staff; and (ii) it allows regular and certain payments of Income Protection premiums to be built into forward budgets more easily than a forecast of what can be an inherently volatile resource cost associated with long-‐term absence. Such certainty is important for business sustainability, especially when the broader economic environment is challenging.

Insurers offering GIP policies usually offer a range of associated services that can assist an employee on sickness absence to return to work in a shorter period of time. For example, GIP providers can offer rehabilitation and other early intervention services that can help to tackle health issues before they become more serious, in turn helping to minimise long-‐term sickness absence. Early intervention services can include Employee Assistance Programmes (EAPs), early intervention helplines, vocation rehabilitation services, mental health first aid, positive ageing guidance, cognitive behavioural therapy and physiotherapy.

Given this strategic benefit of improved certainty with respect to cash flows, our original study was motivated by Unum’s request that we establish the monetary impact on UK private sector businesses of a system of widespread GIP cover for employees. The premise for the research was that, whereas employers tend not to expect any return of monies invested in other types of non-‐salary employee benefits, GIP actually gives something tangible back to the employer. It is this tangible return – which we have termed the so-‐called ‘GIP dividend’ – that our previous study was the first to quantify in 2012. This report provides a refresh of our estimates of the GIP dividend using the most up-‐to-‐date national statistical data and updated data from Unum.

This report also builds on our original study, as documented in the March 2012 report. A further objective of this study was to delve deeper into the potential impact on the GIP dividend of the rehabilitation and other early intervention (or return-‐to-‐work) services that can be chosen as part of a GIP policy (becoming active at different points in the process of a long-‐term absence depending on the level of premium paid) or accessed separately as and when required. Specifically, this report explores how these services impact upon long-‐term sickness absence, with a specific focus on cases involving mental illness and musculoskeletal problems.

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1.2 Policy context In 2013, 131 million days were lost due to sickness, with the average worker taking 4.4 days off work. (ONS 20146). Employees are required to provide their employers with a doctor’s fit-‐note if they are absent from work for more than 7 days continuously.

The current legislation states that an employee is entitled to receive Statutory Sick Pay (SSP) if they are too ill to work, for up to 28 weeks. This was set at £88.45 per week for the tax year ending April 2016. Some employers offer Occupational Sick Pay (OSP) to their employees, over and above the SSP minimum, usually providing full pay for a set number of weeks, followed by a tiered reduction in pay over the period of illness. This differs between employers and can even differ between employees within the same organisation, based on seniority, tenure etc.

In an independent review commissioned by the Government, the authors of the Health at Work report7 (Dame Carol Black and David Frost CBE), noted their conception of the ‘ideal’ system as one in which people who are unable to work are swiftly identified and supported. The fit-‐note was proposed by Dame Black in 2008, with the aim of improving the management and cutting the costs of sickness absence for employers.

The Statement of Fitness for Work (known as the ‘fit-‐note’), was introduced in April 2010 across England, Wales and Scotland. The objectives of this were twofold. First, it was introduced with the aim of improving back to work advice for individuals on sickness absence. Second, it was designed to improve communication between individuals, doctors and employers on whether and how the patient can work.8 These would, in turn, be expected to reduce sickness absence levels across the UK.

However, a report by CBI and Pfizer, published in 20139, concludes that while some employers reported positive impacts, the scheme has not yet achieved its full potential. Their survey revealed that under a fifth (17%) of employers consider the fit-‐note has helped change the culture around rehabilitation and return to work, whilst nearly three quarters (72%) responded that it had not helped.

It does not seem unreasonable, therefore, to conclude that the broad consensus is that the fit-‐note is not the panacea that it was expected to be. This only serves to enhance the potential role that more widespread adoption of GIP policies could play, especially those with associated rehabilitation and other early intervention services, in reducing the number and duration of long-‐term absences.

1.3 Background: The cost to business of employee absence The latest joint CBI/Pfizer Absence and workplace health survey 2013 (containing 2012 survey results) reports a median cost to business per absent employee of £622 in 2012, whilst the average cost is estimated at £975 per absent employee. They estimate an aggregate direct cost of £14 billion across the economy as a whole. The 2011 survey (showing results for 2010) reported a higher aggregate figure (£17 billion) for direct costs.

The CBI/Pfizer 2013 report only examines the direct costs of absence. These costs incorporate the salary costs of absent individuals and of their replacements (incl. temporary staff and overtime by existing

6 Office of National Statistics 2014: Sickness absence in the labour market, February 2014 7 Dame Carol Black and David Frost CBE (2011); Health at work-‐ an independent review of sickness absence 8 In other words, an illness might prevent an employee from continuing to undertake their original role, but that employee could be deployed to other types of role elsewhere in the organisation. 9 CBI/Pfizer (2013); Fit for purpose – Absence and workplace health survey 2013

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employees). As outlined in our 2012 report and featured in this report, Cebr shares Unum’s view that it is also appropriate to include the resource costs associated with recruiting and training replacement staff (temporary or otherwise) as a direct cost, particularly in the case of long-‐term absence. The direct costs of absence feature heavily in our evaluation of the expected impact on business of more widespread adoption of GIP.

CBI/Pfizer’s earlier 2010 report10 distinguishes between direct and indirect costs, defining indirect costs as those associated with the deterioration in customer satisfaction or quality of service that can result from absences, but no further examples were provided. The measurement of this particular, less tangible type of indirect absence-‐related cost is difficult and would require the kinds of primary research (surveys, behavioural research etc.) that were beyond the scope of this study. They are not, therefore, taken any further in this report.

What we have taken forward, however, is the idea that long-‐term absence can impose wider business costs, not just those confined to the absent employee or their replacement(s). We have identified these as particularly falling in the area of the administrative and corporate functions of the business (including HR and legal, for instance). These conceptions of what might also be considered ‘indirect’ costs are relatively tangible and thus more conducive to measurement (see Subsection 2.1 for more detail).

This report also expands on our 2012 report with a more granular assessment of the benefits of employees returning to work faster through the use of early intervention and rehabilitation services by employers for their absent employees. The 2012 report included this as a scenario but the analysis was based on anecdotal evidence provided by Unum. The analysis in this report is based on hard evidence from Unum’s own GIP claims data. As well as considering the role of early intervention and rehabilitation in more general terms, we drill down into an examination of the impact of these services on absences related to specific illnesses – namely mental illness and musculoskeletal conditions.

Benefits excluded from Cebr’s estimates of the GIP dividend

The following benefits were excluded from our estimates of the GIP dividend:

• Reduced rates of absenteeism as a result of staff behavioural changes if GIP is included as part of a broader absence management programme, or as a result of ancillary services being included as part of the GIP scheme, such as early intervention and rehabilitation. In other words, employees who feel valued and incentivised by this additional non-‐salary benefit could be expected to be less inclined to be absent, except as a last resort.

• Wider savings associated with faster return to work, such as lower potential damaging impacts on customer relationships or brand. These were identified as indirect savings by the CBI/Pfizer surveys.

To the extent that such benefits also result from the adoption of GIP schemes, the GIP dividend estimates presented in this report could be considered conservative.

1.4 Long-‐term vs. short-‐term absence The 2013 CBI/Pfizer report makes the point that most employers consider an absence in excess of 20 working days or 28 calendar days as a long-‐term absence. The CIPD Absence Management 2014 report11

10 CBI/Pfizer (2010): On the path to recovery: Absence and workplace health survey 2010 11 CIPD Absence management – annual survey report 2014

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distinguishes between short-‐term absences as those up to seven days and long-‐term absences as those of four weeks or longer duration.

However, there is little difference between these sources in terms of their findings on the implications of long-‐term health or personal problems. CBI/Pfizer found that 30% of all working time lost to employee absence was attributable to long-‐term absence in 2012.12 This reduction, coupled with a general downward trend in instances of sickness absence has meant that the 2013 CBI/Pfizer report estimates that the cost to the economy of long-‐term absences has dropped from £6 billion in 2010 to £4 billion13 in 2012. This drop, the report states, is driven by a reduction in the average absence rate per employee from 6.5 days in 2010 to 5.3 in 2012. While we continue to produce different estimates of the cost to employers of long-‐term absence, the scope of our estimates is different as is the definition of long-‐term absence used as the basis for the calculations.14

From the perspective of a GIP insurer, long-‐term absence tends to mean something different than it does to employers. Income protection policies generally involve a ‘deferred’ period, before which claims against the policy cannot be made. For instance, based on a sample of over 750,000 people with Income Protection provided by Unum, the average deferred period is 26 weeks. Income protection providers would, therefore, be more likely to think of long-‐term absence in terms of a period of six months or more.

The purpose of this and our previous study is to focus on long-‐term absence as it defined for the purposes of GIP – while this can vary across GIP policies, any absence in excess of the average of 26 weeks or six months is considered long-‐term. During the deferred period, the employer must bear the costs of the absence and this again is accounted for in our estimates of the GIP dividend. When the deferred period has elapsed, the GIP provider takes over and this can be beneficial when one considers that the claim duration assumptions that underlie our estimates of the GIP dividend are based on absences typically ranging from 2 years to 35 years, with an average absence duration of 7 years.

Rehabilitation and other early intervention (return-‐to-‐work) services (as described earlier in section 1.1) can be used to minimise the number of absences that become long-‐term and to shorten the duration of claims that do become long-‐term. Whereas in our previous study, we had to adopt high-‐level assumptions based on anecdotal evidence, the motivation for the present study was a closer examination of these effects based on a sample of Unum’s GIP claims data. We then sought to understand how the GIP dividend could be impacted if rehabilitation and other early intervention services were made available and used on a more widespread basis. Our examination reveals that these services are having a positive impact.

1.5 Structure of the report The remainder of this report is structured as follows:

• Section 2 examines the ‘GIP dividend’ by first outlining the methodology and assumptions and then presenting the revised results based on the most up-‐to-‐date data.

• Section 3 assesses the benefits that early intervention and rehabilitation services can have for businesses

12 This is a slight reduction from the 32% observed in 2010. 13 The cost estimates by CBI/Pfizer 2013 report include the direct costs of sick pay, lost output and provision of cover through temporary staff or overtime. 14 See footnote 20 below for further details.

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• Section 4 forecasts the cost of long-‐term sickness absence in 2030.

• Section 5 concludes the report by summarising the key findings.

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2 The 'GIP dividend' This section examines the impact upon UK businesses of a more widespread adoption of GIP schemes as a discretionary non-‐salary benefit. The assumptions and methodology used to evaluate these impacts are outlined herein. This section has been broken down into a number of sub-‐sections reflecting the steps taken to re-‐estimate the ‘GIP dividend’ for UK firms – that is, the tangible savings that GIP schemes tend to give back to the employer.

This section also constitutes an update of Cebr’s March 2012 report. But before presenting the updated findings, we set out the modelling approach and its underlying assumptions.

2.1 The macroeconomic appraisal model The macroeconomic appraisal model constructed to estimate the GIP dividend is built on the foundation of three National Statistics datasets:

• The Department for Business, Innovation and Skills (BIS) “Business Population Estimates for the UK and Regions 2014”. This provides enterprise population, turnover and jobs disaggregated by enterprise size, by industry, including public and private sector and by regions.

• ONS’ Annual Survey of Hours and Earnings (ASHE) 2014, which provides data on the number of employees, median and mean weekly earnings broken down by each occupational class and industry sector.

• ONS Blue Book, Annual Business Survey and supply-‐use tables to fill gaps in the other datasets, such as the lack of turnover data for the financial services industry in the BIS business population dataset.

Following extraction of the relevant data subsets from these sources, we took a number of steps, outlined as follows.

Step 1: Develop a suitably disaggregated salary structure for the economy

NOMIS has produced a matrix detailing the occupational structure of employee jobs by industry sector in England and Wales. This contains a count of employment disaggregated by 9 occupations (SOC 2010) across 99 industries (SIC 2007). However, there are no salary data in this dataset. We therefore matched salaries data from ASHE for each specific industry with the occupational structure of that industry. This facilitated the estimation of more robust sector-‐level average rates of pay based on the distinct occupational structures of those sectors.

Step 2: Use the disaggregated salary structure to develop total weekly and annual wage bills

Using the weekly wages ‘SIC-‐SOC matrix’ developed in Step 1, above, we were able to calculate the total average weekly and annual wage bills for all jobs across all enterprises in each size range in each industry sector. Businesses with less than 5 employees were excluded from the analysis as GIP schemes generally require a minimum of seven employees to be included.

The model was designed to produce separate results for each of the eight size bands. We have consolidated the results across the smaller company sizes (5 to 249 employees) for the purposes of presenting the results and ensuring that separate estimates are available for typical businesses within each of the 250-‐499 employee and 500 plus employee size bands.

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Step 3: Establish the workings of the macroeconomic appraisal model

The model operates by producing ratios reflecting the percentage of total funds invested in premiums in a world of widespread GIP adoption that could be expected to be returned to companies through savings in a number of areas (these savings reflecting elements of the direct and indirect costs of absence outlined in the previous section). These ratios are what we term the ‘GIP dividend’. Specifically, the model incorporates the following in the GIP dividend:

• The obviated need to pay long-‐term absentees occupational and/or statutory sick pay beyond the GIP policy’s deferred period. Thus, beyond 26 weeks (the typical length of deferred period for a GIP policy), the insurer rather than the insured company pays the salary costs of long-‐term absentees. This is the largest source of GIP dividend.

• Other benefits that flow from having a GIP policy in place, including:

– Savings from reduced absence management, which is now largely outsourced to the GIP provider for long-‐term absence.

– Savings in recruitment and training costs associated with improved staff retention rates, due to a ‘happier’ workforce that feels protected from unforeseen events and is, therefore, less likely to want to leave.

– Savings due to reduced red tape and legalities, because disputes would now be referred to the GIP provider.

As already mentioned, the most significant source of GIP dividend is through the first category – obviated occupational and/or statutory sick pay bills beyond the deferred period of the GIP policy. The second category offers relatively small, yet not insignificant contributions to the dividend.

2.2 Underlying assumptions Certain underlying assumptions were necessary in estimating the ‘GIP dividend’ in the world as it is and in a hypothetical world in which there is widespread GIP adoption by private sector employers. This sub-‐section provides details of those assumptions.

Rates and duration of long-‐term absence

The assumed rate of long-‐term absence was a key input to the analysis. However, most data on workplace absence defines long-‐term absence as four weeks or longer. This did not, therefore, allow us to isolate the proportion of aggregate absence that is or could be interpreted as long-‐term from the viewpoint of a GIP provider, that is, absences in excess of six months.

In the absence of these data we instead requested the ‘Fit-‐Note’ database from the ONS. The Statement of Fitness for Work (known as a ‘fit note’), was introduced in 2010 with the intention of helping more people to stay active in work rather than drifting into long-‐term sickness absence. Fit notes are issued by doctors as evidence of their advice about an individual’s fitness for work and a normal method for employees to provide evidence of sickness to employers after the seventh day of absence. Our analysis

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of the Fit-‐Note dataset15 revealed that almost 5.58 out of every 1,000 people requiring any period of workplace absence in any given year are long-‐term absentees.

The duration of long-‐term absence can vary widely, largely depending on the type of illness and age of the individual. We were, as noted above, informed by Unum that the duration of long-‐term absence can vary from several months to 35 years, but that the average is approximately 7 years. We adopted this average duration of 7 years for long-‐term absence for the purposes of our modelling.

Statutory and Occupational Sick Pay arrangements

Employers are required by law to pay Statutory Sick Pay (SSP) for up to 28 weeks (from the fourth day of absence) but many also have occupational sick-‐pay (OSP) schemes that go well beyond these SSP requirements. Primary research commissioned by Unum16 suggests that employers do have occupational sick pay schemes that go beyond statutory sick pay because they wish to be seen as caring and responsible employers, but also because of the need to retain key skills. The research also highlights significant numbers of companies referencing a ‘discretionary’ element in their OSP schemes. They tend not, therefore, to have standard lengths of periods of applicability.

The OSP assumptions adopted for our model were borne out of Cebr’s interpretation of the results of this proprietary survey research carried out by Unum. These assumptions are summarised in the following set of figures. We note that for employees in their later years, OSP is likely to take the form of Ill-‐health Early Retirement Pension payments.

Figure 1 illustrates our OSP and SSP assumptions for small companies with 5-‐49 employees. It shows the percentage of an annual cohort of long-‐term absentees that are on different levels of OSP income coverage in each successive year of absence. For instance, about 80% of a single year’s cohort of long-‐term absentees is on full-‐pay OSP arrangements, whilst the remaining 20% are on statutory sick-‐pay arrangements. However, in years 4 to 7, only 11.4% of the annual cohort of long-‐term absentees is on half-‐pay OSP arrangements.

Figure 2 and Figure 3 show the analogous assumptions for companies of size 50-‐499 employees and of size 500+ employees respectively.

We note that these assumptions translate into the following:

• For firms of size 5-‐49 employees, a weighted average level of OSP across all claimants (including those on no OSP), falls from 80% in year 1 to 6% in year 7.

• For firm of size of 50-‐499 employees, a weighted average level of OSP across all claimants (including those on no OSP) that falls from 90% in year 1 to 8% in year 7.

• For firms of size 500+ employees, a weighted average level of OSP across all claimants (including those on no OSP) that falls from 90% in year 1 to 20% in year 7.

These weighted average levels of OSP are illustrated (as a percentage of salary) with the solid line (mapped to the right-‐hand vertical axis) in Figure 1 to Figure 3 below.

15 The Fit-‐Note dataset is a part of the National Evaluation of ‘Fit-‐Note’ 2011-‐2013 study which evaluates the fit note system introduced in 2010. 16 Unum in 2014 commissioned Holden Research to explore absence management processes within UK private companies. A survey was undertaken to understand formal and informal practices with regards to absence management.

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Figure 1: Occupational sick-‐pay arrangements for companies of size 5-‐49 employees

Source: Cebr analysis, Unum proprietary survey data

Figure 2: Occupational sick-‐pay arrangements for companies of size 50-‐499 employees


0%

20%

40%

60%

80%

100%

0%

20%

40%

60%

80%

100%

120%

Y1 0-‐6 MTHS

Y1 6-‐12 MTHS

Y2 Y3 Y4 Y5 Y6 Y7

% employees

Full-‐pay OSP (LHS) 75% OSP (LHS)

50% OSP (LHS) 25% OSP (LHS)

SSP only (LHS) WEIGHTED AVERAGE LEVEL OF OSP (INCL. 0%) (RHS)

0%

20%

40%

60%

80%

100%

0%

20%

40%

60%

80%

100%

120%

Y1 0-‐6 MTHS

Y1 6-‐12 MTHS

Y2 Y3 Y4 Y5 Y6 Y7

% employees




18


Figure 3: Occupational sick-‐pay arrangements for companies of size 500+ employees


GIP arrangements

In the widespread GIP adoption scenario, the same OSP and SSP arrangements are assumed for the first 26 weeks, that is, for the length of the deferred period of the GIP policy. Beyond 26 weeks, GIP is assumed to pay out an average of 50% of the gross salary of the long-‐term absentee. In all periods, companies are assumed to pay the average GIP premium for all employees.

We used an average GIP premium per person insured as the basis for our calculation. The starting point was the average premium suggested by the latest version of Swiss Re’s Group Watch 201517 publication. This suggested an average premium of £266 per annum per insured person in 2014. However, given the dominance of the highest occupational classes in the current up-‐take of GIP schemes, it was deemed appropriate to use a premium that approached a higher target rate based on the increased risk of illness that would prevail if GIP was also adopted for the lower occupational classes – as in our hypothetical world of widespread GIP adoption. We, therefore, chose an average premium per person insured of about £350 per annum, which is not inconsistent with historic GIP premiums.

Assumptions for other elements of the ‘GIP dividend’

To estimate the final three points set out in Step 3 of subsection 2.1 above, we made the following assumptions:

• That replacement staff (be they temporary hires or overtime staff) are paid the same as the long-‐term absentee would have been paid had they not been absent. However, we assume a 20% negative productivity differential between long-‐term absentees and their temporary/overtime replacements.

17 Swiss Re (2015); Group Watch Press Release (www.swissre.com)

0%

20%

40%

60%

80%

100%

0% 20% 40% 60% 80%

100% 120%

Y1 0-‐6 MTHS Y1 6-‐12 MTHS

Y2 Y3 Y4 Y5 Y6 Y7

% employees




19


• To estimate savings in recruitment and training arising from the earlier return-‐to-‐work of long-‐term absentees, we used the typical size of HR departments, specifically the average ratio of HR staff to all employees from XpertHR18, as shown in the Table 4 below.

Table 4: Ratio of HR staff to total employees

Public sector Private sector

services Manufacturing and production

Median Ratio 1:75 1:63 1:83

Source: XpertHR

• We combined this with intelligence gathered from the literature on the structure of HR departments, most notably that by Brewster et al and Bersin & Associates annual ‘HR Factbook’.19 Namely that: (i) 60% of HR budgets relate to core services (compensation and benefits, payroll and employee relations), but that only two-‐thirds of 60% can be linked to temporary staff, which is incurred in proportion to the number of claimants relative to total employees; and (ii) one-‐third of HR budgets relate to talent management, including recruitment and training, but only four-‐fifths of this could be linked to temporary staff, which is also incurred in proportion to the expected number of claimants relative to total employees.

• For savings related to the outsourcing of absence management to the GIP provider, we assumed that 12.5 per cent of core HR resources are consumed by absence management and that these resource costs are saved in proportion to the number of claimants relative to total employees.

• For savings related to improved staff retention as a result of a ‘happier’ workforce (due to GIP), we assume a hypothetical 1 per cent improvement in staff retention, which reduces HR resource consumption in the area of core services and talent management services.

• Finally, for the potentially lower costs associated with legalities and ‘red tape’, we sourced the intermediate spend by industry on legal services from ONS supply and use tables. We then made the hypothetical assumption that 25 per cent of these costs arise from employment disputes, which we assumed are saved in proportion to the number of claimants relative to total employees.

2.3 The GIP ‘dividend’: Updated findings This section presents the updated findings of our modelling of the GIP dividend and constitutes a refresh of our original 2012 report. The findings were produced by our macroeconomic assessment model, itself based on the underlying assumptions outlined in the previous two subsections.

The cost of long-‐term absence

Based on statutory sick pay (SSP) obligations and occupational sick-‐pay (OSP) arrangements facing employers (as assumed in our model and outlined above), we find a total annual cost of long-‐term absence to the UK private sector of £4.17 billion. While the public sector was not a focus for the study,

18 XpertHR: www.xperthr.co.uk/ 19 See Brewster, Chris et al (2006), “What determines the size of the HR function? A cross-‐national analysis”, in Human Resource Management, Vol. 45, No. 1 and Bersin & Associates (2011), “The HR Factbook 2011”, Executive Summary. The former is UK/European based. The latter is only the executive summary of the report but does provide useful information on HR budgets, staffing and resource allocations. The factbook is based on the survey responses of approximately 300 HR organisations that represent a broad cross-‐section of company size, industry and maturity in the United States.

20


this number rose to £6.71 billion when the public sector was included.20 This is broken down by company size, as shown in Table 5.

Table 5: Breakdown of total annual cost of long-‐term sickness absence across the private sector, by company size bands


Breakdown of total annual cost of LT absence (£ billions)

5-‐249 1.42 250-‐499 0.21 500+ 2.54

Total private sector 4.17

Total economy, incl. public sector 6.71 Source: Cebr analysis

Figure 4 illustrates the absolute change in the annual cost of long-‐term sickness absence from our 2012 report and the updated figures estimated as part of the present study. The cost of long-‐term sickness absence to the UK private sector has risen by a third (33%) from £3.13 billion in 2012 to £4.17 billion in 2014. The largest increase can be observed amongst the largest employers (500+ company size band), with a 42% increase to £2.54 billion in 2014 from the estimated £1.79 billion in 2012. This increase can most likely be attributed to, amongst other things, a rise in statutory sick pay entitlements (an 8% increase) and in total employment (which has risen by 6%) during this period.

Figure 4: Aggregate annual cost of long-‐term absence to the UK private sector (left axis, £ billions) and percentage change between (right axis, %), 2012 and 2014


20 The difference between these estimates and those put forward in the 2013 CBI/Pfizer report are likely due to the following methodological issues. Firstly, we base our modelling upon the incidence of long-‐term sickness absence amongst employees with an assumed average duration per absence, whereas the CBI/Pfizer estimates are based upon the total time lost due to long-‐term sickness absence. Secondly, the definition of long-‐term sickness absence is any absence in excess of four weeks in the CBI/Pfizer work, whereas this report assumes long-‐term absences to be any in excess of six months. Thirdly, the scope of the costs considered are different -‐ our model includes HR and legal costs, whereas the CBI/Pfizer report does not, whilst ours includes lost productivity only in terms of an output differential between permanent and temporary employees, whereas CBI/Pfizer appears to take a broader view of lost output for the employer. Finally, Cebr’s model is based upon both OSP and SSP assumptions, which take into account a tiered decline in salary payments over the period of a long-‐term absence.

1.13

0.21

1.79

3.13

1.42

0.21

2.54

4.17

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5

5-‐249 250-‐499 500+ Total private sector

2012 2015

21


The total cost to the UK private sector of £4.17 billion produces an average cost of long-‐term absence per private sector organisation of £8,763 but this masks significant variation across the company size bands, which are shown in Table 6 below. While the higher numbers for larger enterprises reflect the fact that they have greater numbers of employees, it also reflects the more generous OSP arrangements that tend to be in place in these firms.

Table 6: Average annual cost of long-‐term absence per private sector business, by company size band


Breakdown of average annual cost of LT absence

– cost per company

5-‐249 £3,035 250-‐499 £60,276 500+ £770,166

Total private sector average

£8,763


The ‘GIP Dividend’

We find that, for the UK private sector as a whole, the GIP dividend is 60.9%, which includes all three elements of the GIP dividend set out in section 2.1 above. Taking only the OSP savings, the dividend is 54.9%, meaning an additional 6.0% of GIP dividend is provided by avoiding the wider business costs associated with managing long-‐term absence.

The GIP dividends for each of the different company size bands are shown in Table 7 below.

Table 7: GIP dividend for all private sector companies in each size band


GIP Dividend (OSP savings only) GIP Dividend (all sources)

5-‐249 41.2% 46.2% 250-‐499 38.0% 45.0% 500+ 69.3% 76.1%

Total private sector average 54.9% 60.9%


In monetary terms, the overall private sector GIP dividend of 60.9% translates into £3.68 billion out of a total £5.93 billion invested in GIP premiums being returned to private sector employers across the economy. This is broken down further by company size band in Table 8 below.

22


Table 8: Annual expenditure on GIP premiums and the annual GIP dividend for all private sector companies in each size band


Total spend on GIP premiums (£ billions)

GIP dividend (all sources; £ billions)

5-‐249 2.62 1.24 250-‐499 0.38 0.17 500+ 2.94 2.27

Total private sector

5.93 3.68


Both Table 7 and Table 8 illustrate that the largest firms can expect to yield the highest GIP dividend. This is consistent with the findings of Unum’s OSP survey that mid-‐ and large-‐sized companies are more likely to provide OSP arrangements (as well as more generous) to their employees. This is also demonstrated by the differential in the monetary valuation of the GIP dividend on a per employee basis for companies of 500+ employees relative to that for the other company size bands shown in Table 9 below.21

The average expenditure per private business on GIP premiums and the corresponding GIP dividend per business in each size band are also shown in Table 9.

Table 9: Average annual expenditure on GIP premiums and the annual GIP dividend per private sector company in each size band


Average company spend on GIP premiums

Average company GIP dividend (all

sources)

Average GIP dividend per employee (all

sources)

5-‐249 £5,583 £2,640 £145 250-‐499 £109,664 £50,506 £146 500+ £891,572 £687,918 £255

Private sector average

£12,474 £7,731 £198


2.4 The benefits to employees Our model suggests that employees could also benefit. In a world of widespread GIP adoption employees could be better off to the tune of 1% of the income they would receive under SSP or OSP arrangements. This small yet positive benefit is the result of our assumption that the GIP insurance provider would pay, on average, 50% of an employee’s gross income for the entire duration of their absence (once the deferred period has elapsed). In comparison, under an OSP scenario, our model tends to reach low levels of coverage of both absentees and salary incomes across the company sizes quite rapidly (see Figures 1-‐3 above).

21 In other words, it is not just the fact that larger companies have more employees that is driving the much larger monetary GIP dividend for these businesses. Also reflected are the more generous OSP arrangements that are likely to be in place at such companies.

23


When broken down by the different company size bands, the results suggest that employees of firms employing 5-‐249 employees could be, on average, as much as 30% better off under widespread GIP adoption. The model estimates that workers in firms of 250-‐499 employees could be up to 39% better off, while employees of the larger firms (500+ employees) would be less likely to see any difference between what GIP coverage would offer and what they would receive under their employers’ OSP scheme. This is driven by the proposition that larger firms tend to have more generous OSP arrangements than smaller firms.

24


3 The impact on the GIP dividend of rehabilitation and early intervention services Providers of GIP schemes tend to offer a range of services that can assist an absent employee to return to work in a shorter period of time. Early intervention and rehabilitation services aim to tackle health issues before they become more serious and in turn help to reduce long-‐term sickness absence. Early access to rehabilitation would, all else being equal, be expected to reduce the prevalence of absences becoming long-‐term and/or to reduce the length of long-‐term absence where it does occur. This would be expected to have the effect of delivering a higher GIP dividend. This section of the report tests this hypothesis.

The section examines these issues through an analysis of Unum’s GIP claims data and how these demonstrate that early intervention delivered in the first six months of illness with rehabilitation services can reduce the long-‐term impact of physical and mental health conditions. We then estimate the impact on the GIP dividend of using early intervention and rehabilitation services, both in general terms and for specific illnesses, particularly mental health and musculoskeletal conditions.

3.1 Background and underlying assumptions Unum’s GIP policy has the added benefit of providing early intervention and rehabilitation services. The intention is that, by offering these services, employees have access to rehabilitation services in the first six months of their absence that could help them return to work before they become long-‐term absentees. This helps employers, reducing the financial burden associated with long-‐term absenteeism, such as finding replacement staff, loss of productivity etc. Based on Unum’s data, it was assumed that these services are made available to about 69% of employees covered by GIP schemes.

The impact that early intervention and rehabilitation services can have upon the time taken to return to work is considered in greater detail in the following sub-‐sections. The assumptions are based on Unum’s proprietary claims data and have, therefore, a more solid basis in reality than the assumptions used in our original 2012 report, which were based on anecdotal evidence only.

We assume a flow of additional benefits from the rehabilitation and other early intervention services offered by the insurer as part of a GIP policy. These capture the following:

• Savings on salary costs of replacement staff because the long-‐term absentee is returned to work more rapidly in the world of widespread GIP adoption.

• Productivity savings because the long-‐term absentee is returned to work more rapidly, reducing the time in the job of less productive replacement staff.

• Savings on recruitment and training of replacement staff because the long-‐term absentee is returned to work more rapidly.

3.2 The impact on long-‐term absence Our detailed analysis of Unum’s claims data shows that there are tangible benefits for employers if they can offer their employees early intervention and rehabilitation services22 whilst on sickness absence.

22 Early intervention services include: Employee Assistance Programmes (EAPs), early intervention helpline, vocational rehabilitation services, mental health first aid, positive ageing guidance, cognitive behavioural therapy and physiotherapy.

25


Employees who have access to these services and use them tend to have shorter duration long-‐term absences compared to those that do not. On average, the duration is shorter by 16.6%, which translates to a reduction of more than a year (60 weeks) in the average 7-‐year duration of a long-‐term absence.

In such a scenario, the average private sector firm could see the GIP dividend increase by 4.6% -‐ from 60.9% to 65.6% (Figure 5) compared to a scenario in which early intervention and rehabilitation services are not provided.23 In monetary terms, the GIP dividend for the entire UK private sector rises by £0.28 billion to provide tangible benefits evaluated at £3.95 billion per annum.

Table 10 below shows how the GIP dividend with access to and utilisation of early intervention and rehabilitation increases from the baseline levels presented in the previous section.

Figure 5: Increase in GIP dividend due to early intervention and rehabilitation services, by company size


Table 10: Comparison of monetary GIP dividends when early intervention and rehab services are used and when they are not, aggregate private sector, by company size


GIP dividend without early

intervention (all sources; £'s billions)

GIP dividend with early intervention (all sources; £'s

billions)

Additional GIP dividend from

early intervention (all sources; £’s

billions) 5-‐249 1.24 1.36 0.12

250-‐499 0.17 0.19 0.02 500+ 2.27 2.4 0.14

Total private sector

3.68 3.95 0.28


23 The individual numbers do not sum to the final result due to rounding

46.2% 45.0%

76.1%

60.9%

50.9% 49.8%

80.7%

65.6%

30%

40%

50%

60%

70%

80%

90%

5-‐249 250-‐499 500+ Total private sector

GIP dividend without early intervenpon services

GIP dividend with early intervenpon services

26


We also examined the potential impact on the GIP dividend if early intervention and rehabilitation services are assumed to be available on a widespread basis – that is, for 100% of employees rather than the 69% assumed above based on Unum’s claims data. In these circumstances, the GIP dividend could be substantially higher, increasing further to 70.3%.24 This would constitute an increase in the GIP dividend of 9.4% above the baseline 60.9% which, in monetary terms, equates to an increase to £4.24 billion for the UK private sector as a whole (Table 13). This compares favourably with the baseline of £3.68 billion (which takes no account of early intervention) and the £3.95 billion (based on the 69% level of availability and utilisation suggested by Unum’s claims data). These results are summarised in Tables 12 and 13.

Table 11: The impact on the GIP dividend of early intervention and rehabilitation services, percentage terms


Baseline GIP dividend -‐no early intervention (all

sources)

GIP Dividend with early intervention services available to 69% of employees

(all sources)

GIP Dividend with early intervention services available to 100% of employees

(all sources) 5-‐249 46.2% 50.9% 55.1%

250-‐499 45.0% 49.8% 55.1% 500+ 76.1% 80.7% 85.8%

Total private sector average 60.9% 65.6% 70.3%


Table 12: The impact on the GIP dividend of early intervention and rehabilitation services, monetary terms


Baseline GIP dividend -‐no early intervention (all sources; £’s billions)

GIP dividend with early intervention services available to 69% of all employees (all sources;

£'s billions)

GIP dividend with early intervention services available to

100% of all employees (all

sources; £'s billions) 5-‐249 1.24 1.36 1.47

250-‐499 0.17 0.19 0.21 500+ 2.27 2.4 2.55

Total private sector average

3.68 3.95 4.24


3.3 Mental health conditions This sub-‐section begins by estimating the cost of mental illness before outlining our findings on the impact upon the GIP dividend of using early intervention and rehabilitation services for long-‐term absence caused by mental health conditions.

24 The individual numbers do not sum to the final result due to rounding

27


Cost of long-‐term absence due to mental ill-‐health

Mental illness, including stress, is one of the principal reasons for sickness absence amongst UK employees. The fit-‐note dataset suggests that almost three in every ten fit-‐notes issued by GPs (28%) to employees for long-‐term absence from work are for mental health reasons. (CIPD’s 2014 report25 estimates this figure to be higher at 36%. However, this is based on ‘long-‐term’ being defined as any period longer than 4 weeks, rather than the 6 months used in this report.)

Our model estimates that long-‐term absence due to mental illness costs the UK economy £1.88 billion, with the private sector expected to bear the vast majority of the burden at £1.17 billion per year. This breaks down amongst the three company size bands, as shown in Table 13 below.

Table 13: Breakdown of total annual cost of long-‐term absence due to mental ill-‐health, across the private sector company size bands


Breakdown of total annual cost of LT absence (billions)

5-‐249 £0.40 250-‐499 £0.06 500+ £0.71

Total private sector £1.17

Total economy, incl. public sector £1.88


The impact on the GIP dividend of early intervention for mental ill-‐health

Our analysis of Unum’s claims data suggests that long-‐term absentees suffering from mental health conditions who utilise early intervention and rehabilitation services experience, on average, a long-‐term absence duration that is 18.2% shorter than those who do not utilise them. Using this assumption, we modelled the GIP dividend for the UK private sector in a world of widespread GIP adoption and of levels of utilisation of early intervention and rehabilitation services for mental illness that are in line with those suggested by Unum’s data.

This increases the GIP dividend from the baseline level of 60.9% for the average private sector firm to 63.4%. Because this estimate of the dividend is based on the utilisation of early intervention and rehabilitation services for mental health issues only, it sits in the middle of the range between the baseline 60.9% and the 65.6% estimate based on their use for all causes of long-‐term absence.26 This increase from 60.9% to 63.4% translates into an additional £85 million in GIP dividend in monetary terms. The aggregate monetary dividend increases from the baseline £3.68 billion to £3.76 billion.

25 CIPD Absence management – annual survey report 2014 26 We continue to use the 65.6% value as the top end of the range (rather than 70.3%) for comparison purposes as its basis is the 69% level of availability and utilisation suggested by Unum’s claims data. The 70.3% is based on more widespread (100%) availability of early intervention and rehabilitation services.

28


Table 14: Impact upon the GIP dividend from providing early intervention and rehabilitation services only to those on long-‐term absence caused by mental illness, by company size band


GIP dividend without early intervention (all sources; £'s billions)

GIP dividend with early intervention services to mental health claims (all sources; £'s billions)

New GIP Dividend with early intervention for mental illness (all

sources, %)

5-‐249 1.24 1.28 48.7% 250-‐499 0.17 0.18 47.6% 500+ 2.27 2.31 78.6%

Total private sector 3.68 3.76 63.4%


These findings are presented in average per firm and per employee terms in Table 15, which illustrates that the largest firms can expect to yield the highest GIP dividend. This, as already noted, is consistent with the evidence on better OSP provision in larger companies, which is confirmed by the differentials between larger and smaller firms on a per employee basis.

Table 15: Average annual GIP dividend from providing early intervention and rehab services to those on long-‐term absence caused by ill-‐mental health, by private sector firm and employee in each company size band


Average company GIP dividend (all sources; £'s)

Average GIP dividend per employee (£)

5-‐249 £2,719 £149 250-‐499 £52,146 £150 500+ £700,649 £202


3.4 Musculoskeletal conditions This presents a similar analysis to that outlined in the previous subsection, this time taking a closer look at the use of early intervention and rehabilitation services for employees on long-‐term absence caused by musculoskeletal conditions. We first estimate the cost to businesses of long-‐term absence due to musculoskeletal conditions. This is followed by a similar examination of the impact upon the GIP dividend of using early intervention and rehabilitation services for long-‐term absence caused by musculoskeletal conditions.

Cost of long-‐term absence due to musculoskeletal problems

Musculoskeletal conditions, including back pain, are also one of the primary causes of long-‐term sickness absence. The CIPD 2014 report27 estimates that over a fifth (22%) of all long-‐term sickness absence (defined as more than 4 weeks) is due to musculoskeletal health problems. Similarly, the fit-‐note database implies that 17% of all fit-‐notes issued for sickness absence with longer duration than 6 months were issued for musculoskeletal problems.

27 CIPD Absence management – annual survey report 2014

29


Long-‐term absence due to musculoskeletal problems is estimated to cost the UK economy £1.14 billion, with the private sector expected to bear the vast majority of the burden at £0.71 billion per year. This breaks down amongst the three company size bands, as shown in Table 16 below.

Table 16: Breakdown of total annual cost of long-‐term absence due to musculoskeletal problems, across the private sector company size bands


Breakdown of total annual cost of LT absence (billions)

5-‐249 £0.24 250-‐499 £0.04 500+ £0.43

Total private sector £0.71

Total economy, incl. public sector £1.14


The impact on the GIP dividend of early intervention for musculoskeletal conditions

In cases of absence due to musculoskeletal conditions, our analysis of Unum’s data suggests that employees who have access to early intervention and utilise rehabilitation services experience long-‐term absence durations that are 12.3% shorter than those who do not. We modelled the GIP dividend for the UK private sector in a world of widespread GIP adoption and of levels of utilisation of early intervention and rehabilitation services for musculoskeletal conditions that are in line with those suggested by Unum’s data.

This increases the GIP dividend from the baseline level of 60.9% for the average private sector firm to 62.6%. Because this estimate of the dividend is based on the utilisation of early intervention and rehabilitation services for musculoskeletal issues only, it again sits in the middle of the range between the baseline 60.9% and the 65.6% estimate based on their use for all causes of long-‐term absence. This increase from 60.9% to 62.6% translates into an additional £35 million in GIP dividend in monetary terms. The aggregate monetary dividend increases from the baseline £3.68 billion to £3.71 billion.

The increment in GIP dividend is lower than in the case of mental ill-‐health, but this is largely driven by the lower prevalence of musculoskeletal conditions amongst long-‐term absentees.

30


Table 17: GIP dividend exclusively for musculoskeletal cases across all private sector companies from early intervention and rehab services in each size band


GIP dividend without early intervention (all sources; £'s billions)

GIP dividend with early intervention services to musculoskeletal health problem claims (all sources; £'s billions)

New GIP Dividend with early intervention for

musculoskeletal conditions (all sources,

%)

5-‐249 1.24 1.25 47.9% 250-‐499 0.17 0.18 46.7% 500+ 2.27 2.28 77.7%



These findings are presented in average per firm and per employee terms in Table 18, which illustrates that the largest firms can expect to yield the highest GIP dividend. This, as already noted, is consistent with the evidence on better OSP provision in larger companies. This is again demonstrated by the differentials between larger and smaller firms on a per employee basis.

Table 18: Average annual GIP dividend per private sector firm and employee in each size band


Average company GIP dividend (all sources; £'s)

Average GIP dividend per employee (£)

5-‐249 £2,673 £147 250-‐499 £51,181 £148 500+ £693,158 £257


3.5 Including early intervention for both mental illness and musculoskeletal conditions Given that mental health and musculoskeletal together account for almost half (45%) of all fit-‐notes issued for long-‐term sickness absence, this naturally led us to examine the impact of early intervention services for both sets of conditions upon the GIP dividend.

By providing early intervention and rehabilitation services to those on long-‐term absence caused by mental illness and musculoskeletal conditions, we find that the GIP dividend increases from the baseline level of 60.9% for the average private sector firm to 64.0%. This increase from 60.9% to 64.0% translates into an additional £120 million in GIP dividend in monetary terms. The aggregate monetary dividend increases from the baseline £3.68 billion to £3.80 billion (Table 19).

31


Table 19: Contribution to the GIP dividend (all sources) from early intervention and rehabilitation services applied to both mental illness and musculoskeletal conditions


GIP dividend without early intervention (all sources;

£'s billions)

GIP dividend with early intervention services to

mental and musculoskeletal health problem claims (all sources; £'s billions)

New GIP Dividend with early intervention for mental illness and

musculoskeletal conditions (all sources, %)

5-‐249 1.24 1.29 49.3% 250-‐499 0.17 0.18 48.2% 500+ 2.27 2.33 79.2%



The 64.0% GIP dividend estimate is based on the utilisation of early intervention and rehabilitation services for both mental and musculoskeletal issues. This again sits inside the range between the baseline 60.9% and the 65.6% estimate based on their use for all causes of long-‐term absence. But it is closer to the top end of the range because early intervention is being applied to more instances of long-‐term absence. Table 20 and Table 21 compares the results across the various scenarios by company size band.

Table 20: Comparison of the GIP dividend ratio under various early intervention scenarios, by company size band


Baseline GIP dividend -‐ no

early intervention services

Early intervention

services mental health

Early intervention services

musculoskeletal health

Early intervention services for mental

and musculoskeletal

health

Early intervention services for all illnesses

5-‐249 46.2% 48.7% 47.9% 49.3% 50.9% 250-‐499 45.0% 47.6% 46.7% 48.2% 49.8% 500+ 76.1% 78.6% 77.7% 79.2% 80.7% Total private

sector 60.9% 63.4% 62.6% 64.0% 65.6%


Table 21: Comparison of the average GIP dividend per firm under various early intervention scenarios, by company size (£'s)


Baseline GIP dividend -‐ no

early intervention services

Early intervention

services mental health

Early intervention services

musculoskeletal health

Early intervention services for mental

and musculoskeletal

health


5-‐249 2,640 2,719 2,673 2,752 2,898 250-‐499 50,506 52,146 51,181 52,821 55,829 500+ 687,918 700,649 693,158 705,889 729,239 Total private sector

7,731 7,909 7,804 7,982 8,309


32


Across all firm sizes, the largest GIP dividend is expected to occur under a widespread adoption of GIP with early intervention services for employees on long-‐term absences caused by any illness. This pattern is also observed when examining the GIP dividend on a per employee basis in Table 22 below.

Table 22: Comparison of the average GIP dividend per employee under various early intervention scenarios, by company size (£’s)


Baseline GIP dividend – no early intervention services

Early intervention services mental health

Early intervention services musculoskeletal health

Early intervention services for mental and musculoskeletal health


5-‐249 145 149 147 151 159 250-‐499 146 150 148 152 161 500+ 255 260 257 262 271 Total private sector

198 202 199 204 212


33


4 The cost of long-‐term sickness absence by 2030 This section presents our forecast of the future cost of long-‐term sickness absence to the UK economy. The estimates presented in Sections 2 and 3 are forecasted forward to 2030 taking into account projected growth in the size of the workforce and the fact that that workforce is becoming increasingly aged.

4.1 Forecasts of the UK population and workforce In 2014, the UK working age population (those aged 16 years and above) stood at 52.4 million. This is set to rise by 11% to reach 58.0 million by 2030. However, this general increase masks significant variations across age groups. Figure 6 is based on ONS population projections data and clearly illustrates the ageing of the UK population. The oldest cohort group is expected to increase by almost two-‐fifths (39%) by 2030 from its 2014 levels. This would imply that there could be 15.8 million individuals aged 65 and over in the next 15 years. In contrast, the youngest age group (16 to 29 year olds) and the 40 to 49 age group are expected to shrink by 1% and 2% by 2030 respectively.

Figure 6: Population increase by age groups, 2014-‐2030, index 2014=100

Source: ONS, Cebr analysis

The ageing of the UK population will, in turn, impact on the composition of the workforce28. This is expected to increase by 10% from 30.7 million in 2014 to 33.7 million in 2030. Figure 7 below illustrates the forecasted change of the workforce composition by age groups.

The oldest age groups (50-‐64 years and 65+), using Cebr’s macroeconomic forecasts, are expected to make up a larger proportion of the UK workforce by 2030. The share of the former age group is expected

28 The workforce is defined as the number of people in employment, part-‐time or full-‐time. Whilst the working-‐age population is defined as the number of people aged between 16 and 64 present in the UK population, it does not necessarily mean that they are all in employment.

85

95

105

115

125

135

145

2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030

16-‐29 30-‐39 40-‐49 50-‐64 65 and over Total populapon 16 and above

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to rise by 4% to make up almost a third (30%) of the workforce by 2030 from its current level of 26%. Similarly, the number of individuals aged 65 and over within the workforce is also expected to almost double, rising from 1.11 million in 2014 to 1.97 million by 2030. In contrast, the proportion of 16 to 29 year olds and 40-‐49 year olds making up the workforce is expected to decline from its 2014 levels by 2% and 4% respectively.

Figure 7: Workforce composition in 2014 and 2030, percentage of total employment

Source: OECD, Cebr forecast data

4.2 Forecast of long-‐term sickness absence rate The expected changes in the composition of the workforce will impact on the incidence of long-‐term sickness absence amongst those who are employed. Our analysis of the fit note dataset suggests that almost 5.58 out of 1,000 employees enter long-‐term sickness absence. However, this masks the variations amongst age groups, as shown in Table 23 below. The older age groups, 50-‐64 year olds and 65+, have the highest rates of incidence of long-‐term absence. Over 7 in every 1,000 employees aged between 50 and 64 years are likely to take long-‐term absence due to sickness, whilst this rises to almost 9 in every 1,000 employees for those aged 65+.

Table 23: Long-‐term sickness incidence rates per 1,000 employees, by age group

16-‐29 30-‐39 40-‐49 50-‐64 65 and over

Overall long-‐term absence

rate Incidence rate per 1,000 employees 4.69 4.31 5.29 7.38 8.88 5.58

Source: Fit-‐note dataset, Cebr analysis

Combining the age-‐specific incidence rates of long-‐term absence and the forecasted changes in workforce composition, we were able to estimate an overall long-‐term absence rate that could occur in 2030. This suggests that the rate of long-‐term absence will increase from 5.58 to 5.78 per 1,000

23% 22% 25%

26%

4%

21% 22% 21%

30%

6%

0%

5%

10%

15%

20%

25%

30%

35%

16-‐29 30-‐39 40-‐49 50-‐64 65 and over

2014 2030

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employees. This represents a 4% increase from current levels. Figure 8 below illustrates how we estimate this rate to rise over the forecast period, 2014 to 2030.

Figure 8: Trend in long-‐term absence rate, 2014-‐2030, per 1,000 employees


Based on statutory sick pay (SSP) obligations and occupational sick-‐pay (OSP) arrangements facing employers (as assumed in our model and outlined in section 2), we estimate the total annual cost of long-‐term absence to the UK private sector to rise by 15% to £4.81 billion by 2030. While the public sector was not a focus for the study, this number is expected to rise to £7.60 billion when the public sector is included (Figure 9).

Figure 9: Total cost of long-‐term sickness absence in 2014 and 2030, £'s billions


5.58

5.78

5.45

5.50

5.55

5.60

5.65

5.70

5.75

5.80

£4.17

£4.81

£6.71

£7.60

0

1

2

3

4

5

6

7

8

2014 2030 Total private sector Total economy, incl. public sector

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5 Conclusions This report begins by estimating the cost of long-‐term sickness absence to UK employers. Our findings reveal a total cost of £6.71 billion in 2014, a 3.7% increase since our original study conducted in 2012, which estimated this figure at £6.47 billion. We estimate the majority of this cost (£4.17 billion) to fall upon private sector businesses. The remaining £2.54 billion is borne by public sector employers.

We also find that larger businesses (those employing more than 500 employees) face, on average, long-‐term absence costs of £770,000 per year. This is reflective of their greater numbers of employees, as well as the more generous occupational sick-‐pay arrangements that tend to be in place in these firms.

Analysing the total annual costs of long-‐term absence by type of illness, we find that mental and musculoskeletal health problems together account for a substantial proportion of long-‐term sickness absence. Our findings suggest that the annual cost to the private sector of long-‐term sickness absence due to mental and musculoskeletal health problems alone amount to £1.17 billion and £0.71 billion respectively.

Looking forward to 2030, as the workforce continues to grow and also to age, there is an increased likelihood of illness. This, in turn, impacts the rates of long-‐term absence amongst the working population. Taking these factors into account, we estimate that the total annual cost of long-‐term absence to the UK private sector in 2030 could rise by 15% to £4.81 billion from the 2014 estimate of £4.17 billion. Including the public sector, the total cost of long-‐term absence could be expected to increase from £6.71 billion in 2014 to £7.60 billion by 2030.

In light of these potential annual costs, employers are probably wise to consider contingency planning. We have learned through this study that an effective corporate health and wellbeing strategy incorporates elements of prevention, intervention and protection. Preventative measures can include ergonomic assessments, promoting health campaigns (like stopping smoking) and have the potential to reduce the incidence of physical and mental health issues and, therefore, of absence rates.

Similarly, recognising the need for intervention is also important. By having tools that allow employers to step in and support employees when they first show signs of having mental or physical health problems could help prevent these individuals’ conditions becoming more serious. This would, in turn, be likely to reduce the likelihood of absences becoming long term, as well as reducing the duration of absences that do become long-‐term.

The protection element is generally associated with different types of insurance that protect the employee and employer in the event of unexpected circumstances, such as ‘death in service’, critical illness or private health insurance. Group Income Protection (GIP) policies offer strategic benefits in terms of staff retention and reduced uncertainty about costs. But, unlike other types of insurance offered as non-‐salary benefits, GIP also provides tangible returns to employers, who avoid occupational sick-‐pay and other costs. It is these avoided costs that we associate with the GIP dividend.

We estimate that for every £1 of expenditure on GIP premiums, the average GIP dividend is 61 pence. This can be expected to rise to almost 66 pence in the £1 through the use of the early intervention and rehabilitation services that usually are often part help tackle health issues before they become more serious. But this is based on only assuming the levels of utilisation of these services visible in Unum’s claims data (66%). Widespread access and utilisation would provide a further boost to the likely average GIP premium to over 70p in the £1. Worth considering by employers given the ageing population and increased likelihood of long-‐term illness and absence in the future.

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