Cios productivity framework

Cornwall and the Isle of Scilly: Productivity Framework PART 1: Productivity Framework PART 2: Theory and Evidence Review

Table of Contents Executive Summary .......................................................................................................... 3 Introduction ..................................................................................................................... 8 Part 1: Productivity Recommendations ............................................................................. 9 Part 2: Theory and Evidence Review ............................................................................... 17

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EXECUTIVE SUMMARY E.1

ERS Ltd, alongside the Department for Accounting, Economics and Finance at the University of the West of England (UWE) were commissioned in May 2016 by Cornwall and Isles of Scilly (CIoS) Local Enterprise Partnership (LEP) to develop a Productivity Framework. The overarching purpose of the commission is to provide analysis of productivity issues in order to support the CIoS LEP’s approach to business support.

E.2

Increasing productivity is a national priority with the overarching aim of improving living standards for all. LEPs are responsible for supporting local business growth, creating local jobs and helping people realise their potential. In recent years LEPs have taken on increasing responsibilities to allocate investment in order to tackle persistent economic challenges and achieve productivity-led growth.

E.3

In the context of this local and national priority there is the need for CIoS LEP to understand what productivity is and how funded activities can target productivity in the CIoS context.

Importantly, productivity objectives must be achieved in a way that is sustainable and benefits all communities.

E.4

The Productivity Framework report is structured in two parts:  Part 1: Productivity Recommendations: providing a summary of the recommendations emerging from the literature review. Recommendations are presented under two headings: strategic recommendations, relating to the LEP’s overall approach; and delivery recommendations relating to the provision of business support.  Part 2: The Theory & Evidence Review: provides an overview of the literature and evidence relating to productivity theory. The evidence is presented by the six key lines of enquiry within the study brief and provides the basis for the recommendations presented in Part 1.

Part 1: Productivity Recommendations

E.5

Strategic and delivery recommendations are summarised within the Figure E.1 overleaf. The strategic recommendations highlight that the CIoS economy is not easily aligned to the priorities identified within national strategy, such as target growth sectors and city regions.

However, and more encouragingly, evidence suggests that businesses exhibiting high growth are not exclusively high tech, indicating some potential for traditional sectors. In addition non-sectoral characteristics such as internationalisation (e.g. ownership or sales) have a significant positive influence on productivity.

E.6

The delivery recommendations identify ways in which the CIoS LEP could target productivity overall, for example via the Growth Hub. Existing strategies for innovation and skills closely align with productivity aims, however further consideration of support for: supplier readiness, inward investment, internationalisation and business structures could benefit firms and the LEP area as a whole.

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Productivity Recommendations

Figure E.1 Productivity Recommendations: Strategic Considerations & Suggested Actions

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Part 2: The Theory & Evidence Review Question 1: Can a national definition of productivity be aligned to issues affecting C&IoS? E.7

Productivity is a general term used to cover a range of different performance indicators measuring the concept of output per unit of input. It is most commonly used to refer to labour productivity although can in theory be used to refer to the impact on economic output of any input.

E.8

Labour productivity is seen as an important policy target as (in a free market) it is the key determinant of earnings. Due to the importance of seasonal, part time working in the CIoS economy GVA per hour worked is the preferred measure of labour productivity at a local level (GVA per hour worked = GVA/total workforce hours worked).

E.9

Whilst labour productivity provides an indicator of living standards (due to link to wages and thus material wellbeing), it should be included within a suite of measures to track progress against LEP aims for example wellbeing, inclusion and environmental performance. However there is clear potential for the creation of a virtuous cycle between wellbeing and productivity, as improvements in both can be achieved by similar factors such as skills, education and health.

Question 2: Often productivity has negative connotations, how can we have robust plans in place to overcome short term productivity issues (the loss of jobs) for long term gains (the creation of new jobs, upskilling etc.).

E.10

It is clear that high levels of productivity underpin regional competitiveness, material wellbeing and sustainable economic growth. However, it is important to aim for these overall objectives rather than targeting productivity in isolation. Returning to the definition of productivity, the outputs produced for a given level of inputs, policy should support maximising productivity growth by working on the key drivers to maximise the contribution of working people in the long term, rather than short term strategies of shedding jobs and starving the economy of innovation and investment. Overall it is not necessary or desirable for CIoS to target productivity measures relentlessly or exclusively.

Question 3: How does productivity affect micro and SMEs?

E.11

Academic studies confirm that a lack of financial and intellectual resources reduces SMEs’ ability to invest in key enablers for growth, namely: R&D, skills, capital investment and pursuing uncertain business avenues (risk taking). These policy points directly support the theory of investing to support SMEs to resolve market failures.

E.12

NESTA research identified that just six per cent of UK businesses accounted for half of the new jobs created in existing businesses between 2002 and 2008. Further studies have been undertaken to understand why the majority of small businesses do not grow or only achieve modest growth. Evidence suggests that disposition towards growth is key, with those with high growth aspirations more likely to achieve high growth. Interestingly attitudes towards

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growth can be influenced by socio-economic background, education, affluence and networks.

The findings also suggest that individuals with moderate attitudes to growth may be coached to think more critically about improving performance.

E.13

Some policy interventions differentiate between rural and urban contexts, most significantly EU rural policy. Studies have examined the different economic needs of rural SMEs when compared to their urban and semi-urban counterparts. Whilst rural SMEs may have different characteristics (i.e. more likely to be in primary industries and in family ownership), business feedback suggests there is only limited need for differential policy. Rural firms do report that they face specific challenges in accessing skilled labour and perceive regulatory burdens to be a greater barriers to growth. In addition rural localities may have unique innovation opportunities due to access to natural resources, however they may face barriers due to reduced prospects for knowledge spillovers and collaboration with HE knowledge base.

E.14

Studies have investigated the characteristics of high growth firms and the findings challenge some traditional perceptions about high growth. For example, and encouragingly for CIoS evidence suggests that high growth does occur in traditional sectors; innovation is not dependent on HEIs; access to finance is not as highly valued as business advice and support; and internationalisation is not just about exporting, but partnerships and foreign investment.

Question 4: Smart specialisation is a priority in the current EU Growth Programme; however, whilst there is a high growth innovation element, should CIoS consider defining incremental innovation to raise our larger SME base as a whole?

E.15

Smart Specialisation is a policy steer aimed at ensuring national/regional/local economies focus on their own competitive advantage by matching their existing strengths to business needs and emerging opportunities. The aim is to avoid duplication and fragmentation of effort and to create targeted research and innovation strategies which support the goals and EU Structural Funds in all regions.

E.16

The Smart Specialisation Strategy for England (2015) includes the aim to provide guidance to LEPs about opportunities to benefit from investment in innovation. The Strategy utilises a location quotient to identify the localities with relative strengths in the sectors identified within the UK Industrial Strategy. CIoS is only specifically mentioned in relation to Agritech in terms of local strengths. This clearly reflects the existing sector profile in Cornwall and its emphasis on traditional sectors. As a result Cornwall risks missing out on benefiting from national innovation strategy, therefore should consider local approaches.

E.17

The CIoS RD&I Framework provides a comprehensive steer on how Smart Specialisation can be applied in the County. The Framework firstly identifies the markets that are aligned closest to the England strategy (namely: agri-tech, digital economy, e-health and e-wellbeing, marine technology, space and aerospace) and secondly identifies the need to increase RD&I spending across the business base.

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E.18

A key challenge for CIoS is understanding how traditional sectors can be supported to increase their productivity alongside the more high tech and new sectors. There is a good case for supporting these sectors from an equity perspective, but also in context of evidence which suggests that productivity growth does not necessarily come from new start-ups or new technology. In terms of relative volume of employment, the top five dominant sub-sectors in Cornwall when compared to national averages are: camping, mining, fishing, holiday accommodation and baking. Supporting traditional sectors may provide a further route to enhancing local strengths to create higher value output (e.g. glamping, high tech fishing, and luxury baked goods).

Question 5: How CIoS can tap into the South West supply chain to enable our SMEs to become more productive in key sectors (construction, aerospace, agri-tech and marine)

E.19

Rural areas in Cornwall face particular challenges such as establishing, and benefiting from, local knowledge clusters. Furthermore rural communities have been found to mirror the urban communities they are connected to, this is particularly difficult for very rural and peripheral localities. Cornwall is therefore looking beyond its boundaries at ways in which to creatively extend their supply chains.

E.20

When comparing the priority sectors of LEP in the South West, there are clearly more similarities between the CIoS and the relatively rural Heart of the South West and Dorset than with Wiltshire & Swindon and the West of England. All LEPs are keen to pursue regional strengths in advanced manufacturing & aerospace, and there is a prevalence of sectors that build on environmental and geographic strengths such as agri-food sectors and tourism. CIoS is the only LEP area that specifically mentions construction. However, this is clearly an enabling sector which can support developments and infrastructure investment (e.g. in nuclear or military & defence).

Question 6: If employees are more productive how can we ensure a quality work/life balance?

E.21

Education, skills and health are recognised as clear drivers of well-being, all of which directly contribute to levels of productivity within a firm. Through investment in these channels there appears to be the potential for business to set the foundations for a virtuous circle. Positive feedback loops can be created as improvements in education, skills and health can improve the well-being of staff, which in turn can have positive improvements in business productivity, enabling further rounds of investment.

E.22

As there is evidence of a positive link between productivity and well-being a further examination of ONS and other publicly available indicators could be undertaken to create a bespoke well-being framework for CIoS, based on ONS’s Well-being Wheel.

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INTRODUCTION 1.1

ERS Ltd, alongside the Department for Accounting, Economics and Finance at the University of the West of England (UWE) were commissioned in May 2016 by Cornwall and Isles of Scilly (CIoS) Local Enterprise Partnership (LEP) to develop a Productivity Framework. The overarching purpose of the commission is to provide analysis of productivity issues in order to support the CIoS LEP’s approach to business support.

1.2

Increasing productivity is a national priority with the overarching aim of improving living standards for all. In recent years LEPs have taken on increasing responsibilities to allocate investment in order to tackle persistent economic challenges and achieve productivity-led growth. LEPs are responsible for supporting local business growth, creating local jobs and helping people realise their potential. In Cornwall and the Isles of Scilly, this is further defined within the Cornwall Devolution Deal.

1.3

In the context of this local and national priority there is the need for CIoS LEP to understand what productivity is and how funded activities can target productivity in the CIoS context.

Importantly, productivity objectives must be achieved in a way that is sustainable and benefits all communities.

1.4

The remainder of this report is structured in two parts: Part 1: The Productivity Plan provides a summary of the key findings and recommendations emerging from the literature review. Recommendations are presented under two headings: firstly strategic recommendations, namely considerations for the LEP’s overall approach; and secondly delivery recommendations relating to the provision of business support.

Part 2: The Theory & Evidence Review provides an overview of the literature and evidence relating to productivity theory. This evidence is presented using the six key lines of enquiry within the original study brief, and provided the basis for the recommendations presented in Part 1. The six key questions within the study brief were: 

Can a national definition of productivity be aligned to issues affecting CIoS?



Often productivity has negative connotations, how can we have robust plans in place to overcome short term productivity issues (the loss of jobs) for long term gains (the creation of new jobs, upskilling etc.).



How does productivity affect micro and SMEs?



Smart specialisation is a priority in the current EU Growth Programme; however, whilst there is a high growth innovation element, should CIoS consider defining incremental innovation to raise our larger SME base as a whole?



How CIoS can tap into the South West supply chain to enable our SMEs to become more productive in key sectors (construction, aerospace, agri-tech and marine)



If employees are more productive how can we ensure a quality work/life balance?

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PART 1: PRODUCTIVITY RECOMMENDATIONS What does the theory and evidence tell us about productivity in Cornwall and the IoS? 2.1

Productivity is a measure of output per unit of input, and in theory can be used to describe the impact of any input on economic output. Labour productivity is the most commonly used policy target as it is a key determinant of earnings because higher labour productivity should result in higher wage rates. GVA per hour worked is the preferred measure of labour productivity at a sub-national level as it reflects part-time and seasonal work as well as nonworking populations, which are particularly relevant in the CIoS context. CIoS is currently the lowest ranked of all 39 LEPs using this measure (2014 data).

2.2

Whilst labour productivity provides an indicator of living standards (due to link to wages and thus material wellbeing), it should be included within a suite of measures to track progress against LEP aims for example wellbeing, inclusion and environmental performance.

However there is clear potential for the creation of a virtuous cycle between wellbeing and productivity, as improvements in both can be achieved by similar factors such as skills, education and health.

2.3

At the level of the individual business, labour productivity is increased via more effective use of labour inputs through for example, improved skills, new processes or capital investment (i.e. more effective equipment). At an aggregate geography, productivity measures are also influenced by the sector composition of the business base; a greater proportion of highly productive firms improves the average overall. In order to understand whether productivity growth is typically coming from a shift in the sector composition of an area, or change in the productivity levels of businesses, further location-specific firm level data and sectoral analysis would be beneficial. Existing evidence suggests that the main driver of productivity growth is firms improving their own productivity. Firm level data from other locations finds that internationalisation in the form of foreign ownership or overseas sales is a significant factor in firm level productivity.

2.4

Whilst Cornwall ranks lowest of the LEP areas in terms of productivity, the UK as a whole ranks poorly in global comparisons. More generally, advanced economies have seen persistently low productivity growth; even prior to the 2007-8 financial crisis. In the UK, policy is outlined within HM Treasury’s UK Productivity Plan which emphasises the role of cities/urban growth (e.g. the ‘Northern Powerhouse’) and attracting global businesses (e.g. through lowering Corporation Tax, reducing regulation etc.). Initiatives to support apprenticeships and innovation are also referenced; however, the majority of measures do not target issues most pertinent to CIoS. In the context of this national policy, it would be beneficial if CIoS LEP ensures it is broadly aligned to government-supported programmes and investment such as the Plymouth and South West Peninsular City Deal.

2.5

The EU policy and programmes for 2014-2020 retain their long term focus on improving innovation, enterprise and skills within the context of sustainable development and equality

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of opportunity. The result of the EU referendum in favour of the UK leaving the European Union, does not invalidate the benefits to Cornwall in retaining these policy themes within the context of local strategy and investment. These intervention strands are closely linked to the established method of making investment decisions based on market failure rationale.

2.6

Due to the strong link between innovation and productivity Smart Specialisation is a key strand of European policy in the 2014-20 programme. The policy seeks to ensure that regions/localities build on their existing strengths to achieve growth. The Smart Specialisation Framework for England highlights the role of Higher Education & Research Institutes, Catapult Centres and the 11 sectors identified in the UK Industrial Strategy which are believed to have the greatest potential for growth and jobs. Similar to the UK Productivity Plan, the national policy for Smart Specialisation does not closely align with the local context in CIoS (with the exception of Cornwall’s strengths in the agritech sector). Whilst there may not be a direct presence within Cornwall of the majority of the sectors within the Industrial Strategy, further consideration could be given to the supply chains of the high productivity sectors identified within it (e.g. the construction sector). CIoS’ Research, Development & Innovation Framework analyses on how the principles of Smart Specialisation can be applied in the CIoS context and identifies: agritech, digital economy, e-health & e-wellbeing, marine technology and space/aerospace as market priorities.

2.7

In terms of relative volume of employment, the top five dominant sub-sectors in Cornwall when compared to national averages are: camping, mining, fishing, holiday accommodation and baking. In the context of this profile and the strategic focus on high tech industries, it is important for CIoS to note that high growth firms are not necessarily involved in advanced technology and often come from traditional sectors. For example the Future Fifty, identified as 50 of the fastest growth companies throughout the UK, includes a reasonable representation of firms in traditional sectors such as food and retail/gifts, alongside technology companies. Supporting traditional sectors may provide a further route to enhancing local strengths to create higher value output (e.g. glamping, high tech fishing, and luxury baked goods).

2.8

Research evidence finds that attitudes towards growth are key. Business leaders with growth intentions are more likely to realise high growth, whilst those with no predisposition towards growth may actively resist growth. An individual’s initial growth intentions are influenced by factors such as background, including affluence and socio-economic group.

Importantly evidence shows that those with a moderate predisposition towards growth may be coached or encouraged to reflect on their business and increase their growth intentions.

2.9

When compared to LEPs with similar productivity performance, CIoS is more rural and more peripheral therefore has less easy access to urban markets and labour. Effective infrastructure, both physical (i.e. transport) and digital is essential to ensure peripherality does not exacerbate productivity challenges. Research gathering business feedback has found that the growth challenges perceived by rural firms are not wholly different from their urban

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counterparts, however the barriers to accessing and developing skilled labour may be more acute for rural firms. Rural firms were also found to be more likely to perceive regulation as a barrier to growth when compared to urban businesses. Rural firms could therefore benefit from support to tackle their regulatory obligations.

2.10

When examining data on the characteristics of high growth firms, non-organic growth (e.g. acquisitions) is a significant factor, and even small firms utilise this as a route to achieving growth potential. Supporting firms to effectively change organisational structures could therefore be another perspective on business support provision.

2.11

Table 2.1 summarises the strategic recommendations based on the theory and evidence.

Table 2.1: Summary of Theory and Evidence and Strategic Recommendations Theory & Evidence Recommendations: Strategic Considerations Labour productivity growth closest link to i) GVA per hour worked preferred measure of earnings. Capital productivity is a key labour productivity growth; determinant of profits, while total factor ii) Labour productivity should be considered productivity usually measures the impact of alongside measures of sustainable technological change. development and wellbeing. iii) Build/retain links with Plymouth City Region UK productivity policy focuses on city regions & iv) Identify the potential CIoS supply chains in: investment in high productivity sectors, England Smart Specialisation sectors; CIoS’ particularly high tech.

RD&I Framework target markets; and the UK Industrial Strategy sectors.

Growth intentions matter and a small minority v) Target support at those with strong or of firms account for the majority of gains in moderate growth potential, and seek to productivity growth averages. enhance aspirations.

Rural firms are not wholly different from urban vi) Retain overview of infrastructure issues (i.e. counterparts (provided effective infrastructure maintaining SuperFast Broadband) is in place). Perceptions about regulatory vii) Support effective access to skills & labour barriers may be higher. viii)Support with regulation EU programmes retain their long term focus on ix) SME business support investment decisions improving innovation, enterprise and skills. The based on evidenced economic market result of the EU referendum does not invalidate failure rationale. (For example within the benefits to Cornwall in retaining these Employment & Skills Strategy and RD&I policy themes Framework) High growth does not necessarily mean ‘high x) Consider support in sectors that are ranked tech’, strong business growth can come from highly in terms of employment strengths, traditional sectors. Quality matters more than particularly enhancing output value. quantity of enterprise. xi) Examine whether the Growth Hub Non-organic growth (i.e. acquisitions) an provision supports those seeking to grow important route to high growth. via acquisitions.

Key link between international factors (e.g. xii) Identify priorities and targets for inward trade, ownership) and growth. investment and internationalisation.

What does this mean for business support in CIoS?

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2.12

The key question for this study is what do these insights tell us about supporting businesses growth in CIoS? Table 2.2 provides a summary of delivery recommendations. This is followed by narrative expanding on the recommendations.

Table 2.2 Summary of Delivery Recommendations Evidence i) Firms with international links or outlook demonstrate higher productivity Growth intentions matter as they are key to productivity and growth outcome. However, initial growth ambitions can be influenced by socio-economic factors such as affluence.

Furthermore those with moderate growth ambitions can be coached towards growth.

Sector composition affects the productivity performance of a geographical area as a whole.

Whilst existing CIoS sectors does not feature predominantly in sector strategies, there may be potential within supply chains.

Firm level productivity is key. Cornwall has input (employment) strengths in more traditional sectors such as: camping, accommodation, fishing and baking.

Not insignificant role of non-organic factors in firm level growth Promote Cornwall’s strengths to attract high growth sectors.

Recommendations: Delivery Support for exports and international partnership, and facilitate an international perspective. ii) Leadership development and training targeted at those with high growth ambitions. iii) Support for those with moderate growth ambitions e.g. peer support, reflective business performance assessments, networks etc. iv) Supplier/procurement readiness and marketing training for those in the supply chains of target growth sectors in e.g. UK Industrial Strategy, CIoS RD&I framework, and neighbouring LEP Smart Specialisation strategies. v)

Identify ways to support traditional sectors to add value to their outputs.

vi) Provision of expertise on e.g. growth through acquisitions, succession planning. vii) Targeted investment to attract new high growth businesses to Cornwall.

Action 1: Support Internationalisation Support for Exporting 2.13

Exporting businesses have been shown to be more productive than non-exporting businesses.

This is often driven by exposure to additional competitive pressures but also to new ideas. In addition, there is the potential for more export-oriented businesses to become more resilient as they spread risk across a wider variety of markets.

2.14

Working with UKTI and other partners, the LEP should focus business support on raising awareness of existing services and signposting businesses to those services, as well as filling in gaps in service provision. With regard to the latter, other work ERS has undertaken for UKTI in the North East pointed to a notable gap in respect of support needed by businesses interested in overseas markets, but who were not yet export ready. Further work may be required to determine the nature and extent of support needs in this regard.

Support for International Partnerships

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2.15

Whilst some businesses have it within them to be productive, others need to learn how to become more productive (and all have the potential to be more productive). One of the means by which learning can take place is through relationships with other businesses. This could be a supplier-buyer relationship, a marketing partner, a research partner, a joint venture partner or other relationship.

2.16

There may be a role for the LEP to play in supporting local businesses to explore and develop relationships with overseas businesses. This could be especially important in the context of the UK leaving the EU. Action 2: Supporting Business Leaders High Growth Leaders

2.17

Given that the vast majority of businesses are small businesses and given the key role ownermanagers play in driving productivity, there would appear to be significant scope for seeking to raise productivity by improving the competence of business leaders. Experience elsewhere suggests that many owner-managers are motivated by their passion for the goods and services they produce and are not always necessarily equipped with the full range of skills that ensures they run their business in the most productive manner.

2.18

There are a number of established (and proven) leadership courses delivered by universities (including Lancaster, Swansea and Teesside) and others, which may have relevance and usefulness in Cornwall and Isles of Scilly.

2.19

The LEP might consider supporting the provision of a course in leadership skills, perhaps drawing on good practice from elsewhere and, possibly, working with those existing deliverers and previous experience in Cornwall.

2.20

Peer Networks The evidence suggests that some of the more productive businesses tend to prefer learning from their peers rather than taking advice from traditional business support providers. In this respect, the LEP could play an important role in facilitating peer learning.

2.21

Careful consideration ought to be given to how this could be done most effectively. This might mean going through existing structures (Chambers of Commerce, Federation of Small Business, Sector Groups etc.) or creating new ones that might be more bespoke to needs. It might also require a combination of physical and virtual activity.

2.22

It is suggested that the LEP explore business-led solutions to peer networking and learning, focusing on the types of businesses with potential to become more productive (and grow).

Action 3: High Growth Supply Chains

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2.23

Supplier Readiness Whilst many of the sectors identified within the national strategies do not feature within Cornwall, those that could benefit indirectly from their supply chains need to be in the best possible position to benefit from sector growth. Similarly, the supply chains of the sectors identified in the CIoS RD&I Framework should be ready to benefit from their predicted growth. The LEP could therefore provide support to ensure these businesses are fit to supply and procurement ready, including effective marketing to ensure opportunities are maximised.

Action 4: Firm Level Productivity Innovation in Traditional Sectors

2.24

Evidence suggests that productivity growth is not limited to high technology sectors or happening exclusively within higher education research institutions, but often within traditional sectors. Some of the UKs fastest growing businesses may, for example, utilise or adopt technology rather than develop it. To build on its existing strengths, CIoS could develop business support targeted at creating higher added value in outputs in traditional sectors.

This could include for example: increasing the value of accommodation provision (e.g. ‘glamping’), leisure activities (e.g. high tech fishing) and food products (e.g. luxury baked goods).

Action 5: Supporting change to organisational structures growth

2.25

Traditional business support provision focusses on initiatives such as skills, marketing and management, however, non-organic growth such as acquisitions play a key role in high growth firms. There may therefore be a role for the Growth Hub to play in supporting businesses to grow business through mergers or acquisitions, as well as in succession planning Action 6: Targeted Inward Investment UK-Based

2.26

The evidence indicates that more productive businesses tend to be within particular sectors and be run by people with particular motivations/aspirations. An example of the types of businesses which might fall into both categories would be the cluster of tech businesses in parts of north/east London.

2.27

Critical to these businesses are the networks (social and business) within which they operate.

Within the South West, people looking to start up such businesses tend to gravitate towards Bristol, as much for its social offer as its business opportunities.

2.28

Given the huge costs of living and running a business in London, there has to be an opportunity to tempt some such businesses to relocate to a more affordable location, which can also offer quality of life benefits. Furthermore, it might reasonably be assumed (though would need testing) that many such business owners may be looking for a different kind of lifestyle as they get older. Similarly, albeit on a smaller scale, the same might apply to such businesses that have been set up in Bristol over recent years.

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2.29

It is therefore suggested that exploratory work be undertaken to establish: the size of this potential market, the likelihood of CIoS LEP being able to tap into it and how this might best be achieved. Were this to be a viable proposition, there would be a need to identify one or more key locations where such businesses might cluster and to design/implement engagement with such businesses.

International

2.30

The evidence indicates that, on the whole, overseas-owned business tend to be more productive than UK-owned businesses. This may relate to the drivers of investment being linked to more successful (more productive) companies, the sectors within which they operate, the newness of their operating facilities, their commitment to skills development etc.

2.31

Whilst it is recognised that this is a highly competitive market, there would appear to be merit in the LEP (with partners) undertaking activities which target/engage international businesses operating in key sectors.

Summary

2.32

Strategic and delivery recommendations are summarised within the Figure 2.1 overleaf. The strategic recommendations highlight that the CIoS economy is not easily aligned to the priorities identified within national strategy, such as target growth sectors and city regions.

However, and more encouragingly, evidence suggests that businesses exhibiting high growth are not exclusively high tech, indicating some potential for traditional sectors. In addition non-sectoral characteristics such as internationalisation (e.g. ownership or sales) have a significant positive influence on productivity.

2.33

The delivery recommendations identify ways in which the CIoS LEP could target productivity overall, for example via the Growth Hub. Existing strategies for innovation and skills closely align with productivity aims, however further consideration of support for: supplier readiness, inward investment, internationalisation and business structures could benefit firms and the LEP area as a whole.

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Productivity Recommendations

Figure 2.2 Productivity Recommendations: Strategic Considerations & Suggested Actions

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PART 2: THEORY AND EVIDENCE REVIEW 3.1

In this section we review recent literature and data to respond to the six core questions of the study. The evidence gathered then informs the recommendations in Part 1.

Question 1: Can a national definition of productivity be aligned to issues affecting C&IoS? 

Are there similar areas in the UK and Europe with productivity issues like C&IoS?



Is there a singular definition, or in fact many (sector, high growth, incremental) and how do these work together for common outputs?

Defining Productivity 3.2

Productivity is a general term used to cover a range of different performance indicators measuring the concept of output per unit of input. It is most commonly used to refer to labour productivity although can in theory be used to refer to the impact on economic output of any input. Thus capital productivity – the impact of capital on output - and total factor productivity are sometimes quoted.

3.3

Labour productivity is seen as an important policy target as (in a free market) it is the key determinant of earnings. Broadly speaking, higher labour productivity should result in higher wage rates and earnings both comparatively between sectors and also over time. Higher labour productivity is thus a route to greater material wellbeing. Capital productivity is a key determinant of profits while total factor productivity – which is often used to measure the impact of technological change on output – has a strong role in promoting economic growth.

3.4

Increasing productivity and employment are key factors of economic growth, however, if employment grows at a faster rate than output, labour productivity can fall. Given the limitations of simply increasing employment indefinitely, productivity is regarded as the primary route to growth. Growth in output and productivity provide useful indicators of improvements in standards of living and prosperity, as well as providing a valuable comparison of international competitiveness.

3.5

The ratio nature of the measure means that if output remains the same and jobs are lost, productivity would rise, likewise if new jobs are created in the economy and output remains the same, productivity measures will fall. The optimum solution is for jobs to create higher output value with the same level of input.

3.6

At the level of the individual business, productivity is influenced by factors such as capital investment, access to skilled labour and process innovation. At an aggregate geography, productivity measures are influenced by the sector composition of the business base (i.e. the sector composition across Cornwall). However, evidence suggests the main driver is firms improving their own productivity1.

1

NESTA (2014) The other Productivity Puzzle: http://www.nesta.org.uk/blog/other-productivity-puzzle

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Productivity Measures 3.7

The ONS Productivity Handbook (2007)2 was developed in response to the increasing focus of government agencies and policy-makers on initiatives to improve productivity, and thus an increased demand for statistics to inform assessment. Rapid changes in the sector composition, specifically due to the increasing role of information technology, has created challenges for the measurement of productivity. In 2015 the Chancellor of the Exchequer commissioned a review of UK economic statistics, which concluded that there was a need to improve both productivity and local statistics. The Office for National Statistics (ONS) is now seeking to take an international lead in raising the quality of productivity data, and has made progress in the inclusion of information technology and R&D as part of UK output.

3.8

The measurement of labour productivity requires data on a suitable measure of output and a measure of labour input. The European Union’s (EU) Structural Funds use regional gross domestic product (GDP) per head as the productivity indicator that determines which regions of the EU are eligible for the highest levels of support under the Convergence Objectives, of which Cornwall is a recipient. However, the ONS notes that GVA is preferable to GDP at regional level because it excludes taxes or subsidies on products that are difficult to attribute to local units (Productivity Handbook, p148).

3.9

In the UK, Gross Value Added (GVA) is the most commonly used measure of output. For business units, this is calculated by subtracting expenditure on inputs (such as raw materials, components and business services) from trading income. GVA is thus equal to the sum of wages/salaries and profits. It is a measure of the benefit to society of the activities of a business although omits taking account of external impacts such as pollution and congestion.

3.10

GVA per head is also not considered an effective measure of regional productivity because as GVA is generally a workplace-based and this is compared to residence-based population, it does not reflect commuting patterns or non-working populations. GVA per worker (or GVA per filled job) does apportion GVA to the number of people employed in the region, however, the drawback of this approach, particularly for regional comparisons, is that is does not take into consideration different working patterns such as the combination of full and part time workers. Due to the importance of seasonal, part time working in the CIoS economy GVA per hour worked is the preferred measure of productivity at a local level (GVA per hour worked = GVA/total workforce hours worked).

3.11

It is more challenging to extend the measurement of GVA to the public and voluntary sectors, where output tends not to be quantified (or ‘non-marketed’, to use the technical term). For this reason, aggregate productivity estimates for an area such as CIoS, can be unreliable. This is because aggregate productivity is calculated by dividing aggregate GVA (where some 40% is likely to be non-marketed) by some measure of aggregate labour input. This is one reason 2

ONS (revised 2016) Productivity Handbook: https://www.ons.gov.uk/economy/economicoutputandproductivity/productivitymeasures/methodologies/pro ductivityhandbook

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for using firm level data to explore productivity in an area, as it enables public sector estimates to be dispensed with. We return to this approach below.

The preferred (pragmatic) measure of productivity at a regional level is GVA per hour worked.

Productivity in Cornwall & IoS 3.12

As is well known and indicated by the County’s ongoing status as an area in receipt of EU Convergence funding, Cornwall performs consistently below regional, national and EU averages in terms of productivity. Figures 3.1 and 3.2 overleaf clearly show that there has not been any reduction in the gap between Cornwall and the UK or the South West, in terms of GVA per filled job or GVA per hour worked over the past decade. Indeed, the gap is greater in 2014 than in 2004 in both measures.

Figure 3.3 GVA per Filled Job

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Figure 3.4 GVA per Hour Worked

3.13

Whilst Cornwall performs less well than the wider region and country, it is not alone in being unable to improve productivity performance. It is a challenge faced by the UK as a whole, as well as other advanced economies, a challenge that ought to be better appreciated and understood.

UK Productivity Performance

3.14

Relatively low productivity is a key challenge facing the UK economy. A 2014 paper by the Bank of England explores the issues surrounding the challenge of productivity improvement in the UK: The UK Productivity Puzzle3. It notes that labour productivity in the UK has been “exceptionally weak� since the 2007-08 financial crisis, with wholeeconomy output per hour at around 16 per cent below the pre-crisis trend (Figure 3.3).

Whilst the exact scale of this shortfall is dependent on a 3

Figure 3.3: Whole-economy labour productivity per hour (Bank of England, 2014, UK Productivity Puzzle, Page 115)

Bank of England (2014) UK Productivity Puzzle

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number of the assumptions within the predictions, the fall in productivity and protracted recovery is certainly more significant than those following any other post-war recession.

3.15

The paper reviews the possible reasons behind the productivity shortfall and concludes that a quarter could be explained through either: i) spare capacity within firms due to cyclical factors; or ii) more persistent reasons, such as reduced investment in physical and intangible capital. Firms appear to have retained (or increased) labour despite weak demand, however, investment in physical and intangible assets had been reduced, perhaps due to difficulties in obtaining finance following the financial crisis. This meant that labour was not allocated in the most productive way. The paper concludes that a further quarter of the productivity shortfall may be explained by measurement issues. This still leaves half of the productivity shortfall unexplained.

3.16

A recent publication, the OECD Compendium of Productivity Indicators (2016)4, highlights that many advanced economies are experiencing a productivity slowdown similar to the UK. The concern is that this may reflect a structural (not cyclical) slowdown, with longer term implications for inequality and well-being. The Compendium report notes that whilst there are measurement issues, this is not the underlying cause of the slower productivity growth metrics. The report concludes that that productivity growth began declining before the financial crisis. However, the picture is more varied since the crisis depending on how employment levels subsequently recovered (i.e. the countries that were hit hardest taking longer for employment to recover).

Lagging productivity is a challenge faced across the UK and other advanced economies, it is not a Cornwall-specific issue.

3.17

To further examine the UK productivity shortfall, the Bank of England also reviewed sector performance5. The five sub-sectors that explain the greatest percentage of the productivity shortfall are: oil & gas extraction, education, financial services, social work and building/landscape services. In some of these sectors the productivity shortfall can be explained by changes in regulation or operating models (e.g. the numbers of teaching staff required in schools/nurseries is higher and more staff are required to manage infrastructure and regulatory requirements in financial services). However, oil and gas has been subject to long term decline and obsolescence of equipment in a capital intensive sector. This sectoral analysis also concludes that a catch up in productivity levels is likely to be slow.

3.18

The OECD Compendium report found that manufacturing productivity growth continues to outpace service sectors, with labour productivity falling in ‘information and communication services’, ‘finance & insurance’ and ‘professional services’.

4

OECD (2016) Compendium of Productivity Indicators http://www.oecd.org/std/productivity-stats/oecd-compendium-of-productivity-indicators-22252126.htm 5 Bank of England (2014) The UK Productivity Puzzle - A Sectoral Perspective: http://www.bankofengland.co.uk/publications/Documents/speeches/2014/speech739.pdf

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Some of the sectors dominant in Cornwall have low/declining productivity at a national level.

Areas with Similar Performance to C&IoS 3.19

Within the UK, C&IoS is the lowest (39th) ranked LEP area in terms of GVA per hour worked.

Figure 3.4 overleaf shows the relative performance of the six highest and six lowest performing LEP areas in terms of GVA per hour worked. Greater London and the South East dominate the highest performing LEP areas.

Figure 3.5 Highest and lowest ranking LEPs, GVA per hour worked

3.20

The three lowest performing LEP areas include significant rural areas, however, in contrast Cornwall lacks any significant urban, city and town areas (depicted in light and dark grey in Figure 3.5 overleaf)6. Whilst Cumbria (ranked 34th) is the furthest north LEP in England, these areas do not face the same peripherality challenges as Cornwall in terms of access to markets and infrastructure.

6

Defra (2014) Local Enterprise Partnerships: Rural Urban Maps: https://www.gov.uk/government/statistics/local-enterprise-partnership-lep-detailed-rural-urban-maps

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Figure 3.5 Rural Urban Classification of Lowest four performing LEPs in terms of Productivity

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3.21

Within the South West, the urban north of Swindon & Wiltshire and the West of England are the only LEP areas that perform above the England average. Using 2014 data, Heart of the South West, Dorset and GFirst and ranked: 31st, 20th and 15th respectively (out of 39 LEPs).

Supporting the argument that access to markets is a key factor.

Figure 3.6 GVA per hour Worked, South West LEPs

Whilst some are rural, areas with similar productivity performance do not face peripherality challenges to the same extent as Cornwall. Infrastructure/access to markets is therefore a key priority.

Firm Level Measures of Productivity 3.22

In order to be able to identify possible policy intervention options at the level of the individual business (e.g. via the Growth Hub), it is necessary to understand firm level performance.

Productivity performance can vary hugely from firm to firm, which can be somewhat hidden in headline measures. Research into how output and productivity changes at the individual firm level seeks to identify whether headline figures are driven by: a) improved productivity in existing firms or b) newer firms replacing low productivity firms in a given geographic area.

3.23

Whilst there are no studies regarding Cornwall in particular, the Wales Institute of Social and Economic Research, Data & Methods (WISERD) undertook a study of firm level productivity in Wales7. The research, funded by ESRC and HEFCW sought to identify the determinants of productivity to inform policy. The paper uses ‘FAME’ company accounts data to explore the role of regional skills and international activity. The study finds that internationalisation in the form of foreign ownership or oversea sales is a significant factor, alongside high skilled workers; both of which dominated agglomeration effects.

7

WISERD (2012) Firm Performance in Wales: http://wiserd.ac.uk/files/6613/6550/0055/WISERD_WPS_007.pdf

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3.24

Similar studies using the Annual Business Survey are based on arguably more robust data but with fewer firm level variables than FAME. Studies using South West regional data confirm the association between higher levels of productivity and foreign ownership and exporting activity but in addition allow some assessment of the strength of impact of a number of quantifiable firm level factors on productivity. As shown below in Table 3.1.

Table 3.1: The Impact of Productivity Drivers: Evidence from Firm-Level Data % change in productivity - single plants (2012 data)

% change in productivity - multi plants (2012 data)

% change in productivity - all plants (2003 data)

% change in productivity - all plants (2001 data)

0.6

1.0

2.9

2.4

1.0

0.0

1.2

0.7

-

-

1.6

-

-0.7

-0.2

-0.7

-1.0

A 10% increase in population density

0.1

-0.1

0.1

-

A 100% increase in population density

-

-

1.3

-

Webber et al (2016)

Webber et al (2016)

Boddy et al (2007)

Boddy et al (2005)

Change in productivity driver A 10% increase in capital stock A 10% increase in the percent of the local labour force with NVQ4+ A 10% increase in % of local labour force with NVQ 2-3 A 10% increase in minimum travel time to London and the 4 next largest cities

Source:

3.25

Such studies also highlight how productivity is influenced by the sector in which the typical firm is operating. This allows an illustration of how overall UK workforce productivity could be increased by a shift in employment away from low productivity sectors into more productive sectors. The impact of a shift of 1% of the workforce between sectors is summarised in Table 3.2.

Table 3.2: Impact on Overall Productivity (% change in GVA/FTE) 1% of workforce into

Transport Manufacturing Retail

1% of workforce out of Agriculture and mining

0.26

0.11

0.16

Hotels and catering

0.59

0.44

0.49

Construction

0.34

0.19

0.24

Source: Webber et al (2016), author’s calculations.

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3.26

Unfortunately, firm level data sets only include a limited number of variables influencing productivity at the firm level. Typically, the studies referred to above are only able to explain some 35% of the variation in productivity between firms. Other variables for which quantitative data is not available include management quality, the workplace environment, HR policies, and the suitability of workforce skills. It is likely that the dissemination of good practice in these areas by CIoS LEP would have a positive impact on productivity. In addition, some of the more nuanced aspects of agglomeration, such as the creativity and vigour of the business milieu, are capable of long term influence by the LEP. Analysis of Cornwall firm level data could be beneficial and would allow analysis of:  The most significant factors influencing productivity of firms in CIoS  The extent to which productivity is held back by peripherality and an absence of a sizeable urban centre  Specific trends over time influencing the main productivity drivers

3.27

Some of the evidence around the more intangible drivers of firm level productivity performance such as ambition and socio-economic background are reviewed under Question 3 later in this Chapter.

National Policy and the CIoS Economy

3.28

The former Chancellor George Osborne’s Productivity Plan ‘Fixing the Foundations’8 includes 15 policy priorities that are arranged under two 2 pillars of activity: long term investment and a dynamic economy (Figure 3.7).

8

HM Treasury (2015) Fixing the Foundations: https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/443898/Productivity_Plan_web.pdf

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Figure 6.7: HM Treasury ‘Fixing the Foundations’: Productivity Framework (page 7)

3.29

The ‘long term investment’ pillar of the Framework includes aims to reduce Corporation Tax, encourage savings and investment, improve skills (from schools through to apprenticeships and universities), and create effective energy, transport & digital infrastructure. The ‘dynamic economy’ strand incorporates housing, reducing the welfare bill, raising employment, encouraging open markets/international trade and supporting cities beyond the greater South East. Whilst the headline policies are linked to some of the five main drivers of productivity (i.e. investment, innovation, skills, enterprise and competition), within the ONS’s Productivity Handbook (2007), innovation and enterprise are notably lacking, as well as consideration of structural challenges.

3.30

The Productivity Plan has faced criticism as the policy tool to address productivity challenges.

The Business, Innovation and Skills (BIS) Committee is appointed by the House of Commons to examine the expenditure, administration, and policy of the Department for Business, Innovation and Skills. In January 2016 a Committee inquiry9 concluded that businesses described the plan as too vague and impractical, that it “represents more of an assortment of largely existing policies collected together in one place than a new plan for ambitious productivity growth” (page 5). The Committee recommended that an implementation plan and measures of success ought to be created for each of the policies listed.

9

House of Commons BIS Select Committee (2016) The Government’s Productivity Plan: Second Report of Session 2015-16 http://www.publications.parliament.uk/pa/cm201516/cmselect/cmbis/466/466.pdf

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The national productivity plan does not reflect the diversity of local economies, specifically peripheral or rural localities found in Cornwall.

3.31

We now know that this policy is subject to change following the UK referendum vote to leave the EU, and subsequent personnel changes across the Government. It is particularly notable that there is increased emphasis on strategy in the title of the Department for Business, Energy and Industrial Strategy (formerly known as the Department for Business, Innovation and Skills) hinting at a more strategic/interventionist approach.

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Question 2: Often productivity has negative connotations, how can we have robust plans in place to overcome short term productivity issues (the loss of jobs) for long term gains (the creation of new jobs, upskilling etc.).

3.32

It is clear that high levels of productivity underpin regional competitiveness, material wellbeing and sustainable economic growth. However, it is important to aim for these overall objectives rather than targeting productivity in isolation. Returning to our initial definition of productivity, the outputs produced for a given level of inputs, policy should support maximising productivity growth by working on the key drivers discussed above so as to maximise the contribution of working people in the long term rather than tolerating short term strategies of shedding jobs and starving the economy of innovation and investment.

It is not necessary or desirable for CIoS to target productivity measures relentlessly or exclusively. There can be a cycle of mutual benefit between, for example, the drivers of wellbeing and productivity to create longer term and sustainable growth.

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Question 3: How does productivity affect micro and SMEs? 

Ensuring we outline the effects on the islands and within rural communities

Growth in Micro and SMEs 3.33 Write et al. (2015)10 sought to summarise research evidence in order to inform SME growth policy. They confirm that a lack of financial and intellectual resources reduces SMEs’ ability to support key enablers for growth namely: R&D, skills, capital investment and pursuing uncertain business avenues (risk taking). SMEs are often less willing or able to invest, therefore risk lagging behind larger business counterparts.

3.34 These policy points directly support the theory of investing to support SMEs to resolve market failures. Market failures can come in the form of:  Public Goods: those that are non–rival and non-excludable when consumed. Gives rise to the problem of ‘free-riding’ when some consumers fail to pay, therefore returns to suppliers are less than the value to society as a whole.  Externalities: when an activity produces benefits or costs that are not directly priced in the market e.g. positive externalities or spillovers of R&D or the negative externalities of pollution from fossil fuels.  Information Failures: Full information is needed for the market to operate efficiently.

Where full information is not available this is known as ‘information asymmetry’ about the good and services being traded. This leads to sub-optimal decision-making.  Market Power: Inefficient or a lack of potential competition can mean the market does not operate efficiently. This may be due to high start-up costs, and exacerbated by those in power strategically protecting their positon via e.g. predatory pricing.

Source: HM Treasury, Green Book (2011) 3.35

In addition to the market failures listed above, government intervention may also be justified for equity reasons. This is the basis of the EU Convergence programme which seeks to redress the balance across European regions. Following the vote to leave the EU, it will be essential for Cornwall to make the case for investment to support its lagging performance.

Market failure and equity investment rationales link strongly to the enablers of SME growth.

3.36

When supporting micro and SME businesses, information failures are often cited, with businesses undervaluing the impact of the support on their own performance. A 2011 report (for BIS)11 looked at the barriers to the take up of business support amongst SMEs. The study

10

Wright, Roper, Hart, Carter (2015) Joining the dots: Building the evidence base for SME growth policy International Small Business Journal 2015, Vol. 33(1) 3 –1 11 Research to understand the barriers to take up and use of business support (2011), Centre for Enterprise and Economic Development Research for BIS

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found that fast growing businesses were more likely to have used external assistance in the last three years from both public and private sources. New businesses (less than 1 year old) and medium sized businesses had the highest propensity to seek external assistance, whilst micro businesses were most likely to use solely public sources for support. Finally, those seeking support were more likely to have larger management teams and more highly qualified managers. Women-led businesses were more likely to use public sources of support than male-led businesses. Write et al. (2015) also note the importance of leadership and dynamism, local programmes to support SMEs to improve management capabilities, and the development of Directors/Boards, each of which could help businesses grow.

3.37

The connection between innovation and high growth is well evidenced, however a further relationship between innovation and exporting is explored in Love and Roper (2015)12. The study finds that SMEs who are innovative are more likely to export successfully, and thus generate growth from exports than firms less likely to innovate.

Encouraging internationalisation has the potential to support innovation and growth.

3.38

The SME Finance Monitor by BDCR Continental tracks the attitudes and demand for finance amongst SMEs. Access to finance is suggested as a barrier to growth for SMEs, however the finance monitor shows 80% of SMEs are ‘happy non seekers of finance’ (Q2 2015)13 and this figure had been increasing over time. In March 2016 the Finance Monitor reports that SMEs were beginning to return to seeking external finance, most specifically larger, ‘more ambitious’ SMEs (that is those who have plans to expand by 20% or more)14.

Access to finance is not necessarily a barrier to growth for SMEs with 80% ‘happy non seekers of finance’.

3.39

BIS paper (Aug 2015) ‘Sociology of Enterprise’15 seeks to understand why the majority of small businesses do not grow or only achieve modest growth. Small businesses are a vital part of the economy, therefore understanding barriers to growth is identified as a priority. The paper acknowledges that whilst research has identified the factors such as access to capital and skills and regulatory barriers, it suggests this analysis is limited in scope and complexity. It notes that entrepreneurs are “highly heterogeneous” and behave in different ways.

3.40

The paper concludes that there is a spectrum of disposition towards growth, and that this has an impact on ambition and business behaviour (such as use of capital resources). Whilst https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/32250/11-1288-researchbarriers-to-use-of-business-support.pdf 12 Love J and Roper S (2015) SME innovation, exporting and growth: a review of existing evidence.

International Small Business Journal 33(1): 28–48 13 BDRC Continental (2015) SME Finance Monitor: http://bdrc-continental.com/wp-content/uploads/2015/09/BDRCContinental_SME_FM_Q2_2015-FINAL.pdf 14 BDRC Continental (2016) Press Release: SME Finance Monitor Q4, 2015 http://bdrc-continental.com/wpcontent/uploads/2016/03/SME-FM-D2-260216-3.pdf 15 https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/453064/BIS-15-482sociology-of-enterprise.pd

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these attitudes or dispositions are not easily observable, they are key to small business performance. Those that are more growth-inclined displayed behaviours such as innovation and perform better in the long run. This group were more likely to come from a ‘higher status family’, be younger and have more of an international outlook. In contrast growth resistant businesses owners who did not have a vision for growth and did not want to take on staff tended to be older, not attended university and not been in a management role before. This BIS paper supports earlier findings that small businesses are inclined to resist change if they perceive they do not belong or would not feel comfortable in the new environment16.

3.41

The policy conclusions within this BIS report highlight the benefits of supporting businesses who are growth-inclined, but importantly does not ‘write off’ growth-ambivalent businesses as a lost cause. This is because they note that dispositions and behaviours may have been influenced by socio-economic background or networks, hence individuals may be coached to think more critically about how to improve their business performance. This evidence points to the importance of how support is delivered as well as what support is provided.

These conclusions are particularly pertinent in the CIoS context which has historically had lower educational attainment and income levels.

Rural Communities

3.42

Some policy interventions differentiate between rural and urban contexts. Most significantly, EU rural development policy sits alongside the Common Agricultural Policy’s direct payments to support rural communities to meet economic, environmental and social objectives. The EU's rural development policy is funded through the European Agricultural Fund for Rural Development (EAFRD) worth €100 billion from 2014-2020. Rural policy shares a number of objectives with other European Structural and Investment Funds (ESIF).

3.43

Studies have examined the different economic needs of rural SMEs when compared to those located in urban or semi-rural localities. Lee and Cowling (2015)17 identified that SMEs in UK rural localities are more likely to perceive regulation as a barrier to growth, whilst urban firms are more likely to be concerned about the general state of the economy. As the study confirms, this reflects firm characteristics in that businesses get smaller the more rural they are, they are more likely to be in primary industries and family ownership also increases as firms become more rural. Urban firms are more likely to be younger, be larger in size and have multi-site operations.

Rural SMEs in Cornwall may particularly benefit from support to alleviate the burdens of regulation.

16

Understanding growth in microbusinesses (Allinson et al., 2013) and Understanding growth in small businesses (Allinson et al., 2015) 17 Lee N. and Cowling M. (2015) “Do Rural Firms Perceive Different Problems? Geography, Sorting, and Barriers to Growth in UK SMEs” Environment and Planning C: Government and Policy, 33 (1), pp. 25-42.

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3.44

Lee and Cowling (2015) also find some evidence that skills shortages are more acute for rural firms. This suggests that improving the mobility of workers in rural locations and improving skills of existing workers could benefit rural firms. Overall, the study concludes there is only limited need for differential policy for small business in rural areas. A NESTA report18 (2007) examines the different innovation challenges that rural firms face and how these are changing over time. The NESTA report concludes that the role of land-based industries is decreasing, and as connectivity is improving, the economic structures in rural areas tend to mirror neighbouring urban areas.

Whilst rural SMEs may benefit from targeted support to access and improve skills, there is only limited evidence for different policy approaches.

3.45

NESTA (2007) highlights the “important relationship� between natural resources in rural localities and innovation, particularly in the context of sustainable technology and growth. It is acknowledged that rural localities are disadvantaged in their ability to innovate due to not being as able to benefit from knowledge spillovers and access to knowledge transfer due to low business density and distance/density of HE knowledge base. Rural firms also tend to be smaller, with potentially limited resources for investment and face higher infrastructure costs (e.g. transport). This is potentially exacerbated by a reduced drive to be competitive.

3.46

Initiatives to improve the HE knowledge base in Cornwall (as well as the Scottish Highlands and Cumbria) have sought to create a local knowledge base and retain skills within rural localities. Improving broadband infrastructure has also sought to ensure rural localities can compete effectively by opening up markets and access to personnel. The access to natural resources (wave, crop-based energy) provides an opportunity which is reflected in Cornwall’s policy emphasis on low carbon technology.

Rural localities across Cornwall & Isles of Scily may have unique innovation opportunities due to access to natural resources, but face barriers due to reduced prospects for knowledge spillovers and collaboration with HE knowledge base.

Characteristics of High Growth Businesses

3.47

In 2009 NESTA19 identified that just six per cent of UK businesses accounted for half of the new jobs created in existing businesses between 2002 and 2008. This prompted a policy focus on programmes targeted at high growth potential firms (those with an average annual employment growth of 20 per cent or more over three years) rather than developing a broad offer of business support. Whilst fast growing businesses could be found in all sectors, spanned established firms and start-ups, and were both small and large organisations, they were found to be significantly more innovative than other firms. Their innovation challenged

18

Rural Innovation, NESTA Dec 2007 https://www.nesta.org.uk/sites/default/files/rural_innovation.pdf The vital 6 per cent: How high-growth innovative businesses generate prosperity and jobs (2009), NESTA: http://www.nesta.org.uk/publications/vital-6 19

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and replaced weaker existing business and therefore drove longer term productivity growth by replacing those lagging behind.

3.48

More recent evidence from NESTA20 confirms that quality matters more than quantity.

Interestingly, the report noted that new businesses were not necessarily more productive, with existing businesses being the main contributors to productivity growth.

High growth firms come in many guises and the quality of enterprise matters more than quantity of enterprises.

3.49

In an updated NESTA paper (2014)21 the evidence suggests that innovative firms grow twice as fast as less innovative firms, but confirmed that high growth firms vary in size, sector, business model and ownership. This makes identifying them particularly challenging when targeting policy interventions. However, high growth firms were found to invest “substantially” in training despite the high opportunity cost of doing so when sales are growing rapidly.

3.50

NESTA usefully examines and challenges six policy approaches which aim to support high growth firms (HGFs). Their conclusions are summarised in Table 3.3 below: Table 3.3: Misalignment between public policy and the characteristics of high growth firms (HGFs) Source: NESTA 2014 (page 18) Public policy to support HGFs A major thrust of policy is aimed at increasing R&D within firms.

The nature of HGFs HGFs often source and use a variety of ‘open’ sources of innovation, such as links to customers and end-users [i.e. not necessarily HEIs or in firm investment in R&D]

There is a strong emphasis on developing sources of entrepreneurial finance.

Most HGFs prefer to retain full ownership and the majority use (and prefer) traditional sources of debt funding.

There is a strong focus on exporting and export development.

HGFs often internationalise through a wide variety of international market entry modes, such as joint ventures, overseas FDI, overseas acquisitions, and partnering.

Public policy concentrates support towards high-tech firms and sectors.

The overwhelming majority of HGFs emanate from traditional sectors of the economy, with high-tech firms comprising a very small minority of the overall population of HGFs.

High growth policy strongly focuses on assistance for new ‘de novo’ start-ups.

The majority of HGFs emerge from the existing population of SMEs (of all ages) within the economy. They are often firms who have undergone important growth ‘triggers’ such as management buy- out, management buy-ins or acquisitions.

20

NESTA (2014) The Other Productivity Puzzle http://www.nesta.org.uk/blog/other-productivity-puzzle NESTA (2014) Increasing ‘The Vital 6 Percent’: Designing Effective Public Policy to Support High Growth Firms https://www.nesta.org.uk/sites/default/files/working_paper_-_increasing_the_vital_6_percent.pdf 21

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Business support is strongly oriented towards support for organic growth.

Forms of non-organic growth (i.e. acquisitions) are very important for firms undertaking rapid growth, even within smaller firms who often see acquisition as a key element to achieve rapid growth.

The main policy ‘tools’ used to support HGFs take the form of ‘transactional’ instruments such as grants, subsidies, tax incentives etc.

HGFs tend to value ‘relational’ forms of support above direct financial assistance. Assistance with strategic guidance and organisational development are perceived to be particularly beneficial.

The vast majority of business support is provided directly by the public sector or through private sector intermediaries.

The preference of many HGFs is to obtain advice and guidance from their peers within industry, rather than directly from the public sector or intermediaries.

The table above provides a number of interesting, and encouraging, points for Cornwall that can inform intervention approaches:  High growth does and can occur in traditional sectors;  Internationalisation is not just exporting;  Business value advice and support (e.g. from peers) above financial assistance;  Innovation is not dependant on HEIs and their spin offs; and  Acquisitions are important.

3.51

Levie and Autio (2013)22 investigated the connection between growth intentions and achievement of enterprise growth. The meta-analysis concluded that growth intentions do matter, and the effect is not small. The proportion of businesses with high growth intentions was found to be a greater predictor of economic growth, than start up and self-employment rates. Business owner characteristics that are highlighted in the paper are: innovativeness (pro-activeness and risk-taking) as well as perception of the size of their home market (the greater the size of the home market the greater aspirations). Overall this indicates that the attitudes and perceptions, culminating in growth intentions are a reasonable predictor of success.

In areas seeking to grow, it would be beneficial to track and encourage growth intentions, for example via programmes that encourage growth aspirations.

22

ERC White paper: Growth and growth intentions (2013), Levie and Autio

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Question 4: Smart specialisation is a priority in the current EU Growth Programme; however, whilst there is a high growth innovation element, should C&IoS consider defining incremental innovation to raise our larger SME base as a whole? 

Including the effects on traditional and emerging sectors



Including how this would affect C&IoS GVA and productivity as a whole

EU Smart Specialisation Policy 3.52

Investing in research, innovation and entrepreneurship is central to European policy. Smart Specialisation is a policy steer aimed at ensuring national/regional/local economies focus on their own competitive advantage by matching their existing strengths to business needs and emerging opportunities. The aim is to avoid duplication and fragmentation of effort and to create targeted research and innovation strategies which support the goals and EU Structural Funds, namely a knowledge economy in all regions23. The Commission defines Smart Specialisation or RIS3 strategies as follows: Definition of Smart Specialisation (RIS3) Strategies: • They focus policy support and investments on key national/regional priorities, challenges and needs for knowledge-based development, including ICT-related measures; • They build on each country's/region’s strengths, competitive advantages and potential for excellence; • They support technological as well as practice-based innovation and aim to stimulate private sector investment; • They get stakeholders fully involved and encourage innovation and experimentation; • They are evidence-based and include sound monitoring and evaluation systems.

Source: Guide to Research and Innovation Strategies for Smart Specialisation (RIS 3) (page 8)

3.53

The emphasis on Smart Specialisation Strategies (RIS3 or S3) aims to deliver more sustainable growth via more effective investment in education employment growth, innovation and poverty reduction and moving towards a low carbon economy.

Smart Specialisation in England and Cornwall

3.54

The Smart Specialisation Strategy for England (2015)24 includes the aim to provide guidance to LEPs about opportunities to benefit from investment in innovation. The Strategy utilises a location quotient to identify the localities with relative strengths in the sectors identified

23

Smart Specialisation Platform (RIS3): http://s3platform.jrc.ec.europa.eu/ris3-design BIS (2015) Smart Specialisation in England https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/436242/bis-15-310-smartspecialisation-in-england-submission-to-european-commission.pdf 24

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within the UK Industrial Strategy25. CIoS is only specifically mentioned in relation to Agritech in terms of local strengths (a location quotient in excess of 2). This clearly reflects the existing sector profile in Cornwall and its emphasis on traditional sectors.

Cornwall risks missing out on benefiting from national innovation strategy, therefore must adopt local approaches.

3.55

The CIoS RD&I Framework26 provides a comprehensive steer on how Smart Specialisation can be applied in the County. The Framework firstly identifies the markets that are aligned closest to the England strategy (namely: agri-tech, digital economy, e-health and e-wellbeing, marine technology, space and aerospace) and secondly the desire to increase RD&I spending across the business base.

3.56

A key challenge for CIoS is understanding how prevalent traditional sectors can be supported to increase their productivity alongside the more high tech and new sectors. There is a good case for supporting these sectors from an equity perspective, but also in context of evidence which suggests that productivity growth does not necessarily come from new start-ups or new technology.

3.57

In order to identify the sectors with input strengths (i.e. high employment) in Cornwall relative to other areas of the UK, we have constructed a location quotient (LQ) for employment by sector (Table 3.4). The LQ shows the proportion of the CIoS employment accounted for by a sector compared with that for the UK as a whole. Thus a value of 1.0 signifies that the sector accounts for the same proportion of employment as in the UK as a whole. A value of 2.0 indicates that the sector employs a proportion of the labour force double that in the UK as a whole. Table 3.4 overleaf shows all sectors where there are more than ten firms in Cornwall and where the LQ is 1.5 or more. The table is based on 2011 data.

Table 3.4: Location Quotient: 1, 2, 3 digit SIC codes SIC code and description: 1, 2 & 3 digit sectors with LQ 1.5 & ABOVE

LQ value

553 : Camping grounds, recreational vehicle parks and trailer parks

8.78

08 : Other mining and quarrying

8.71

031 : Fishing

8.43

552 : Holiday and other short stay accommodation

7.17

03 : Fishing and aquaculture

5.81

559 : Other accommodation

5.36

107 : Manufacture of bakery and farinaceous products

4.78

799 : Other reservation service and related activities

3.98

101 : Processing and preserving of meat and production of meat products

3.95

301 : Building of ships and boats

3.73

25

Aerospace, Agricultural Technology, Automotive, Construction, Information Economy, International Education, Life Sciences, Nuclear, Offshore Wind, Oil and Gas and Professional & Business Services.

26 CIoS LEP (2016) Research, Development and Innovation Framework: http://www.cioslep.com/assets/uploads/documents/1461574419_C&IoS%20RD&I%20Framework%20FINAL.p df

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3.58

55 : Accommodation

3.66

105 : Manufacture of dairy products

3.34

551 : Hotels and similar accommodation

2.86

91 : Libraries, archives, museums and other cultural activities

2.79

910 : Libraries, archives, museums and other cultural activities

2.79

B : Mining and quarrying

2.63

473 : Retail sale of automotive fuel in specialised stores

2.53

10 : Manufacture of food products

2.51

323 : Manufacture of sports goods

2.34

873 : Residential care activities for the elderly and disabled

2.32

331 : Repair of fabricated metal products, machinery and equipment

2.31

592 : Sound recording and music publishing activities

2.28

024 : Support services to forestry

2.13

33 : Repair and installation of machinery and equipment

2.1

563 : Beverage serving activities

1.98

I : Accommodation and food service activities

1.96

016 : Support activities to agriculture and post-harvest crop activities

1.91

478 : Retail sale via stalls and markets

1.87

141 : Manufacture of wearing apparel, except fur apparel

1.86

463 : Wholesale of food, beverages and tobacco

1.82

032 : Aquaculture

1.75

74 : Other professional, scientific and technical activities

1.7

453 : Sale of motor vehicle parts and accessories

1.68

462 : Wholesale of agricultural raw materials and live animals

1.67

772 : Renting and leasing of personal and household goods

1.66

853 : Secondary education

1.63

493 : Other passenger land transport

1.61

162 : Manufacture of products of wood, cork, straw and plaiting materials

1.59

472 : Retail sale of food, beverages and tobacco in specialised stores

1.59

75 : Veterinary activities

1.58

750 : Veterinary activities

1.58

932 : Amusement and recreation activities

1.58

14 : Manufacture of wearing apparel

1.56

471 : Retail sale in non-specialised stores

1.53

16 : Manufacture of wood and of products of wood and cork, except furniture;

1.51

87 : Residential care activities

1.5

The location quotients can be used to suggest sectors in which CIoS27 may be able to lead the way in introducing innovation into sectors where its economy is currently strong. These are likely to be sectors in which CIoS has some basis for competitive advantage, whether that lies

27

LQs for the Scillies are not shown as few sectors have ten firms or more. Data confidentiality prohibits the publication of data where less than 10 firms are represented.

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in resource endowment, skills availability or geography, and thus may hold the potential for further growth.

3.59

The key to productivity growth is a shift towards higher value added outputs. This is more likely to be the case where: higher-priced market segments are catered for, or where hightech innovation is being applied and where a high level of specialist skills are required. In CIoS this may be apply to, for example: ‘glamping’, luxury food, high tech fishing or the creative sector.

The RD&I Framework provides guidance on how Smart Specialisation can be applied in Cornwall & Isles of Scilly. Opportunities to support sector strengths to increase output value would complement this approach in enhancing productivity.

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Question 5: How can C&IoS tap into the South West supply chain to enable our SMEs to become more productive in key sectors (construction, aerospace, agri-tech and marine)?

3.60

Rural areas in Cornwall face particular challenges such as establishing, and benefiting from, local knowledge clusters. Furthermore rural communities have been found to mirror the urban communities they are connected to, this is particularly difficult for very rural and peripheral localities. Cornwall is therefore looking beyond its boundaries at ways in which to creatively extend their supply chains.

3.61

Table 3.5 includes the priority sectors identified within the strategies of the four closest LEPs. It is important to note that whilst some LEP list priority sectors, not all do. In cases where priority sectors are not specifically identified by the LEP, the sectors of focus listed below have been identified from those mentioned within LEP strategies.

Food & Drink











Heart of the SW





Agri-food



Dorset







Adult Social Care



Wiltshire & Swindon





Health & Life Science



Informatio n Economy

Military & Defence



Creative & Digital Media

‘High Tech'

West of England









Construction



New Nuclear

Other

Marine

E-health

Digital

Health

Professional & Financial Services

Agriculture / Land Based

CIoS

Advanced Manuf. & Aerospace

Tourism

Low Carbon / Enviro Goods & Services

Table 3.5 Priority Sectors for South West LEPs

International Education; Retail; Creative

3.62

There are clearly more similarities between the CIoS and the relatively rural Heart of the South West and Dorset than with Wiltshire & Swindon and the West of England. All LEPs are keen to pursue regional strengths in Advanced Manufacturing and Aerospace, and environmental and geographic strengths via the agri-food sectors and tourism.

3.63

CIoS is the only LEP area that specifically mentions construction. However, this is clearly an enabling sector which can support developments and infrastructure investment (e.g. in nuclear or military & defence).

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Question 6: If employees are more productive how can we ensure a quality work/life balance? 

3.64

Consideration of the contribution that education, skills, and health & wellbeing interventions make to productivity.

At a macroeconomic level, since Richard Easterlin’s seminal paper “Does Economic Growth Improve the Human Lot” in 1974, much work has gone into understanding the link between economic growth and well-being. Easterlin and others have suggested an increase in GDP (and implicitly productivity) does not necessarily lead to an increase in happiness as GDP does not capture everything that determines economic well-being. The Easterlin Paradox suggests that once a certain level of GDP has been reached, any further increase in GDP does not appear to increase happiness – this is shown in the chart below here, where GDP per capita has increased yet life satisfaction has remained relatively stable.

Figure 3.8: GDP as a measure of well-being (Source: ONS, 2014)

3.65

This ‘paradox’ is not uniformly accepted by all academics as other authors have reported contradictory results (e.g. Stevenson and Wolfers, 2008). Regardless of the academic debate, it has long been recognised that traditional measures of progress such as GDP (and hence productivity) are increasingly considered as an incomplete picture of the state of welfare. For example, it excludes determinants of well-being outside of economic production, includes economic ‘bads’ (such as pollution, disease, crime, war), imperfectly measures output and hence productivity of public services, and says nothing about the sustainability of well-being over time.

3.66

This recognition of the frailties of GDP and productivity as a measure of societal progress has acted as a catalyst to the growing international interest in alternative measures of progress.

For example, in 2009 the Commission on the Measurement of Economic Performance and Social Progress, chaired by the Nobel Prize winning economist Joseph Stiglitz, published a

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report on the limits of GDP as an indicator of progress. The Commission recommended that more relevant economic performance and social progress indicators be developed for assessing policies aimed at advancing the progress of society. As such, the commission suggested a framework based on the three pillars approach of measuring economic, social and environmental progress.

3.67

The Organisation of Economic Cooperation and Development launched the ‘Better Life Initiative’ in May 2011. They similarly developed a framework for measuring well-being progress where GDP and productivity were only part of the overall picture – see Figure 3.8 below.

Figure 3.8: The OECD well-being conceptual framework (Source: OECD 2011)

3.68

The framework recognises that there are many other drivers of an individual’s well-being beyond economic growth. It also captures the relationship between an individual’s well-being at a moment in time and the sustainability of this over time. It does this by emphasising the relationship between well-being to the stock of ‘capitals’.

3.69

Increasing the skills of the workforce and developing human capital in particular, has an important role to play in driving productivity growth (Department for Business Innovation and Skills, 2015). As such, developing human capital is therefore important to increasing individual well-being and sustaining it over the long-term.

3.70

Any depletion of human, or indeed social, capital is likely to have negative effects on productivity growth and well-being, both in the short and long-term. However, this is not necessarily the case for economic and environmental capital. Any depletion of economic and environmental capital can potentially increase economic growth and productivity in the shortterm. This however, is not sustainable and comes at a cost of lower levels of growth,

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productivity and well-being over the long-term. The framework therefore emphasises the need of policy makers to manage both stocks and flows; this emphasises the need for smart and sustainable growth for Cornwall and the Isles of Scilly.

3.71

The OECD recognised that day-to-day experience of life is essentially at the local level and therefore describe a need for its framework to be applied at low levels of spatial aggregation.

As such, in 2014 they issued their first report on “How’s Life in Your Region”. The report provides practical guidance for using well-being measures, but unfortunately for this project it is of limited use as any analysis provided is restricted just to the regional level (e.g. South West England).

3.72

It will be challenging to apply any such macro-level framework based on the OECD model directly to Cornwall and the Isle of Scilly. This is because it combines both individual wellbeing with sustainability over time using the four capitals approach (natural capital, human capital, economic capital and social capital). The main challenge here is that the availability of regularly updated ‘capitals’ data at a local level is extremely limited and would therefore be extremely costly to produce, and what was produced would be of questionable quality.

3.73

A more fruitful approach for Cornwall and the Isle of Scilly to follow would be to concentrate on the flow measures. The OCED framework splits this down into two components – material conditions and quality of life. Again there would be limitations on the amount and quality of data available at lower levels of disaggregation, but the availability and quality for flow data, particularly for material conditions, would be much improved than that for stock data. For example the Office for National Statistics already produce a number of time series data sources for economic, labour market and housing data. The quality of life indicators would be more challenging, but it should be possible to identify a core dataset that could be regularly updated to monitor progress against most, if not all the eight quality of life indicators identified in the framework.

3.74

In 2010 the UK’s Prime Minister, David Cameron, launched the National Well-being Programme in order to measure progress that goes beyond just the economy and includes a wider quality of life perspective. A public consultation and debate ensued which led to the development and publication of a measurement framework comprising 10 domains and 41 measures of well-being. These domains and measures are presented within a framework called the ‘ONS Well-being Wheel’. This wheel, which includes the ten domains and individual indicators, are shown in Figure 3.9 below:

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Figure 3.9: Well-being Wheel (Source: ONS, 2016)

3.75

The individual measures include objective measures, such as life expectancy and levels of unemployment, and subjective measures about how people feel about progress, such as satisfaction with life and levels of anxiety (Gov.UK, 2013).

3.76

Of the 41 individual indicators, which include both objective and subjective measures, 21 of these have been reported by the ONS at a regional level, but the author is unaware of ONS publishing any detailed analysis of these indicators at a county level.

3.77

The implication for Cornwall and the Isle of Scilly is that if they adapted ONS’s well-being wheel framework, then they would have to do so using a much reduced set of indicators.

Obviously the weakness of this approach is that much of the richness of the national picture is lost.

3.78

However, it might be argued that ONS has produced an overly complicated set of indicators which have inhibited its adoption into mainstream policy interventions. Indeed, a number of countries and organisations, such as Butan, the New Economics Foundation, Gallop etc, have produced indices in order to simplify the presentation of well-being indicators. Therefore, If Cornwall and the Isle of Scilly wished to pursue the route of producing a reduced set of indicators to represent the well-being wheel, it should consider identifying a single indicator to represent the 10 domains of the wheel rather than the 41 separate indicators.

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3.79

Central to any well-being framework is the use of subjective well-being data, however, the use of subjective well-being (measures of stated preference) to evaluate progress has been questioned by some economists who in the main are predisposed to studying objective measures (revealed preference). Subjective measures have been criticised due to both theoretical issues and the reliability and validity of the data.

3.80

Academics have argued that it is futile for policy makers to target subjective well-being due to the issue of relativity and the adaptive process known as the hedonic treadmill (Layard, 2005) – both of which can help to explain the effects of diminishing marginal returns to income (Hirsch 1976, Luttmer, 2005).

3.81

In terms of data capture, Bertrand and Mullainathan (2001) group the problems with measurement into three categories; 1) cognitive problems, 2) social desirability, 3) non attitudes, wrong attitudes and soft attitudes. Pessimistically they report that the measurement error in subjective well-being data is small enough to include it only as an independent variable in any economic model. They concluded that it cannot reasonably be used as a dependent variables, given that the measurement error likely correlates in a very causal way with the explanatory variables. This assessment means that any analysis based on understanding the determinants of subjective well-being is flawed, and as such the implicit indication is that so are any policies targeted at improving subjective well-being.

3.82

However, the micro foundation of these objections has been questioned by behavioural economists and psychologists who highlight that choices made, even by a rational agent, can be bounded (Kahneman and Krueger, 2006). There is also sufficient evidence, which suggests that self-reporting SWB is sufficiently reliable and valid. For example Diener, and Diener (1995) examine test-retest reliability of country level SWB and found that rank order of nations over time is highly stable - similar conclusions were reported by Veenhoven and Ehrhardt (1995) in his international analysis.

3.83

Oishi (2011) reported on that research has shown that people with positive SWB have more positive work behaviours and outcomes and more satisfying close relationships, better health and longer lives (Borman et al. 2001; Wright et al. 2002; Danner et al., 2001). Oishi and Scimmack’s (2010) review the literature and conclude “Together, these findings indicate that self-reported well-being provides meaningful information regarding the functioning of societies.” (p466).

3.84

Oswald et al. (2014) report that subjective well-being is also reported to influence productivity, both in terms of changes to short-term positive effect and in terms of long-term due to major real life (un)happiness shocks. After assessing the results from a number of experiments they concluded that “happiness makes people more productive”.

3.85

The evidence suggests that it is now possible to reliably measure SWB and if something is measured consistently then it is much more likely to become an object of policy. Diener, Oishi and Lucas’s (2015) suggest that societies should monitor subjective wellbeing and create

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policies to foster it, because higher well-being leads to, rather than just being correlated with, outcomes that societies highly desire.

3.86

MacCulloch (2016)28 assessment was that subjective well-being data (e.g. happiness) was useful for economic policy evaluations as it captures all the costs and benefits of a policy that otherwise would be hard to determine and aggregate; it can provide estimates of the welfare effects of policy on specific groups; and it may be a better way to estimate cost and benefits than willingness to pay surveys.

On balance any framework exploring the linkages between well-being and productivity for Cornwall and the Isles of Scilly should include both objective and subjective measures.

3.87

At a microeconomic level the link between well-being and productivity has long been documented (Hafner et al. 2015; Edmans, 2012; Bockerman and Ilmakunnas 2012), although understanding of the causal linkages between the two variables is less clear.

3.88

However, not all studies find a positive link between well-being and skills. For example, it has also been reported that high levels of subjective well-being can cause inertia in terms of knowledge acquisition (Martin et al., 1993)29 - and therefore act as a block to productivity improvements. Martin et al (1993) reported that those who are moderately happy achieve the most in terms of income and education.

3.89

While work continues on understanding the precise relationship between well-being and productivity, although not universally accepted, there is a general consensus that there is a strong link between well-being and productivity.

3.90

Much research has already been undertaken into understanding the determinants of wellbeing. Of the determinants identified arguably skills, education and health are the levers by which business can affect the well-being of their staff and as such increase productivity.

3.91

Education and skills are thought to improve productivity directly and indirectly. Directly those with higher levels of education and skills are better able to take on more complicated and difficult tasks. Indirectly the rate of technological diffusion is also expected to increase with a more skilled and educated workforce (Rogers, 2003).

3.92

The Department of Business, Innovation & Skills (2015) published a review of the link between UK skills and productivity. The report concluded that skills improvements account for approximately a fifth of the growth in average labour productivity. They cited a number of empirical studies. One of which was Holland et al (2013)30 who reported that productivity

28

MacCulloch, R., (2016) Can “happiness data� help evaluate economic policies? Available at SSRN. Martin, L.L., Ward, D.W., Achee, J.W. and Wyer, R.S. (1993) Mood as input: People have to interpret the motivational implications of their moods. Journal of Personality and Social Psychology, 64(3), p.317.

30 Holland, D., Liadze, I., Rienzo, C. and Wilkinson, D. (2013) The relationship between graduates and economic growth across countries. BIS Research Paper, 110.

29

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levels increase by between 0.2% and 0.5% per cent, for every 1% increase in the workforce population with a university education.

3.93

The link between skills and its interaction with innovation was explored by Brandbenberg et al (2007)31. They concluded that in order to maximise innovation performance and improvements in productivity, it is important to combine skills development with investments in R&D. This link between innovation and skills was extended by Mason et al (2012)32. They analysed certified and uncertified skills and concluded that as information and communication technologies become increasingly important to business so too should the development of vocational skills.

3.94

Generally, formal education is also positively correlated with wellbeing and hence productivity. The positive correlation between education and wellbeing is reported in a number of studies from a variety of different countries - USA (Blanchflower and Oswald, 2011)33, Switzerland (Frey and Stutzer, 2000) and Sweden (Gerdtham and Johannesson, 2001)34, as well as in cross-national studies (Clark and Lelkes, 2005; Graham and Felton, 2006)35. Blanchflower and Oswald (2011) reported that levels of well-being increases with each additional level of attainment.

3.95

These findings, however, are not unanimously accepted with other authors finding either no relationship (van den Berg and Ferrer-i-Carbonell, 2007)36 or even a negative relationship between education levels and well-being (Shields and Price 2005). One explanation offered is that the relationship between education and well-being is non-linear meaning that after a certain level the returns to well-being from education diminish or become negative (Gerdtham and Johannson, 2001).

3.96

Outside of the effect on the individuals, Winters (2015)37 reported that there are positive human capital externalities to an area. They concluded that formal schooling does not just increase earnings and other benefits for the individual, but that wider benefits can also ‘spill over’ to the wider local population, even if they have relatively little education.

31 Brandenburg, B., Günther, J. and Schneider, L. (2007) Does Qualification Drive Innovation? A Microeconometric Analysis Using Linked-employer-employee Data (No. 10). Halle Institute for Economic Research 32

Mason, G., O'Leary, B. and Vecchi, M. (2012) Certified and uncertified skills and productivity growth performance: Cross-country evidence at industry level. Labour economics, 19(3), pp.351-360.

33 Blanchflower, D.G., Oswald, A.J. (2011) International happiness. National Bureau of Economic Research.

34 Gerdtham, U.-G., Johannesson, M. (2001) The relationship between happiness, health, and socio-economic factors: results based on Swedish microdata. Journal of Socio-Economics. 30, pp. 553–557 35 Graham, C., Felton, A. (2006). Inequality and happiness: insights from Latin America. Journal of Economic Inequality. 4, pp. 107–122.

36 van den Berg, B., Ferrer-i-Carbonell, A. (2007) Monetary valuation of informal care: the well-being valuation method. Health Economics 16, pp. 1227–1244.

37 Winters, J.V. (2015) Do higher levels of education and skills in an area benefit wider society?. IZA World of Labor.

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3.97

Berger and Fisher (2005)38 addressed the question of what policy makers can do to boost the economic well-being of their population. They concluded that high-wage, high-productivity areas are areas with a well-educated workforce. They encouraged policy makers to strengthen their economies and attract highly productive and high-wage employers by investing in education.

3.98

The importance of skills and its link to well-being and productivity is also embedded in studies which have focussed on the concept of ‘good work’ (Bevan, 2012)39. Good work emphasises the link between employee health and wellbeing, and business performance and productivity.

The origins of the good work framework can be traced back to by the Swedish Metal Workers Federation. Since then its foundation have been adopted and built on by many national and trans-national organisations, including the European Foundation for Improvement of Living and Working Conditions, European Commission and the International labour Organisation.

What is common across these organisations is that skills and competencies development are central to each of their good work frameworks.

3.99

In terms of health, one direct mechanism through which this link between well-being and productivity works is through lower levels of absenteeism. Black and Forest (2011) reported that 140 million working days were lost in the UK due to sickness absence each year, while 300,000 individuals leave the workforce altogether due to ill-health.

3.100 Absenteeism is only the tip of the iceberg and perhaps a more prevalent but perhaps less recognised mechanism through which productivity is affected may be through presenteeism - this is when an individual attends work but is unwell, either physically or mentally. This reduced level of health while working can result in reduced individual performance and therefore lower levels of productivity.

3.101 Presenteeism within businesses is generally not recorded and often unrecognised by business as a potential issue. While rates of absenteeism are much easier to monitor for businesses, presenteeism often goes unnoticed. The extent of this problem was highlighted in a report by the Centre for Mental Health (2011) which estimated that presenteeism for mental ill-health alone cost the UK economy ÂŁ15bn per year.

3.102 Even when judged using purely neo-classical assumptions, where the firm is solely motivated by profit maximisation and ignoring more progressive sustainable and ethical business motives, using simple cost benefit economic analysis, there appears to be a clear business case for businesses to invest in the health and well-being of their staff.

3.103 Within this framework education, skills and health are recognised as clear drivers of wellbeing, all of which directly contribute to levels of productivity within a firm. Through investment in these channels there appears to be the potential for business to set the 38 Berger, N. and Fisher, P., 2013. A well-educated workforce is key to state prosperity. Economic Policy Institute, 22(1).

39 Bevan, S., 2012. Good work, high performance and productivity. Work Foundation.

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foundations for a virtuous circle. Positive feedback loops can be created as improvements in education, skills and health can improve the well-being of staff, which in turn can have positive improvements in business productivity, enabling further rounds of investment.

3.104 If monitoring well-being is identified as a strategic priority for Cornwall and Isle of Scilly, it needs to be able to articulate why it is measuring it, what is (and is not) to be measured, the frequency with which it will be measured and finally consider how it is to be used in evaluating policy initiatives.

As there is evidence of a positive link between productivity and well-being, the recommendation from this review is that a fuller examination of ONS and other publicly available indicators should be undertaken. The aim of this review will be to create a bespoke well-being framework for Cornwall and the Isles of Scilly, based on ONS’s Well-being Wheel.

Given its documented link to productivity, through regular updating and monitoring of this well-being framework, policy makers should be able to access, at least to some degree, the actual and relative progress of Cornwall and the Isles of Scilly.

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