Cornwall and the Isle of Scilly: Productivity Framework ... Framework - PARTS … · Importantly, productivity objectives must be achieved in a way that is sustainable and benefits

Cornwall and the Isle of Scilly: Productivity Framework

PART 1: Productivity Framework

PART 2: Theory and Evidence Review

C&IoS Productivity Framework 2

Table of Contents

Executive Summary .......................................................................................................... 3

Introduction ..................................................................................................................... 8

Part 1: Productivity Recommendations ............................................................................. 9

Part 2: Theory and Evidence Review ............................................................................... 17


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.


Productivity Recommendations

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


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


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.


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.


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


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?


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 non-

working 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


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

http://futurefifty.com/


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

earnings. Capital productivity is a key

determinant of profits, while total factor

productivity usually measures the impact of

technological change.

i) GVA per hour worked preferred measure of

labour productivity growth;

ii) Labour productivity should be considered

alongside measures of sustainable

development and wellbeing.

UK productivity policy focuses on city regions &

investment in high productivity sectors,

particularly high tech.

iii) Build/retain links with Plymouth City Region

iv) Identify the potential CIoS supply chains in:

England Smart Specialisation sectors; CIoS’

RD&I Framework target markets; and the

UK Industrial Strategy sectors.

Growth intentions matter and a small minority

of firms account for the majority of gains in

productivity growth averages.

v) Target support at those with strong or

moderate growth potential, and seek to

enhance aspirations.

Rural firms are not wholly different from urban

counterparts (provided effective infrastructure

is in place). Perceptions about regulatory

barriers may be higher.

vi) Retain overview of infrastructure issues (i.e.

maintaining SuperFast Broadband)

vii) Support effective access to skills & labour

viii) Support with regulation

EU programmes retain their long term focus on

improving innovation, enterprise and skills. The

result of the EU referendum does not invalidate

the benefits to Cornwall in retaining these

policy themes

ix) SME business support investment decisions

based on evidenced economic market

failure rationale. (For example within

Employment & Skills Strategy and RD&I

Framework)

High growth does not necessarily mean ‘high

tech’, strong business growth can come from

traditional sectors. Quality matters more than

quantity of enterprise.

x) Consider support in sectors that are ranked

highly in terms of employment strengths,

particularly enhancing output value.

Non-organic growth (i.e. acquisitions) an

important route to high growth.

xi) Examine whether the Growth Hub

provision supports those seeking to grow

via acquisitions.

Key link between international factors (e.g.

trade, ownership) and growth.

xii) Identify priorities and targets for inward

investment and internationalisation.

What does this mean for business support in CIoS?


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 Recommendations: Delivery

Firms with international links or outlook

demonstrate higher productivity

i) Support for exports and international

partnership, and facilitate an international

perspective.

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.

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.

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.

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.

Firm level productivity is key. Cornwall has

input (employment) strengths in more

traditional sectors such as: camping,

accommodation, fishing and baking.

v) Identify ways to support traditional

sectors to add value to their outputs.

Not insignificant role of non-organic factors in

firm level growth

vi) Provision of expertise on e.g. growth

through acquisitions, succession planning.

Promote Cornwall’s strengths to attract high

growth sectors.

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


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 owner-

managers 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.

Peer Networks

2.20 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


Supplier Readiness

2.23 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.


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.


Productivity Recommendations

Figure 2.2 Productivity Recommendations: Strategic Considerations & Suggested Actions


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

http://www.nesta.org.uk/blog/other-productivity-puzzle


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/productivityhandbook

https://www.ons.gov.uk/economy/economicoutputandproductivity/productivitymeasures/methodologies/productivityhandbook

https://www.ons.gov.uk/economy/economicoutputandproductivity/productivitymeasures/methodologies/productivityhandbook


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


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 whole-

economy 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 Bank of England (2014) UK Productivity Puzzle

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

http://www.bankofengland.co.uk/publications/Documents/quarterlybulletin/2014/qb14q201.pdf




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

http://www.oecd.org/std/productivity-stats/oecd-compendium-of-productivity-indicators-22252126.htm

http://www.bankofengland.co.uk/publications/Documents/speeches/2014/speech739.pdf


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

https://www.gov.uk/government/statistics/local-enterprise-partnership-lep-detailed-rural-urban-maps


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


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

http://wiserd.ac.uk/files/6613/6550/0055/WISERD_WPS_007.pdf


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 driver

% 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)

A 10% increase in capital stock

0.6 1.0 2.9 2.4

A 10% increase in the percent of the local labour force with NVQ4+

1.0 0.0 1.2 0.7

A 10% increase in % of local labour force with NVQ 2-3

- - 1.6 -

A 10% increase in minimum travel time to London and the 4 next largest cities

-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 -

Source: Webber et al

(2016) Webber et al

(2016) Boddy et al (2007) Boddy et al (2005)

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.


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

https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/443898/Productivity_Plan_web.pdf


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

http://www.publications.parliament.uk/pa/cm201516/cmselect/cmbis/466/466.pdf


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.


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


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 well-

being and productivity to create longer term and sustainable growth.


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

https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/220541/green_book_complete.pdf


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-research-barriers-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/wp-content/uploads/2016/03/SME-FM-D2-260216-3.pdf 15 https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/453064/BIS-15-482-sociology-of-enterprise.pd

https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/32250/11-1288-research-barriers-to-use-of-business-support.pdf

https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/32250/11-1288-research-barriers-to-use-of-business-support.pdf

http://bdrc-continental.com/wp-content/uploads/2015/09/BDRCContinental_SME_FM_Q2_2015-FINAL.pdf

http://bdrc-continental.com/wp-content/uploads/2016/03/SME-FM-D2-260216-3.pdf

http://bdrc-continental.com/wp-content/uploads/2016/03/SME-FM-D2-260216-3.pdf

https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/453064/BIS-15-482-sociology-of-enterprise.pd

https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/453064/BIS-15-482-sociology-of-enterprise.pd


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.


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 19 The vital 6 per cent: How high-growth innovative businesses generate prosperity and jobs (2009), NESTA: http://www.nesta.org.uk/publications/vital-6

https://www.nesta.org.uk/sites/default/files/rural_innovation.pdf

http://www.nesta.org.uk/publications/vital-6


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 The nature of HGFs

A major thrust of policy is

aimed at increasing R&D

within firms.

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 21 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

http://www.nesta.org.uk/blog/other-productivity-puzzle

https://www.nesta.org.uk/sites/default/files/working_paper_-_increasing_the_vital_6_percent.pdf


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

https://www.google.co.uk/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&ved=0ahUKEwjy747K6fTMAhVFDMAKHVjwAJMQFggcMAA&url=http%3A%2F%2Fwww.enterpriseresearch.ac.uk%2Fwp-content%2Fuploads%2F2013%2F12%2FERC-White-Paper-No_1-Executive-Summary3.pdf&usg=AFQjCNHnGSHovfmOUug9O4SU8zgxDl7Wug&bvm=bv.122676328,d.ZGg


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 24 BIS (2015) Smart Specialisation in England https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/436242/bis-15-310-smart-specialisation-in-england-submission-to-european-commission.pdf

http://ec.europa.eu/regional_policy/sources/docgener/presenta/smart_specialisation/smart_ris3_2012.pdf

http://s3platform.jrc.ec.europa.eu/ris3-design

https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/436242/bis-15-310-smart-specialisation-in-england-submission-to-european-commission.pdf

https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/436242/bis-15-310-smart-specialisation-in-england-submission-to-european-commission.pdf


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.pdf

http://www.cioslep.com/assets/uploads/documents/1461574419_C&IoS%20RD&I%20Framework%20FINAL.pdf

http://www.cioslep.com/assets/uploads/documents/1461574419_C&IoS%20RD&I%20Framework%20FINAL.pdf


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

3.58 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.


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 high-

tech 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.


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.

Table 3.5 Priority Sectors for South West LEPs

Low

Car

bo

n /

En

viro

Go

od

s

& S

ervi

ces

Tou

rism

Agr

icu

ltu

re /

Lan

d B

ased

Foo

d &

Dri

nk

Ad

van

ced

Man

uf.

&

Aer

osp

ace

Hea

lth

Mar

ine

Pro

fess

ion

al &

Fin

anci

al

Serv

ices

Dig

ital

Oth

er

CIoS E-health Construction

Heart of the SW

Agri-food New Nuclear

Dorset Adult Social Care

International

Education; Retail; Creative

Wiltshire & Swindon

Health &

Life Science

Informatio

n Economy

Military & Defence

West of England

Creative &

Digital Media

‘High Tech'

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).


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

balance?

Consideration of the contribution that education, skills, and health & wellbeing

interventions make to productivity.

3.64 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


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 short-

term. This however, is not sustainable and comes at a cost of lower levels of growth,


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 well-

being 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:


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.


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


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 well-

being. 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. 29 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.


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.


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 £15bn 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 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

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.


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.