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Developing a Robust Evaluation Evidence Base for Business Support - Professor Kevin Mole (ERC)

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Developing a Business Support Framework where does the evidence lead us? Kevin Mole (ERC) Associate Professor
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Page 1: Developing a Robust Evaluation Evidence Base for Business Support - Professor Kevin Mole (ERC)

Developing a Business Support

Framework –

where does the evidence lead us?

Kevin Mole (ERC)

Associate Professor

Page 2: Developing a Robust Evaluation Evidence Base for Business Support - Professor Kevin Mole (ERC)

Business Support Framework

Which way forward for business support policy?

From previous UK evaluations

> Business Link

From an International review of support:

> Syntens and Growth-houses

Page 3: Developing a Robust Evaluation Evidence Base for Business Support - Professor Kevin Mole (ERC)

Choices for business support policy

broader or deeper?

Evaluation of Business Links mid 2000

Historically the network model had local Business Link

Organizations as franchisees

SBS the funders of the programme wanted to explore

good practice in local Business Link Organizations

Mole K F, Hart M, Roper S, Saal D S, 2011, "Broader or deeper?

Exploring the most effective intervention profile for public small business support" Environment and Planning A 43 87 - 105

Page 4: Developing a Robust Evaluation Evidence Base for Business Support - Professor Kevin Mole (ERC)

Business Link Organisations

had choices

Sma l l

Bu si n e ss

Se r v i c e

Ba se l i n e

F u n d i n g

£ Learning and

Skills Council

£ European

Social/Structural

Funds

£ Regional

Development

Agencies

Page 5: Developing a Robust Evaluation Evidence Base for Business Support - Professor Kevin Mole (ERC)

How many firms helped versus

how much each was helped

Low High

High High-Low

Pipeline

Forcing

High-High

Managed

Pipeline Forcing

Brokerage

Low Low-Low

Light-touch

Brokerage

Low-High

Managed

Brokerage

Intensity of assistance

Pro

port

ion o

f F

irm

s a

ssis

ted

Page 6: Developing a Robust Evaluation Evidence Base for Business Support - Professor Kevin Mole (ERC)

Clustering Managed Brokerage

0

200

400

600

800

1000

1200

1400

BLO

Tyne and Wear

South Yorks

Durham

N. Manch

Merseyside

Nrthumbria

E.Lancs

Herts

B'ham

Salop

All barCost

per

inte

rvention

Page 7: Developing a Robust Evaluation Evidence Base for Business Support - Professor Kevin Mole (ERC)

Model 3: Forcing Clients through

the Pipeline/Funnel

‘Trigger points’ to identify

firms that may be

‘amenable’ to intensive

assistance.

BLOs are very keen to

get a high proportion of

firms through to the

end of the funnel

Page 8: Developing a Robust Evaluation Evidence Base for Business Support - Professor Kevin Mole (ERC)

Broader versus deeper

Low High

High High-Low

Pipeline

Forcing

High-High

Managed Pipeline

Forcing

Brokerage

Low Low-Low

Light-touch

Brokerage

Low-High

Managed

Brokerage

Intensity of assistance

Pro

port

ion o

f F

irm

s a

ssis

ted

Page 9: Developing a Robust Evaluation Evidence Base for Business Support - Professor Kevin Mole (ERC)

Impact Coefficients in Regression

Models of Employment

E mp l o y me nt

Gr o wt h

Co e f f

t -

st a t

A. I n t e nsi v e l y - a ssi st e d f i r ms

L i g h t - t o u c h 0 . 0 2 5

2 . 7 5

7

M a n a g e d

Br o k e r a g e 0 . 0 69

4 . 1

1 7

P i p e l i n e

F o r c i n g

0 . 0 1

8

1 . 2

7 5

M a n a g e d

p i p e l i n e

f o r c i n g

b r o k e r a g e 0 . 0 3 5

1 . 7

54

Page 10: Developing a Robust Evaluation Evidence Base for Business Support - Professor Kevin Mole (ERC)

Significant differences between the profiles

of BLO assistance

The key differences between the four models of BL assistance/BLOs were: > Managed brokerage BLOs were most likely to be providing

intensively-assisted firms with business planning assistance or action plan development

> Help with raising finance was also most likely to be offered by managed brokerages;

> Managed brokerages and BLOs operating both managed brokerage and Pipeline Forcing managed pipeline forcing brokerage were most likely to be providing assistance with e-commerce and IT.

Page 11: Developing a Robust Evaluation Evidence Base for Business Support - Professor Kevin Mole (ERC)

But timing of BL impact means that we may

be too early to judge…

0

10

20

30

40

50

60

already next

year

next 2 3>5 5+ none

Intense

Other

Page 12: Developing a Robust Evaluation Evidence Base for Business Support - Professor Kevin Mole (ERC)

Data linking shows that effects can take place after

considerable time lags…

Page 13: Developing a Robust Evaluation Evidence Base for Business Support - Professor Kevin Mole (ERC)

Syntens in The Netherlands

Many SMEs are not innovative

Syntens reaches beyond…

> Engaging groups of ‘missing’ companies

through Futurized businesses

> Diagnosing innovative capacity

> Providing a tailored innovation roadmap

Page 14: Developing a Robust Evaluation Evidence Base for Business Support - Professor Kevin Mole (ERC)

Futurized Businesses identified a middle group of late adopters

1. First, they used Chambers of Commerce data to identify companies

with no previous contact that had five plus employees in :

manufacturing, construction, wholesale, transport and business

services.

2. A team from Syntens, the Chamber of Commerce and other

regional partners prioritized this list based on the importance of

sectors, and the potential of the companies.

3. small local areas were selected for a campaign

> including talking to local representatives, and

> gaining publicity in local papers and radio.

4. SMEs were phoned by well prepared and experienced Syntens

consultants, who listened to the challenges that faced owner and

tried to arrange a meeting with the SME manager (consultants had

a 50% success rate whereas a call centre had a 1-in-10 rate)

Page 15: Developing a Robust Evaluation Evidence Base for Business Support - Professor Kevin Mole (ERC)

Consultants Visited

Consultants prepared a profile of the

> ambition,

> willingness to change,

> opportunities,

> innovation capabilities and

> current problem and needs.

The profile and current problems leads the consultant to offer activities

or referrals to third parties.

The consultants also followed up with extra information because they

argued that this group of firms were poor at searching for new

knowledge.

Page 16: Developing a Robust Evaluation Evidence Base for Business Support - Professor Kevin Mole (ERC)

Innovation Quick Scan (web based)

Innovator

Follower 7 5

Natural Systematic

Innovation P

ote

ntial

10

0 8

Page 17: Developing a Robust Evaluation Evidence Base for Business Support - Professor Kevin Mole (ERC)

Innovation Quick Scan (web based)

Innovator

Follower 7 5

Innovation Urgency

Ambition

Natural Systematic

Innovation P

ote

ntial

10

0

6

8

Page 18: Developing a Robust Evaluation Evidence Base for Business Support - Professor Kevin Mole (ERC)

Syntens Process …producing a

roadmap…

Syntens cost €40m in 2009 to act as a sounding board, point of referral

and innovation specialist.

Synten’s tailored consultancy is time-rationed: companies can receive a

maximum of 16 hours per year per company.

The consultants determine the innovation ability of a business looking

at 10 enablers of innovation success, which are very broad

including: strategy, organization, culture, finance, skills, getting

knowledge and technology, generating ideas, realizing ideas,

marketing new products and the exploitation of new products.

The outcome from the 2 days of tailored consulting is a roadmap of

where the company might need to improve to match their innovation

capability with their innovative ambition.

In this sense the programme, responds to the need for SMEs to have

a strategic sounding board and a space for reflection.

Page 19: Developing a Robust Evaluation Evidence Base for Business Support - Professor Kevin Mole (ERC)

Prospects for Syntens

Syntens say that 55% of firms followed up their contact to

become more innovative

“..it is sound policy to invest time and effort in less

innovative companies but only if you work in a demand

driven (“listen”) way and ensure that the visits are

performed by experienced consultants”

However, there is no rigorous evaluation beyond the take-

up evidence

Page 20: Developing a Robust Evaluation Evidence Base for Business Support - Professor Kevin Mole (ERC)

The Growth House as a Central Hub

Page 21: Developing a Robust Evaluation Evidence Base for Business Support - Professor Kevin Mole (ERC)

The nine objectives of the GHs for 2012

(Contract of requirements)

1 A minimum of 2.650 high-growth enterprises is selected each year through

business diagnosis and these are provided a growth plan and further

undertake a user evaluation.

2 At least 80 % of the selected enterprises are referred to intermediaries.

3 At least 70 % of the selected enterprises will recommend GHs to others.

4 At least 80 % of the intermediaries are satisfied with the particular GH.

5 At least 80% of local collaborators are satisfied with the GHs.

6 At least 70% of the selected enterprises will refer intermediary to others.

7 High-growth enterprises will increase employment by at least 10% in

comparison to similar enterprises in the control group from 2011 to 2012.

8 High-growth enterprises will increase turnover by at least 15% in

comparison to similar enterprises in the control group from 2011 to 2012.

9 High-growth enterprises will increase export by at least 10% in comparison

to similar enterprises in the control group from 2011 to 2012.

Page 22: Developing a Robust Evaluation Evidence Base for Business Support - Professor Kevin Mole (ERC)

The Growth Wheel Startup Company (vaeksthjulet.dk)

Page 23: Developing a Robust Evaluation Evidence Base for Business Support - Professor Kevin Mole (ERC)

Growth House managers assessments of

system strengths…

• Firms receiving GH services have higher growth rates than firms in the control group (confirmed by DBA evaluations).

• The face-to-face interaction with firm owners is a major strength of the programme.

• The GHs have highly educated programme advisers, commonly with several years of experience from private companies either as business owners or employees, and this is highly respected by firm owners.

• Business diagnosis can change a firms’ view of its major challenges; a change necessary to unleash its growth potential.

• Changing the mind-set of owners is key to the firms’ success.

• The GHs can ‘push’/motivate the firms into receiving necessary consulting services, which they may otherwise have hesitated to take actions to receive.

• The GHs do not compete in the market of private consultant .

Page 24: Developing a Robust Evaluation Evidence Base for Business Support - Professor Kevin Mole (ERC)

…and weaknesses

Operational

• Programme advisers are limited in the amount of time that they can spend with the firm, before referring it to intermediaries.

• Private intermediaries are not publicly screened or evaluated other than online user evaluations. There are 2537 private consultants to choose from at the GH internet site.

Evaluation

• Activities need to be evaluated more thoroughly on qualitative measures to provide specific answers to the antecedents of growth in firms.

• The evaluation only gives insight into the satisfaction on an aggregate level –GHs only learn informally (through direct contact with client firms) whether the companies are satisfied with the services.

• the GH programme is evaluated on the firms satisfaction with private intermediaries, but GHs have no right to influence the firm’s choice of the specific private intermediary to avoid any distortion of a freely competitive market.

Page 25: Developing a Robust Evaluation Evidence Base for Business Support - Professor Kevin Mole (ERC)

International Evidence

Authors Title Programme Method Finding

Cumming, D.

J. & E. Fischer

(2012).

Publicly

funded

business

advisory

services and

entrepreneuria

l outcomes

The Innovation

Synergy

Center in

Markham

Controls are

included for

endogeneity

and/or

Heckman-

sample

selection

corrections.

Adviser hours

increased both

sales from the

firm and their

likelihood to

obtain

intellectual

property rights

Hoffmann, A,

Hoeg-Kock

and Storey, D

J (2012)

Theory and

practice of

entrepreneurs

hip policy:

gazelle

hunting by

government

Growth

Houses, 2008

and 2009, and

2010-11

Control group

analysis using

population

wide control

groups

Growth house

clients grew

sales faster (or

their sales fell

less) than

control group

firms

Page 26: Developing a Robust Evaluation Evidence Base for Business Support - Professor Kevin Mole (ERC)

International Evidence

Authors Title Progra

mme

Method Finding

Kosters

S. and M.

Oschonka

(2011)

Public

business

advice in the

founding

process: an

empirical

evaluation of

subjective

and economic

effects

Start-up

advice

Propensity

score

matching

No evidence found for better

start-up performance with

advice, but indications that

advice helps those with

fewer resources to

overcome barriers in the

founding process

Jarmin, R.

(1999)

Evaluating

the Impact of

Manufacturin

g Extension

on

Productivity

Growth

MEP

(technic

al but

also soft

support)

Difference-

in-

difference,

fixed-effects

models,

two-stage

selection

model

Positive impact of

programme confirmed, with

larger productivity growth

effect for small firms (rather

than for large firms). Value

added also significantly

higher than for control

group.

Page 27: Developing a Robust Evaluation Evidence Base for Business Support - Professor Kevin Mole (ERC)

Conclusion

>Existing businesses are more likely to

survive

>SME owner-managers can be encouraged to

reflect on their performance

>The mechanism for business support is to

develop the business plan

>‘Deeper’ approaches like Syntens and

Growth houses diagnose and develop action

plans to spur action


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