The Changing Face of the UK High Street: Forecasting the future for 2020

Professor Cathy Parker

@placemanagement

#HSUK2020

Our partner HSUK2020 towns:Alsager, Altrincham, Ballymena, Barnsley, Bristol (St George), Congleton, Holmfirth, Market Rasen, Morley and Wrexham

100,000 !

An academic study. Why bother?

People do not want to go into six different shops for six different articles; they prefer to buy the lot in one shop.

The American Grocer, 1892

For better or worse this distributive revolution is carrying us away from shopkeeping to mass distribution

McNair, 1931

Change in retailer location 2000-11

Out of town up 50 million square feet

Town centre down 46 million square feet

Department for Transport 2011

Online share of home retailing 2014

UK

Germany

Europe av

France

Poland

0.00% 2.00% 4.00% 6.00% 8.00% 10.00% 12.00% 14.00% 16.00%

Centre for Retail Research 2013

Online retailing

16% pa£52 bn in 2015

M-retailing

62% this year£7.92 bn

Centre for Retail Research 2013

Town centre share of retail spend

2000

49.4%2011

42.2%2014

39.8%

Parliament 2014

• Vital & Viable Town Centres• Planning Policy Guidance/Statements• Business Improvement Districts• High Street Britain 2015• The Portas Review• Understanding High Street Performance• Future High Streets Forum

The response

Place management

Nature of place management schemes

IPM 2009

What causes High Street Change?

What influence do individual locations have?

10000 studies found

2345 after clean up

923 ‘retail’ highlighted

253 town centre/high st

173 studies reviewed

Mostly from UK and Europe

City CentreTown CentreHigh StreetNeighbourhood CentreDistrict CentreSuburban CentreOut of town Centre

Focus of data

166 factors influence performance

And if 166 factors were not enough…..• Partner towns identified 50 additional factors

that influence the High Street• 33 additional studies reviewed• 201 factors finally identified, but:

– how much influence does each one have? – what should towns be focussing on?

The Delphi Technique

The Delphi method is unique in its method of eliciting and refining group judgement as it is based on the notion that a group of experts is better than one expert when exact knowledge is not available.

(Paliwoda, 1983).

22 Experts participated Practitioner Academic

Major retailer Manchester Metropolitan University

Shopping centres owner University of Leicester

Urban consultant University of Dundee

Retail letting agency University of Ulster

Urban policy group Oxford University

Trade association University of Manchester

Professional body University of Liverpool

University of Portsmouth

University of Loughborough

Consensus reached on

1. How much influence each factor has on the vitality and viability of the High Street

2. How much control a location has over the factor

Not worth it! Get on with it!

Forget it! Live with it!

3.300 3.500 3.700 3.900 4.100 4.300 4.500 4.7002.700

2.900

3.100

3.300

3.500

3.700

3.900

ACTIVITY HOURS

APPEARANCE

RETAILERS

VISION&STRATEGY

EXPERIENCE

MANAGEMENTMERCHANDISE

NECESSITIES

Anchor stores

NETWORKS & PART-NERSHIPS

WITH COUNCIL

DIVERSITYWALKING

ENTERTAINMENT AND LEISURE

PLACE ASSURANCE

ATTRACTIVENESS

ACCESSIBLE

PLACE MARKETING

Comparison/convenience

RECREATIONAL SPACE

Barriers to Entry

Chain vs independent

Safety/crime

LIVEABLE

ADAPTABILITY

How much factor influences vitality and viability

Ho

w m

uch

to

wn

can

in

flu

ence

fac

tor

Top 25 priorities

Forecasting the future for your High Street

Spatial

Macro

Meso

Micro

The HSUK2020 Model of High Street Change

Data

• Footfall supplied by Springboard• 62 UK towns and cities• 30 months of footfall (2012-2014)• 563,828,709 people counted!

Spatial factors

Location Distance to centre Size/Type of townSpatial structure

Towns can’t do anything about these factors!

Towns in NW & NE have 10% less footfall than expected

Macro factorsEconomy

Consumer trends Business rates

Ageing populationTechnology

Retail planning policy

Towns can’t change these

on their own

25% decline in footfall in last 3 years (internet shopping and recession)We predict 21% decline by 2020

Meso factorsBarriers to entry

Competition (other towns)Comparison/Convenience

Out of town shoppingTenant variety Vacancy rates

Towns interact with these/have some

Influence

A stronger or OOT centre within 10 miles account for 30% less footfall

Micro factorsCleanliness

Visual appearanceNetworking

Opening HoursAttractions

Centre MarketingAmenities

Car-parkingEntertainment

Leadership

Our model predicts that micro factors explain up to 37% of variation in footfall

Clean

lines

s

Visual

app

eara

nce

Networ

king

Openi

ng h

ours

Attrac

tions

Centre

mar

ketin

g

Amen

ities

Car-p

arkin

g

Enter

tain

men

t

Lead

ersh

ip

Avera

ge0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

4.00

4.50

DelphiAverage

Macro

Meso

Micro

Partnerships have 64 % of potential influence they could have

(losing 13.3% footfall)

Spatial

RESULTS from #HSUK2020 towns

“..lively, diverse, intense cities contain the seeds of their own regeneration…”