Geodemographic Profiling,Knowledge Workers and

Networks

Dr Tom Williamson

Visiting Professor

Institute of Criminal Justice Studies

University of Portsmouth

Geodemographic Profiling• Charles Booth: 19th Century industrialist turned

social scientist• Profiled all homes in London: 5 broad groups• 30.7% below the poverty line• Descriptive map of London Poverty 1889• http://booth.lse.ac.uk/• Chicago School. Park Burgess and McKenzie

1925. Lost until rediscovered by the commercial sector in 1980s.

• Cf. Harris, R., Sleight, P., Webber, R. (2005) Geodemographics, GIS and Neighbourhood Targeting. Wiley.

Importance of Neighbourhood context

• Geodemographic software MOSAIC. 11 broad neighbourhood groups 61 smaller types.

• Built from census, commercial transaction and survey data to provide the neighbourhood profile.

• Massive amount of data or is it ‘knowledge’.

Knowledge

• ‘Knowledge is the sum of what is known to mankind’ OED

Progression towards knowledge.

• Data.• Information. Analysis of data provides

information• Intelligence is information prepared for action• Intelligence acted upon provides experience• Experience contributes to our knowledge and

understanding and allows us to test hypotheses

Networks and the digital divide• Between traditional manual systems and the ever-

widening influence of ICT networks.• The ‘Future is Digital’. • Wrong!, digital will be a given in the 21st Century.

We will live in a networked society. Transactions and travel captured digitally.

• ICT automatically captures data. The Future is Data. Combine harvesters. Data aggregators.

• Google type technologies together with analytical tools means we are all becoming ‘knowledge workers’ processing the digital harvest.

Widely used in the commercial sector

Site location

Segmenting customers: Targeting of communications

Perceptions of local crime rate

A B C D E F G H I J K

Walton North ward (NE corner)

Low level of social cohesion

Most prevalent Index profiles

Community coding of Electoral Register

• 46,330,000 records on file• 99.1% coded by community of origin• 130 Cultural, Ethnic, Linguistic CEL types• 13 Cultural, Ethnic, Linguistic CEL groups

CoverageNUMBER AND % RECORDS BY CEL GROUP

CEL GROUP RECORDS %

AFRICAN 139,920 0.302

CELTIC 10,238,813 22.097

EAST ASIAN 176,886 0.382

ENGLISH 32,735,358 70.648

EUROPEAN 582,716 1.258

GREEK ORTHODOX 103,043 0.222

HISPANIC 143,246 0.309

JAPANESE 5,740 0.012

JEWISH AND ARMENIAN 47,404 0.102

MUSLIM 1,018,107 2.197

NORDIC 36,277 0.078

SIKH 285,036 0.615

SOUTH ASIAN 491,126 1.060

INTERNATIONAL 29,088 0.063

UNRECOGNISED 154,247 0.333

DATA ERROR 149,080 0.322

TOTAL 46,336,087 100.000

The following maps are created in a novel way

• 1 : We have examined a UK database containing 46 million records. Each contains personal name + family name + postcode

• 2 : We have classified 180,000 family names and 100,000 personal names on the basis of ethnicity, loosely defined

• 3 : Using these tables we have coded 99.3% of the 46 million records according to their most likely ‘cultural/ethnic/linguistic group’

• 4 : We have then selected the 60,000 UK postcodes containing 7 or more individuals identified as belonging to a group which is neither British nor Irish

• 5 : The postcodes have then been coloured according to the group with the highest number of names in the postcode.

• 6 : One of the maps shows the distribution of all major groups within Greater London.• 7 : The other map features the largest of just three groups in Birmingham and the Black

Country• 8 : In the Black Country map there is a green background behind each postcode. The strength

of the green colouring indicates the proportion of the population in the postcode with a South Asian name. Thus the map shows both the level of concentration of South Asian names in a postcode and which of the minority groups is most strongly represented.

Black Country : dominant names by postcodeBlue = Sikh, Yellow = Pakistani, Red = Hindu

The ethnic map of London

R. Webber

Hackney

Brent

Health communications : Camden PCT                       

   Camden PCT : Recognisable Adults by 'CEL' based on personal name and family name

 

    CEL 'Imported from overseas'     CEL from British Isles  

    CEL Count   CEL Count     CEL Count  

    BANGLADESH 2,826   INDIA NORTH 476     ENGLAND 49,753  

    PAKISTAN 2,001   GREECE 406     IRELAND 8,265  

    ITALY 1,741   TURKEY 347     SCOTLAND 6,036  

    PORTUGAL 1,210   SOMALIA 313     WALES 3,166  

    CYPRUS 1,137   INDIA SIKH 304          

    GERMANY 1,104   YUGOSLAVIA 292          

    HONG KONG 1,101   MUSLIM INDIAN 258          

    INDIA HINDI 924   GHANA 242          

    NIGERIA 907   IRAN 211          

    JEWISH 891   DENMARK 208          

    MUSLIM OTHER 839   CHINA 199          

    FRANCE 794   SWEDEN 185          

    POLAND 772   JAPAN 180          

    SPAIN 713   SRI LANKA 178          

    PAKISTANI KASHMIR 533   HINDU NOT INDIAN 166          

          VIETNAM 142          

                       

Residential segregation : selected Local Authorities

Ethnic and religious profiling

• Legal in the UK

• Ethnic marketing is a growing business

• Public sector applications?

Conclusions

• ICT Networks will become increasingly pervasive in 21st Century

• Knowledge no longer in the hands of the ‘police’ or ‘police officers’. Consumers of knowledge.

• Geodemographic, cultural, ethnic and language profiling will become easily accessible.

• Challenge is whether we buy into this ‘knowledge’ as a new way of doing business or continue ignoring it.