6 th UK SNA Conference 12 th – 16 th April 2010 University of Manchester

1. 6th UK SNA Conference12th – 16th April 2010University of Manchester http://www.socialsciences.manchester.ac.uk/disciplines/sociology/events/sn/ Deadline for abstract submission is…TODAY! But if you are interested please send a mail to elisa.bellotti@manchester.ac.uk And I will give you an extended deadline.. Also Feb 10th 3.30pm-5.00pm. Bernie Hogan Oxford UniversityHanson Room Humanities Bridgeford Street Seminar programme: Bernie will present some of his work on socialnetworks and media convergence. Mar 3rd 3.30-5.00pm. Johan Koskinen Oxford UniversityArthur Lewis Boardroom (2.016) Seminar programme: Johan will discuss statistical issues in socialnetwork analysis.

2. In partnership with Social Network Analysis in the public and private sector. Elisa Bellotti The Mitchell Centre for Social Network Analysis Univerity of Manchester Benefits and challanges

3. Layout of the presentation • Brief introduction to ONA and case studies • 1st case study: On_Air • The questionnaire • Population • whole network analysis • subgroups • exchange analysis • egonetworks • 2nd case study: KCC • The questionnaire • Population • whole network analysis • exchange analysis • Final observations

4. Applications of SNA in private and public sector: ONA Organizational network analysis: a method for studying communication and socio-technical networks within a formal organization. • Two case studies • A large bank group in Italy (ON_Air) • A County Council in UK (KCC) Team: Giuseppe Lisena (OpenKnowledge_Milan) Emanuele Quintarelli (OpenKnowledge_Milan) Elisa Bellotti (Univeristy of Manchester) Laurence Lock Lee (Optimice_Sidney)

5. ON_Air • In 2008, one of the largest bank group in Italy approached Open Knowledge to lead a research project on the training dept in HR. • The office is the outcome of a previous merging of two main banks and few little ones, therefore the different training offices have been reduced to one, with several branches around the country. • The client was interested in mapping the network of relationships of employees, to find out the informal structure of the office. • This informal structure was affected by: • The dispersion across the country • The relatively new merge of offices from different banks • The questionnaire • Attributes • Relationships

6. The two waves

7. General overview of respondents

8. Respondents attributes (example) *Aggregated data for Naples 09: Napoli Imbriani 16% Napoli Bovio 4% Role City Office

9. PROBLEM SOLVING “I ask this person when I have an unexpected problem that needs to be solved quickly”Roster: list of people. Grade: never, often, always.

10. Problem solving: whole structure (grading: always) 2008 2009 5 strong components with more than 3 people in, the main one has 15 nodes (blue – 11%). 1 main strong component with 33 nodes (blue - 24%).

11. Symmetry and Density

12. Problem solving: clique analysis (by city, grading: often - always) 2008 2009 23 cliques, 37 nodes over 129 belong to at least one clique (28%) 53 cliques, 54 nodes over 137 belong to at least one clique (39%) Red = Milano Blue = Torino Yelllow = Firenze Turquoise = Torri di Quartesolo Pink = Sarmeola di Rubano Dark Green = Napoli Light Green = Napoli piazza Bovio Grey = Foligno Red = Milano Blue = Torino Yellow = Piacenza Turquoise = Torri di Quartesolo Pink = Sarmeola di Rubano Black = Napoli Green = NA

13. Problem solving: clique analysis (by office, grading: often - always) 2009 2008 Red = FMC Blue = Staff Green = ELSS Yellow = FTP Turquoise = IS Red = FMC Blue = Staff Green = ELSS Yelllow = FTP

14. EXCHANGE ANALYSISAND CRITICAL PLAYERS

15. Exchange Analysis The next slide look at how value through relationships is exchanged between offices (example). The concept of supply (my response to other actor requests) and Demand (my requests for assistance from others) is used Mismatches between supply and demand are areas for investigation.

16. Exchange Analysis – By office 2008 2009

17. Critical Player Analysis 2009 50% connections held by top 33% - 2008 was 32% (very low vulnerability)

18. EGONET

19. Egonet: R. B. R.B Aver MAX MIN 49 1 25,6 96 R.B Aver MAX MIN 14% 35,3% 100% 25,2%

20. ATTRIBUTES My net All Office: in my office 0,92 0,04 In In-Out Out In In-Out Out In In-Out Out In In-Out Out Gender: of my gender 0,06 0,33 Role: of my role 0,92 -0,16 In In-Out Out In In-Out Out In In-Out Out In In-Out Out Place: in the same branch 0,02 -0,04 E-I index

21. Indegree: Ho much my colleagues search me? A very high indegree, much higher than average. Leadership position. Outdegree: How much do I ask my colleagues? A very high outdegree. Good relationship with colleagues. A leadership position in a flat organization

22. Betweeness: how many times am I in between my colleagues? Very high value. Mediator and facilitator in a geographical sparse and very large network.

23. Broker Profile R. B.

24. OUTCOME OF THE ANALYSIS • The two wave research project offers a valuable tool for evaluating the informal network of communication, mutual help and personal support across the Training offices of the group. • The geographical location still plays an important role in shaping the boundaries of personal contacts. • Despite the lack of focused interventions between first and second wave, the network seems more connected and integrated in time two, with a wider main component, more cohesive subgroups and higher overlap between them. • Exchange analysis show the sectors in greater need of contacts. • Egonetwork analysis as a reliable instrument to investigate informal roles and rate the performances of individuals in communicating with eachothers.

25. KCC • In 2009, the KCC main task was to reach the government standards - National Indicator 8 (NI8) - in increasing adult participation in sport and active recreation. • In order to address this task, the council needs to map the network through which information circulate across sport agency on the count territory. • The research aimed to identify the pool of people who provide advice, information and/or motivation to help these agencies in delivering increased adult participation in sport and active recreation. • The questionnaire • Attributes • Relationships

26. The questions Roster: all the count agencies listed, people select the ones they have any kind of relatioship with Questions: 1.* How would you value advice provided by those listed below, to assist you with increasing adult participation in sport and active recreation?  Advice might include how to improve an activity or where to get further resources and support. Grade: very important; important; moderately important; not very important; do not go for advice 2.* How would you value information provided by those listed below, aimed at supporting you to increase adult participation in sport and active recreation? Information might include latest news, products and services available, funding opportunities, or examples of good practice.  Grade: very useful; useful; moderately useful; not very useful; does not provide information

27. 3.* Who of those listed below have you worked with to deliver activities to increase adult participation in sport and active recreation? Please rate how effective this was. Grade: very effective; effective; moderately effective; not very effective; have not worked with to deliver activities 4.* Who of those listed below would you like to have more contact with in helping you to increase adult participation in sport and active recreation. How would you rate the potential impact this person could have on your work if more contact was made possible? Grade: very large impact; large impact; moderate impact; small impact; do not need more contact 5.* Of those listed below that you currently work with, who motivates you to take on the challenge of increasing adult participation in sport and active recreation? How would you rate the level of motivation? Grade: very motivating; motivating; moderately motivating; a little motivating; not motivating at all

28. Survey Statistics • 93 completed • 9 incomplete • 162 not started • 353 people nominated • 26 “not started” have 4+ nominations • 35 “not started” have 3+ nominations

29. Demographics

30. Demographics – Organisational Category

31. Demographics – Participation Category

32. Completed Incomplete Completed analysis Are there people who completed the survey who aren’t connected? Not started

33. Critical Information “Information provided by this person is very important to me”

34. Delivery “This person has been very effective in helping me on delivery tasks”

35. Communicate More “Greater access to this person could have a very large impact on my performance”

36. Strategy/Support/Delivery Are delivery people learning from support staff or other deliverers? - Could investigate some of the 335 nodes Delivery is going to that we don’t have attribute data - Looks like Delivery units would benefit from interacting more with other delivery units … facilitated by support? - Looks like Delivery may be “under-serviced” by support and strategy. Suggest some specific “partnering” activities: Strategy/Delivery and Support/Delivery Advice / Information Links

37. % Loss of Connections % People Removed Critical Player Analysis 50% of Connections held by top 13%

38. Main Findings • The partnership is critically dependent on KSLO with potential drawbacks being: • Overloading of KSLO staff leading to programme delays • Potential limit to “reach” of the programme • Longer term issues around sustainability • Connections to delivery units less than optimal • Strategy and Support functions well connected, but less so with delivery • Connections between delivery units tend to rely on KSLO and support units. Direct connections would be more effective • Lack of specialist knowledge on “Adult participation in Sport and Active Recreation”? • Analysis suggests that there may be no “specialist” authority?

39. Strenght and limits of the two projects

40. BENEFITS FOR THE CLIENTS • On_Air: the SNA tools applied proved to be very useful for the client, but at the time of the surveys the Bank did not have a specific goal on how to use results. Therefore benefits remain potential, no focused intervention has been put in place. • KCC: the SNA tools had to face the difficulties of the data collection, therefore results are less reliable. However, the Council had a specific target of intervention in mind (meeting the Goverment standards), therefore it did make use of results and put targeted interventions in place. The pool of strategic people have been involved in the decisonal process.