Big Data for Small Places ANALYTICS CAPACITY- BUILDING FOR COMMUNITY DEVELOPMENT DR. NELSON P. ROGERS, COMMUNITY INGENUITY
Overview Big Data for Small Places Project The Opportuni-es The Challenges The Approach The Partners The An-cipated Results 15-10- 11 BIG DATA FOR SMALL PLACES - NELSON ROGERS 2
The OpportuniMes: What Big Data Can Do Everybody knows Percep-on vs. Reality 15-10- 11 BIG DATA FOR SMALL PLACES - NELSON ROGERS 3
The OpportuniMes: What s Happening New Master s Degree Programs Carleton University - collabora>on of six academic disciplines Specializa>on in Data Science or Business Analy>cs Queen s University School of Business Master of Management Analy>cs York University Master of Business Analy>cs 15-10- 11 BIG DATA FOR SMALL PLACES - NELSON ROGERS 4
The OpportuniMes: What is Available Sta>s>cs Canada Census Profiles and CANSIM tables (by province, district, community, postal code) popula>on, age, sex, dwellings, families, marital status, language hvp://www12.statcan.gc.ca/census- recensement/2011/dp- pd/prof/index.cfm?lang=e&mm Ontario Workforce Boards Labour Market Reports hvp://www.workforceplanningontario.ca/labour- market- trends/publica>ons.htm 15-10- 11 BIG DATA FOR SMALL PLACES - NELSON ROGERS 5
The OpportuniMes: What is Available (cont d) But Wait! There s More Analyst: OMAFRA Economic Development Analysis Resource hvp://www.omafra.gov.on.ca/english/rural/edr/edar/#analyst Newcomer and Youth Community Indicators Tool hvp://www.omafra.gov.on.ca/english/rural/edr/nyci/index.html Rural Ontario Ins>tute: Focus On Rural Ontario - Fact Sheets hvp://www.ruralontarioins>tute.ca/focus- on- rural- ontario.aspx And that s only the -p of the iceberg 15-10- 11 BIG DATA FOR SMALL PLACES - NELSON ROGERS 6
The Challenges Snapshot overview of Big Data hvp://www.zdnet.com/ar>cle/the- enterprise- opportunity- of- big- data- closing- the- clue- gap/
The Challenges 15-10- 11 BIG DATA FOR SMALL PLACES - NELSON ROGERS 8
The Challenges Funding programs and accountability guidelines require use of analy-cs But - Access: Where is the data? Who owns it? Volume: How much is out there? Too much to handle? Accuracy: How big are the errors and omissions? Analysis: What s really important? What does it mean? U-liza-on: Now that we know what are we going to do? 15-10- 11 BIG DATA FOR SMALL PLACES - NELSON ROGERS 9
The Project: Big Data for Small Places Partners: Lanark County Planning Council for Children, Youth and Families Lanark Renfrew Health & Community Services Local Immigra>on Partnership of Lanark and Renfrew Town of Mississippi Mills Municipality of North Grenville Funded in part by: Ontario Ministry of Agriculture, Food, and Rural Affairs Rural Economic Development Program Valley Heartland Community Futures Development Corpora>on Eastern Ontario Development Program 15-10- 11 BIG DATA FOR SMALL PLACES - NELSON ROGERS 10
Thomas H. Davenport The New World of Business AnalyMcs Business Analy-cs can be defined as the broad use of data and quan>ta>ve analysis for decision- making within organiza>ons... It includes analy>cs, of course, but involves harnessing them to meet defined business objec>ves. Business analy>cs empowers people in the organiza-on to make bexer decisions, improve processes and achieve desired outcomes Despite the name, business analy-cs is not restricted to private- sector, profit- seeking businesses. The meaning of business here is that of an immediate task or objec>ve, with analy>cs being a means to achieve that objec>ve. Governmental and non- profit organiza-ons can use business analy-cs to advance their objec-ves as well Interna>onal Ins>tute for Analy>cs (2010) hvp://www.iianaly>cs.com/ 15-10- 11 BIG DATA FOR SMALL PLACES - NELSON ROGERS 11
The Approach To Succeed with Big Data Start Small hvps://hbr.org/2012/10/to- succeed- with- big- data- start (Harvard Business Review) Mentoring: Not reinven>ng the wheel, using exis>ng exper>se Networking: Connec>ng with experts and fellow- travellers Training: Customized to meet the needs of rural communi>es & organiza>ons Case Studies: Significant, Manageable, Relevant 15-10- 11 BIG DATA FOR SMALL PLACES - NELSON ROGERS 12
Project AcMviMes Consulta-on with partners Assess current state of analy>cs capacity Select appropriate test case Training Sessions - Intro to Analy>cs for Rural Community Development Adapt, test and evaluate business analy>cs course Overview of relevant data sources and indicator systems Follow- up with partners Specific, relevant data sources and indicator systems Evalua-on Lessons learned re: project content and format 15-10- 11 BIG DATA FOR SMALL PLACES - NELSON ROGERS 13
Project Case Studies Lanark County Planning Council for Children & Youth Report Card on Wellbeing of Children & Youth Lanark Renfrew Health & Community Services Index of Wellbeing especially mental health Local Immigra>on Partnership of Lanark and Renfrew Evidence of benefits of local immigra>on & in- migra>on Town of Mississippi Mills Evidence- based ac>ve transporta>on policies and priori>es Municipality of North Grenville Effec-ve management of demand for recrea>on facili>es 15-10- 11 BIG DATA FOR SMALL PLACES - NELSON ROGERS 14
What we Learned: tentamve conclusions project evaluamon in progress Rural municipali-es and organiza-ons Priori-ze community axrac-veness/ community wellbeing common theme among economic development, health, social service groups Have some business analy-cs exper-se, but use it for administra>on not strategic planning Are unaware of many relevant data sources and indicator systems Have connec-on to a library but rarely use it to find data sources and indicators Are being pushed into data access & analy-cs by grant applica>ons and accountability measures Tend to dive into the data (get the numbers) with livle prepara>on on fundamentals of analy>cs 15-10- 11 BIG DATA FOR SMALL PLACES - NELSON ROGERS 15
What we Learned: tentamve conclusions (cont d) Challenges Mismatch of boundaries and catchment areas problems with data access and relevance Wide varia>on among organiza>ons re: how data is collected, stored, shared Ontario Non- Profit Network is working on this Redefining/reframing issues to determine what can/cannot be answered by data Understanding how to answer What do people need? expert opinion, demand, comparables Project administra>on burden of accountability (trivia), arbitrary rules of funding agencies 15-10- 11 BIG DATA FOR SMALL PLACES - NELSON ROGERS 16
AnMcipated Long- term Results BeXer Understanding challenges and opportuni>es in using analy>cs for community development Mentoring and Networking what works/what doesn t Training Introduc>on to Analy>cs for Rural Community Development adapted, delivered, evaluated, revised Consultants understanding when to use them, what to ask, what to do with results Results: Capacity for evidence- based decision- making and performance indicators BeXer decisions, bexer accountability, bexer communi-es 15-10- 11 BIG DATA FOR SMALL PLACES - NELSON ROGERS 17
Big Data for Small Places Project Admin Financial and Legal Administra>on: Open Doors for Lanark Children and Youth Training Provider: Algonquin College, Corporate Training Project Management: Robert Leitch, MEd, Sonop>c Communica>on and Nelson Rogers, MSW, EdD, Community Ingenuity nelson@communityingenuity.ca 15-10- 11 BIG DATA FOR SMALL PLACES - NELSON ROGERS 18