Secrets of Data Ceris Anderson Street Games This

Secrets of Data Ceris Anderson - Street. Games

This Session • How to get the most from data • How to turn it into evidence of impact • How to use it to help unlock resources

This Session • Why is it important to collect and analyse data? • What data should we collect or look up? • How can we use this data better? • What are the limitations of data collection? • What other information and feedback would be useful? • What can we do with the data and evidence once it is collected?

What is the one thing you most want to cover in this session today?

Why is it important to collect and analyse data?

Why is it important? It can help to: • Keep track of progress and assess how things are going • Identify which sessions are working well and where changes/ improvements may be needed. • Identify who is coming (and who is not), is it the intended target group? • Identify how often people are coming…. . are they in danger of dropping out? • Provide consistent performance measurement. • Evidence need & progress, lobby for further support, assist sustainability It is an essential part of good project management

Data collection is important but it can also be a challenge………… What are the key challenges you face with data collection?

What data do you typically collect in your projects?

What data? • This must be driven by the aims and objectives of your project: – – – – Sports participation Participant engagement, Retention, Progression Volunteer engagement and development Training and qualifications Health improvement Reducing crime and ASB Others……. . • Can they all be measured by data collection?

Data Collection • Try to keep it as simple as possible • Only collect what you really need • Explain to project staff, coaches, volunteers and participants why you collect the information and why it is important • Ensure systems are in place from the outset • Make use and share the data

Data Collection • Record attendance at each session • Encourage ‘live data’ uploads • Participant app • Membership cards

Data is collected………Then what?

Analyse/Review the Data • Total participant numbers • Who is attending (profile) and who isn’t • What activities are they doing? • How often are they coming? • How long have they been coming? • Who has dropped out? Are there any patterns? • How do we know if there has been any progression?

Birmingham

Use the data to inform delivery, make changes and shape planning

Sessional data to keep an eye on……… Sessional Factors • Which sport/activity • Day/Time • Venue type/location • Which coach External Factors • Weather • Holidays • What’s on TV/new ‘pulls’ Data tells you what, but may not explain why……may need to explore further

Know the participants The data can help show the profile of participants: • • Newbies Settling ins Core Dedicated

Know your participants Use your data to tailor actions Category 1 “The newbies” 2 “The settling ins” 3 “The core” 4 “The dedicated” Actions required • Needs lots of attention – make them feel welcome, explain session, no surprises • Buddy systems, help them make friends • Taster sessions • Send text/message if possible to say they have been missed • Incentives • Reminders about next sessions • Needs lots of attention • ‘Spice up’ sessions, tell them about festivals and events • Rewards/awards (non-sporty) • Reminders about next sessions • Send text/message if possible to say they have been missed • Involve them to events and festivals • Provide more challenges • Input into session planning, youth-led • Provide responsibility • 1 -1 discussion, identify pathways, potential exit routes, leadership • Become a buddy to those in group ‘ 1’ • Able to ‘find their own way’ into activities, volunteering or officialdom

What are the limitations of data collection?

Not everything that can be counted counts, and not everything that counts can be counted”. [Albert Einstein] “

Data is far more powerful when partnered with other information and feedback

Data Limitations • Data collection can provide very useful information and show trends but it will not explain why • It will not identify why something is working well or not so well • What is behind the data? • What are the ‘life stories’? • It can be hard to prove causality

Other information • Gather feedback: – Why is something working well – What are the success factors? – What have been the challenges – What could be done differently • What are the ‘stories’ that bring the data to life? • What progress or impact has the project made?

How to find out • You may decide to conduct in-depth research • But you can also gather useful feedback simply and cheaply Informal conversations Graffiti Boards Social Media Photo or Video Evidence Conducting interviews Ask young people to do ‘paired pal’ interviews • Surveys • Hold focus Groups • Projective techniques • • •

Wider project Aims • You may need to collect other data or use progress ‘markers’: – Questionnaires or interviews (may be tailored to your project or national surveys like the GPAQ) – Evaluation tools (e. g. engagement ladders, Rickter Assessment, Outcomes star) – Partner data (e. g. crime stats, NEET records)

Reported ASB Incidents in XYZ by Hour: Nov to Jan 12 -13 & 13/-14

What other data tools may help?

Other data tools Sport England: • • Active People Interactive Market Segmentation Tool Local Area Profiles Local Economic Value of Sport Tool Other useful tools and websites: • • • Neighbourhood Statistics Health Profiles Child Health profiles Crime data Poverty Are there others you find useful?

Use the data and evidence to share information & demonstrate your work

Using & Sharing your project data and evidence • Review progress internally • Identify which sessions are working well and where changes/improvements may be needed – Act on it! • Provide feedback on progress to everyone involved • Use the data to show the value and impact of your project to partners, the wider community, funders and others • Use the data and evidence to support the case for continued and increased levels of funding.

Build the project ‘story’ • What has been learnt about: – Numbers attending, year-on-year growth – Key trends: can these guide future delivery/ investment – Success in attracting key target groups – The activities or growth in a particular sport – The development of local capacity – Contributions towards physical activity targets – Contributions towards improving quality of life

Build the project ‘story’ • • • Project Case studies – What has happened – What worked well – What has been learnt Individual ‘pen portraits’ – Progress of an individual participant, volunteer, leader or coach Other sources: – Do other partners have data or evidence which supports the work – Has there been any press or political interest? Use all the different sources to ‘tell the story’

Case Studies

Case Studies - Video

Summary • Data collection is an essential part of good project management • It is key to sustainability and securing funding • It’s not just about numbers • Make sure everyone knows what it being collected and why • Use and share the data and evidence

Help • Help is available……please do ask if you aren’t sure on monitoring data or have queries on collection evidence and demonstrating impact • Views session – Tomorrow: 12. 05 -1. 05 ‘Making your case for investment’

www. streetgames. org 0161 707 0782 ceris. anderson@streetgames. org Views Support: Matthew Rivitt, Haseeb Malik, Joe Keohane & Daniel Grice

Secrets of data

https: //www. youtube. com/watch? v=IYok. ALw. Sj. E

Spare slides

Statistic Summary gives you an overview of your project and also allows you to focus on particular dates or clubs.

Allow you to analyse the rates of participation and the popularity of each sport.

The Evidence section allows you to store various forms of information which demonstrate the impact and success of your work.

Data Analysis Example: Doorstep Sport Clubs • DSCs record attendance data • Street. Games collates from DSCs (by club/org/region/nationally) • Review internally at DSC project board • Report to Sport England Quarterly • What do you do with the data you collect?