It’s been a very tiring and emotional week – Brexit woes, World Cup blues, Trump’s visit, more Brexit woes – we all need something to cheer us up. So as well as reminding you all that Bake Off is about to start I thought I would share a couple of cool data tools that I have been using recently – they are not revolutionary and I’m sure some of you have come across them already but importantly, they are based on facts (Oh yes, Mr Trump) and they may just inspire you…..

1. The Manchester Cost Calculator – most social purpose organisations now have to define their worth in terms of cost benefits and cashable savings. This calculator uses data from numerous sources including the invaluable PSSRU dataset from Kent University, but makes them easier to use. The tool groups items into categories and provides costs such as a GP consultation, a parenting programme, weekly provision for a homeless household and so on. Plus you can inflate prices and see which agency bears the bulk of the spending. It’s a marvellous tool – I have recently used it to build a CBA tool for a charity working to prevent growth in the numbers of looked after children.

2. The Age UK Loneliness Heat Map – this shows the relative risk of loneliness across 32,844 neighbourhoods in England. It is based on 2011 Census data for marital status, self-reported health status, age and household size. The English Longitudinal Study of Ageing (ELSA) shows that these four factors predict around 20% of the loneliness observed among older people 65 and over. I have been using this in my role as trustee of Age UK Richmond-upon-Thames, to help identify the areas most likely to contain lonely older people so that we can plan our outreach/community work more efficiently and effectively.

3. Women’s Aid Infographic – I’m not usually a great fan of infographics, I would always rather have a table or a graph but I think that this one produced by Women’s Aid is a really clever way of showing the potential impact of a service. I have already sent it to three charity clients grappling with how to illustrate their deep dive/case study data but it could also be used for commercial clients to illustrate a customer journey eg. in the financial services sector it could show much money you could save for retirement if certain decisions are made vs other decisions.