I started at Bristol Older People’s Forum in April 2016. In week 2 I was sat with our sole funder asking who we were funded to reach. ‘Over 55s’ was the answer. But I already knew (I had wasted no time finding what was known!) we were much older than 55+. ‘Are we supposed to have members representative of all over 55s in Bristol then?’ ‘well, yes’. Hm. It felt very much like this discussion had not been had before and I was… surprised. We were monitored every 6 months on ‘equalities’ but this was small sample meeting attendees (and mostly the same attendees each time). We did also have a very large sample members survey from the year before but it focused on what issues were faced - it’s purpose was to guide BOPF campaigning work.

I learnt fast. Funder monitoring was the only time data of any type was collected and reported on - and, as can often happen, it was seen as something we had to do, for them, but not something that we should/could be doing for ourselves, to guide strategy (it also seemed the funder wanted to see it being done but did not cast a critical eye). To us, data was mainly a necessary evil. Our database was run as simply as possible and only name and address held. I could see straight away that our membership (and so database), and our knowledge of our members (though not linked to database), was our real (and unique) strength.  

About 6 months later after I started I saw an email about DataKind coming to Bristol for an older people themed datadive (in about 3 weeks time). They wanted a local older people’s charity. Contacting larger charities than us had not come to anything and so, although late in the day, I jumped at it.

What a great experience. Our chair, Judith (77), was inspiring and made all the difference to the pitch. We had a great team of data scientists for the weekend. Time had been tight for me and my team of 3 to find and clean the data we needed, and formulate the questions - and I had so many questions!

We found out our membership is much older, is more likely to be disabled, is spread across the city, more likely to be female, as likely to be BAME. We already knew 50% were not online at all, 50% on low incomes. It became clear, and supported by what Judith thought, that our members were those most disadvantaged, most in need, most vulnerable. We used this data as insight to guide strategic planning work, the trustees gradually became familiar and confident with the data and I added depth by capturing more meaningful feedback via meetings to paint the full picture.

We finalised new strategic objectives a few months later. We wanted to stay focused, with member services, on the older and more disadvantaged in the city, but knowing our expertise means we are able to speak for all older people. Our actions on data included widening what we hold on the database, and meeting ‘monitoring’ forms asking what WE want to know.

We share our data and insight and no longer see it as a funder requirement. We have been frustrated at time and software not allowing ongoing data ‘diving’ - time to manage volunteers being a particular challenge.  But we found the evidence we needed, and we continue to gather feedback from our members at every meeting, and to achieve stunningly high survey response rates that are the envy of everyone we speak to! It has also lead to me becoming more up to date on the data world and making new contacts.

The next data challenge is probably to increase efficiency of internal systems, and data on funders and stakeholders that will support our objective of diversified funding to ensure sustainability of our work. The final words should go to a member, to explain why we do all this, “life is a struggle, but BOPF gives me hope”.