It's possibly too early in the year to be talking about reflections - especially as I only recently finished formulating my predictions - however, a recent HACT meeting about Community Investment led to a period of reflection on the fact that Trafford Housing Trust is now six years old. In that time we've spent £5 million on Community Investment and I thought it would be worthwhile bringing together what we've learned. As ever I'm really interested in your views and insights on the subject, so please feel free to leave a comment or reach me on Twitter.
Lesson One: Community Investment is “Mission Central” for THT
It's not that we are a landlord who does Community Investment as part of a CSR initiative, or just that it sounds like the sort of thing we should be doing. Community Investment directly gets us to where we aim to be. Our values state that we will be “at the heart of neighbourhoods which are safe and clean, where communities have a strong voice and where people choose to live.” I'm not saying we're perfect, our approach should (but still doesn’t) involve everyone on the staff and not just a small Community Investment team, but we strive to see that our budgets deliver community benefits as well as great levels of landlord service.
Lesson Two: Our Activity Is Structured At The Neighbourhood Level
We think it's vital that our Community Investment work is driven not by us, but by the customers and the communities in our neighbourhoods. Our approach has five steps:
1 - Having hard data about the strengths, weaknesses and needs of communities at the level of our neighbourhoods. For most neighbourhoods, we feel this information is still fragmented, or held exclusively in people’s heads, which often mean it has key elements that are missing.
2 - Having “soft” data about the same things. Listening to what customers and community leaders say, examining plans and actions of other stakeholders to maximise impact/avoid duplication, observing how things are actually used in the local area, learning from best practice elsewhere. This is about having well attuned “eyes and ears” and good local and national networks to inform them.
3 - Understanding that data. Our early experience was that we frequently jumped to conclusions about what the data told us and as a result we moved too quickly into solution mode. This step is crucial and one we are now bolstering by bringing in much stronger analytical skills. Intelligence, not just data, and causality are the prizes here.
A good example of this approach is education. How many times will we try to address poor educational attainment by improving schooling, when actually the problem is that at home there is neither a culture that values education, nor quiet space for students to study. This step is not without controversy; seasoned professionals view the rigour of a regression analysis at this stage as somehow questioning their finely honed “gut instinct”; missing the point that that is precisely the point!
4 - Selecting the outcomes/benefits we want to achieve and then the projects that will best achieve them. Note the order here; too often our drive has been to “do” something, rather than “achieve” something. We’ve learned from this and increasingly we look at the benefits we want to achieve and work backwards to the projects that are needed to deliver them. We seek to answer the “Why are we doing this?” question, before the “What are we going to do?” one. No more creating a nice project, just because it’s a trophy!
5 - And finally, the old challenge of how we measure impact and value for money. Here’s where a national framework would be invaluable, but we don’t underestimate the difficulties of producing something meaningful. We would ideally be looking for something that enables us to know that:
i. The distribution of resources and benefits is fair in relation to need and opportunity
ii. Absolute cost/benefit assessments (CBA) can be made on individual projects to support “go/no go” decisions
iii. Comparative CBA can be made to select preferential projects from the universe of possible ones
iv. Retrospective CBA can be carried out to compare expected outcomes from a project with those actually delivered
v. Whole organisation assessments of “value added” can be made on an annual basis
Problems Still To Address
Although these steps represent the methodology that we are using, we are the first to accept that it is far from perfect! We still have a list of problems that we need to solve.
a) The information is collected in many and varied ways, at different times and when data from other organisations is also examined, different meanings of the same word can lead the unwary into bear traps of inconsistency.
b) Understanding of data is not a science, but an art – and in some cases the political lens through which that data is viewed will be a more important driver of understanding than and statistical technique.
c) Even with the best understanding available, at best we are left with a “fuzzy” picture of what's best to do. As a result somebody, somewhere, still needs to make a decision, stick their neck out, do something and be accountable for the outcome. Mistakes are inevitable; Boards must treat these as opportunities to learn, not reasons to punish.
d) There are real pressures to do what everyone else is doing – even if the circumstances aren’t the same. The herd mentality of following your neighbour is still a driver of too many project decisions.
e) A focus on needs and community opinions can hamper innovation. Steve Jobs didn’t use focus groups to design products that people said they wanted, he used creative innovation to design products that people didn’t yet know they wanted. Maybe that is why so much Community Investment we see is a recycling of old ideas.
f) Many of our Community Investment activities are selected by community groups themselves. The scale of their thinking is often small, when a bigger project would give proportionately more impact, and their time horizons are short, further reinforcing the “quick and dirty” approach to creating value.
I'd be interested in your own approaches and thoughts on this issue. It seems like Community Investment is one of those topics that could best be attacked with a crowd-sourced approach, allowing us to pool our differing opinions and learn from the mistakes and successes of others.
Lesson One: Community Investment is “Mission Central” for THT
It's not that we are a landlord who does Community Investment as part of a CSR initiative, or just that it sounds like the sort of thing we should be doing. Community Investment directly gets us to where we aim to be. Our values state that we will be “at the heart of neighbourhoods which are safe and clean, where communities have a strong voice and where people choose to live.” I'm not saying we're perfect, our approach should (but still doesn’t) involve everyone on the staff and not just a small Community Investment team, but we strive to see that our budgets deliver community benefits as well as great levels of landlord service.
Lesson Two: Our Activity Is Structured At The Neighbourhood Level
We think it's vital that our Community Investment work is driven not by us, but by the customers and the communities in our neighbourhoods. Our approach has five steps:
1 - Having hard data about the strengths, weaknesses and needs of communities at the level of our neighbourhoods. For most neighbourhoods, we feel this information is still fragmented, or held exclusively in people’s heads, which often mean it has key elements that are missing.
2 - Having “soft” data about the same things. Listening to what customers and community leaders say, examining plans and actions of other stakeholders to maximise impact/avoid duplication, observing how things are actually used in the local area, learning from best practice elsewhere. This is about having well attuned “eyes and ears” and good local and national networks to inform them.
3 - Understanding that data. Our early experience was that we frequently jumped to conclusions about what the data told us and as a result we moved too quickly into solution mode. This step is crucial and one we are now bolstering by bringing in much stronger analytical skills. Intelligence, not just data, and causality are the prizes here.
A good example of this approach is education. How many times will we try to address poor educational attainment by improving schooling, when actually the problem is that at home there is neither a culture that values education, nor quiet space for students to study. This step is not without controversy; seasoned professionals view the rigour of a regression analysis at this stage as somehow questioning their finely honed “gut instinct”; missing the point that that is precisely the point!
4 - Selecting the outcomes/benefits we want to achieve and then the projects that will best achieve them. Note the order here; too often our drive has been to “do” something, rather than “achieve” something. We’ve learned from this and increasingly we look at the benefits we want to achieve and work backwards to the projects that are needed to deliver them. We seek to answer the “Why are we doing this?” question, before the “What are we going to do?” one. No more creating a nice project, just because it’s a trophy!
5 - And finally, the old challenge of how we measure impact and value for money. Here’s where a national framework would be invaluable, but we don’t underestimate the difficulties of producing something meaningful. We would ideally be looking for something that enables us to know that:
i. The distribution of resources and benefits is fair in relation to need and opportunity
ii. Absolute cost/benefit assessments (CBA) can be made on individual projects to support “go/no go” decisions
iii. Comparative CBA can be made to select preferential projects from the universe of possible ones
iv. Retrospective CBA can be carried out to compare expected outcomes from a project with those actually delivered
v. Whole organisation assessments of “value added” can be made on an annual basis
Problems Still To Address
Although these steps represent the methodology that we are using, we are the first to accept that it is far from perfect! We still have a list of problems that we need to solve.
a) The information is collected in many and varied ways, at different times and when data from other organisations is also examined, different meanings of the same word can lead the unwary into bear traps of inconsistency.
b) Understanding of data is not a science, but an art – and in some cases the political lens through which that data is viewed will be a more important driver of understanding than and statistical technique.
c) Even with the best understanding available, at best we are left with a “fuzzy” picture of what's best to do. As a result somebody, somewhere, still needs to make a decision, stick their neck out, do something and be accountable for the outcome. Mistakes are inevitable; Boards must treat these as opportunities to learn, not reasons to punish.
d) There are real pressures to do what everyone else is doing – even if the circumstances aren’t the same. The herd mentality of following your neighbour is still a driver of too many project decisions.
e) A focus on needs and community opinions can hamper innovation. Steve Jobs didn’t use focus groups to design products that people said they wanted, he used creative innovation to design products that people didn’t yet know they wanted. Maybe that is why so much Community Investment we see is a recycling of old ideas.
f) Many of our Community Investment activities are selected by community groups themselves. The scale of their thinking is often small, when a bigger project would give proportionately more impact, and their time horizons are short, further reinforcing the “quick and dirty” approach to creating value.
I'd be interested in your own approaches and thoughts on this issue. It seems like Community Investment is one of those topics that could best be attacked with a crowd-sourced approach, allowing us to pool our differing opinions and learn from the mistakes and successes of others.
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