By Caroline Duvier @Caroline_Duvier
Quality. It’s a word that has many different meanings. Quality of life. Quality TV show. Quality of a report. It is also a very strange word to pronounce!
In this piece, I will look at the quality of data. Now before you recoil in horror or boredom, bear with me. I hope to make this interesting for you. I’ll start by talking about baking cakes. A cake is a (hopefully) wonderfully scrumptious result of a bunch of ingredients, measured by quantity, and baked for a set amount of time at a set temperature. It can be a lot of fun to bake a cake. And even more fun to eat it.
The making of the cake
What does baking a cake have to do with quality of data, you ask? Try and substitute the cake for something you are trying to figure our in your organisation. Let the cake be a result you’re trying to get, such as happy residents (i.e. customer satisfaction). Cake is now happy residents. What are the ingredients? A variety of things, most likely, such as a comfortable home, good repairs and maintenance service, good neighbourhood, closeness to family and friends, good transport links to work, and a lot more.
For each of these ‘ingredients’ to the ‘happy resident’ cake, you will need to have data. How many repairs were carried out, how quickly did the operatives show up, was the resident satisfied with the repair, is it an ongoing issue or a one-time fix? How many cases of anti-social behaviour have been recorded in this neighbourhood, has this particular resident ever complained themselves? Do they report being happy with where they live? How far in miles are their family and friends? How many bus and train lines exist in this neighbourhood, where do they go? Does the resident have a car?
Each of these questions can be answered with either a number or a value. These can be added to be ‘baked’ into the final result, happy resident. The resident can be unhappy or happy or anything in-between, just like a cake that can be scrumptious or…not.
What you can now do is compare a bunch of your residents on how happy they are. What makes a happy resident? Which ingredients work and which ones turn the dough sour? The point of this analogy is that whatever question you are trying to answer in your organisation, it is very likely that you will need data to answer it.
You also cannot have any odd ingredients to throw into the mix, the better the quality of your ingredients, the better the cake will be. The same holds for data. Data can be measured on a variety of dimensions, such as reliability, validity, accurateness, compatibility. Just like you would not just buy a packet that says ‘flour’, you look more closely at it. Is it fine or coarse, whole meal, plain, or self-raising?
The ostrich’s head is out of the sand
The social housing sector is very well aware that data are an issue (yes, it’s plural). HACT have written numerous pieces on data quality and are currently working on a data standard for the sector, together with OSCRE. The organisation I used to work for knew that their data needed a good clean, and most people I speak to in the sector know their data aren’t as good as they could be. I wrote two journal papers on data quality, trying to highlight why it is important to work on data quality as a sector. Nobody no longer hides behind their bad data.
The problem seems to be, how do we move forward? Once you begin to scratch the surface of data quality, you begin to realise how much of an iceberg it really is. This is not to discourage anyone, but it does highlight that data quality has been ignored for so long that it turned from a small piece of olive oil down the drain into a fat berg. Cleaning this fat berg is hard and unpleasant work. It has to be done, though, otherwise the pipes will be blocked and it all just blows up in our faces. And no cake.
Now that we are all on the same page in terms of acknowledging our data quality issues, we can start dreaming about what we could do if we did have high quality data. Before we do that, we do need to talk about the journey to get here first, and some of the stumbling blocks to be aware of.
Silos should be reserved for wastewater treatment plants
Not all social housing providers are created equal. With the stock transfer came the creation of a whole new set of organisations, all with the same goal, but with very different organisational structures and models. This section might not be relevant for highly innovative, entrepreneurial housing providers. It is relevant for a lot of organisations that are structured in a hierarchical way with different departments. I hazard a guess that this applies to most social housing organisations.
The hierarchical structure is a very popular model for organising a corporation. Very few people at the top, some in the middle, most at the bottom. You then have departments that carry out different tasks. There is the Rent Collection team, the Asset Management team, the Finance team, the HR team, the Media and Communications team, and a few others. Most of these teams will have their own systems they work with, their own spreadsheets, their own hard-copy folders dating back 20 years or longer.
People take notes, write emails, have phone conversations, and check things online, such as average house prices for an area. All of this is data. Just in those two sentences, I listed seven different ways to collect and store data, and none of these are compatible or speak to each other. Now multiply this by every department your organisation has.
Departmentalisation is not necessarily a bad thing, but it can have some side effects detrimental to getting data quality under control. The biggest impact of having clearly defined and separated roles and departments is the likelihood of people thinking in silos. Their work is focused on their departmental goals, not necessarily the organisational goals. The finance team will try and balance the books. The rent collection team will concentrate on collecting rents.
While each of these roles is important, they tend to become narrow in their approach, almost naturally. It is like Newton trying to figure out why the apple fell. You try and understand an issue by looking at the individual parts, not the whole. This is known as reductionism. The issue with such an approach is that nothing in this world is without connections. Everything works as part of a system. If we understand social housing as a system, we begin to draw connections between departments, and this opens up new avenues for projects, for innovation, and finally, for achieving great housing for all.
When staff of an organisation identify with their department more than with the organisation itself, they become protective of their jobs. This includes the data they handle. The Housing Development Board in Singapore noticed this when they tried to implement a new data warehouse. Theirs is a huge organisation covering all housing in Singapore. They used over 200 different systems, not including data on spreadsheets.
The goal was to have a single data warehouse in which all data in the organisation is fed. One of the problems was that staff were protective of ‘their’ data and did not want to share it with others. It took a lot of dedication, training, education, and time to change people’s hearts and get on board with the project. In the end, it worked and they now have a single system, allowing them to use data from all sorts of different parts of the organisation and analysing them in ways previously unimaginable. All this comes with huge cost savings, greater employee satisfaction and performance, and greater efficiency as an organisation.
The key is dedication
Social housing has an interesting and wobbly history in the UK. From having a third of the housing share in the country after World War 2, we are ever more decreasing in size. We all know the policies behind this, so let’s not get wound up again. Many organisations are struggling to do anything other than react to the constant pressures exerted on them. Apart from policies that change quicker than our underwear, the sector does not have a strong track record of data analytics.
Housing provision was simply that – housing provision. With badly built properties in the 60’s and 70’s came the need for maintenance and repairs, new regulations regarding damp and mould require a closer look at the properties, and now with the coronavirus pandemic, reliable data has shown to be more important than ever.
Going from reacting to changes to being proactive requires a lot of dedication throughout the organisation. The board needs to be on board (see what I did there?), as well as the senior management team. Support from the top is important, as the top is the living example of the values the organisation holds. A chief executive seen to be dedicated, caring about the residents and staff, actively involved in activities, will be able to create much more traction for change than a chief executive who seems removed and distant.
The recognition needs to be there for resources dedicated to data quality across the entire organisation. People’s roles could temporarily change, or new people hired who champion across the organisation for better data quality. This includes ongoing training sessions, educational tools for staff members (and residents), and most importantly, people need to know why any of this is important to them, their role, their department, and the organisation. Thankfully plenty of material exists that highlights the positive effect of high data quality, so this should not be an issue.
It’s all just unicorns and rainbows
Achieving high quality data is an ongoing process that never stops. This does not have to be a chore, though. I do not find baking cakes a chore, I rather enjoy it. The secret, I find, to anything in life, is to find the positives about something and sticking to it. For data quality, the positives are plentiful. Good quality data boosts confidence. You can go from “I’m having a hunch about this”, to” Check out this amazing graph that shows which of our customer engagement approaches over the last three months worked best!”.
You can get creative with your data collection and what you want to do with it. And if you caught the bug of creativity, other people are likely going to follow you. People start to see their positive contributions to the organisation and start to become engaged. Sadly, all of this will take time. A long time. But it is worth it in the end, because your organisation will be better for it, your staff will be happier, and so will your residents. It’s all just unicorns and rainbows.
Title of piece
There is a reason why I chose Quality Street in the title of this piece. My PhD research focuses on sustainability in social housing. Quality streets for me are streets where people can safely carry out their activities, are inclusive, do not cause air or noise pollution, and get people to where they need to be. Houses on these streets are also of high quality, affordable for the residents to live in and heat.
Data quality plays a large aspect in achieving quality streets. If you have high quality data, you can monitor progress, you can compare different approaches, you can select a choice based on a range of criteria. I believe we all work towards the same thing with different perspectives. What I love about Social Housing Matters is that it allows us to share our ideas, to gain knowledge in something we didn’t know about, and if something really interests us, we can make new connections with people we have not worked with before. I am very excited to be part of this new endeavour and look forward to engaging with many of you. And whatever you do, make sure you do it to a high quality data standard.
About the Author
Caroline Duvier studied Psychology before moving into a very wild goose-chase after a well-fitting job. Stints in research and development, Legoland (yes), higher education teaching, led to working for a social housing provider in Yorkshire for three years. Starting with a knowledge transfer partnership, which are partnerships between Universities and corporations, she then moved to working in the sustainability team and enjoyed switching the lights off so that everyone worked in darkness to save the planet.
During her time working in social housing she started her PhD. The research focus is on sustainable social housing, in particularly looking at decision making and what is needed to incorporate sustainability in managerial decision making. Caroline now works as a teaching assistant at the University of Leeds for the amazing MSc Sustainable Cities. She still has her feet firmly grounded in working to create better social housing.
You can email her at firstname.lastname@example.org