We live in a world obsessed with data and, thanks to the internet, we can track, monitor and report on just about everything. The more data, the better, and big data is now big business. The danger is that data gets misunderstood, becomes overwhelming and then detrimental to your business. Information overload is very real and can have a paralysing effect. Faced with almost infinite quantities of data, the choices and decisions themselves can become infinite. Getting your hands on good quality data starts, funnily enough, at the beginning, but also at the end.
Step 1 – Acknowledge the need for data
As a housing stock portfolio & asset manager, you have a task list as long as your arm, targets and KPIs to keep you focused, a finite budget and yet still only 24 hours in a day. So, how will you hit those targets with the resources at your disposal? Data would be great, wouldn’t it? It could help you focus your efforts and optimise your budget. That’s an excellent starting point; just understanding the need for accurate data itself means you’re serious about the challenge. The next step is to decide on what it is you want to measure.
Step 2- Agree why you need the data
Now you have decided, “wouldn’t it be great if…”, it’s important that you review and agree on the “why”. Why gather all this data? To start a successful data management programme, you have to start at the end; what’s your overall objective and what do you want to achieve?
If you have a stock of 1,000 houses and 10 per cent of them are not meeting the government’s energy standard, you’ll most likely want to identify those homes and tenants in most need of help and support. In parallel to that objective, you’ll probably want to know if there is a subset of those homes with tenants in fuel poverty and, in turn, which of that subset are eligible for grant funding, and for what. Once you have that data, you might also want to cross reference those homes with your maintenance budget and see if the items you wish to implement tie in with any scheduled maintenance programmes that may be already planned but are beyond your direct remit.
Today’s economic climate and variables in the energy sector mean that understanding your data and optimising your budget are no longer luxuries – they are essentials.
Step 3 – Decide on data collection
The next thing is to decide what data you will collect, who will be collecting it, what you will do with it, and how you will store and maintain it.
It’s fine to collect all this data, but there are data maintenance decisions attached. Do you know what you want to do with it once you have it? Have you agreed a format for keeping it up to date and for ensuring the accuracy of what you have? Let’s assume you have; assumptions are dangerous, but let’s move along.
How will you collate the data? To whom do you trust it? What’s the most economical way to get information on your 1,000 homes or the buildings you manage? Building surveying is one of the options.
Do you already employ an ICT manager who can help you integrate, cleanse and augment what you already hold? After all, you may already have most of what you need.
Businesses grow organically or through mergers and acquisitions. Many great housing associations have grown this way. That can mean several things. On the positive side, with everybody on board, change can be embraced quickly and the best of both parties taken for the benefit of the newly-formed organisation. On the negative side, organic growth can be slow and poor practices are likely to become culturally ingrained. Rapid funded growth can result in growth at all costs, with poor systems and processes, leading to a mash-up of two or more systems vying for attention. This in turn will create conflicts, both in terms of the data itself and the team tasked with managing the stock.
Exploiting and understanding your assets’ big data is imperative if you want to make wise decisions on their future improvement. You should therefore set out: what you need to know; what you would like to know; and what you do actually know. Once you have established those points, it will make asset management much easier.
Step 4 – Decide about exploitation
We are very fortunate that software exists to help. Technology is evolving rapidly, both how it’s designed and how we consume it.
Yet today, many housing providers are still perfectly happy to manage their stock using Excel via a series of linked (or not) spreadsheets. Others have designed and implemented extremely expensive software solutions, bespoke to their needs.
In life, there will always be extremes; managing your stock for free on Excel or paying vast fees for a bespoke solution is a case in point. Extremes can be extremely cheap or expensive, extremely good or bad, and the outputs can vary just as wildly.
The same problems exist when it comes to data. Too much data and you are paralysed into inaction. Not enough data and you have no choice apart from inaction (how can you – you don’t know enough).
Neither solution helps improve your assets, get people out of fuel poverty, save money or reduce the carbon footprint of your organisation.
However, there is a middle ground, a solution which can exploit your data meaningfully. Our approach to data with our customers is rather like starting a journey. We establish where you are today, where you want to go, then use our software and algorithms to help you work out the shortest route to that destination, much like your car’s sat-nav.
The process begins with understanding what records you currently hold on your portfolio. We take that data, knowing there will be blank fields (no-one has perfect data, by the way), augment it with rational, intelligent assumptions, essentially backfilling the holes, and then run the new dataset against the latest iteration of SAP.
Step 5 to exploit your assets’ Big Data: Take action
The next bit is the most important. What do you do with the data, and can you interact with it easily? Knowing you have a problem and being able to pinpoint it is only the start of the solution.
Much like an appointment with a doctor, they can only recommend that you take the prescribed medicine; actually taking the next step is harder and invariably costs more. But go to your board armed with accurate data, in an understandable format, and able to demonstrate a robust, impartial decision-making process, you’ll secure the funding and consent you need to make those improvements and meet those targets.
In summary, data can be both good and bad, but two things are certain – bad data definitely leads to bad decisions and no data equals no decisions. Only good data can enable meaningful progress.
Stewart Little is CEO of IRT Surveys.
