This article initially appeared in the January 2018 issue of Housing Technology*
In today’s interconnected digital world, housing providers’ boldest and smartest innovations are in data management, according to Thames Valley Housing and Semarchy.
Challenges in housing
What are the biggest challenges facing housing providers today? Is it keeping properties safe and residents healthy? Is it complying with government regulations? When and where to build new properties? Staying aware of commercial opportunities? Developing employee performance and leadership skills? Planning and innovating for the future?
According to a recent report from Call of the Wild, it’s all of them. In a dynamic market and interconnected digital environment where change occurs on a daily basis, housing providers need to be quick and agile, whether they’re responding to resident issues, pouring over new regulations or identifying potential revenue streams. The task is daunting, but it doesn’t need to be difficult, as long as companies understand the one key issue that underpins every single challenge - data management.
Why is data important to Thames Valley Housing?
In order to provide a smooth service for our Thames Valley Housing residents, in an environment where there are a myriad of organisations and individuals supporting them, everyone needs to be clear about the latest interaction as well as historical data, from identifying potential problems, managing repairs, communicating and implementing regulations and managing financial information. Good data management is about ensuring all that information is in one place and making sure it is up-to-date, comprehensive and interactive. At Thames Valley Housing, we manage and administer around 16,000 properties across London, Middlesex, Berkshire, Surrey, Hampshire, Oxfordshire, Buckinghamshire, Wiltshire and Sussex, and have over 1,000 properties under construction. With such a wide geographical area and huge variety of needs, we have thousands of data interactions every day. Poor management of these interactions and the data from these can lead to huge inefficiencies, high costs and dissatisfied residents. Good data management makes for successful communications for both the short and long term. That is why it is a key priority for us.
The problem of disorganised data
A few years ago, we came across a fairly common problem. Many of our estates have services delivered by management agents, and when it came to areas such as repairs we were becoming increasingly unable to understand our responsibilities versus those of our agents. When a resident noted a leaky pipe, for example, who fielded the request, who organised the repair, and who paid the cost? It was the same with a repair in a communal area; if we wanted to fold the cost into a tenant’s service charge, we had to ensure that the managing agent wasn’t responsible and therefore hadn’t already made the charge.
In both examples, it’s easy to envision the problem in human terms, as isolated issues of miscommunication and misinformation; doing so allows you to rationalise unfortunate events with the facts that everyone makes mistakes and that issues are often easily rectified. But a deeper survey revealed that these were data problems that offered no easy answers. By retracing the chain of command, we discovered that the breakdown was due to our slow and obtuse data infrastructure. Critical information got held up in the system, did not or could not reach the right person, or found its way to people unable to do anything with it. In some cases, our staff often had to manually refer to legal documentation and leases.
That’s what happens when agent responsibilities change estate by estate and recharging arrangements are equally varied. And it’s a major problem. As a recent report, ‘Crackdown on unfair managing agents’, from the Department for Communities & Local Government explained, solving a housing issue in a fair and timely manner that empowers consumers requires navigating a complex system of regulations and dealing with often illegal agent practices. In response, the DCLG plans to create a fairer property management system, which could help to reduce the £700 million-£1.4 billion that DCLG’s researchers estimated is lost every year due to superfluous service charges.
These charges are something we experienced at first-hand. Sometimes we would end up spending money on projects that were ultimately an agent’s responsibility. But the costs were broader than that. For instance, because residents would sometimes have to wait for a long time while we uncovered the responsible party, we would experience ruptures in customer service, our reputation with residents suffered, and sorting through the issue made us fall behind on internal processes such as long-term planning, something that should be totally unaffected by the repairs part of the company.
Dealing with data’s immensity
At a time when 90 per cent of all UK adults are internet users (including 83 per cent of low-income people) and 90 per cent of UK adults aged 16-75 are daily smartphone users, nearly every rule, regulation, and conversation relevant to business can and will be encoded as a bit of data. A housing provider like Thames Valley Housing collects and monitors thousands of data points each day.
They aren’t just raw, relative numbers; they are the representation of our entire organisation, from management to operations to logistics. And they have the potential to grow exponentially, as the internet of things (IoT) enables the real-time collection of data from boilers, drones and other sensors. Of course, IoT data won’t be valuable until it has surmounted the twin problems of abundance and integration with existing data architecture. To do that, housing providers will need a high level of data clarity, something that can elude systems predating the digital evolution.
For us, leveraging xDM, the cutting-edge intelligent master data management (MDM) solution from Semarchy, has allowed us to keep pace with trends and position ourselves for the future. xDM increases our flexibility by focusing on data quality as an asset. That reduces our dependency on applications (they come and go as the business needs) and increases our ability to pull out and serve up good data just in time for it to be consumed by the business.
Integral to this process is the ability in xDM to categorise data, so that essential data can be guaranteed to certain quality levels, while informal data can be dealt with more flexibly. Doing this means our business focuses on the data sets that matter without losing the ability to absorb new data quickly. It’s a boundary-pushing innovation in data architecture and governance, and the pay-offs have been enormous.
The failure of band-aid solutions
Dealing with serious data issues is tricky, because there is always tension between quick fixes and long-term solutions. Resident problems take priority, because they are issues affecting our most valuable assets. If they’re unsatisfied with anything, we want to be able to help them immediately. But we also have to be able to properly evaluate the severity and responsibility of their problem and put in place realistic expectations.
Taking short-term measures, such as adding new workflow processes, we were relatively ineffective. Agents that needed to communicate with the repairs team would often operate outside the new channels, choosing instead phone or email, as was their habit. The work got done, but we had no way to track or monitor its status, and thus no way to use that information in process evaluations and analyses. The incomplete data was like a black hole in our operations. We needed a full information overhaul that would give us a single system catering to the pan-organisation needs, such as housing officers spotting potential problems and developers predicting the optimal time and place to build a property to meet community needs.
An overhaul with MDM
Like other regulated industries (the NHS, financial services, etc.), our information framework is risk-management. ‘Getting our house in order’ initially required the establishment of a governance framework to explain how we would assess and manage information, with regard to policies, standards, procedures, taxonomies, and outputs, such as training, guides, and third-party agreements.
By creating data asset categories and assigning them owners, we were able to account for each piece of data. By prioritising data quality, we could set clear data targets, such as having email addresses for 80 per cent of our residents. This put us on the pathway to developing a ‘totalising future’ for data, meaning that there would be an information strategy for everyone in the organisation, so that responsibilities would be known, and the right person would have the right data at the right time.
This was possible because we overlaid xDM on our existing system. Doing this ensured that all business-critical data had a defined source and a clear meaning. With data ownership clearly defined and managed, we could open and close new data sets as necessary; Semarchy’s solutions are agile enough to flex as our business practices evolve. This is one of the most critical aspects of the entire overhaul; across the entire organisation, MDM became the door through which all data had to pass in order to be ordered, incur meaning, and contribute value.
With xDM in place, we have the base to pursue more sophisticated value-driven data projects, such as building a data lake, where all raw data is stored in native form with a flat architecture, rather than in files and folders of a hierarchical system, and receives a unique identifier with extended metadata tags, facilitating the easy queuing of relevant data. We can also decouple our core business systems from our data and cut down from roughly 40 applications by deploying applications across core businesses processes and a combination of software as a service (SaaS). In finance, for example, we can create one core application covering processing, ledgers, forecasting, supplier management, payments, and reporting. And for customers we can feed information through a single CRM system, consolidating contact centre automation, marketing automation, salesforce automation and customer dashboard data.
Housing data for the future
If housing providers want to succeed, they need to grasp that, in a digital world, their operational base is their MDM. Not only will it help them smooth communications with agents, but it will help them discover insights about themselves and their clients, make predictions about the future, and receive general recommendations. This can only happen, though, by embracing the latest and smartest analytics: autonomous or semi-autonomous data science. Techniques in this realm include data and text mining, machine learning, pattern recognition, and forecasting and visualisation. But, like the details of fixing a leaky pipe, they can only be effectively deployed if they have reams of clear, ordered data.
We may be drowning in data, but the answer is not to drain the ocean. It’s to learn how to swim, and get a better boat!
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