Many in the Scottish housing community will be looking forward to the 31st May with a combination of apprehension and anticipation. As many will be all too well aware, that is the deadline for landlords to submit their Annual Return on the Charter (ARC) submissions to the Scottish Housing Regulator. Providing sound data will ensure that the Regulator can make the most accurate assessment of performance and risk.

But what makes good quality data? The Global Fund (an international partnership fighting Aids, tuberculosis and malaria in low-income countries, with an annual budget of $4 billion) suggests that data quality may be boiled down to seven key elements. In simplified terms, these elements can be summarised as follows:

1) Accuracy – Is the data measuring what it is supposed to?

2) Reliability – Is the data measured and reported in a systematic way?

3) Completeness – Does the data cover all relevant housing units?

4) Timeliness – Is the data up-to-date?

5) Precision – Is the data available at the right level of detail?

6) Integrity – Are there systems in place to ensure figures cannot be deliberately manipulated?

7) Confidentiality – Are the personal details of tenants and staff protected?

In relation to accuracy, it’s crucially important to check the Scottish Housing Regulator’s own performance indicator definitions – or those provided by whichever body you are reporting to. This includes making sure you are aware of any changes to these since the last time you submitted a return. It’s equally important to make sure that your data is entered accurately and is completely free of errors, biases or typos.

To ensure the reliability of your data, you also need to have robust systems in place to maintain absolute consistency irrespective of who prepares the figures.

With data systems and processes that fulfil these criteria, landlords can take confidence that the chances of errors are minimised. Yet, with the best will in the world, sometimes mistakes can happen, as illustrated by the volume of amendments that get made to ARC submissions each year. Last year, for instance, there were a total of 252 corrections made to the numeric values originally submitted to the Scottish Housing Regulator.

Validation has a crucially important role to play in keeping the number of returns that have to be subsequently corrected to an absolute minimum. By validating the dataset both internally (that is, sense-checking both within and across variables) and externally (i.e. by comparing the data against current and historic data from peer group organisations), any anomalies are more likely to be identified prior to submission. Adding a further quality assurance step, with an in-depth review by a fresh pair of eyes, provides a robust triple-layer approach to validation.

While it is vital that data submitted to the SHR is as water-tight as possible, in other situations a degree of pragmatism may be appropriate. A question one might ask, therefore, is: “is this data fit for purpose?”. I recall the advice of a statistics consultant with whom I worked in Nepal. He passed on a rule-of-thumb that had been developed in the (highly reputable) institution at which he had worked for many years: typically 80% of data is sound, 10% is questionable and 10% is rubbish. The focus should be on addressing the problematic 20%, to bring it (if possible) to the necessary quality for the intended purpose. This should certainly be the case where data will be reported externally. However, if the figures will merely be used for a quick-and-dirty analysis for internal use only, perhaps that 80% may be good enough while at the same time making sure to establish appropriate caveats about any potential issues with the quality of the data being used.

Ultimately, it’s worth remembering why we collect and analyse data in the first place. In the words of Charles Babbage, the inventor of the first mechanical computer: “errors using inadequate data are much less than those using no data at all”.

If you’re currently in the process of preparing your own organisation’s data for this year’s ARC submission, I hope that you are on track to submit a return that is both accurate and on time. By ensuring that data is produced right in the first instance, you and your organisation will save time and effort. Good luck!

Russell Young is data services manager at HouseMark Scotland