Light Specific Data

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I remember many years ago reading VS Naipaul’s “A house for Mr Biswas”. It’s a recognised classic, a tale of a Hindu Indian with a small disability, trying to fit in the community of rural Trinidad and Tobago. I recommend it, a brilliant and insightful book, that was acclaimed world-wide.

Early in the novel, Mr Biswas sets out to acquire a home library to appear well-read and intelligent. To do so, he orders x feet of book. He doesn’t particularly care what the books are, but he builds a library for himself.

The character collects books like many organisations collect data.  

I have met many people in organisations, who are more focussed at time on the quantity of data we have, rather than the quality of it. Often its very burdensome to look too deeply into our data. Its expensive and often irritating to have to fix it. No wonder many obsess about the abstract concept of big data, most of us have not actually cracked small data yet.

I have met many ICT and data professionals, who have tried to make improving data quality their aim. Personally I have been there myself, creating exception reports and generating automated prompts, in order to flag up issues to staff before they become much bigger data problems. They like me I think were all universally hated, and referred to at times, to be the data police! It’s a moniker I can live with, and deep down I know good quality data, leads to better decisions.

How often do you and your organisation question your data quality? Only on one occasion in my career, have I seen an organisation underline the importance of data to staff on a full day of presentations. Everyone should try it.

How often in particular, are staff involved in :-

• Inaccurate data
• Incomplete data. If data is incomplete, organisations may make decisions based on a false understanding of the situation.
• Outdated data: If data is not kept up-to-date, organisations may make decisions based on out of date information. This can lead to missed opportunities or a failure to identify new trends
• Lack of data standardization: Poor data quality can also be caused by a lack of data standardization, which makes it difficult to compare and combine data from different sources. This can lead to confusion and mistakes in decision making.
• Inconsistency in data: Inconsistency in data can lead to difficultly in tracking progress and identifying areas for improvement, which can lead to poor decision making.

Lets think now about the last time you spotted a data anomaly.

I have discovered many when migrating data from one system to another. Often systems are patched historically and data left incorrect in-situ. Data migrations do tend to flush a lot of this out. One example I saw around this involved car-port assets that were thought deleted seven years back. We had to reinstate them as historic data referred and related to them. Watch out for this yourself.

Another lovely data story I remember was from a West Midlands socialhousing landlord. I cannot actually remember what I was on-site doing, but I was asked if I could do my client a favour. I try to be a helpful bloke, so yes, I would always try my best to help, even if it caused me to miss my lunch!

What they were looking to do is mailshot/SMS txt all their live tenants over the age of 65. Quite an easy query in most integrated housing systems, (if you can avoid any Mr Void’s in one particular one, I am not so rude to highlight – but you guys know who you are!). My SQL query was soon done and its results dropped into Excel. (Not a database itself, before you ask!).

Now many people would have surely stopped there, passed the list and maybe the query on and cracked on with my lunch BLT. Being me I just thought I would check the sensibility of what was being pulled out, based on Dates of Birth. It was then that I wondered if I had made a serious scientific discovery, or was just looking at some dodgy data. I discovered that over a hundred of their tenants were over 1,000 years old. Digging further, they all lived in a place called Tipton.

I had never been to Tipton at that point, and wondered if it might be one of those types of communities you read about in Japanese islands or Southern Greece, for extraordinary life expectancy. Since then I have visited Mad O'Rourke's Pie Factory, in Hurst Ln (on my birthday actually, a few years back and it was bostin, although thankfully not the 4lb Desperate Dan Cow pie), so I was in no doubt that life expectancy, could well be nearer the west Midlands average in Tipton town.

The sad truth was that the DOBs were habitually entered incorrectly in the RSLs old Tipton Office, and never challenged or corrected. So I had to cancel David Attenborough and the film crew, it was just sh*t data, that could be easily corrected by a temp.

Its not just old people with poor data that we need to concern ourselves with, the young-uns can be problematic too. At another big West Midlands RSL, I looked into a problem with residents being button-holed by DLO staff to provide satisfaction feedback, but it was often residents still of school age. A great story for the Wolverhampton based Express & Star, although on investigation a lot of resident data was being incorrectly recorded, including tenant ages (defaulting to 0, as DOB could be entered as today) and the wrong household member being flagged as the ‘main’ resident.

Once pinned down to a couple of housing staff requiring some training, plus a regular report to flag them to fix them all, the problem was no more. In this last case, the problem was causing the DLO issues, and had a source right back when the tenancy was set up. Be aware of this type of thing. Often one dept needs to ‘take one’, for the wider team, which isn’t always an easy sell.

Anyway, the thought I would like to leave you with, is that we all need to really doubt all our data, all the time. Take ownership of it and how it should be fixed. Then keep fixing it!

At some point, being aware of the above and putting this into practice, your data will take you and your tenants to a better future.

If we at Acutance Consulting can help your organisation with data issues, 

please just get in touch, for a friendly chat over a brew & a macaroon ☕😋.

       Related Post: Data is bad enough, but what dodgy software have you lurking in your systems too? 

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I would be pleased to connect with you on LinkedIn - http://uk.linkedin.com/in/tonysmiththathousingitguy Message me with any issues or queries, you would like to be explored in this blog. We generally receive a couple of suggestions each month.

Hawkwind - Light Specific Data.
(c) Tony Smith, Acutance Consulting www.acutanceconsulting.co.uk 07854-655009


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