Today, here in the UK we have one those rainy, grey, gloomy days (what some might say as typically, but that’s not the case)…moods range from ‘oh dear’ to ‘must book my sunny holiday!’
Well, things didn't get any better when the post arrived…solving client data everyday makes me over critical about others’ data, a feeling of incredulity runs through every cell in my body when I see my name absolutely mangled on this envelope.
Not going to mention any company names, but this a rather large UK telecoms company…who are probably spending a fair size budget on data quality.
I've scanned the offending envelope so you can see…
Now, my name is Anish Raivadera
As you can see on the image, there are some errors:
1. I now have a middle name and that’s my first name as well!
2. I also have a prefix to my name, the number one, same as my house number (coincidence? probably not)
3. They have used my first name enough times, but not to be put off, a second line with ‘care of’ is introduced with my first name again!
4. Lastly another new surname ‘Ra’ on the second line
Anyone who knows about systems will recognise that this takes some doing…it’s very unlikely someone entered the information this way.
I’ve been a customer of theirs for years!
Now here’s my take on this…
- Lots of companies spend money on data management, data quality, data cleansing…but the bigger they are they more problems they have
- Large companies are faced with many systems and data needs to be fed between them, and there is a lot of room for error
- The number of times I have heard ‘we spent millions on a data quality, but it does not really improve the quality’ is too many too mention
Let me qualify…this is not all big companies, but certainly quite a few.
Often the need to have a data quality system focuses on complex IT infrastructure requirements rather than the actual quality of data.
Obviously, you do need the right infrastructure to fit into your company, but more focus is needed on the actual quality.
It’s not about the infrastructure, it’s about the methodology. Understanding how data is corrupted, how it can be measured and how it can be fixed.
Rather than spending millions on the IT and a small fraction on data, they should immediately increase their budgets to warrant the importance of that data.
This company may potentially lose a loyal customer…but I’m not the only one this is happening to, I’m sure the systems defects are affecting many.
For me, this comes under the heading of Reputation Risk. Bad data is only going to hurt you.