It seems weird to describe data has having a personality, can’t think of anything more non-personal than pure data; but looking at data for so many companies over the years, you can’t help but notice that ‘data takes on the personality of the company’.
Where a company is unclear or disorganised (for whatever reasons), data is overlooked or token efforts are made to improving the data.
In management terms, you here the phrase ‘how you do anything, is how you do everything’, and that seems to be the case with data.
Let me explain a bit more.
Each company’s data has patterns in terms of quality. Some are patterns of poor quality and some are patterns of good quality replicated throughout their databases.
The patterns are the personality.
The patterns are a result of:
- Their systems; and/or
- Their attitude towards data
Let’s look at these two in a bit more detail.
A good system will think primarily about its users. In terms of data, data entry capabilities and reporting are key features for a successful implementation.
Both of these can be enhanced or diminished by the system.
If systems are developed well, then more often than not, careful consideration has been given to the quality of data. Now, there are many data operations to think about, but the two most important operations are Data Entry and Data Matching.
If the system does everything it can do to capture data correctly while considering who is, when, why and what is being captured, then you have done the best you can in ensuring the systems help capture data accurately.
It’s not just about data entry, it’s also about how the data is moved through the organisation. Data often resides in multiple data sources (the terms ‘upstream’ or ‘downstream’ are used to denote the position of the data in relation to its life cycle).
At some point the data has to be matched to create accurate views. Matching requires extreme care because for certain organisations, matching incorrectly can cause huge legal and operational issues.
Hence, a good attitude to developing systems well, will naturally lead to thinking about data and how users can benefit.
So, when I see some data, you can quickly and accurately guess what their systems are like, and guess how the systems were developed in the first place.
You can also postulate how the systems are affecting data entry.
Their Data Attitudes
Some companies care passionately about their data, others don’t understand the need to care about their data at all, most reside somewhere in the middle.
Where care is taken:
- You will see users having confidence in their data
- You will see better quality reporting and decision making
- For marketing data, you will see better Marketing ROI
- You will have a professional data supplier helping them
- You will see regular cleansing and data entry training
Where care is not taken:
- You will see multiple disparate sources of data
- You will have poor data entry procedures or none at all
- You will see users complaining about their data
- You will see a constant need to buy more data rather than manage what’s already there
- You will see very little data cleansing
Just by looking at an organisation's data, you get a feeling straight away about how they work internally.
I’m not expecting every company to be perfect, but you just get a general sense of how things may be.
Make sure your data is managed and measured; user confidence and results will be significant.
If you are responsible for data, if you haven't done so already, put in place those procedures you need to have great data - you will certainly see the upsides.