I was reading an interesting blog post from Ben Gallagher discussing where bad data comes from. He listed six very sensible ways that bad data is getting into your systems, and how to prevent that; then included a seventh: Lazy customers.
Customers are regularly accused of deliberate sabotage, with malice aforethought. They enter wrong information, in the wrong places, in the wrong format. They skip information. They ensure that duplicates appear in databases, that their information can’t be found and that a single view of that customer can’t be created. They use different email addresses just to confuse us, and they’re so pushed for time that they try every trick to confound our plans to collect their data.
There’s no doubt that some customers will deliberately use false data, especially when an organisation is trying to get data from them for which they see no relevance – remember, this data is the customer’s to give, not an organisation’s by right. So asking for a telephone number, for example, when you’re inviting the customer to subscribe to an e-mailed newsletter, will result in a high level of fake data – unless you use phone validation of course.
But customers do usually take care when providing information which is required, and when the reason is clear – a postal address when purchasing online, or an email address when subscribing to a newsletter. And, as it’s their data, they’ll usually know what it consists of and how to format it. What the customer cannot know, though, or can really be expected to care about, is how your online forms work and what your back-end databases expect to receive. They don’t know and don’t care that you expect a building number in one field and not in another, or that you want telephone numbers without spaces but postal codes with spaces and in upper case. When customers are expected by businesses to have the same computer code running through their heads as the company has working behind data entry forms, they’re bound to disappoint and receive all the blame for the poor data collected as a consequence.
Pointing the Finger
Without exception poor data quality is the result of poor design, poor programming, poor planning and poor processes on behalf of the organisation. When data entry forms, for whatever purpose, are properly designed, with the least burden of quality placed on the customer; requiring the least amount of work to complete, with the correct fields in the correct order for the customer concerned, and with validation and verification systems in place to catch the maximum number of errors, the data quality increases and the need to blame the customer disappears.
If you’re still blaming the customer for your poor data quality, it’s time to step back and take a look at your own business processes. Blaming the customer is a cop out and needs to stop.