Tag Archives: address
Murphy’s First Law of Bad Data – If You Make A Small Change Without Involving Your Client – You Will Waste Heaps Of Money
I have not used my personal encounter with bad data management for over a year but a couple of weeks ago I was compelled to revive it. Why you ask? Well, a complete stranger started to receive one of my friend’s text messages – including mine – and it took days for him to detect it and a week later nobody at this North American wireless operator had been able to fix it. This coincided with a meeting I had with a European telco’s enterprise architecture team. There was no better way to illustrate to them how a customer reacts and the risk to their operations, when communication breaks down due to just one tiny thing changing – say, his address (or in the SMS case, some random SIM mapping – another type of address).
In my case, I moved about 250 miles within the United States a couple of years ago and this seemingly common experience triggered a plethora of communication screw ups across every merchant a residential household engages with frequently, e.g. your bank, your insurer, your wireless carrier, your average retail clothing store, etc.
For more than two full years after my move to a new state, the following things continued to pop up on a monthly basis due to my incorrect customer data:
- In case of my old satellite TV provider they got to me (correct person) but with a misspelled last name at my correct, new address.
- My bank put me in a bit of a pickle as they sent “important tax documentation”, which I did not want to open as my new tenants’ names (in the house I just vacated) was on the letter but with my new home’s address.
- My mortgage lender sends me a refinancing offer to my new address (right person & right address) but with my wife’s as well as my name completely butchered.
- My wife’s airline, where she enjoys the highest level of frequent flyer status, continually mails her offers duplicating her last name as her first name.
- A high-end furniture retailer sends two 100-page glossy catalogs probably costing $80 each to our address – one for me, one for her.
- A national health insurer sends “sensitive health information” (disclosed on envelope) to my new residence’s address but for the prior owner.
- My legacy operator turns on the wrong premium channels on half my set-top boxes.
- The same operator sends me a SMS the next day thanking me for switching to electronic billing as part of my move, which I did not sign up for, followed by payment notices (as I did not get my invoice in the mail). When I called this error out for the next three months by calling their contact center and indicating how much revenue I generate for them across all services, they counter with “sorry, we don’t have access to the wireless account data”, “you will see it change on the next bill cycle” and “you show as paper billing in our system today”.
Ignoring the potential for data privacy law suits, you start wondering how long you have to be a customer and how much money you need to spend with a merchant (and they need to waste) for them to take changes to your data more seriously. And this are not even merchants to whom I am brand new – these guys have known me and taken my money for years!
One thing I nearly forgot…these mailings all happened at least once a month on average, sometimes twice over 2 years. If I do some pigeon math here, I would have estimated the postage and production cost alone to run in the hundreds of dollars.
However, the most egregious trespass though belonged to my home owner’s insurance carrier (HOI), who was also my mortgage broker. They had a double whammy in store for me. First, I received a cancellation notice from the HOI for my old residence indicating they had cancelled my policy as the last payment was not received and that any claims will be denied as a consequence. Then, my new residence’s HOI advised they added my old home’s HOI to my account.
After wondering what I could have possibly done to trigger this, I called all four parties (not three as the mortgage firm did not share data with the insurance broker side – surprise, surprise) to find out what had happened.
It turns out that I had to explain and prove to all of them how one party’s data change during my move erroneously exposed me to liability. It felt like the old days, when seedy telco sales people needed only your name and phone number and associate it with some sort of promotion (back of a raffle card to win a new car), you never took part in, to switch your long distance carrier and present you with a $400 bill the coming month. Yes, that also happened to me…many years ago. Here again, the consumer had to do all the legwork when someone (not an automatic process!) switched some entry without any oversight or review triggering hours of wasted effort on their and my side.
We can argue all day long if these screw ups are due to bad processes or bad data, but in all reality, even processes are triggered from some sort of underlying event, which is something as mundane as a database field’s flag being updated when your last purchase puts you in a new marketing segment.
Now imagine you get married and you wife changes her name. With all these company internal (CRM, Billing, ERP), free public (property tax), commercial (credit bureaus, mailing lists) and social media data sources out there, you would think such everyday changes could get picked up quicker and automatically. If not automatically, then should there not be some sort of trigger to kick off a “governance” process; something along the lines of “email/call the customer if attribute X has changed” or “please log into your account and update your information – we heard you moved”. If American Express was able to detect ten years ago that someone purchased $500 worth of product with your credit card at a gas station or some lingerie website, known for fraudulent activity, why not your bank or insurer, who know even more about you? And yes, that happened to me as well.
Tell me about one of your “data-driven” horror scenarios?
In contrast to addressing the management and process issues, we might say that the technical issues are actually quite straightforward to address. In my original enumeration from a few posts back, I ordered the data issue categories in the reverse order of the complexity of their solution. Model and information architecture problems are the most challenging, because of the depth to which business applications are inherently dependent on their underlying models. Even simple changes require significant review to make sure that no expected capability is inadvertently broken. (more…)
Coincidentally, my company is involved with a number of different customers who are reviewing the quality criteria associated with addresses. Each scenario has different motivations for assessing address data quality. One use case focuses on administrative management – ensuring that things that need to happen at a particular location have an accurate and valid address. A different use case considers one aspect of regulatory compliance regarding protection of private information (since mail delivered to the wrong address is a potential exposure of the private information contained within the envelope). Another compliance use case looks at timely delivery of hard copy notifications as part of a legal process, requiring the correct address. (more…)
In my recent series of posts, I have been noodling on the differences between the concept of an “address,” which implies delivery, and “location,” which provides a much broader view of geographic points in space that have relevance to business or operational activities. In my last post, we looked at the characteristics of each of these concepts and some critical differences.
And to continue those thoughts, as opposed to the level of precision provided by location coordinates, there is lingering ambiguity associated with addresses. For example, with a residential address, we could be talking about any of these points:
- The location of the mail drop;
- The location of the front door;
- The location of the front of the driveway;
- The median point of the parcel frontage; or
- The center of the rooftop,
among other potential places. But, as my last set of posts was intended to highlight, there is great importance of high quality location information, and a good starting point is address standardization and cleansing. You need to be able to resolve known addresses into precise locations as well as map locations to their nearest addresses. Yet many organizations don’t have any handle on their own address standardization and cleansing strategy. It might be worth a quick scan and see how many different address cleansing tools are in place, how many people are assigned to manage those tools, and the many different sets of rules used in different business processes. Any replication of utility or functionality might be a sign that it is time to revisit that address cleansing strategy from an enterprise standpoint and standardize on one framework to reduce complexity and duplicative work.
In my last post, I introduced the notion that the persistence and/or use of location data as attribution is becoming ubiquitous. Whether we look at the stand-alone GPS devices that decorate the array of windshields across the parking lot or the capabilities typically embedded within our mobile telephones, precise location is, to some extent, overtaking the concept of “address.”
And perhaps there is some value to increasing the use of dimensional coordinates in lieu of an address. As I commented in my previous post, there are still many situations where errors or flaws in location information lead to business impacts. A common example involves marketing or sales mailings – incorrect delivery addresses increase costs when mailings or catalogs are sent to nondeliverable or incorrect addresses. (more…)