Book Review: Cervo and Allen on MDM in Practice

Henrik Gabs LiliendahlLeave a comment

Master Data Management is becoming increasingly popular and so are writing books about Master Data Management.

Last month Dalton Cervo and Mark Allen published their contribution to the book selection. The book is called “Master Data Management in Practice: Achieving True Customer MDM”.

As disclosed in the first part of the title, the book emphasizes on the practical aspects of implementing and maintaining Master Data Management and as disclosed in the second part of the title, the book focuses on customer MDM, which, until now, is the most frequent and proven domain in MDM.  

In my opinion the book has succeeded very well in keeping a practical view on MDM. And I think that limiting the focus to customer MDM supports the understanding of the issues discussed in a good way, though, as the authors also recognizes in the final part, that multi-domain MDM is becoming a trend.   

Mastering customer master data is a huge subject area. In my eyes this book addresses all the important topics with a good balance, both in the sense of embracing business and technology angels with equal weight and not presenting the issues in a too simple way or in a too complex way.  

I like how the authors are addressing the ROI question by saying: “Attempts to try to calculate and project ROI will be swag at best and probably miss the central point that MDM is really an evolving business practice that is necessary to better manage your data, and not a specific project with a specific expectation and time-based outcome that can be calculated up front”.

In the final summary the authors say: “The journey through MDM is a constantly learning, churning and maturing experience. Hopefully, we have contributed with enough insight to make your job easier”. Yep, Dalton and Mark, you have done that.

Bookmark and Share

Party On

Henrik Gabs Liliendahl2 Comments

The most frequent data domain addressed in data quality improvement and master data management is parties.

Some of the issues related to parties that keeps on creating difficulties are:

  • Party roles
  • International diversity
  • Real world alignment

Party roles

Party data management is often coined as customer data management or customer data integration (CDI).

Indeed, customers are the lifeblood of any enterprise – also if we refer to those who benefit from our services as citizens, patients, clients or whatever term in use in different industries.

But the full information chain within any organization also includes many other party roles as explained in the post 360° Business Partner View. Some parties are suppliers, channel partners and employees. Some parties play more than one role at the same time.

The classic question “what is a customer?” is of course important to be answered in your master data management and data quality journey. But in my eyes there is lot of things to be solved in party data management that don’t need to wait for the answer to that question which anyway won’t be as simple as cutting the Gordian Knot as said in the post Where is the Business.

International diversity

As discussed in the post The Tower of Babel more and more organizations are met with multi-cultural issues in data quality improvement within party data management.

Whether and when an organization has to deal with international issues is of course dependent on whether and in what degree that organization is domestic or active internationally. Even though in some countries like Switzerland and Belgium having several official languages the multi-cultural topic is mandatory. Typically in large countries companies grows big before looking abroad while in smaller countries, like my home country Denmark, even many fairly small companies must address international issues with data quality.

However, as Karen Lopez recently pondered in the post Data Quality in The Wild, Some Where …, actually everyone, even in the United States, has some international data somewhere looking very strange if not addressed properly.

Real world alignment

I often say that real world alignment, sometimes as opposed to the common definition of data quality as being fit for purpose, is the short cut to getting data quality right related to party master data.

It is however not a straight forward short cut. There are multiple challenges connected with getting your business-to-business (B2B) records aligned with the real world as discussed in the post Single Company View.  When it comes to business-to-consumer (B2C) or government-to-citizen (G2C) I think the dear people who sometimes comments on this blog did a fine job on balancing mutating tables and intelligent design in the post Create Table Homo_Sapiens.

Bookmark and Share

When a Cloudburst Hit

Henrik Gabs Liliendahl2 Comments

Some days ago Copenhagen was hit by the most powerful cloudburst ever measured here.

More powerful cloudbursts may be usual in warmer regions on the earth, but this one was very unusual at 55 degrees north.

Fortunately there was only material damage, but the material damage was very extensive. When you take a closer look you may divide the underground constructions into two categories.

The first category is facilities constructed with the immediate purpose of use in mind. Many of these facilities are still out of operation.

The second category is facilities constructed with the immediate purpose of use in mind but also designed to resist heavy pouring rain. These facilities kept working during the cloudburst. One example is the metro. If the metro was constructed for only the immediate purpose of use, being circling trains below ground, it would have been flooded within minutes, with the risk of lost lives and a standstill for months.

We have the same situation in data management. Things may seem just fine if data are fit for the immediate purpose of use. But when a sudden change in conditions hit, then you know about data quality.

Bookmark and Share

A Sudden Change: South Sudan

Henrik Gabs Liliendahl2 Comments

This tenth Data Quality World Tour blog post is about South Sudan, a new country born today the 9th July 2011.

Reference data

The term “reference data” is often used to describe small collections of data that are basically maintained outside an enterprise and being common to all organizations. A list of countries is a good example of what is reference data.

Sometimes the terms “reference data” and “master data” are used interchangeable. I started a discussion on that subject on the mdm community some time ago.

One problem with reference data as a country list is if you are able to keep such a list updated. A country list doesn’t change every day, but sometimes it actually does like today with South Sudan as a new country.  

Suddenly changing dimensions

If you have master data entities linking to reference data like a country list it is not that simple when the reference data changes. If you have a customer placed in what is South Sudan today that entity should rightfully link to Sudan regarding yesterday’s transactions, but you may also have changed the name of Sudan to North Sudan which is the continuing part of the former Sudan. 

We call that kind of challenge “slowly changing dimensions” but it actually looks like “suddenly changing dimensions” when we have to figure out who belongs to where at a certain time.

Previous Data Quality World Tour blog posts:

A pain in the …

Henrik Gabs Liliendahl1 Comment

When we move around in the traffic we may have different roles at different times. Sometimes I drive a car, sometimes I’m a pedestrian and sometimes I ride a bicycle. The traffic infrastructure tries to separate these roles by having roads for cars, sidewalks (pavements) for pedestrians and bicycle paths for bicycles. But in intersections these separations meets and creates cases of who’s to have the upper hand and sometimes all three constructions aren’t available, so pedestrians and bicycle riders may use a road made for cars.

I have just completed a short (kind of) holiday where we took our bicycles on a tour around parts of the Baltic Sea coast through four different countries: Denmark, Germany, Poland and Sweden. Our start and end was in Copenhagen, which is known for having extremely good conditions for bicycling coined by the term “Copenhagenization”.     

The quality and availability of bicycle paths varied a lot on the route. Sometimes you felt that the bicycle paths were constructed to make the life of bicycle riders as miserable as possible. When the bicycle path wasn’t there or was too bad we hit the road, which was extremely unpopular among the car drivers. Not at least German Mercedes drivers love their horns.

But I guess it’s nothing personal. When I drive my car I also think pedestrians and bicycle riders are a pain in the …

Such cases of not liking a role you have yourself at another time also applies to a lot of other situations in life. For example I’m not very excited about all the data quality checks and mandatory fields I have to deal with in the CRM system when I have sold a data quality tool or service. I see them as a pain in the …

And oh yes, after finishing the cycling tour I did have some pain…

Bookmark and Share

Psychographic Data Quality

Henrik Gabs LiliendahlLeave a comment

I have just read an article on Mashable by Jamie Beckland called The End of Demographics: How Marketers Are Going Deeper With Personal Data.

The article explains how new sources of available data makes it possible for marketers to get a much closer look at potential customers and thereby going from delivering a broad message to a huge crowd to delivering a very targeted message to a small group of people with a high probability of getting a response.  In short: Marketers are going from demographic marketing to psychographic marketing.

I believe this is true and ongoing (as I have also been involved in such activities).

The data quality issues we have always known in direct marketing is surely very similar in the psychographic marketing which is going on in the social media realm and in connection with eBusiness.

In my eyes, the concept of a single customer view is also a key to getting success in psychographic marketing.  

You are not delivering a targeted message if you are delivering two different messages to two user profiles belonging to the same real world individual.

Your message will be very frustrating if you treat someone as a prospect customer if that someone already is an existing customer perhaps in another channel.

The effectiveness of psychographic marketing depends on a match between the psychographic variables, the behavioral variables and the demographic variables. As seen in the example in the Mashable article a good old thing as geocoding will be needed here.

An exciting thing in the rise of psychographic marketing is that it will add to the trend in data quality technology where it’s much more than simple name and address cleansing and deduplication.  Rich location data will despite the virtual playground be further important. The relations between customers and products as described in the post Customer Product Matrix Management will be further refined in psychographic marketing.       

Bookmark and Share

Timing Your Social Media Activity

Henrik Gabs LiliendahlLeave a comment

When engaging in social media I often consider what time and what day to publish a new blog post, tweeting about it and promoting it on LinkedIn.

My audience is roughly distributed as 40 % Americas (almost all in North America), 40 % EMEA (almost all in Europe) and 20 % Asia and Pacifics.

That makes it a pretty much around the clock audience with a peak in page views and comments between UTC 14:00 and 17:00, which is when the working day in Europe is still on and the Americans are waking up.  However that doesn’t necessary mean that I should publish in the peak hours. In fact I haven’t been able to measure that the time of publishing affects number of page views and comments. So I’ll keep on publishing at the time I have anything to say and have the time to write about it.

If I look at weekdays working days are double as busy as weekends with Monday as best day probably catching up with people that don’t do social media in weekends. So I’ll keep on publishing at the days I have anything to say and feel inspired to write about it.

Bookmark and Share

Howcatchem

Henrik Gabs Liliendahl3 Comments

I’m sad to learn that Peter Falk has died. Peter Falk is most known as Lieutenant Columbo in the American television series Columbo, which has been shown all over the world including in my country when I was a teenager.

I think Columbo would have been a great data quality specialist too. Underestimated by the smart guys but focused on the important details while exercising the art of “howcatchem”. Opposite to his “whodunit” colleagues who are sitting on a horseback chasing the villains down a crowded city street or doing the same in a car while smashing most other cars on the way.

Bookmark and Share

Data Quality as Competitive Advantage

Henrik Gabs Liliendahl13 Comments

I always wanted to make the above headline, but unfortunately one of the hardest things to do is documenting the direct link between data quality improvement and competitive advantage. Apart from the classic calculation of the cost of returned direct mails most other examples have circumstantial evidences, but there is no smoking gun.

Then yesterday I stumbled upon an example with a different angle. A travel company issued a press release about that new strict rules requires that your name on the flight ticket have to be exactly spelled the same and hold the same name elements as in your passport. So if you made a typo or missed a middle name on your self registration you have to make a correction. Traditional travel companies do that for free, but low-cost airlines may charge up to 100 Euros (often more than the original ticket price) for making the correction.

So traditional travel companies invokes a competitive advantage in allowing better data quality – and the low-cost airlines are making profit from bad data quality.  

Bookmark and Share

History of Data Quality

Henrik Gabs Liliendahl4 Comments

When did the first data quality issue occur? Wikipedia says in the data quality article section titled history that it began with the mainframe computer in the United States of America.

Fellow data quality blogger Steve Sarsfield made a blog post a few years ago called A Brief History of Data Quality where it is said “Believe it or not, the concept of data quality has been touted as important since the beginning of the relational database”.

However, a predominant sentiment in the data quality realm is that data quality is not about technology. It is about people. People are the sinners of data quality flaws and as the main part of the problem people should also be the overwhelming part, if not the only part, of the solution.

So I guess data quality challenges were introduced when people showed up in the real world. How and when that happened is a matter of discussion as discussed in the blog post Out of Africa.

As explained in the post Movable Types the invention of movable types in printing some hundreds of years ago (the most important invention since someone invented the wheel for the first time) made a big boost in knowledge sharing among people – and also a big boost in data and information quality issues.

But I think the saying “To err is human, but to really foul things up you need a computer” is valid. Consequently I also think you may need a computer to help with cleaning up the mess and to prevent the mess from happening again. End of (hi)story.    

Bookmark and Share