Most Times the Home Team Wins

25th May 2012

This summer is going to be huge if you like sports. The Olympics is coming to London and only 14 days away from now we have the European football (soccer) championship in Poland and Ukraine.

As usual hopes are high for the England soccer team. But statistics doesn’t support the hopes. The England team haven’t really succeeded since the World Cup victory on home ground at Wembley in 1966. That victory was mainly (and now I’m going to be shot in the streets of London) due to a ghost goal.

In business, and in data quality and MDM business too, the home team usually also wins.

Yesterday I noticed a tweet telling that the MDM tool vendor Orchestra Network has been selected as tool vendor by a large bank. The bank is Credit Agricole, a big financial service provider based in France. Orchestra Networks is also based in France. A home win so to say.

In the post The Pond it was told how else dominating American tool vendors may in the first place succeed in expansion to Europe by coming to London, but in fact having a hard time competing in continental Europe due to diversity issues.

European tool vendors going to North America often tries to disguise as a home team. Orchestra Network for example uses Boston & Paris as place of origin in the messaging. Other examples are the leading open source data management tool vendor Talend with dual head quarter in Paris and California, hot Danish MDM vendor Stibo Systems messaging out of Atlanta and the Swedish business intelligence success QlikTech who officially has moved to Pennsylvania.

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Posted by Henrik Liliendahl Sørensen

MDM Summit Europe 2012 Preview

17th April 2012

I am looking forward to be at the Master Data Management Summit Europe 2012 next week in London. The conference runs in parallel with the Data Governance Conference Europe 2012.

Data Governance

As I am living within a short walking distance of the venue I won’t have so much time thinking as Jill Dyché had when she recently was on a conference within driving distance, as reported on her blog post After Gartner MDM in which Jill considers MDM and takes the road less traveled. In London Jill will be delivering a key note called: Data Governance, What Your CEO Needs to know.

On the Data Governance tracks there will be a panel discussion called Data Governance in a Regulatory Environment with some good folks: Nicola Askham, Dylan Jones, Ken O’Connor and Gwen Thomas.

Nicola is currently writing an excellent blog post series on the Six Characteristics Of A Successful Data Governance Practitioner. Dylan is the founder of DataQualityPro. Ken was the star on the OCDQblog radio show today discussing Solvency II and Data Quality.

Gwen, being the founder of The Data Governance Institute, is chairing the Data Governance Conference while Aaron Zornes, the founder of The MDM Institute, is chairing the MDM Summit.

Master Data, Social MDM and Reference Data Management

The MDM Institute lately had an “MDM Alert”  with Master Data Management & Data Governance Strategic Planning Assumptions for 2012-13 with the subtitle: Pervasive & Pandemic MDM is in Your Future.

Some of the predictions are about reference data and Social MDM.

Social master data management has been a favorite subject of mine the last couple of years, and I hope to catch up with fellow MDM practitioners and learning how far this has come outside my circles.

Reference Data is a term often used either instead of Master Data or as related to Master Data. Reference data is those data defined and initially maintained outside a single enterprise. Examples from the customer master data realm are a country list, a list of states in a given country or postal code tables for countries around the world.

The trend as I see it is that enterprises seek to benefit from having reference data in more depth than those often modest populated lists mentioned above. In the customer master data realm such big reference data may be core data about:

  • Addresses being every single valid address typically within a given country.
  • Business entities being every single business entity occupying an address in a given country.
  • Consumers (or Citizens) being every single person living on an address in a given country.

There is often no single source of truth for such data.

As I’m working with an international launch of a product called instant Data Quality (iDQ™) I look forward to explore how MDM analysts and practitioners are seeing this field developing.

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Posted by Henrik Liliendahl Sørensen

Broken Links

3rd March 2012

When passing the results of data cleansing activities back to source systems I have often encountered what one might call broken links, which have called for designing data flows that doesn’t go by book, doesn’t match the first picture of the real world and eventually prompts last minute alternate ways of doing things.

I have had the same experience when passing some real (and not real) world bridges lately.

The Trembling Lady: An Unsound Bridge

When walking around in London a sign on the Albert Bridge caught my eye. The sign instructs troops to break steps when marching over.

In researching the Albert Bridge on Wikipedia I learned that the bridge has an unsound construction that makes it vibrate not at least when a bunch of troops marches across in rhythm. The bridge has therefore got the nickname “The Trembling Lady”.

It’s an old sign. The bridge is an old bridge. But it’s still standing.

The same way we often have to deal with old systems running on unstable databases with unsound data models. That’s life. Though it’s not the way we want to see it, we most break the rhythm of else perfectly cleansed data as discussed in the post Storing a Single Version of the Truth.  

The Øresund Bridge: The Sound Link

The sound between the city of Malmö in Sweden and København (Copenhagen) in Denmark can be crossed by the Øresund Bridge. If looking at a satellite picture you may conclude that the bridge isn’t finished. That’s because a part of the link is in fact an undersea tunnel as told in the post Geocoding from 100 Feet Under.

Your first image about what can be done and what can’t be done isn’t always the way of the world. Dig into some more sources, find some more charts and you may find a way.

However, life isn’t always easy. Sometimes charts and maps can be deceiving.

Wodna: The Sound of Silence.

As reported in the post Troubled Bridge over Water I planned a cycling trip last summer. The route would take us across the Polish river Świna by a bridge I found on Google Maps.

When, after a hard day’s ride in the saddle, we reached the river, the bridge wasn’t there. We had to take a ferry across the river instead.

I maybe should have known. The bridge on the map was named Wodna. That is Polish for (something with) water.

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Posted by Henrik Liliendahl Sørensen

Turning a Blind Eye to Data Quality

19th February 2012

The idiom turning a blind eye originates from the sea battle at Copenhagen where Admiral Nelson ignored a signal with permission to withdraw by raising the telescope to his blind eye and say “I really do not see the signal”.

Nelson went on and won the battle.

As a data quality practitioner you are often amazed by how enterprises turns the blind eye to data quality challenges and despite horrible data quality conditions keeps on and wins the battle by growing as a successful business.

The evidence about how poor data quality is costing enterprises huge sums has been out there for a long time. But business success are made over and again despite of bad data. There may be casualties, but the business goals are met anyway. So, the poor data quality is just something that makes the fight harder, not impossible.

I guess we have to change the messaging about data quality improvement away from the doomsday prophesies, which make decision makers turn a blind eye to data quality challenges, and be more specific on maybe smaller but tangible wins where data quality improvement and business efficiency goes hand in hand.        

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Posted by Henrik Liliendahl Sørensen

Search and if you are lucky you will find

9th February 2012

This morning I was following the tweet stream from the ongoing Gartner Master Data Management (MDM) conference here in London, when another tweet caught my eyes:

 

This reminded me about that (error tolerant) search is The Overlooked MDM Feature.

Good search functionality is essential for making the most out of your well managed master data.

Search functionality may be implemented in these main scenarios:

Inside Search

You should be able to quickly find what is inside your master data hub.

The business benefits from having fast error tolerant search as a capacity inside your master data management solution are plenty, including:

  • Better data quality by upstream prevention against duplicate entries as explained in this post.
  • More efficiency by bringing down the time users spends on searching for information about entities in the master data hub.
  • Higher employee satisfaction by eliminating a lot of frustration else coming from not finding what you know must be inside the hub already.

MDM inside search capabilities applies to multiple domains: Party, product and location master data.

Search the outside

You should be able to quickly find what you need to bring inside your master data hub.

Data entry may improve a lot by having fast error tolerant search that explores the cloud for relevant data related to the entry being done. Doing that has two main purposes:

  • Data entry becomes more effective with less cumbersome investigation and fewer keystrokes.
  • Data quality is safeguarded by better real world alignment.

Preferably the inside and the outside search should be the same mash-up.

Searching the outside is applies especially to location and party master data.

Search from the outside

Website search applies especially to product master data and in some cases also to related location master data as described in the post Product Placement.

Your website users should be able to quickly find what you publish from your master data hub be that description of physical products, services or research documents as in the case of Gartner, which is an analyst firm.

As said in the tweet on the top of this post, (good) search makes the life of your coming and current customers much easier. Do I need to emphasize the importance of good customer experience?

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Posted by Henrik Liliendahl Sørensen

Extreme (Weather) Information Quality

5th February 2012

This morning I had my scheduled train journey from London, UK to Manchester, UK cancelled.

It’s not that I wasn’t warned. The British press has been hysterical the last days because temperature was going to be below freezing and some snowfall was expected. For example BBC had a subject matter expert in the studio showing how to pack the trunk of your car with stuff feasible for a trip across the North Pole.

Anyway, encouraged by that the train was set to go on the online status I made my way to Euston Station, where I was delighted to see the train was announced for none delayed departure on the screen there. Only to be very disappointed by the message, 10 minutes after scheduled departure, saying that the service was cancelled “due to the severe weather conditions”.

Well, well, well. The temperature is above freezing this lovely Sunday morning. There is practically no wind and only some watery remains of tonight’s snowfall on the ground. With that interpretation of the raw data I guess you couldn’t go around in Scandinavia a considerable part of the year.

But that is how it is when making raw data into information. Different results indeed.

I guess it is good business for Virgin Train not to be prepared for a little bit of snow when operating in England thus making the first sign of the white fluffy stuff from above being “severe weather conditions”.

My next business analysis with Virgin Train will be targeting at the refund procedure. Hope the customer experience will be just fine.

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Posted by Henrik Liliendahl Sørensen

Multi-Occupancy

26th January 2012

The fact that many people doesn’t live in a single family house but live in a flat sharing the same building number on a street with people living in other flats in the same building is a common challenge in data quality and data matching.

The same challenge also applies to companies sharing the same building number with other companies and not to say when companies and households are in the same building. So this is a common party master data issue.

Address verification and geocoding is seen as important methods for achieving data quality improvement related to the top data quality pain all over being quality of party master data and aiming at getting a single customer view.

Multi-occupancy is a pain in the (you know) getting there.

My pain

I have had some personal experiences living at multi-occupancy addresses lately.

One and a half years ago I was living a painless life in single family house in a Copenhagen suburb.

Then I moved closer to downtown Copenhagen in a flat as mentioned in post Down the Street.     

The tradition in Denmark is to send letters and make deliveries and register master data with a common format of units within a building and having separate mailboxes with flat ID and names for each flat. I have received most of my post since then and got all deliveries I’m aware of.

Then I moved to London in a flat. Here the flats in my building have numbers. But the postman delivers the letters in one batch in the street door, and there are no names on the doorbells in front of the door.

So now I sense I don’t get many letters and today I had to order the same stuff trice from amazon.co.uk, because I haven’t received the first two packages despite of their state of the art online accessible package tracking systems that tells me that delivery was successful.    

Master data pains unresolved

Address reference data at building number level and related geocodes are becoming commonly available many places around these days.

But having reference data and real world aligned location and related party master data at the unit level is still a challenge most places. Therefore we are still struggling with using address verification and geocoding for single customer view where a given building number has more than a single occupancy.

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Posted by Henrik Liliendahl Sørensen

Nationally International

29th October 2011

I am right now in the process of moving most of my business from the Kingdom of Denmark to the United Kingdom.

During that process I have become a regular customer at the Gatwick Express, the (sometimes) fast train going from London’s second largest airport to central London.

When buying tickets online they require you to enter a billing address. Here you can choose between entering a UK address or an international address.

If you enter a UK address the site takes advantage of the UK postal code system where you just have to enter a postcode, which is very granular in the UK, and a house number, and then the system will know your address.

Alternatively you can choose to enter an international address. In that case you will get a form with more fields for you to enter. But, in order not to be too international the form still have the UK way of formatting an address.

Also the default country is United Kingdom which I guess is the only value that should not be applicable for this form.

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Posted by Henrik Liliendahl Sørensen

The Pond

1st October 2011

The term ”The Pond” is often used as an informal term for the Atlantic Ocean, especially the North Atlantic Ocean being the waters that separates North America and Europe.

Within information technology and not at least my focus areas being data quality and master data management there is a lot of exchange going on over the pond as European companies are using North American technology and sometimes vice versa. Also European companies are setting up operations in North America and of course also the other way around.

Some technologies works pretty much the same regardless of in which country it is deployed. A database manager product is an example of that kind of technology. Other pieces of software must be heavily localized. An ERP application belongs to that category. Data quality and master data management tools and implementation practice are indeed also subject to diversity considerations.

When North American companies go to Europe my gut feeling is that an overwhelming part of them chooses to start with a European or EMEA wide head quarter on the British Isles – and that again means mostly in the London area.

The reasons for that may be many. However I guess that the fact that people on the British Isles doesn’t speak a strange language has a lot to say. What many North American companies with a head quarter in London often has to realize then is, that this move only got them half way over the pond.  

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7 Comments | Data Quality Tools, Master Data | Tagged: , , , | Permalink
Posted by Henrik Liliendahl Sørensen

The Location Domain

10th September 2011

When talking master data management we usually divide the discipline into domains, where the two most prominent domains are:

  • Customer, or rather party, master data management
  • Product, sometimes also named “things”, master data management

One the most frequent mentioned additional domains are locations.

But despite that locations are all around we seldom see a business initiative aimed at enterprise wide location data management under a slogan of having a 360 degree view of locations. Most often locations are seen as a subset of either the party master data or in some cases the product master data.  

Industry diversity

The need for having locations as focus area varies between industries.

In some industries like public transit, where I have been working a lot, locations are implicit in the delivered services. Travel and hospitality is another example of a tight connection between the product and a location. Also some insurance products have a location element. And do I have to mention real estate: Location, Location, Location.

In other industries the location has a more moderate relation to the product domain. There may be some considerations around plant and warehouse locations, but that’s usually not high volume and complex stuff.  

Locations as a main factor in exploiting demographic stereotypes are important in retailing and other business-to-consumer (B2C) activities. When doing B2C you often want to see your customer as the household where the location is a main, but treacherous, factor in doing so. We had a discussion on the house-holding dilemma in the LinkedIn Data Matching group recently.

Whenever you, or a partner of yours, are delivering physical goods or a physical letter of any kind to a customer, it’s crucial to have high quality location master data. The impact of not having that is of course dependent on the volume of deliveries.   

Globalization

If you ask me about London, I will instinctively think about the London in England. But there is a pretty big London in Canada too, that would be top of mind to other people. And there are other smaller Londons around the world.

Master data with location attributes does increasingly come in populations covering more than one country. It’s not that ambiguous place names don’t exist in single country sets. Ambiguous place names were the main driver behind that many countries have a postal code system. However the British, and the Canadians, invented a system including letters opposite to most other systems only having numbers typically with an embedded geographic hierarchy.

Apart from the different standards used around the possibilities for exploiting external reference data is very different concerning data quality dimensions as timeliness, consistency, completeness, conformity – and price.

Handling location data from many countries at the same time ruins many best practices of handling location data that have worked for handling location for a single country.

Geocoding

Instead of identifying locations in a textual way by having country codes, state/province abbreviations, postal codes and/or city names, street names and types or blocks and house numbers and names it has become increasingly popular to use geocoding as supplement or even alternative.

There are different types of geocodes out there suitable for different purposes. Examples are:

  • Latitude and longitude picturing a round world,
  • UTM X,Y coordinates picturing peels of the world
  • WGS84 X, Y coordinates picturing a world as flat as your computer screen.

While geocoding has a lot to offer in identifying and global standardization we of course has a gap between geocodes and everyday language. If you want to learn more then come and visit me at N55’’38’47, E12’’32’58.

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17 Comments | Data Architecture, Multi-Domain MDM | Tagged: , , , | Permalink
Posted by Henrik Liliendahl Sørensen

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