Customer Relationship Mess (CRM)

Henrik Gabs LiliendahlLeave a comment

I have several times witnessed how a sales department for a lot of good reasons has forced the implementation of a CRM (Customer Relationship Management) software package disconnected from the ERP (Enterprise Resource Planning) system and other applications where customer master data have been handled until then.

The good reasons have been that the current applications didn’t fit the business processes in a dynamic sales department and perhaps that the current monolithic enterprise solution was too inflexible for the business needs in sales.

While this move may have been a great success in sales force automation the downside is often that the single customer view has been limited to a single customer view seen from the windows in the sales department offices.

In order to have a 360 degree view of customer you have to cover all the view points in the enterprise embracing all departments being in contact with the customer and thereby accessing and maintaining customer master data.

Those who feel the pain when a company doesn’t maintain such a view is the customer and those who enjoys when a company have that view is the customer.

Lately I had two experiences as a customer. A bad experience facing a lousy approximately 110 degree customer view from a phone company and a well executed 360 degree view from an insurance company. Both cases haven’t been around one of my favorite subjects being identity resolution. Both companies have my citizen ID.

It is just so that some companies cares more about single department business needs than true customer relationship management. IT’s a mess.

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Where is the Business?

Henrik Gabs Liliendahl6 Comments

In technology enabled disciplines we often like to divide an organization into two distinct parts being IT (Information Technology) and “the business”.

I am aware that we do that to emphasize that our solutions has to be business centric opposite to technology centric. We mustn’t fall into the trap of discussing technology too early and certainly not selecting certain technology brands as the first step of our solutions.

A problem however is where to find “the business” in an organization. The top management surely represents all of the business (including the IT part of the business). But in order to find the so called subject matter experts we are looking down the levels in the organization where people don’t belong to “the business” but to sales, marketing, customer service, purchase, production, human resources, finance and so on.

Some technology enabled disciplines belong to a certain department. But disciplines as (enterprise wide) data quality and master data management are supposed to support most departments. The business. So where do we find the business? And who are we by the way?

Call them?

Assuming it doesn’t matter who we are: Let’s go find “the business”. I guess it doesn’t help calling the reception and ask them to put us through to “the business”. Actually the manned reception probably doesn’t exist today. And it will be surprising to get a machine asking:

  • Do you want to speak with IT? Press 1.
  • Do you want to speak with “the business”? Press 2.

If we are in my home country Denmark we also have a linguistic issue. If I ask google to translate “the business” from English to Danish I get the word “forretningen”. If I ask google to translate “forretningen” from Danish back to English I get the word “shop”. So calling “forretningen” will probably get me to the shop floor. Not a bad place, a true gemba, but maybe not the only one.

Everyone belongs to “the business”

In data quality and master data management there is a question used all over to exemplify a common challenge within these disciplines.

The question is: What is a customer?

The challenge is that people from different departments will have different definitions. Marketing defines a customer one way, sales tend to do it a bit different, finance sees it yet in another way and production has their view point. And the stereotype IT guy defines a customer as a row in the customer table.

So now we are asking for Alexander the Great from “the business” to come cutting the Gordian Knot.

That is probably not going to happen.

More likely someone from any business unit will be able to negotiate a proper conceptual solution covering all requirements from the different business units. And from what I see around it may often be someone who’s human resource master data record is related to the IT part of the business. Or was. The main point is having a holistic view of the business where everyone belongs.    

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The Letter Ø

Henrik Gabs LiliendahlLeave a comment

This blog is written in English. Therefore the letters used are normally restricted to A to Z.  

The English alphabet is one of many alphabets using Latin (or Roman) letters. Other alphabets like the Russian uses Cyrillic letters. Then there are other script systems in the world which besides alphabets are abjads, abugidas, syllabic scripts and symbol scripts. Learn more about these in the post Script Systems.

My last surname is “Sørensen”. This word contains the lower case letter “ø” which is “Ø” in upper case. This letter is part of two alphabets: The Danish/Norwegian and the Faroese. Sometimes data has to be transformed into the English alphabet. Then the letter “ø” may be transformed to either “o” or “oe”. So my last surname will be either “Sorensen” or “Soerensen” in the English alphabet.

The town part of my address is “København”. The word “København” is what we call an endonym, which is the local word for place or a person. The opposite of endonym is exonym. The English exonym for “København” is “Copenhagen” which of course only has letters from the English alphabet. The Swedish exonym for “København” is “Köpenhamn”. Here we have a variant of “Ø” being “Ö”. The letter “Ö” exists in a lot of alphabets as Swedish, German, Hungarian and Turkish.

Usually “Ø” is transformed to “Ö” between Danish/Norwegian and these alphabets. The other way we usually accept the letter “Ö” in Danish/Norwegian master data.

These issues are of course a problem area in data quality, data matching and master data management. And with the complexity only between alphabets using Latin characters there is of course much more land to cover when including Cyrillic and Greek letters and then the other scripts systems with their hierarchical elements.

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Fitness Data

Henrik Gabs Liliendahl4 Comments

About a month ago I wrote about how my personal data was on-boarded in the local fitness club in the post called Right the First Time.

Since then I have actually succeeded in visiting the gym twice a week and used the amazing technology necessary to get me in action.

As a complete data geek I of course use the full TV screen on the machine not to watch TV but to display the full dashboard with key performance indicators related to my workout. These include:

  • Time done / remaining
  • Pulse with red alert when I’m over the healthy threshold for my age
  • Distance I would have gone if I wasn’t in the same fixed position
  • Calories burned

As with many data presentations we here have a mix of hard facts, like the time done, and then some assumed figures like calories burned. The machine doesn’t really measure the actual accurate burning but calculates the assumed burning as a function of power level, speed, my weight and age.  

It’s actually a question if I really want to know about the calories burned. My conclusion is yes. The time done is wasted anyway, the high pulse doesn’t last and the distance is virtual. So the calories burned fit the purpose of use. It keeps me going.   

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Multi-Channel Data Quality

Henrik Gabs Liliendahl4 Comments

When I hear terms as multi-channel marketing, multi-channel retailing, multi-channel publishing and other multi-channel things I can’t resist thinking that there also must be a term called multi-channel data quality.

Indeed we are getting more and more channels where we do business. It stretches from the good old brick and mortar offline shop over eCommerce and the latest online touch points as mobile devices and social media.

Our data quality is challenged by how the way of the world changes. Customer master data is coming from these disparate channels with various purposes and in divergent formats. Product master data is exposed through these channels in different ways.     

We have to balance our business processes between having a unique single customer view and a unified product information basis and the diverse business needs within each channel.  

Some customer data may be complete and timely in one channel but deficient and out of date in another channel. Some product data may be useful here but inaccurate there.

I think the multi-channel things makes yet a business case for multi-domain (or multi-entity) master data management. Even if it is hard to predict the return on investment for the related data quality and master data management initiatives I think it is easy to foresee the consequences of doing nothing.

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Extreme Data Quality

Henrik Gabs LiliendahlLeave a comment

This blog post is inspired by reading a blog post called Extreme Data by Mike Pilcher. Mike is COO at SAND, a leading provider of columnar database technology.

The post circles around a Gartner approach to extreme data. While the concept of “Big Data” is focused on the volume of data the concept of “Extreme Data” also takes into account the velocity and the variety of data.

So how do we handle data quality with extreme data being data of great variety moving in high velocity and coming in huge volumes? Will we be able to chase down all root causes of eventual poor data quality in extreme data and prevent the issues upstream or will we have to accept the reality of downstream cleansing of data at the time of consumption?

We might add a sixth reason being the rise of extreme data to the current Top 5 Reasons for Downstream Cleansing.

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Electronic Data Processing

Henrik Gabs Liliendahl2 Comments

A comment on my last blog post took me back to the days when I started working with Information Technology (IT). At that time our métier actually wasn’t called IT but EDP (Electronic Data Processing) – at least that was the case in my home country Denmark where we used the local TLA being EDB (Elektronisk Data Behandling).

I have earlier touched the long standing discussion about if “data quality” should be rebranded as “information quality” for example in the post called new blog name, as this should also require a new name for this blog.

The words data and information are indeed used very randomly around. In MDM (Master Data Management) we have two main domains being Customer Data Integration (CDI) and Product Information Management (PIM). Wonder if customer data is old school and product information is new school?

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Business and Pleasure

Henrik Gabs Liliendahl14 Comments

The data quality and master data management (MDM) realm has many wistful songs about unrequited love with “the business”.

This morning I noticed yet a tweet on twitter expressing the pain:

Here Gartner analyst Ted Friedman foresees the doom of MDM if we don’t get at least the traction from “the business” that BI (Business Intelligence) is getting.

In my eyes everything we do in Information Technology is about “the business”. Even computer games and digital entertainment is a core part of the respective industries. I also believe that IT is part of “the business”.

“The rest of the business” does see that some disciplines belong in the IT realm. This goes for database management, programming languages and network protocols. These disciplines are not doomed at all because it is so. “The rest of the business” couldn’t work today without these things around.

Certainly I have seen some IT based disciplines and related tools emerged and then been doomed during my years in the IT business. Anyone remembers case tools?   

With case tools I remember great expectations about business involvement in application design. But according to Wikipedia the main problems with case tools are (were): Inadequate standardization, unrealistic expectations, slow implementation and weak repository controls.

In other words: “The rest of the business” never really got in touch with the case tools because they didn’t work as supposed.

The business traction we see around BI (and the enabling tools) now is in my eyes very much about that the tools have matured, actually works, have become more user friendly and seems to create useful results for “the rest of the business”.

Data quality tools and MDM tools must continue to follow that direction too, because for sure: Data Quality tools and MDM tools does not solve any severe problems internally in the IT part of “the business”.

It’s my pleasure being part of that.

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The Art in Data Matching

Henrik Gabs Liliendahl12 Comments

I’ve just investigated a suspicious customer data match:

A Company on Kunstlaan no 99 in Brussel

was matched with high confidence with:

The Company on Avenue des Arts no 99 in Bruxelles

At first glance it perhaps didn’t look as a confident match, but I guess the computer is right.

The diverse facts are:

  • Brussels is the Belgian capital
  • Belgium has two languages: French and Flemish (a variant of Dutch)
  • Some parts of the country is French, some parts is Flemish and the capital is both
  • Brussels is Bruxelles in French and Brussel in Flemish
  • Kunst is Flemish meaning Art (as in Dutch, German and Scandinavian too)
  • Laan is Flemish meaning Avenue (same origin as Lane I guess)
  • Avenue des Arts is French meaning Avenue of Art (French is easy)

Technically the computer in this case did as follows:

  • Compared the names like “A Company” and “The Company” and found a close edit distance between the two names.
  • Remembered from some earlier occasions that “Kunstlaan” and “Avenue des Arts” was accepted as a match.
  • Remembered from numerous earlier occasions that “Brussel”(or “Brüssel) and “Bruxelles” was accepted as a match.

It may also have been told beforehand that “Kunstlaan” and “Avenue des Art” are two names of the same street in some Belgian address reference data which I guess is a must when doing heavy data matching on the Belgian market.

In this case it was a global match environment not equipped with worldwide address reference data, so luckily the probabilistic learning element in the computer program saved the day.

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Survival of the Fit Enough

Henrik Gabs Liliendahl2 Comments

When working with data quality and master data management at the same time you are constantly met with the challenge that data quality is most often defined as data being fit for the purpose of use, but master data management is about using the same data for multiple purposes at the same time.

Finding the right solution to such a challenge within an organization isn’t easy, because it despite all good intentions is difficult to find someone in the business with an overall answer to that kind of problems as explained in the blog post by David Loshin called Communications Gap? Or is there a Gap between Chasms?

An often used principle for overcoming these issues may (based on Darwin) be seen as “survival of the fittest”. You negotiate some survivorship rules between “competing” data providers and consumers and then the data being the fittest measured by these rules wins. All other data gets the KISS of death. Most such survivorship rules are indeed simple often based on a single dimension as timeliness, completeness or provenance.

Recently the phrase “survival of the fittest” in evolution theory has been suggested to be changed to “survival of the fit enough” because it seems that many times specimens haven’t competed but instead found a way into empty alternate spaces.

It seems that master data management and related data quality is going that way too. Data that is fit enough will survive in the master data hub in alternate spaces where the single source of truth exists in perfect symbioses with multiple realities.

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