The Problem with Multiple Purposes of Use

23rd May 2012

Today I noticed this tweet by Malcolm Chisholm:

I agree.

The problem with the “fitness for use” or “fit for the purpose of use” definition of data quality has been a recurring subject on this blog starting with the post Fit for What Purpose? through to lately the post Inaccurately Accurate discussing the data quality of the British electoral roll seen from either a strict electoral point of view and the point of view from external use of the electoral roll.

The problem with “fitness of use” becomes clear when data quality has to be addressed within master data management. Master data has, per definition so to say, many uses.

My thesis is that there is a breakeven point when including more and more purposes where it will be less cumbersome to reflect the real world object rather than trying to align all known purposes.

Today Jim Harris made an (as ever) excellent post related to how data actually represents what it purports to represent – now and tomorrow too. Find the post called Syncing versus Streaming on the Data Roundtable.

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Do You Want Social MDM?

22nd May 2012

This weekend I noticed a tweet from the MDM tool vendor Orchestra Networks:

There is clearly something completely wrong with this tweet. Why on earth should a French company use an American date format?

Apart from that there is a very good point. Why should tool vendors work on solving imaginable future master data management issues as integrating social network profiles with traditional customer master data while there are plenty of issues that need a better solution today?

Personally I think social MDM is going to be huge. I had some of my first musings on the subject some years ago in the post Social Master Data Management. Probably we will start with some Lean Social MDM, and that is honestly also as far as I have explored this field until now.

What about you. Do you want social MDM?

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Avoiding Contact Data Entry Flaws

19th May 2012

Contact data is the data domain most often mentioned when talking about data quality. Names and addresses and other identification data are constantly spelled wrong, or just different, by the employees responsible of entering party master data.

Cleansing data long time after it has been captured is a common way of dealing with this huge problem. However, preventing typos, wrong hearings and multi-cultural misunderstandings at data entry is a much better option wherever applicable.

I have worked with two different approaches to ensure the best data quality for contact data entered by employees. These approaches are:

  • Correction and
  • Assistance

Correction

With correction the data entry clerk, sales representative, customer service professional or whoever is entering the data will enter the name, address and other data into a form.

After submitting the form, or in some cases leaving each field on the form, the application will check the content against business rules and available reference data and return a warning or error message and perhaps a correction to the entered data.

As duplicated data is a very common data quality issue in contact data, a frequent example of such a prompt is a warning about that a similar contact record already exists in the system.

Assistance

With assistance we try to minimize the needed number of key strokes and interactively help with searching in available reference data.

For example when entering address data assistance based data entry will start with the highest geographical level:

  • If we are dealing with international data the country will set the context and know about if a state or province is needed.
  • Where postal codes (like ZIP) exists, this is the fast path to the city.
  • In some countries the postal code only covers one street (thoroughfare), so that’s settled by the postal code. In other situations we will usually have a limited number of streets that can be picked from a list or settled with the first characters.

(I guess many people know this approach from navigation devices for cars.)

When the valid address is known you may catch companies from business directories being on that address and, depending on the country in question, you may know citizens living there from phone directories and other sources and of course the internal party master data, thus avoiding entering what is already known about names and other data.

When catching business entities a search for a name in a business directory often leads to being able to pick a range of identification data and other valuable data and not at least a reference key to future data updates.

Lately I have worked intensively with an assistance based cloud service for business processes embracing contact data entry. We have some great testimonials about the advantages of such an approach here: instant Data Quality Testimonials.

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Social MDM, Privacy and Data Quality

17th May 2012

The term “Social MDM” has been promoted quite well this week not at least as part of the social media information stream from the ongoing user conference of the tool vendor Informatica.

In a blog post called Informatica 9.5 for Big Data Challenge #2: Social Jody Ko of Informatica introduces the opportunities and challenges.

In the closing remarks Judy says: “There’s still a long way to go to bring social data into the mainstream enterprise, in part due to concerns over privacy and the potential “creepiness” factor of mining social data.”

As I understand it the spearhead Social MDM part of the tool release is a Facebook App that provides connectivity between Facebook and the MDM solution.

Industry analyst R “Ray” Wang examines this in the blog post News Analysis: Informatica Launches MDM 9.5. The analysis states that it now is time to “drive data out of Facebook and not into Facebook”.

The opportunities and challenges of driving data out of Facebook was discussed in a post called exactly Out of Facebook here on the blog some years ago.

Balancing privacy with data hoarding is still for sure a subject that in no way is settled and probably never will be.

Connecting systems of record in traditional MDM solutions with social network profiles is in no way a walk over too. The classic data quality challenges with uniqueness of records and completeness of data only gets more difficult, but also, there are great opportunities for getting a better picture of your customers and other business partners.

If you are interested in Social MDM and the related challenges and opportunities there is a LinkedIn group for Social MDM.

The group is new, less than a month old at the present time, but there is already a lot of content to dip into, including:

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Häagen-Dazs Datakvalitet

12th May 2012

There is a term called foreign branding. Foreign branding is describing an implied cachet or superiority of products and services with foreign-sounding names

Häagen-Dazs ice cream is an example of foreign branding. Though the brand was established in New York the name was supposed to sound Scandinavian.

However, Häagen-Dazs does sound and look somewhat strange to a Scandinavian. The reason is probably that the constellation of the letters “äa” and “zs” are not part of any native Scandinavian words.

By the way, datakvalitet is the Scandinavian compound word for data quality.

Getting datakvalitet right in world wide data isn’t easy. What works in some countries doesn’t work in other countries, not at least when we are talking datakvalitet regarding party master data such as customer master data, supplier master data and employee master data.

One of the reasons why datakvalitet for party master data is different is the various possibilities with applying big reference data sources. For example the availability of citizen data is different in New York than in Scandinavia. This affects the ways of reaching optimal datakvalitet as reported in the post Did They Put a Man on the Moon.

As part of the ongoing globalization handling international datakvalitet is becoming more and more common. Many enterprises try to deploy enterprise wide datakvalitet initiatives and shared service centers handles party master data uncommon to the people working there. This often results in finding a strange word like Häagen-Dazs.

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Social Commerce and Multi-Domain MDM

8th May 2012

The term social commerce is said to be a subset of eCommerce where social media is used to ultimately drag prospects and returning customers to your website, where a purchase of products and services can be made.

In complex sales processes, typically for Business-to-Business (B2B) sales, the website may offer product information sheets, demo requests, contact forms and other pipeline steps.

This is the moment where your social media engaged (prospective) customer meets your master data as:

  • The (prospective) customer creates and maintains name, address and communication information by using registration functions
  • The (prospective) customer searches for and reads product information on web shops and information sites

One aspect of this transition is how master data is carried over, namely:

  • How the social network profile used in engagement is captured as part of (prospective) customer master data or if it should be part of master data at all?
  • How product information from the governed master data hub has been used as part of the social media engagement or if the data governance of product data should be extended to use in social media at all?

Any thoughts?

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Big Reference Data as a Service

5th May 2012

This morning I read an article called The Rise of Big Data Apps and the Fall of SaaS by Raj De Datta on TechCrunch.

I think the first part of the title is right while the second part is misleading. Software as a Service (SaaS) will be a big part of Big Data Apps (BDA).

The article also includes a description of LinkedIn merely as a social recruitment service. While recruiters, as reported in the post Indulgent Moderator or Ruthless Terminator?, certainly are visible on this social network, LinkedIn is much more than that.

Among other things LinkedIn is a source of what I call big reference data as examined in the post Social MDM and Systems of Engagement.

Besides social network profiles big reference data also includes big directory services, being services with large amount of data about addresses, business entities and citizens/consumers as told in the post The Big ABC of Reference Data.

Right now I’m working with a Software as a Service solution embracing Big (Reference) Data as a Service thus being a Big Data App called instant Data Quality.

And hey, I have made a pin about that:

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Data Quality vs Big Data

3rd May 2012

If you go to Google Insight and ask for how it goes with search interest for “data quality” versus how it is with “big data” you’ll get this graph:

“Data quality” (blue line) is a bear market. The interest is slowly but steadily decreasing. “Big data” (red line) is a bull market with a steep rising curve of interest starting in early 2011 and exploding in 2012.

So, what can you do if your blog is about data quality? For my part I’m writing a blog post on my data quality blog mentioning the term “big data” as many times as possible :-)

I’m not saying “big data” is uninteresting. Not at all. I even use the term “big reference data” when describing how to exploit big directories and social network profiles in the quest for improving party master data quality.

In the short period of the “big data” hype it has often been said, that why should we start working with “big data” when we can’t manage small data yet?

While this makes some sense, it will in my eyes be a mistake not to try exploring what data quality techniques we can apply to “big data” and what data quality advantages we can harvest within “big data”.

We have known for years that the amount of data being available is drastically increasing. Now we just have a term to be used when searching for and talking about it. Like it or not; that term is “big data”.

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Social MDM and Systems of Engagement

28th April 2012

Social Master Data Management has been an interest of mine the last couple of years and last week I have tried to reach out to others in exploring this new era of Master Data Management by creating a group on LinkedIn called Social MDM.

When reading a nice blog with the slogan ”Welcome to the Real (IT) World!” by Max J. Pucher I came across a good illustration by John Mancini showing the history of IT and how the term “Systems of Record” is being replaced (or at least supplemented) by the term “Systems of Engagement”:

Master Data Management (MDM) includes having a System of Record (SOR) describing the core entities that takes part in the transactional systems of record that supports the daily business in every organization. For example a golden MDM record is describing the party that acts as a customer on an order record while the products in the underlying order lines are described in golden MDM records for the things dealt with within the organization.

Social Master Data Management (Social MDM) will be about supplementing that System of Record so we are able to further describe the parties taking part in the new Systems of Engagement and link with the old Systems of Records. These parties are reflected as social network profiles that are owned by the same human beings who are our (prospective) customers, part of the same household or are a contact for a company being a (prospective) customer or any other business partner.

For a guy like me who started in IT in the mainframe era (just after it had ended according to the above illustration) and went on with mini computers, PC’s and the internet it’s very exciting to be moving on into the social and cloud era.

It will be good to be joined by even more data quality and MDM practitioners and anyone else in the LinkedIn Social MDM group.

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At Least Two Versions of the Truth

26th April 2012

Precisely one year ago I wrote a post called Single Company View examining the challenges of getting a single business partner view in business-to-business (B2B) party master data.

Yesterday Robert Hawker of Vodafone made a keynote at the MDM Summit Europe 2012 telling about supplier master data management.

One of the points was that sometimes you really want the exactly same real world entity to be two golden records in your master data hub, as there may be totally different business activities made with the same legal entity. The Vodafone example was:

  • Having an antenna placed on the top of a building owned by a certain company and thus paying a fee for that
  • Buying consultancy services from the same company

I have met such examples many times when doing data matching as told in the post Entity Revolution vs Entity Evolution.

However at one occasion, many years ago, I worked in a company where not having a single business partner view nearly became a small disaster.

Our company delivered software for membership administration and was at the same time a member of an employer organisation that also happened to be a customer.

A new director got the brilliant idea, that cancelling the membership of the employer organization was an obvious cost reduction.

The cancellation was sent. The employer organisation confirmed the cancellation adding, that they were very sorry that internal business rules at the same time forced them to not being a customer anymore.

Cancellation was cancelled of course and damage control was initiated.

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