Master Data

Hierarchy Management in Social MDM

Henrik Gabs Liliendahl3 Comments

Hierarchy management is a core feature in master data management (MDM). When it comes to integrating social data and social network profiles into MDM, hierarchy management will be very important too.

Aggregated Level of Social MDM in B2C

The primarily privacy related challenges of social MDM not at least within business-to-consumer (B2C) have been a topic of a lot of blogging lately.  Examples are:

One way of overcoming the privacy considerations is linking to social data and social network profiles at an aggregate level.

Using aggregate level linking is already well known in direct marketing with the use of demographic stereotypes. These stereotypes are based on groups of consumers often defined by their address and/or their age. Combining this knowledge with product master data was examined in the post Customer Product Matrix Management.

Social MDM will add new dimensions to this way of using hierarchies in master data and linking the data across multiple channels without the need to uniquely identify a real world person in every aspect.

Contact Level Social MDM in B2B

As discussed in the post Business Contact Reference Data social network profiles has lot to offer within mastering business-to-business (B2B) contact data.

While access to external reference data at the account level has been around for many years by having available public and commercial (and even open) business directories, the problem of identifying and maintain correct and timely data about the contacts at these accounts has been huge.

Integrating with social networks can help here and social networks are actually also integrating more and more with the traditional business directories. LinkedIn has business directory links for larger companies today and lately I noticed a new professional social network called CompanyBook that is based on linking your profile to a (complete) business directory. By the way: The business directory data available in CompanyBook is surprisingly deep, for example revenue data is free for you to grab.

When it comes to contact data they are basically maintained out there by you. A service like LinkedIn is often described as a recruitment service. In my eyes it is a lot more than that. It is along with similar services a goldmine (within a minefield) for getting MDM within B2B done much better.

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Big Data and Multi-Domain Master Data Management

Henrik Gabs LiliendahlLeave a comment

The possible connection between the hot buzz within IT today being “big data” and the good old topic of master data management has been discussed a lot lately. An example from CIO UK today is this article called Big data without master data management is a problem.

As said in the article there is a connection through big master data (and big reference data) to big transaction data. Big transaction data is what we usually would call big data, because these are the really big ones.

The two most mentioned kind of big transaction data are:

  • Social data and
  • Sensor data

I also have seen a lot of connections between these big data and master data in multiple domains.

Social Data

Connecting social data to Master Data Management (MDM) is an ongoing discussion I have been involved in for the last three years lately through the new LinkedIn group called Social MDM.

The customer master data domain is in focus here, as the immediate connection here is how to relate traditional systems of record holding customer master data and the systems of engagement where the big social data are waiting to be analyzed and eventually be a part of day-to-day customer centric business processes.

However being able to analyze, monitor and take action on what is being said about specific products in social data is another option and eventually that has to be linked to product master data. In product master data management the focus has traditionally been on your own (resell) products. Effectively listening to social data will mean that you also have to manage data about competing products.

Attaching location to social data has been around for long. Connecting social data to your master data will also require that your location master data are well aligned with the real world.

Sensor Data   

During the past many years I have been involved in data management within public transportation where we have big data coming in from sensors of different kind.

The big problem has for sure being able to connect these transactions correctly to master data. The challenges here are described in the post Multi-Entity Master Data Quality.

The biggest problem is that all the different equipment generating the sensor data in practice can’t be at the same stage at the same time and this will eventually create data that if related without care will show very wrong information about who was the passenger(s), what kind of trip it were, where the journey happened and under which timetable.

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Data Driven Data Quality

Henrik Gabs LiliendahlLeave a comment

In a recent article Loraine Lawson examines how a vast majority of executives describes their business as “data driven” and how the changing world of data must change our approach to data quality.

As said in the article the world has changed since many data quality tools were created. One aspect is that “there’s a growing business hunger for external, third-party data, which can be used to improve data quality”.

Embedding third-party data into data quality improvement especially in the party master data domain has been a big part of my data quality work for many years.

Some of the interesting new scenarios are:

Ongoing Data Maintenance from Many Sources

As explained in the article on Wikipedia about data quality services as the US National Change of Address (NCOA) service and similar services around the world has been around for many years as a basic use of external data for data quality improvement.

Using updates from business directories like the Dun & Bradstreet WorldBase and other national or industry specific directories is another example.

In the post Business Contact Reference Data I have a prediction saying that professional social networks may be a new source of ongoing data maintenance in the business-to-business (B2B) realm.

Using social data in business-to-consumer (B2C) activities is another option though also haunted with complex privacy considerations.

Near-Real-Time Data Enrichment

Besides updating changes of basic master data from business directories these directories typically also contains a lot of other data of value for business processes and analytics.

Address directories may also hold further information like demographic stereotype profiles, geo codes and property data elements.

Appending phone numbers from phone books and checking national suppression lists for mailing and phoning preferences are other forms of data enrichment used a lot related to direct marketing.

Traditionally these services have been implemented by sending database extracts to a service provider and receiving enriched files for uploading back from the service provider.

Lately I have worked with a new breed of self service data enrichment tools placed in the cloud making it possible for end users to easily configure what to enrich from a palette of address, business entity and consumer/citizen related third-party data and executing the request as close to real-time as the volume makes it possible.

Such services also include the good old duplicate check now much better informed by including third-party reference data.

Instant Data Quality in Data Entry

As discussed in the post Avoiding Contact Data Entry Flaws third-party reference data as address directories, business directories and consumer/citizen directories placed in the cloud may be used very efficiently in data entry functionality in order to get data quality right the first time and at the same time reduce the time spend in data entry work.

Not at least in a globalized world where names of people reflect the diversity of almost any nation today, where business names becomes more and more creative and data entry is done at shared service centers manned with people from cultures with other address formatting rules, there is an increased need for data entry assistance based on external reference data.

When mashing up advanced search in third-party data and internal master when doing data entry you will solve most of the common data quality issues around avoiding duplicates and getting data as complete and timely as needed from day one.

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Business Contact Reference Data

Henrik Gabs Liliendahl2 Comments

When working with selling data quality software tools and services I have often used external sources for business contact data and not at least when working with data matching and party master data management implementations in business-to-business (B2B) environments I have seen uploads of these data in CRM sources.

A typical external source for B2B contact data will look like this:

Some of the issues with such data are:

  • Some of the contact data names may be the same real world individual as told in the post Echoes in the Database
  • People change jobs all the time. The external lists will typically have entries verified some time ago and when you upload to your own databases, data will quickly become useless do to data decay.
  • When working with large companies in customer and other business partner roles you often won’t interact with the top level people, but people in lower levels not reflected in such external sources.

The rise of social networks has presented new opportunities for overcoming these challenges as examined in a post (written some years ago) called Who is working where doing what?

However, I haven’t seen so many attempts yet to automate and include working with social network profiles in business processes. Surely there are technical issues and not at least privacy considerations in doing so as discussed in the post Sharing Social Master Data.

Right now we have a discussion going on in the LinkedIn Social MDM group about examples of connecting social network profiles and master data management. Please add your experiences in the group here – and join if you aren’t already a member.

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Instant Data Enrichment

Henrik Gabs LiliendahlLeave a comment

Data enrichment is one of the core activities within data quality improvement. Data enrichment is about updating your data in order to be more real world aligned by correcting and completing with data from external reference data sources.

Traditionally data enrichment has been a follow up activity to data matching and doing data matching as a prerequisite for data enrichment has been a good part of my data quality endeavor during the recent 15 years as reported in the post The GlobalMatchBox.

During the last couple of years I have tried to be part of the quest for doing something about poor data quality by moving the activities upstream. Upstream data quality prevention is better than downstream data cleansing wherever applicable. Doing the data enrichment at data capture is the fast track to improve data quality for example by avoiding contact data entry flaws.

It’s not that you have to enrich with all the possible data available from external sources at once. What is the most important thing is that you are able to link back to external sources without having to do (too much) fuzzy data matching later. Some examples:

  • Getting a standardized address at contact data entry makes it possible for you to easily link to sources with geo codes, property information and other location data at a later point.
  • Obtaining a company registration number or other legal entity identifier (LEI) at data entry makes it possible to enrich with a wealth of available data held in public and commercial sources.
  • Having a person’s name spelled according to available sources for the country in question helps a lot when you later have to match with other sources.

In that way your data will be fit for current and future multiple purposes.

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The Problem with Multiple Purposes of Use

Henrik Gabs Liliendahl3 Comments

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?

Henrik Gabs Liliendahl5 Comments

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

Henrik Gabs Liliendahl9 Comments

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

Henrik Gabs Liliendahl4 Comments

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

Henrik Gabs LiliendahlLeave a comment

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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