Sharing Social Master Data

21st February 2012

If a company runs a Customer Relationship Management (CRM) system all employees are supposed to enter their interactions with customers and prospects including adding new accounts and contacts if it’s the first engagement.

With the rise of social networks first engagements are increasingly done in those networks. Furthermore new employees often bring old contacts from former employments with them thus utilizing an established relationship that probably is manifested in one or more already existing social network connections.

As explained in the post Social Master Data Management the term ”Social CRM” has been around for a while. We now see CRM solutions where the account and contact master data primarily is build on extracting those data from social networks.

I have just tried out such a solution called Nimble.

If you are more than a one-man-band company it’s interesting in what degree you are willing (or forced) to share your connections as master data entities for the CRM solution.

In Nimble you have the choice of differentiate for each network. I would probably freely choose a setup with Twitter and LinkedIn as shared with the team, but Facebook as private:

But that is just how I think based on my way of using social networks.

There is a fundamental data quality versus privacy issue around utilizing employee’s social network connections as master data for CRM and eventually enterprise wide Master Data Management (MDM).

All things equal data quality will be best if everyone contributes within reason. Not at least in sales, but also more or less in other functions, you are hired also because of your relations.

What do you think?

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Informatics for adding value to information

20th February 2012

Recently the Global Agenda Council on Emerging Technologies within the World Economic Forum has made a list of the top 10 emerging technologies for 2012. According to this list the technology with the greatest potential to provide solutions to global challenges is informatics for adding value to information.

As said in the summary: “The quantity of information now available to individuals and organizations is unprecedented in human history, and the rate of information generation continues to grow exponentially. Yet, the sheer volume of information is in danger of creating more noise than value, and as a result limiting its effective use. Innovations in how information is organized, mined and processed hold the key to filtering out the noise and using the growing wealth of global information to address emerging challenges.”

Big data all over

Surely “big data” is the buzzword within data management these days and looking for extreme data quality will be paramount.   

Filtering out the noise and using the growing wealth of global information will help a lot in our endurance to make a better world and to make better business.

In my focus area, being master data management, we also have to filtering out the noise and exploit the growing wealth of information related to what we may call Big Master Data.

Big external reference data

The growth of master data collections is also seen in collections of external reference data.

For example the Dun & Bradstreet Worldbase holding business entities from around the world has lately grown quickly from 100 million entities to over 200 millions entities. Most of the growth has been due to better coverage outside North America and Western Europe, with the BRIC countries coming in fast. A smaller world resulting in bigger data.

Also one of the BRICS, India, is on the way with a huge project for uniquely identifying and holding information about every citizen – that’s over a billion. The project is called Aadhaar.

When we extend such external registries also to social networking services by doing Social MDM, we are dealing with very fast growing number of profiles in Facebook, LinkedIn and other services.

Surely we need informatics for adding the value of big external reference data into our daily master data collections.

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What to do in 2012

28th December 2011

The time between Christmas and New Year is a good time to think about if you are going to do the right things next year. In doing so, you will have to look back at the current year and see how you can develop from there.

In my professional life as a data quality and master data management practitioner my 2011 to do list included these three main activities:

  • Working with Multi-Domain Master Data Quality
  • Exploiting rich external reference data sources in the cloud
  • Doing downstream data cleansing

In a press release from May 2011 Gartner (the analyst firm) Highlights Three Trends That Will Shape the Master Data Management Market. These are:

  • Growing Demand for Multidomain MDM Software
  • Rising Adoption of MDM in the Cloud
  • Increasing Links Between MDM and Social Networks

It looks like I was working in the right space for the first two things but stayed in the past regarding the third activity being downstream data cleansing.

The third thing to embrace in the future, social MDM we may call it, has been an area of interest for me the last couple of years and actually some downstream data cleansing projects has touched making master data useful for including social media networks in the loop.  

I’m not sure if 2012 will be a breakthrough for social MDM, but I think there will be some exciting opportunities out there for paving the road for social MDM.

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Lean Social MDM

22nd August 2011

I have previously written some blog posts about “Social MDM” using the term “Social MDM” to describe the trend of having social media (master) data as a new complexity on top of the already known conundrum of mastering traditional master data.

Stephan Zoder of IBM Initiate discussed this topic in a recent post called CMM is Actually High-Frequency, Social MDM (where CMM is about Customer Motivation Management).

As I also briefly examined the term “Lean MDM” last week I wonder if it is possible to start embracing social media (master) data under a term as “Lean Social MDM”.

The lean MDM post included an actual real life project I have been involved in, which was about how the car rental giant Avis achieved lean MDM for the Scandinavian business.

An underlying business case for this project was that many decisions about car rental is made by individual persons who may act as an employee at (changing) employers and as private renters. Therefore the emphasis of the master data management was at the person in contact, user and private roles.  

Having a “single person view” is in my eyes, if it wasn’t before, a good place to start your “Lean Social MDM” journey.     

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More Social Master Data Management

22nd July 2011

Yesterday my American cyberspace friend Jim Harris was so kind to send an invitation for Google+ – the new social network service you must hook into. Thanks Jim, now I had to fill in yet a profile, upload the same picture as always and start networking from scratch once again :-)

As many people I have several profiles in different social network services as Twitter, Facebook and LinkedIn. As I’m doing business also with German speaking countries I also use XING as alternative to LinkedIn as told in the post LinkedIn and the other Thing.

In a comment to that post my Austria based French connection Olivier Mathurin noted: “Disconnected duplicated siloed professional profiles, mmm…”

In a post on this blog called Social Master Data Management made one year ago it is discussed how social CRM will add new sources from social networks to the external reference data sources we already know from old time CRM.

With all the different faces everyone are wearing in the social media realm this isn’t going to be easy and one may consider if social master data management is a wrong path giving the individual nature and built-in privacy in social networking services.    

Well, Gartner (the analyst firm) says that increasing links between MDM and social networks is one of the Three Trends That Will Shape the Master Data Management Market.

So, acknowledging that Gartner predictions are self-fulfilling, you better get moving into LinkedIn, Xing, Viadeo, Twitter, Facebook, (forget MySpace), Google+  and what’s next.

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Non-Obvious Entity Relationship Awareness

16th March 2011

In a recent post here on this blog it was discussed: What is Identity Resolution?

One angle was the interchangeable use of the terms “Identity Resolution” and “Entity Resolution”. These terms can be seen as truly interchangeable, as that “Identity Resolution” is more advanced than “Entity Resolution” or as (my suggestion) that “Identity Resolution” is merely related to party master data, but “Entity Resolution” can be about all master data domains as parties, locations and products.

Another term sometimes used in this realm is “Non-Obvious Relationship Awareness”. Also this term is merely related to finding relationships between parties, for example individuals at a casino that seems to do better than the croupiers. Here’s a link to a (rather old) O’Reilly Radar post on Non-Obvious Relationship Awareness.

Going Multi-Domain

So “Non-Obvious Entity Relationship Awareness” could be about finding these hidden relationships in a multi-domain master data scope.

An example could be non-obvious relationships in a customer/product matrix.

The data supporting this discovery will actually not be found in the master data itself, but in transaction data probably being in an Enterprise Data Warehouse (EDW). But a multi-domain master data management platform will be needed to support the complex hierarchies and categorizations needed to make the discovery.   

One technical aspect of discovering such non-obvious relationships is how chains of keys are stored in the multi-domain master data hub.

Customer Master Data

The transactions or sums hereof in the data warehouse will have keys referencing customer accounts. These accounts can be stored in staging areas in the master data hub with references to a golden record for each individual or company in the real world. Depending on the identity resolution available the golden records will have golden relations to each other as they are forming hierarchies of households, company family trees, contacts within companies and their movements between companies and so on.

My guess as described in the post Who is working where doing what? is that this will increasingly include social media data.

Product Master Data

Some of the same transactions or sums hereof in the data warehouse will have keys referencing products. These products will exist in the master data hub as members of various hierarchies with different categorizations.

My guess is that future developments in this field will further embrace not just your own products but also competitor products and market data available in the cloud all attached to your hierarchies and categorizations.   

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Follow Friday Diversity

1st October 2010

Every Friday on Twitter people are recommending other tweeps to follow using the #FollowFriday (or simply #FF) hashtag.

So do I.

Below please find my follow Friday recommendations grouped by global region:

 

Canada: @carrni @datamartist @sheezaredhead @andrewsinfotech @aniagl @DQamateur @bivcons @projmgr @DQStudent @datachickUnited States: @GarnieBolling @stevesarsfield @UtopiaInc @bbreidenbach @fionamacd @RobertsPaige @BIMarcom @IDResolution @FirstSanFranMDM @dan_power @merv @NISSSAMSI @jilldyche @howarddresner @GartnerTedF @RobPaller @marc_hurst @dcervo @datamentors @VishAgashe @IBMInitiate @RamonChen @JackieMRoberts @philsimon @Nick_Giuliano @DataInfoCom @juliebhunt  @Futureratti  @dqchronicle  @jonrcrowell @elc  @Experian_QAS @paulboal @im4infomgt @WinstonChen @ocdqblog @KeithMesser @murnane @BrendaSomich @alanmstein @JGoldfed @jaimefitzgerald @tedlouie @bslarkin

Venezuela: @pigbar

Ireland: @daraghobrien @KenOConnorData @MapMyBusiness: United KIngdom: @SteveTuck @VeeMediaFactory @mktginsightguy @Daryl70 @Teresacottam @AnishRaivadera @ExperianQAS_UK @DataQualityPro @SarahBurnett @faropress @jschwa1 @mikeferguson1 @jtonline @Master_OBASHI @Nicola_Askham; France: @DataChannel @mydatanews @jmichel_franco @ydemontcheuil;Switzerland: @alexej_freund @openmethodology; Austria: @omathurin; Germany: @stiebke @dwhp @dakoller @marketingBOERSE; Belgium: @guypardon; Netherlands: @harri00413 @GrahamRhind; Denmark: @jeric40 @eobjects @StiboSystems;Norway @Orvei; Sweeden: @MrPerOlsson @DarioBezzina; Finland: @JoukoSalonen; Lithuania: @googlea; Italy: @Stray__Cat

Algeria: @aboussaidi; South Africa: @MarkGStacey

Pakistan: @monisiqbal; India: @MDMAnswers @twitrvenky @ashwinmaslekar; Indonesia: @VaiaTweets

Australia: @emx5 @vmcburney;New Zeeland: @JohnIMM @Intelligentform

It’s my hope, that I in the future will be able to interact even more diverse.

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Out of Facebook

1st September 2010

Some while ago it was announced that Facebook signed up member number 500,000,000.

If you are working with customer data management you will know that this doesn’t mean that 500,000,000 distinct individuals are using Facebook. Like any customer table the Facebook member table will suffer from a number of different data quality issues like:

  • Some individuals are signed up more than once using different profiles.
  • Some profiles are not an individual person, but a company or other form of establishment.
  • Some individuals who created a profile are not among us anymore.

Nevertheless the Facebook member table is a formidable collection of external reference data representing the real world objects that many companies are trying to master when doing business-2- consumer activities.

For those companies who are doing business-2-business activities a similar representation of real world objects will be the +70,000,000 profiles on LinkedIn plus profiles in other social business networks around the world which may act as external reference data for the business contacts in the master data hubs, CRM systems and so on.

Customer Master Data sources will expand to embrace:

  • Traditional data entry from field work like a sales representative entering prospect and customer master data as part of Sales Force Automation.
  • Data feed and data integration with traditional external reference data like using a business directory. Such integration will increasingly take place in the cloud and the trend of governments releasing public sector data will add tremendously to this activity.
  • Self registration by prospects and customers via webforms.
  • Social media master data captured during social CRM and probably harvested in more and more structured ways as a new wave of exploiting external reference data.

Doing “Social Master Data Management” will become an integrated part of customer master data management offering both opportunities for approaching a “single version of the truth” and some challenges in doing so.

Of course privacy is a big issue. Norms vary between countries, so do the legal rules. Norms vary between individuals and by the individuals as a private person and a business contact. Norms vary between industries and from company to company.

But the fact that 500,000,000 profiles has been created on Facebook in a very few years by people from all over world shows that people are willing to share and that much information can be collected in the cloud. However no one wants to be spammed by sharing and indeed there have been some controversies around how data in Facebook is handled. 

Anyway I have no doubt that we will see less data entering clerks entering the same information in each company’s separate customer tables and that we increasingly will share our own master data attributes in the cloud.

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Follow Friday Data Quality

28th August 2010

Every Friday on Twitter people are recommending other tweeps to follow using the #FollowFriday (or simply #FF) hash tag.

My username on twitter is @hlsdk.

Sometimes I notice tweeps I follow are recommending the username @hldsk or @hsldk or other usernames with my five letters swapped.

It could be they meant me? – but misspelled the username. Or they meant someone else with a username close to mine?

As the other usernames wasn’t taken I have taken the liberty to create some duplicate (shame on me) profiles and have a bit of (nerdish) fun with it:

@hsldk

For this profile I have chosen the image being the Swedish Chef from the Muppet show. To make the Swedish connection real the location on the profile is set as “Oresund Region”, which is the binational metropolitan area around the Danish capital Copenhagen and the 3rd largest Swedish city Malmoe as explained in the post The Perfect Wrong Answer.

@hldsk

For this profile I have chosen the image being a gorilla originally used in the post Gorilla Data Quality.

This Friday @hldsk was recommended thrice.

But I think only by two real life individuals: Joanne Wright from Vee Media and Phil Simon who also tweets as his new (one-man-band I guess) publishing company.

What’s the point?

Well, one of my main activities in business is hunting duplicates in party master databases.

What I sometimes find is that duplicates (several rows representing the same real world entity) have been entered for a good reason in order to fulfill the immediate purpose of use.

The thing with Phil and his one-man-band company is explained further in the post So, What About SOHO Homes.

By the way, Phil is going to publish a book called The New Small. It’s about: How a New Breed of Small Businesses is Harnessing the Power of Emerging Technologies.

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Business Directory Musings

27th July 2010

This coming Sunday I have worked professionally within Information Technology for 30 years. As I will be on a (well deserved!) vacation in Andalusia on Sunday, I’ll better post my thoughts today.

I have had a lot of different positions and worked in a lot of different domains. The single subject I have worked with the most is business directories.

My first job was at the Danish Tax Authorities and one of the assignments was being a secretary to the committee working for a joint registration of companies in Denmark. Besides I learned a lot about working in political driven organizations and about aligning business and technology I feel good about having been part of the start of building a public sector master data directory. Such directories are both essential for an effective public administration and can be used as external reference data in private enterprises as a valuable mean to improve data quality with business partner master data.

Later I have been working a lot with improving data quality through matching solutions around business directories. This goes from the Dun & Bradstreet WorldBase holding nearly 170 million business entities from all over the world, over databases like the EuroContactPool to national databases either holding all businesses (available) in a single country or given industry segments.

I guess I also will be spending some additional years from now with integrating business directory information into business processes as smooth as possible and preferable along with a range of other kind of external reference data.

One of the new sources building up in the cloud in the realm of business directories is master data references in social networks. The LinkedIn Companies feature is a prominent example. Of course such directories have some data quality issues. This is seen in looking at the companies where I currently work:

  • DM Partner A/S seems OK
  • Omikron Data Quality has 90 employees according to the company profile (filled out by yours truly). Then it’s strange that there are only 25 profiles in the network. But that’s because most employees are in Germany where the competing network called Xing is stronger.
  • Trapeze Group Europe has not been updated with a recent merger and not all profiles has changed their profile accordingly yet. But I’m sure that will be done as time goes by.

I have no doubt though that including information from social networks will become a part of integrating business partner master data in my future.

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