Master Data

GDPR Data Portability and Master Data Sharing

Henrik Gabs Liliendahl2 Comments

PortabilityOne of the controversial principles in the upcoming EU GDPR enforcement is the concept of data portability as required in article 20.

In legal lingo data portability means: “Where the data subject has provided the personal data and the processing is based on consent or on a contract, the data subject shall have the right to transmit those personal data and any other information provided by the data subject and retained by an automated processing system, into another one, in an electronic format which is commonly used, without hindrance from the controller from whom the personal data are withdrawn.”

In other words, if you are processing personal data provided by a (prospective) customer or other kind of end user of your products and services, you must be able to hand these data over to your competitor.

I am sure, this is a new way of handling party master data to almost every business. However, sharing master data with your competitor is not new when it comes to product master data as examined in the post Toilet Seats and Data Quality.

Sharing party master data with your competitor will be yet a Sunny Side of GDPR.

MDM / PIM Platform Vendors Need to Grow Up Too

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Participating in digital ecosystems is the way forward for enterprises who wants to be tomorrow’s winners through digital transformation.

Some figures from Gartner, the analyst firm, tells this about digital transformation:

  • 79% of top performing companies indicate that they participate in a digital ecosystem
  • 49% of typical companies indicate the same
  • 24% of trailing companies does it

These figures were lately examined by Bryan Kirschner of Apigee (now part of Google) in a Cio.com article called Ecosystems: when digital transformation grows up.

Master Data Share
Master Data Share for Business Ecosystems

As a Master Data Management (MDM) and/or Product Information Management (PIM) platform vendor you should support your current and prospective clients with means to participate in digital ecosystems.

Current offerings from MDM and PIM platforms vendors have become quite mature in supporting inhouse (enterprise wide) handling of master data and product information. Next step is supporting sharing within business ecosystems. A concept for that is introduced in Master Data Share.

The Sunny Side of GDPR

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Happy SunDon’t panic about GDPR. Don’t neglect either. Be happy.

Recently Ditte Brix Andersen of Stibo Systems wrote a blog post called Preparing for GDPR – Burden or Opportunity?

As Ditte writes, the core implication of GDPR is: “Up until now, businesses have traditionally ‘owned’ the personal data of their customers, employees and other individuals. But from May 25th, 2018 individuals will be given several new personal data rights, putting the ownership right back in to the hands of each individual”.

I agree with Ditte that the GDPR coming into force can be seen as an opportunity for businesses instead of a burden. Adhering to GDPR will urge you to:

  • Have a clear picture about where you store personal data. This is not bad for business too.
  • Express a common understood idea about why you store personal data. Also very good for business.
  • Know who can access and update personal data. A basic need for risk handling in your business.
  • Document what kind of personal data you handle. Equally makes sense for doing your business.
  • Think through how you obtain consent to handle personal data. Makes your business look smart as well.

In fact, after applying these good habits to personal data you should continue with other kind of party master data and all other kinds of master data. The days of trying to keep your own little secret, even partly to yourself, versions of what seems to be the truth is over. Start working in the open as exemplified in the concept of Master Data Share.

Master Data or Shared Data or Critical Data or What?

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What is master data and what is Master Data Management (MDM) is a recurring subject on this blog as well as the question about if we need the term master data and the concept of MDM. Recently I read two interesting articles on this subject.

Andrew White of Gartner wrote the post Don’t You Need to Understand Your Business Information Architecture?

In here, Andrew mentions this segmentation of data:

  • Master data – widely referenced, widely shared across core business processes, defined initially and only from a business perspective
  • Shared application data – less widely but still shared data, between several business systems, that links to master data
  • Local application data – not shared at all outside the boundary of the application in mind, that links to shared application and master data

Teemu Laakso of Kone Corporation has just changed his title from Head of Master Data Management to Head of Data Design and published an article called Master Data Management vs. Data Design?

In here, Teemu asks?

What’s wrong in the MDM angle? Well, it does not make any business process to work and therefore doesn’t create a direct business case. What if we removed the academic borderline between Master Data and other Business Critical data?

The shared sentiment, as I read it, between the two pieces is that you should design your “business information architecture” and the surrounding information governance so that “Data Design Equals Business Design”.

My take is that you must look from one level up to get the full picture. That will be considering how your business information architecture fits into the business ecosystem where your enterprise is a part, and thereby have the same master data, shares the same critical data and then operates your own data that links to the shared critical data and business ecosystem wide master data.

Master Data or

IIoT (or Industry 4.0) Will Mature Before IoT

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Internet of Things (IoT) is a hot topic in the data management world and yours truly is also among those who sees IoT as a theme that will have a tremendous impact on data management including data quality, data governance and Master Data Management (MDM).

However, I think the flavour of IoT called Industrial Internet of Things (IIoT) or Industry 4.0 will mature, and already have matured, before the general IoT theme.

globalIIoT / Industry 4.0 is about how manufacturers use connected intelligent devices to improve manufacturing processes where the general IoT theme extends the reach out in the consumer world – with all the security and privacy concerns related to that.

A clue about the maturity in IIoT is found in a Forbes article by Bernard Marr. The article is called Unlocking The Value Of The Industrial Internet Of Things (IIoT) And Big Data In Manufacturing.

In this article, Justin Hester of automotive part manufacturer Hirotec tells about their approach to embracing IIoT. Justin Hester states that “…we can finally harness the data coming in from all of these different sources, whether they are machines, humans, parts – but I think the real challenge is the next step – how do I execute? That’s the challenge.”

Indeed, how to execute and take (near) real-time action on data will be the scenario where Return on Investment (ROI) will show up. This means, as explained in the article, that you should make incremental implementations.

It also means, that you must be able to maintain master data that can support (near) real-time execution. As IIoT/Industry 4.0 is about connected devices in business ecosystems, my suggestion is a data architecture as described on Master Data Share.

Your Toughest Upstream Product Information Sharing Issue

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Only 5 percent of organizations share all their product data electronically with supply chain partners. So, there is room for improvement.

At Product Data Lake we want to find out what are the issues that is holding companies back from smoothly sharing product information with trading partners.

We will start with where product information is born: Upstream, at the manufacturer. If you work at a company being a manufacturer of goods, please answer the below question:

PS: If you do not work for a manufacturer, but know someone who does, please forward the poll.

Encompassing Relational, Document and Graph the Best Way

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The use of graph technology in Master Data Management (MDM) has been a recurring topic on this blog as the question about how graph approaches fits with MDM keeps being discussed in the MDM world.

Multi-Domain MDM GraphRecently Salah Kamel, the CEO at the agile MDM solution provider Semarchy, wrote a blog post called Does MDM Need Graph?

In here Salah states: “A meaningful graph query language and visualization of graph relationships is an emerging requirement and best practice for empowering business users with MDM; however, this does not require the massive redesign, development, and integration effort associated with moving to a graph database for MDM functionality”.

In his blog post Salah discusses how relationships in the multi-domain MDM world can be handled by graph approaches not necessarily needing a graph database.

At Product Data Lake, which is a business ecosystem wide product information sharing service that works very well besides Semarchy MDM inhouse solutions, we are on the same page.

Currently we are evaluating how graph approaches are best delivered on top of our document database technology (using MongoDB). The current use cases in scope are exploiting related products in business ecosystems and how to find a given product with certain capabilities in a business ecosystem as examined in the post Three Ways of Finding a Product.

Room for Improvement in the PIM World

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Ventana Stibo ReportThe analyst firm Ventana Research recently made a report called The Next Generation of Product Information Management with the subtitle Maximizing the Potential Value of Products for Customers and Suppliers.

One, perhaps shocking, number mentioned in the report is that there is “room for improvement, as only 5 percent of organizations share all their product data electronically with supply chain partners”.

However, this resonates very well with my experience, as it has been hard to find a good way to share all kind of product information electronically with all your trading partners, as:

  • The most common used way today is exchanging spreadsheets, which is cumbersome and error prone and therefore many companies experience that it simply is not done or only done partly and certainly not timely.
  • Using consensus data pools (eg GS1 GDSN) only covers a fraction of product groups and product data elements with varying penetration and coverage in different geographies
  • Providing supplier product data portals (and customer product data portals) is a flawed one-sided concept as discussed in the post PIM Supplier Portals: Are They Good or Bad?

This is the reason why Product Data Lake has been launched.

You can get an 18 pager write up of the research report free from Stibo Systems here.

PS: If you are a PIM solution vendor or a PIM system integrator you can, as a legal entity, help with and gain from filling this room by becoming a Product Data Lake Commissioner.

MDM Summit Europe 2017 Preview

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Next week we have the Master Data Management (and Data Governance) Summit Europe 2017 in London. I am looking forward to be there.

MDMDG2017The Sponsors

Some of the sponsors I am excited to catch up with are:

  • Semarchy, as they have just released their next version multi-domain (now promoted as multi-vector) MDM (now promoted as xDM) offering emphasizing on agility, smartness, intelligence and being measurable.
  • Uniserv, as they specialize in hosted customer MDM on emerging technology infused with their proven data quality capabilities and at the same time are open to coexistence with other multi-domain MDM services.
  • Experian Data Quality, as they seem to be a new entry into the MDM world coming from very strong support for party and location data quality, however with a good foundation for supporting the whole multi-domain MDM space.

The Speakers

This year there are a handful of Danish speakers. Can’t wait to listen to:

  • Michael Bendixen of Grundfos pumping up the scene with his Data Governance Keynote on Key Factors in Successful Data Governance
  • Charlotte Gerlach Sylvest of Coloplast on taking care of Implementing Master Data Governance in Large Complex Organisations
  • Birgitte Yde and Louise Pagh Covenas of ATP telling how they watch after my pension money while being on a Journey Towards a New MDM System
  • Erika Bendixen of Bestseller getting us dressed up for Making Master Data Fashionable by Transforming Information Chaos into a Governance-Driven Culture.

10 Analyst Firms in the MDM Space

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When working with Master Data Management (MDM) it is always valuable to follow the analyst firms that are active on this subject and the related subjects as data quality, data governance and data management in general. You can learn from their insights – and disagreements – on the matters. Here are 10 analyst firms I follow:

Gartner, the large analyst firm known for their magic quadrants, hype cycles and cool vendor lists. There is a lot of brain power in this firm and they have never been caught in admitting a mistake. Quite a lot of posts on this blog mentions Gartner.

Forrester, another firm with heaps of analysts. Forrester has though been less prominent in the MDM world since Robert Karel left for Informatica. However, there are lots of wider insights to gain from as mentioned in the post Ecosystems are The Future of Digital and MDM.

The MDM Institute, which basically is Aaron Zornes, known as the Father Christmas of MDM. Aaron Zornes was the inspirational source in my recent post called MDM as Managed Service.

The Information Difference, headed by Andy Hayler. They publish a yearly MDM landscape report latest referenced on this blog in the post Emerging Database Technologies for Master Data.

Bloor Group has occasionally made reports about MDM latest mentioned on this blog in the post The MDM Market Wordle.

Ventana Research has been especially active around Product Information Management (PIM) as seen in the recent press release on their Product Information Management Research.

Intelligent Business Strategies, run by Mike Ferguson. No nonsense, plain English insights from the around the UK Midlands. Home page here.

Constellation Research, the Silicon Valley perspective. Home page here.

The Group of Analysts has published a series of interviews with MDM and PIM notabilities as for example this one with Richard Hunt of Agility Multichannel on Content Gravity.

Aberdeen Group, a company you as a MDM vendor can hire to put numbers on your blog as for example Stibo Systems did here.

Analysts