Business outcome is the end goal of any data management activity may that be data governance, data quality management, Master Data Management (MDM) and Product Information Management (PIM).
Business outcome comes from selling more and reducing costs.
At Product Data Lake we have a simple scheme for achieving business outcome through selling more goods and reducing costs of sharing product information between trading partners in business ecosystems:
The scientific news of the day is the observed collision of two neutron stars resulting in gravitational waves, an extremely bright flash – and gold.
The connection between gravitational waves and Master Data Management (MDM) was celebrated here on the blog when those waves were detected for the first time as told in the post Gravitational Waves in the MDM World.
Now we have seen a bright flash resembling what happens when two trading partners collide, as in makes business together encompassing sharing master data and product information. Seen from my telescope this improves data quality and thereby business outcome (gold, you know) as explained in the post Data Quality and Business Outcome.
In his post Andrew connects the classic dots: How does technology lead to business outcome? Especially the use of cloud solutions and the multi-tenant aspect is in the focus. Andrew asks: What do you see “out there”?
My view is that multi-tenant is not just about offering the same subscription based cloud solutions to a range of clients. It is about making clients sharing the same business ecosystem work in the same MDM realm. This is the platform described in Master Data Share.
Oh, and what does that have to do with business outcome? A lot. Organizations will not win the future the race by optimizing there inhouse MDM capabilities alone. With the rise of digitalization, they need to connect with and understand their customers, which I believe is something Reltio is good at. Furthermore, organisations need to be much better at working with their business partners in a modern way, including at the master data level. The business outcome of this is:
Having complete, accurate and timely data assets needed for understanding and connecting with customers. You will sell more.
Having a fast and seamless flow of data assets, not at least product information, to and from your trading partners. You will reduce costs.
Having a holistic view of internal and external data needed for decision making. You will mitigate risks.
Some of the hot topics on the agenda today is the EU General Data Protection Regulation (GDPR) and the data lake concept. These are also hot topics for me, as GDPR is high on the agenda in doing MDM (and currently TDM – Test Data Management) consultancy and the data lake approach is the basic concept in my Product Data Lake venture.
In my eyes the data lake concept can be used for a lot of business challenges. One of the them was highlighted in a CIO article called Informatica brings AI to GDPR compliance, data governance. In here Informatica CEO Anil Chakravarthy tells how a new tool, Informatica’s Compliance Data Lake, can help organisations getting a grasp on where data elements relevant to be compliant with GDPR resides in the IT landscape. This is a task very close to me in a current engagement.
In here Julie says: “Adoption of cloud-based MDM or MDM-as-a-Service is on the rise, opening up new dimensions for how organizations take advantage of MDM and data governance.”
Julie’s article is part 3 of a six part series on the “New Age of Master Data Management”, so I may touch on a dimension that is covered in the upcoming articles. This dimension is how business ecosystems must be a part of your organizations MDM roadmap, and that dimension is, according to Gartner, the analyst firm, covering 8 underlying dimensions as told in the post From Business Ecosystem Strategy to PIM Technology.
Working with MDM in a business ecosystem context does require MDM in the cloud of some sort. Inhouse Mater Data Management and Product Information Management (PIM), which may be on premise or in the cloud or perhaps a hybrid, is only the beginning. Collaboration with business partners in a sophisticated environment will be controlled by a cloud solution.
Master Data Management (MDM) is a lot about data modelling. When you buy a MDM tool it will have some implications for your data model. Here are three kinds of data models that may come with a tool:
An off-the-shelf model
This kind is particularly popular with customer and other party master data models. Core party data are pretty much the same to every company. We have national identification numbers, names, addresses, phone numbers and that kind of stuff where you do not have to reinvent the wheel.
Also, you will have access to rich reference data with a model such as address directories (which you may regard as belonging to a separate location domain), business directories (as for example the Dun & Bradstreet Worldbase) and in some countries citizen directories as well. MDM tools may come with a model shaped for these sources.
Tools which are optimized for data matching, including deduplication of party master data, will often shoehorn your party master data into a data model feasible for that.
A buildable model
When it comes to multi-domain MDM we will deal with entities that are not common to everyone.
Here a capability to build your model in the MDM tool is needed. One such tool I have worked with is Semarchy. Here semi-technical people are able to build and deploy incrementally more complex data models, that are default equipped with needed functionality around handling a golden copy and auditing data onboarding and changing.
A dynamic model
Product Information Management (PIM) requires that your end users can build the model on the fly, as product data are so different between product groups.
This model resembles the data model in most PIM solutions (and PIM based MDM solutions), except that we have the party and their two-way partnerships at the top, as Product Data Lake takes care of exchanging data between inhouse PIM solutions at trading partners participating in business ecosystems.
So, it may be about time to take some bets on the next one.
First question will naturally be if Gartner is able to get the report out this year? Last year it was scheduled for November 2016 but was two months late into the next year, maybe due to some struggling with the vendors, who also are clients at Gartner, based on the form of a single MDM quadrant opposite to earlier years multiple MDM quadrants for customer and product MDM.
The scheduled date on the Gartner website is 10/31/17, which to none US people reads at the 10th day in the 31st month in year 17.
Next question is if there are new entries or vendors dropping off? Another market report from Information Difference had a somewhat different crowd as examined in the post Varying Views on the MDM Market 2017.
In the comments to this post readers have posted questions about Magnitude Software, TIBCO Software and Riversand Technologies. Are they in danger? And who might be new entries?
Finally, of course we can have a guess on who will be able to brag about being the leaders. Will Informatica and Orchestra Networks be followed by other ones? Riversand was close last year in that visionaries space. Stibo Systems moves in from the challengers room.
Feel free to have your bet, or set the odds, in the comments below.