Now that we have determined that MDM, Data Governance, Data Cleansing and Data Quality are important as well as the new trend for blogging, tweeting and discussion in general, I ask the most important question . . . HOW? When do we get to the discussions on the content?
I am a very detail oriented person; I have to be as one of my largest accounts requires me to participate in the day to day deployment of global MDM processes for one the largest automotive manufacturers! I am very interested to learn how businesses in other industries manage their data. I would hope that sharing of information and best practices among industry partners will be a win-win situation. At a minimum the discussion will be refreshing; the sharing of innovative information the will spawn the creative improvement needed to create truly efficient knowledge driven business processes, data classifications, metadata and definitions and translation. . . is anyone interested in discussing the logistics of managing translation as part of Master Data Management?
Is anyone interested in discussing my struggles and sharing yours trying to find standard global translations for ISO UOM (Unit of Measures)?
Is anyone interested in discussing what fields should be included in a MDM Data Governance Program for MRO data; UNSPSC, warranty, term of warranty, lead time, estimated price, ECCN, etc.
What Schema or classification structures are you using for spare parts and maintenance items? What about a discussion on using a public vs. priority classification system?
What are some best practices for migrating, profiling, structuring, mismatching and re-verifying legacy system data?
We have a nifty data mismatch process for manufacturer contact information; will this be easily implemented for a CRM data project? What about patient contact information in the healthcare industry?
There are a few bloggers out there that continually add content to their writings but it is starting to appear to be a small group, anyone out there interested in achieving data quality want to discuss “real” life best practices, lesson learned or discuss HOW of MDM, data quality or data cleansing.
Tags: automotive, Data Cleansing, data quality, DATAForge, dataquality, ECCN, eOTD, linkedin, manufacturing, mdm, MRO, spare parts, Translation, UNSPSC
Jackie, I am with you on this one.
No doubt that we need discussions on why data governance, master data management and data quality is important – and sure we actually also have that in the blogosphere.
Also we need to exchange ideas on how to establish ROI for these disciplines. That exist too.
But we certainly also need to share concrete opinions, experiences and observations on exactly how to achieve improvements – may they be of general nature or be specific to the single entity types and lines of business.
This will actually help in going round the circle. If we know how to solve the issues we will be much better in clarifying the investment part of the ROI. In doing that we will see that most people actually already know that data quality etc. is important, but many people, not at least senior management, don’t want to go to action if there is no facts for how to succeed.
In the realm of data quality tools and services there seem to be some trend of having it look like a kind of magic sorcery. It is a kind of an art – but as you have pointed out, it is mostly a question of ensuring efficient knowledge driven business processes, having the right data classifications and metadata definitions, activating translations and so on.
There is a whole world of real world examples we can share.
Jackie,
I’m in! As the name of my blog implies, The Data Quality Chronicle was setup to do just as you propose; get into the details of how data quality is implemented. With regard to the specific questions you asked above, I’m most experienced with cleansing/profiling and implementation of CDI with CRM packages (Microsoft Dynamics CRM to be specific).
I look forward to the exchange!
William
Jackie,
To pick up on one of your questions – classification of maintenance items, I have a real world example that demonstrates just how challenging this can be!
On a recent project I needed to develop the requirements for an asset register for a major rail project. The complication was the fact that different organisations would be managing the assets on completion of the project. The two main organisations have different asset classification structures which are totally incompatible. Due to their different origins, they reflect different classes of assets in different ways, have different levels of granularity, and different ‘branches’ in the tree structure. Additionally, both organisations are continuing to refine their classifications on an ongoing basis, with no synchronisation and no driver to adopt a more consistent approach.
A further complication is that the CAD team use the Uniclass coding system, which is fine for buildings etc. but is light on the particular assets required.
I was able to develop an approach which all parties are happy with, but this did make the overall process more complex than a typical infrastructure project.
Hope this example is of some use.
Julian
Hi Jackie
I hear you.
One of my goals for Data Quality Pro was to create a channel for the many practitioners who can’t find the time to get to conferences or even blog about how they are delivering these initiatives on the ground.
I think the DQ/MDM/DG blogosphere has really expanded in the last 12 months but I agree we could do with a lot more case studies and practical accounts.
Shameless plug coming up…
I’m launching http://www.DQDirections.com late in Q2 this year to provide a virtual presentation platform for many of these case study organisations, many of them I’m sure will find their way out onto the blogosphere in the form of interviews and podcasts.
In the meantime, I’m also keen to gather and collaborate on more “how” stories, theory is great but I agree we need more stories from the coalface.
Jackie,
Count me in too.
I will be happy to share real world examples from my experience in requirements definition, sourcing, migrating, profiling, structuring, mismatching and re-verifying legacy system data.
I look forward to learning from the experience of others. Working together we can achieve far more.
Ken
So are you going to set up a mailing list Jackie? Google groups or something? I guess the interest is there.
DaveP
What makes it so difficult is that business processes ultimately drive many of the things you mentioned, Jackie. So, in your example, the fields included in an MRO project would be driven by the business processes that are in play. We have to start by asking “what does the business need in order to accomplish its mission?” In my experience from the vendor side of things, the process would not only vary across industry, but vary within an industry. Ford wouldn’t use the same MRO schema as Chrysler because they have different business processes.
In Julian’s response, you can see how the business processes of two similar companies challenged him – great insight into how processes drive schema.
Ultimately, we’re dependent upon factors like corporate history, business processes, partnerships, the corporation’s position as a leader, and future business expansion plans to help us build a custom job every time. It certainly doesn’t make the job of a consultant easy.
Steve
Dave,
If you are participating in Linked In, I have a Data Cleansing User Group to discuss and understand how to improve data quality. I also just created a parallel Google group. The statistics around Data Quality are overwhelming and there are mountains of discussions, white papers and tweets available pertaining to Data Quality, Governance, Profiling and Master Data Management. I think we need to take a step into the details to discuss and understand how to improve data quality by reviewing processes, sharing lessons learned and tips n’ tricks of data cleansing.
Jackie
Steve,
Interesting enough, a standardized MRO schema is exactly what my goal is. Currently we classify (name) the MRO items to the manufacturer verified item name and attributes to describe the items. The standardization permits accuracy in purchasing and set up of tasking for maintenance. I have actually had an introductory meeting with Automotive Industry Action Group (AIAG), discussing the options of driving standard MRO naming conventions to support manufacturers, tier 1, tier 2, etc. We are working with ECCMA’s Open Technical Dictionary to drive standard naming conventions and attributes providing a technical description to support not only purchasing but engineering and manufacturing.
Jackie
If that’s your goal, it’s groundbreaking and important work. Go get ‘em. Keep a journal, because when it’s all done, you should write the book.
Julian,
Just curious did you maintain the two different naming structures and providing a dynamic referencing system? Were each of the classification home grown or were they public classification structures?
The classification of maintenance items is a challenge especially when you are working at multiple manufacturing facilities where the terminology and classifications are localized. We set up the standards, provided a clean classified and attributed record verified to the manufacturer of the component to the plant which improved our ability to standardize the MRO data up front. Part of our work with the maintenance and engineering departments was to set up synonym search capabilities which enhance the ability to find a part.
Jackie
[...] Data Quality Open Issues and Questions? – Jackie Roberts of DATAForge issues the blogosphere challenge of discussing real-world best practices for MDM, data governance, and data quality. This blog post received some great comments. [...]