Today I attended the Informatica MDM Day for EMEA here in London.
London has a lot of attractions. If you for example want to see a lot of big price tags and go to a public toilet with a very nice odeur the place to go is the famous luxury department store called Harrods.
Harrods, represented by Peter Rush, presented their Product Information Management (PIM) journey at the Informatica event. So, how does a luxury PIM implementation look like?
It starts with realising that traditional product master data in retail has mostly been about the buy-side, but today, not at least in light of the multi-channel challenge, you must add the sell-side to product master data, meaning having customer friendly product information.
After setting that scene Harrods went into selecting a PIM solution, meaning eliminating possible vendors one by one until the lucky one was chosen. In this case Heiler (now Informatica). In the last stages evaluated vendors were sent home based on criteria like roadmap, being in Texas and as the last step the price.
Some years ago I wrote a blog post called Hierarchical Completeness. This post also had some excellent comments and David Loshin made a good follow up post called Hierarchy Data Completeness and Semantic Convergence.
The importance of hierarchical completeness, not at least within Product Information Management (PIM), has become close to me again.
It is a numbers game. Often having an advanced PIM solution on board is based by the fact that you have many products to manage. Too many products for a single data steward to control. Add to that today’s challenges of doing multi-channel business and tomorrows challenges of embracing social media engagement. This means a lot more attributes and digital assets per product and perhaps more products to manage as told in the post called Social PIM.
All products aren’t equal. The one size fits all term doesn’t apply to selling shoes or any other range of products. The attributes and assets needed differ per product categorization and the performance measures and expectations for each product.
No, this is not an(other) attempt to challenge Gartner, the analyst firm, in making quadrants about vendors in the Master Data Management (MDM) realm.
This an attempt to highlight some capabilities of Multi-Domain MDM solutions here focusing on party and product master data and the sell-side and the buy-side of MDM as discussed some years ago in the post Sell-side vs Buy-side Master Data Quality.
A simple quadrant will look like this:
- The upper right corner is where MDM started, being with solutions back then called Customer Data Integration (CDI).
- The Product Information Management (PIM) side is quite diverse and depending on the industry vertical where implemented:
- Retailers and distributors have their challenges with sometimes high numbers of products that goes in and comes out as the same but with data reflecting different viewing points.
- Manufacturers have other issues managing raw materials, semi-finished products, finish products and products and services used to facilitate the processes.
- Everyone have supplies.
- The supplier master data management has more or less also been part of the PIM space but looks more like customer master data and should be part of a party master data discipline also embracing other party roles as employee.
Also, this quadrant is by the way without other important domains as location (as discussed in the post Bringing the Location to Multi-Domain MDM) and asset (as discussed in the post Where is the Asset?)
A big talk in the media in Denmark this weekend is the story about that a little harbor restaurant specializing in serving fish has been denied continuing using the name Jensens Fiskerestaurant (Jensen’s Fish Restaurant in English). A lower court has earlier disallowed the name Jensens Fiskehus (Jensen’s Fish House in English).
The opponent is a large restaurant chain called Jensen’s Bøfhus (Jensen’s Beef House in English).
This has brought a so called shitstorm over the restaurant chain in social media, not at least on Facebook. Jensen is the most common surname in Denmark. A bit more than a quarter of a million people, which is 5 percent of the population, are called Jensen. So how can a big chain be the only one allowed to use the name Jensen for a restaurant?
PS: I remember this nasty restaurant chain name from when I coded name parsing routines in the old days. “Jensen’s Bøfhus” initially came out as “S. Bøfhus Jensen”. Some of the remedy was to apply external reference data to name parsing as checking if a business entity with a similar name exists on the address.
One of the top challenges in product Master Data Management (MDM) is the sharing of master data attributes and digital assets across the ecosystem of manufacturers, distributors, retailers and end users.
There seems to be a range of solutions emerging in order to cover that land. Three kinds of approaches will be:
- Supplier engagement within Product Information Management (PIM) solutions.
- Similar solutions within wider IT offerings.
- Social PIM.
Master Data Management (MDM) platforms with strong offerings for the product domain comes with built-in functionality for engaging suppliers in the process of collecting product master data attributes and related materials as product sheets, images and other digital assets.
You may also find similar functionality within the broader software suites as for example the SAP Product Stewardship Network.
A somewhat different approach may be called Social PIM as explained in the post Time to Turn Your Product Master Data Social? Here the collection process is sort of independent of in-house systems. This may, in the long run, help with having your suppliers having to attend many different solutions and also help your customers depending on where you sit in the ecosystem.
What is your experience regarding sharing product master data?
When we talk about multi-domain Master Data Management (MDM) we often focus on the two dominant MDM domains being customer (or rather party) MDM and product (or maybe things) MDM.
The location domain is the third bigger domain within MDM. Location management can be more or less complex depending on the industry vertical we are looking at. In the utility and telco sectors location management is a big thing. Handling installations, assets and networks is typically supported by a Geographical Information System (GIS).
Master Data Management is much about supporting that different applications can have a unified view of the same core business entities. Therefore, in the utility and telco sectors a challenge is to bring the GIS application portfolio into the beat with other applications that also uses locations as explained in the post Sharing Big Location Reference Data.
The last couple of days I enjoyed taking part in the Nordic user conference for a leading GIS solution in the utility and telco sector. This solution is called Smallword.
It is good to see that at least one forward looking organization in the utility and telco sector is working with how location master data management can be shared between business functions and applications and aligned with party master data management and product master data management.
Last week I had some fun making a blog post called The True Leader in Product MDM. This post was about how product Master Data Management still in most places is executed by having heaps of MS Excel spreadsheets flowing around within the enterprise and between business partners, as I have seen it.
When it comes to customer Master Data Management MS Excel may not be so dominant. Instead we have MS CRM and the competing offerings as Salesforce.com and a lot of other similar Customer Relationship Management solutions.
CRM systems are said to deliver a Single Customer View. Usually they don’t. One of the reasons is explained in the post Leads, Accounts, Contacts and Data Quality. The way CRM systems are built, used and integrated is a certain track to create duplicates.
Some remedies out there includes periodic duplicate checks within CRM databases or creating a federated Customer Master Data Hub with entities coming from CRM systems and other databases with customer master data. This is good, but not good enough as told in the post The Good, Better and Best Way of Avoiding Duplicates.
During the last couple of years I have been working with the instant Data Quality service. This MDM service sits within or besides CRM systems and/or Master Data Hubs in order to achieve the only sustainable way of having a Single Customer View, which is an instant Single Customer View.