Missing Parts to Model Relation Information: The Biggest Roadblock in realizing “Connected” Use Case

In my first blog on this series “Connected Common Sense,” I had mentioned about the failure to derive value from data and make it meaningful due to missing building blocks. In this blog, I will focus on one such example.
To enable “connected” use case for predictive service – a basic building block is the availability of correct technical information about the product and well-maintained parts to a model relationship. For most  manufacturers – this is the missing link and quickly becomes a major roadblock in taking connected use-case from a mere MVP to a real-life feature.
I recently got the first-hand experience of this “missing link” when my leading brand refrigerator’s water line broke last month. My service technician had to make three visits before the nasty water leakage was finally repaired. The biggest problem was to find the part number. The local appliance store had to spend almost an hour, including multiple phone calls with the manufacturer to figure out the part needed for the repair. Finally, when the part arrived – it didn’t fit in as there was a slight variation in my model.
Even if you factor in-store clerk and service technician’s technical aptitude – the information was not available to them easily, and they had to scramble around for a piece of information at the expense of a disgruntled customer.
This is not a unique experience, and I am sure you have your share of stories too. However, the crux of the problem lies in buried data either in disparate systems or within different departments. This breaks the information chain and eventually impact the serviceability of a product. How can you expect your digital drive to be successful with incoherent data?
So, now we understand the business repercussion of ‘buried data’ not being easily available to aftermarket departments. But why does the missing link between parts to model exists? Let’s drill down to the bottom of the problem. 
Right at the inception of the production process, OEMs use Product lifecycle management (PLM) tools to manage engineering drawings, engineering bill of materials (E-BOMs) and keep track of different versions as engineering changes are made. As the product lifecycle matures from PLM to the manufacturing stage, the E-BOM from PLM systems should get converted (automatically or manually) to the manufacturing bill of materials (M-BOM). Ideally, there should be a tight integration between PLM and manufacturing to enable this information flow of BOMs and a smooth transition from PLM to manufacturing. However, historically, PLM Tools providers (focused on Engineering drawing and repository tools) and Manufacturing ERP Solution providers (focused on production processes) have remained in two different silos. Most OEMs, therefore, fail to maintain robust documentation right at the production stage.
As the product gets rolled out in the market, OEMs have to provide service parts for these new models available in the market or at dealerships. However, very few companies typically use Service-BOM concept to identify clearly their service parts – OR – they identify service parts in their generic product BOM. Many companies identify the serviceable parts only during their Parts Catalog authoring process, and the information remains buried in Parts catalogs. Again, a classic case of information remaining buried in disparate documentation and not getting passed to the next stage.
This situation gets even more complicated for a global company with decentralized operations, where country / region specific models are handled locally. This means that the master data of models may get customized and locked in disparate local IT systems, which in an ideal scenario should have been maintained in a homogenous system and made accessible to all regions.
Stretch this problem over 10 – 15 years (average mid-sized commercial machine/home appliance life) and you have various life-events that has affected the serviceability of that machine.
Multiple Model Changes, Model Consolidations (regional, strategic changes or thru mergers)
Model Obsolescence, Part Substitutions due to engineering changes, Part Substitutions due to supplier changes, Part / Component Changes due to Warranty issues, Design ownership changeover of parts from proprietary to All Makes.
In each of these life-events of a machine, service BOM is affected but is not maintained in master data Or is maintained but not in a homogeneous integrated system. In most of the companies – the only place this information goes in is Parts Catalog process, which feeds it into other parts distribution IT systems – on need basis.
Needless to say – in most of the cases, the information chain is broken, associativity of Parts to a Model relationship is lost – or best case – buried deep in disparate systems.
 
So while organizations spend millions on an IoT platform and build shiny POCs that works great for a couple of machines, rolling out a full-fledged connected aftermarket use case for all products is sheer fantasy.  No matter how many ‘boutique agencies’ you outsource or how much dollars you invest, the solution lies in applying common sense and work backward towards building a solid groundwork.
 
My next blog covers perhaps the most crucial aspect of connected common sense – Technology First or Business First, highlighting the importance of an empowered workforce to reimagine a connected business model. Stay tuned!

• connected business model
• Digitization
• IoT
• OEM
• Product lifecycle management