“…good argument for a merged OSS/BSS, wouldn’t you say?”
The question above was posed in relation to Friday’s post about the currency and relevance of OSS compared with research reports, analyses and strategic plans as well as how to extend OSS longevity.
This is a brilliant, multi-faceted question from John. My belief is that it is a double-edged sword.
Out of my experiences with many OSS, one product stands out above all the others I’ve worked with. It’s an integrated suite of Fault Management, Performance Management, Customer Management, Product / Service Management, Configuration / orchestration / auto-provisioning, Outside Plant Management / GIS, Traffic Engineering, Trouble Ticketing, Ticket of Work Management, and much more, all tied together with the most elegant inventory data model I’ve seen.
Being a single vendor solution built on a relational database, the cross-pollination (enrichment) of data between all these different modules made it the most powerful insight engine I’ve worked with. With some SQL skills and an understanding of the data model, you could ask it complex cross-domain questions quite easily because all the data was stored in a single database. That edge of the sword made a powerful argument for a merged OSS/BSS.
Unfortunately, the level of cross-referencing that made it so powerful also made it really challenging to build an initial data set to facilitate all modules being inter-operable. By contrast, an independent inventory management solution could just pull data out of each NMS / EMS under management, massage the data for ingestion and then you’d have an operational system. The abovementioned solution also worked this way for inventory, but to get the other modules cross-referenced with the inventory required engineering rules, hand-stitched spreadsheets, rules of thumb, etc. Maintaining and upgrading also became challenges after the initial data had been created. In many cases, the clients didn’t have all of the data that was needed, so a data creation exercise needed to be undertaken.
If I had the choice, I would’ve done more of the cross-referencing at data level (eg via queries / reports) rather than entwining the modules together so tightly at application level… except in the most compelling cases. It’s an example of the chess-board analogy.
If given the option between merged (tightly coupled) and loosely coupled, which would you choose? Do you have any insights or experiences to share on how you’ve struck the best balance?