Let’s say you act for a service provider and the diagram below represents the number of variations you could offer to customers – the number that are technically supported by your solution.
That’s 13,824,000 colours.
By comparison, the following diagram contains just 20 colours:
If I asked you what colours are in the upper diagram, would you say red, orange, yellow, green, blue, etc? Is it roughly the same response as to the lower diagram?
If you’re the customer, and know you want an “orange*” product, will you be able to easily identify between the many thousands of different orange hues available in the upper diagram? Would you be disenfranchised if you were only offered the two orange hues in the lower diagram instead of thousands? Or might you even be relieved to have a much easier decision to make?
The analogy here to OSS is that just because our solutions can support millions of variants, doesn’t mean we should. If our OSS try to offer millions of variants, it means we have to design, then build, then test, then post-sale support millions of variants.
However, in reality, we can’t provide 100% coverage across so many variants – we aren’t able to sufficiently design, then build, then test, then post-sale support every one of the millions of variants. We end up overlooking some or accept risk on some or estimate a test spread that bypasses others. We’ve effectively opened the door to fall-outs.
And it’s fall-outs that tend to create larger customer dissatisfaction metrics than limited colour palettes.
Just curious – if you’ve delivered OSS into large service providers, have you ever seen evidence of palette analysis (ie variant reduction analysis) across domains (ie products, marketing, networks, digital, IT, field-work, etc)?
For example, have you ever seen a product list, the SKUs (Stock-keeping units, or distinct product offerings) in your product catalogue, running into the tens or hundreds of thousands? That’s a decision that’s been made upstream of our OSS, but has a massive impact in the complexity of what we have to design, build, test, manage and maintain.
Alternatively, have you ever pushed back on decisions made upstream to say you’ll only support a smaller sub-set of options? This doesn’t seem to happen very often. If we use the SKU example above, upstream teams often push back against an SKU reduction. That could impact revenues (either through triggering a churn event or migration to an alternate plan that might have lower ARPU). However, I’d counter that by citing The Whale Curve, which indicates that many SKUs are actually harming an organisation’s profitability. A reduction in SKUs may reduce top line, but could very well improve the bottom line of an organisation.
* Note: When I’m talking about colours, I’m using the term figuratively, not necessarily the hues on a particular handset being sold through a service provider.