>Sounds more like it simply doesn't work very well, rather than any of the reasons you listed.
The use case you've described has a defined problem and a measurable metric. Problem: We think load times influence conversions: Metrics: Measure load times and see if they are correlated with conversions. Maybe in your case somebody decided to skip the research part and just pay to reduce load times.
Imagine a totally difference scenario. You work for a established (30+ years old) company that sells consumer goods. Executives approve a $25 Million budget to "improve the customer experience" over the next 3 years.
This directive goes to all the various organizations: Sales and Marketing, Product Development, Technology, Customer and Market Research, Customer Support, etc. The various orgs have 3 months to come back to executive management to justify how much budget they need and their execution strategy. Each org thinks thinks they are the key mover in improving customer experiences and wants as much of that budget as possible. Every org works at a difference speed and with different philosophies (e.g. all work is done in-house versus some or a lot of work done by external agencies).
Let's add some more reality into this. Even if the CXO of an org thinks they don't need to be in this process, it looks bad if they don't say they have a strategy and need budget. There's also a significant chance that 9 months into this project somebody will get restless and the whole initiative will get restructured with different timelines and goals.
I could do on, but armies of Analysts and Data Scientists will get pulled into this to drive "data driven decision-making." A lot of the expectations will that the "smart people" will show that everyone's particular biases will be the most important one and needs.
It's hardly an environment for anybody to do rigorous analysis or for anybody in an Analytical role to shine. Think the scenario sounds insane and made up? It's not. Welcome to big-co.
The use case you've described has a defined problem and a measurable metric. Problem: We think load times influence conversions: Metrics: Measure load times and see if they are correlated with conversions. Maybe in your case somebody decided to skip the research part and just pay to reduce load times.
Imagine a totally difference scenario. You work for a established (30+ years old) company that sells consumer goods. Executives approve a $25 Million budget to "improve the customer experience" over the next 3 years.
This directive goes to all the various organizations: Sales and Marketing, Product Development, Technology, Customer and Market Research, Customer Support, etc. The various orgs have 3 months to come back to executive management to justify how much budget they need and their execution strategy. Each org thinks thinks they are the key mover in improving customer experiences and wants as much of that budget as possible. Every org works at a difference speed and with different philosophies (e.g. all work is done in-house versus some or a lot of work done by external agencies).
Let's add some more reality into this. Even if the CXO of an org thinks they don't need to be in this process, it looks bad if they don't say they have a strategy and need budget. There's also a significant chance that 9 months into this project somebody will get restless and the whole initiative will get restructured with different timelines and goals.
I could do on, but armies of Analysts and Data Scientists will get pulled into this to drive "data driven decision-making." A lot of the expectations will that the "smart people" will show that everyone's particular biases will be the most important one and needs.
It's hardly an environment for anybody to do rigorous analysis or for anybody in an Analytical role to shine. Think the scenario sounds insane and made up? It's not. Welcome to big-co.