“The Business Doesn’t Care About How You Solve the Problem”. When I read this topic detail, you mention that they don’t care about the technical part, which I agree. But you have to sell your leaders the high level part on how you do things still so it will not bite you in the end or if you want to leave a good long lasting impression.
To put it an analogy, when talking to leaders, assuming electrical cars don’t exist, you will want them to buy a car that can run more miles for the same amount of fuel. Although the investment is more expensive, the ROI is better on the long run and you need to show this path is more profitable over the long term.
Of course, most use cases you don’t need to tread much carefully on those parts as doing things inefficiently is insignificant to the impact of data initiatives at least on the start and where execution of speed makes a huge difference.
You have to know the context of the business to determine if the way of doing things efficiently matter. The biggest reason a data team is formed within a company besides helping achieving the company bottom line is to make things efficient and efficiency is much more than just operational costs, from having more visibility of the data for more opportunities the business can yield to making developers and consumers more productive and data literate.
Great read! I believe we have seen a lot of promotions of data people into leadership roles that were 'leading' rather than 'lagging' i.e. anticipating someone's readiness rather than making them do the job ahead of the promotion.
“The Business Doesn’t Care About How You Solve the Problem”. When I read this topic detail, you mention that they don’t care about the technical part, which I agree. But you have to sell your leaders the high level part on how you do things still so it will not bite you in the end or if you want to leave a good long lasting impression.
To put it an analogy, when talking to leaders, assuming electrical cars don’t exist, you will want them to buy a car that can run more miles for the same amount of fuel. Although the investment is more expensive, the ROI is better on the long run and you need to show this path is more profitable over the long term.
Of course, most use cases you don’t need to tread much carefully on those parts as doing things inefficiently is insignificant to the impact of data initiatives at least on the start and where execution of speed makes a huge difference.
You have to know the context of the business to determine if the way of doing things efficiently matter. The biggest reason a data team is formed within a company besides helping achieving the company bottom line is to make things efficient and efficiency is much more than just operational costs, from having more visibility of the data for more opportunities the business can yield to making developers and consumers more productive and data literate.
Great read! I believe we have seen a lot of promotions of data people into leadership roles that were 'leading' rather than 'lagging' i.e. anticipating someone's readiness rather than making them do the job ahead of the promotion.
great read! it can be challenging to engage business folks too. And sometimes we need to develop a proof-of-concept to show them the way.
Enjoyed the read! Will be waiting for the follow up deep dive