At Castlight Health, I have worked with two data science teams that developed multiple data products. Based on my experience, I noticed that in a data product development team, the data science and engineering team is usually twice as big as the application development team. In other words, if you are developing a data product, your invest twice as much in the data science and engineering team as you would in an application engineering team in any given period.
Another important fact is that the data science and engineering team needs to work about twice as long as the application engineering team. Think about it this way. If you are developing a Maps product, the maps application engineering team might be about 4 engineers who work for an year to build the product. However the maps data teams will be about 8 people and will work for two years to create and operationalize the first version of the product.
If you are a product manager involved in planning a data product, this is a good insight to share with your stakeholders and investment decision makers. This of course is a rough idea based on data products in the healthcare industry.
Another important fact is that the data science and engineering team needs to work about twice as long as the application engineering team. Think about it this way. If you are developing a Maps product, the maps application engineering team might be about 4 engineers who work for an year to build the product. However the maps data teams will be about 8 people and will work for two years to create and operationalize the first version of the product.
If you are a product manager involved in planning a data product, this is a good insight to share with your stakeholders and investment decision makers. This of course is a rough idea based on data products in the healthcare industry.
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