Metadata
- Author: Taylor A Murphy
- Full Title:: Analytics Should Be an Assembly Line
- Category:: 🗞️Articles
- Document Tags:: Data Team Vision and Mission,
- URL:: https://tayloramurphy.substack.com/p/analytics-should-be-an-assembly-line?r=44i2a&utm_campaign=post&utm_medium=web&triedRedirect=true
- Finished date:: 2024-09-19
Highlights
Analytics as an assembly line is about centering the fact that most companies and data professionals should be focusing on the basics: consistently measuring their business via metrics, aka descriptive analytics. The majority of companies do not measure their business well, if at all. (View Highlight)
We severely need this in data. Data solutions and outcomes are still too expensive, even with AI. Having an assembly line mentality is an acknowledgement that the demand for “data insights” will always be greater than your capacity and that you are aiming to be as efficient and effective as possible while still maintaining a high bar for quality. (View Highlight)
You should push for alignment on metrics first before ever building a dashboard. (View Highlight)
A key point in the strongest framing of Tristan’s argument is that good metrics are necessary to deliver the outcome of a great data team but they’re not the whole story. Cars are made on an assembly line but we don’t simply deliver them to people without training and appropriate infrastructure in place. Similarly, there is a required mindset and operations shift required for operators to use metrics consistently to drive their business forward. This is not easy but it is possible. (View Highlight)
Incidentally, this is why BI is such a tough business. When you’re aligned on the metrics and how they relate to each other, you don’t need fancy BI. The causal relationships between metrics are already defined and visualization is a necessary, but relatively simple step. (View Highlight)