
CEO wants our SaaS startup to become “data driven”. What does this mean to you? - dataderp
I fear that this is something of a buzzword, but so far:<p>- Everyone has access to the company&#x27;s financial metrics
 - Our graphing and querying tools are open to employees (small 20 person company)<p>I&#x27;m thinking of:<p>- A monthly data&#x2F;metrics talk
 - Making sure the majority of engineering tickets have a definable success metric that can be measured afterwards in terms of app downloads
 - Logging all data requests, and making this public so that people can see that we are not reinventing the wheel<p>Any more suggestions?
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fuscy
I find it admirable although a bit concerning that there's transparency with
the financial metrics. Most employees don't need to know that information,
both for the company's sake and for theirs.

That information can affect the employees as they will be making plans:

\- if the metrics look bad then they will make plans to jump ship,
productivity will drop, word will spread or they will simply worry when it's
not their job to worry about financials.

\- if the metrics look good then they can expect some pay raises or benefits
or improvements which might or might not be in the future plans of the
company.

The company being a startup can be affected if the information leaks out.
Possible investors might back out or propose some outrageous things or the
competition will see inside the company also and they will be "data driving"
on your back.

Financial information should be on a need to know basis.

Now back to the issue at hand about "data driven". From my experience, this
means that the company will aggregate all kinds of events and data (financial,
user, metrics, feedback, everything). Some of it will be for vanity (like app
downloads) and some will be actionable (like where did the app downloads come
from which allows you do double down on a good source).

The purpose of the "data driven" company is continuous improvement through
data. Observe data, propose changes based on data, experiment (A/B testing at
the minimum), observe results and carry on the cycle. For example: the UI of
the application, the UX, the features offered or the price points for the
features. Everything should be registered, tested and improved upon.

You said something related to engineering tickets being related to app
downloads. That is a pretty huge conjecture there but if the data shows this
then it must be true (!Warning: correlation does not imply causation).
Recording the trend and velocity of the engineering tickets is a good metric
that can be actioned upon later on. Usually the 5 why are applied to determine
possible relations between events and getting to the core issue of something
so you can do actions and tweaks on it (why has the number of tickets
increased/decreased? etc.).

As for the monthly data/metrics talk: the "data driven" company is based on a
constant 24/7 talk about the metrics and how to act upon them.

Also as for making the data requests public, the same as for the financial
metrics apply (need to know basis or some kind of marketing point).

