One of the hardest things in data is proving value.
What?
It helps to view any data initiative, small or large, as a small startup. In the startup world, one of the most important things to do is finding product-market fit.
This is all about understanding your customer and what they REALLY want.
In data, we can look at this in a similar way: How do we find out what efforts we should prioritize for our stakeholders?
In that spirit, here is a list of 30 questions to ask your stakeholders or yourself to figure out if the current efforts make sense:
What are your top objectives for this week, month, quarter, and year?
What is a typical task you perform often and would like to see more automated?
What are the top objectives of your stakeholders?
How do you measure success?
What data sources are you already using?
What data sources would you like to use more of?
How long would it take our team to build this?
What is the estimated lifetime value of this work?
Is there a depreciated return on value over time?
How many engineering hours will it take to maintain?
Can the responsibility easily be transferred, or is this dependent on 1-2 people?
What is the opportunity cost of doing this? Put differently, what other pursuits would need to get sacrificed?
Does it make more sense to buy a solution or build something in-house?
How will our team measure engagement of our new solutions with stakeholders?
In dollar terms, how much labor cost is this solution saving over time?
Does this solution drive more revenue? How do we prove this?
Is this solution reducing company liability? If so, how and how much?
Has this been done before? If so, how much time did it take them? If not, is there a good way to estimate how much time this would take to do?
How is this data going to be acted upon? If a stakeholder requests real-time but the actions are manual, consider what real-time really means here.
Apply Occam's razor to your solution: How can we achieve the results with the least amount of necessary permutations in our existing infrastructure.
Would this solution be very visible to the organization? If not, it may be harder to defend the value of this effort.
Is anyone else in the organization currently tackling this problem? Are we duplicating efforts? This requires talking to more people than just your direct stakeholders.
Has there been any effort in the past to address this issue? If so, get all the possible learnings you can get.
Are we considering this because it’s popular knowledge or a new shiny state-of-the-art tool, or is it truly relevant for our business?
How bad would it be if this effort fails?
What would be the repercussions of not doing this? How fast will the business feel the impact? How large would this impact be? Be concrete.
Can we deploy a quick minimum viable product to get buy-in earlier?
How confident am I we can deliver on our promises within a reasonable amount of time?
How many dependencies does this project have? Is this something we can run mostly internally, or does it need coordination with a lot of other teams?
Does this solution keep pace with the growth in scale of the business? How long will it take before this becomes obsolete?
What are some questions you like to ask stakeholders?
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