What it’s your favorite part about using Aha?
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Using pivot tables
I/we can work on a difficult topic for a few weeks in depth, surface for air without losing our direction at 40,000 feet, and vice versa.
The tracking of many moving parts is made simpler by epics by initiative. even one pivot table that has eliminated the requirement to construct roadmap slides; it is now automatically created out of aha for both internal users and clients.
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You are currently giving me the greatest aha moment because what you just said is exactly what I’m going for when it comes to conveying our priorities and the reasons we are doing what we are. It appears that I need to research pivot tables for my reports.
The fact that our product is currently organized in Aha according to roughly 10 separate components and 3 development pods is my primary challenge.
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While we’re more pods but less components, we kept all of that out of aha for the simple reason that aha data represents what problem we will solve, Jira is how we will build the solution to that problem. So, one aha product, one set of initiatives and epics - and Jira holds the pod split.
Might be similar enough to share something over DM if you want to compare notes.
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Many of our users volunteer to be interviewed. Through exit interviews, a “interview card in our app,” and a few additional support and social media channels, we are gathering those. I’m searching for a programme to manage the scheduling now that I have a tonne of emails from possible candidates. I presently maintain a lengthy Excel list of prospective candidates and send out emails in batches (each user in BCC) that contain a link to calend.ly. I stop seeding once there are enough interviews for the upcoming few weeks; otherwise, I go through the same process again with fresh emails. Although I’m fresh to the game, it appears that this automation has previously been created. Could anyone explain how they handle the invitation process and get a steady flow of user interviews?
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I wonder if there are any good analytic tools for slack. Such that could identify related messages and create a dataset that can be analyzed. Automating this process would free up resources and potentially allow better processing of data as it grows (for a very busy channel especially). People have poor recall or biased memory with data (we all know that person who is an exception). But for people as a whole, this tends to be the case. Further, being dependent on a singular person is bad business practice. That person leaves, and so does whatever knowledge they have.
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Brilliant idea! I would definitely love to see and hear more of it, if it exists or is ever developed by someone. As you have truly mentioned that depending on a single person is any day a risk which needs to be seriously considered by every company.
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