Well UI/HMI for operational data is something I do daily but a good operational dashboard takes time. Really have to get your feed back from the actual users and I am not just talking people who glance at the dashboard, but people who are going to use it to carry out operational actions.
I simply glanced and felt while there was a lot of great information the presentation for a ‘dashboard’ was too busy - and I prefer lists to graphics. When I think about DAI in the Defi space I think about a pie and total outstanding, increase or decrease as one key metric (how much DAI is there, how much did it change in last 24Hrs) that is the first metric that determines the 100% mark. The second piece of the pie is how much as a % of the total moved from one cut of pie to another. What does the Pie look like (where is the lions share, and what does the ‘other’ total).
So when I think of DAI operations I am going to want to see a list of places DAI lives in order of % of total show nothing < 1% and no more than maybe 10-15 places. In the first column top show yesterdays total DAI and the %'s allocated to the places DAI lives for yesterday, and then second column showing Today and then +/- % change.
The following statement applies to all the catagories. 2-3 sigma is a data standard that can be used against all events in a catagory. Say DAI mints. If 95% of these are <1K we only care about these perhaps if the number of them in a day exceeded the 3 sigma threshold of the past 30-90 days of data. Same with burns. This also applies to sizes. If 3 sigma of all the last mints/burns is 100K then use that as the flag. The point here isn’t using a fixed value but using a statistical metric to define one value and then using another hard value to flag interesting events that are outside the ‘normal’ however you define this statistically or operationally. (this needs to be defined by users and the data generally)
When I think of operations dashboards, and being an operator of a machine/system, what I want to go into the background are things that are ‘normal’ and events that are ‘expected’ or within well defined statistical bounds. What should stand out are events that are outside of statistical bounds or as a magnitude often cases we would flag these with alarms that define various types of operational responses (alarm acknowledgement, cell phone mail/text, a possible predefined action - turn this down or off). Realize I am speaking from near approaching 20+ years of operational experience with an additional download of my friends 30+ years. We together know exactly what we want to see from operations dashboards, alarm handlers, UI/HMI screens because we are the ones that actually use them. Hence while I can make comments the real users are risk teams and in the end the drive for development should come from those who are going to use this information ‘for’ a purpose.
I honestly have no clue what ‘DAI engagement’ would look like. One idea you might want to include now that I think about this is the concept of moving DAI vs. static DAI. One important metric on top of DAI outstanding from yesterday to today and the pie 100% kind of display noted above would be to have another set of columns that show DAI moved in last 24hours and +/- % of outstanding in the same columns. I will try to do a spreadsheet mock up with wholly made up data based off of what you have up when I look and then you can see if this helps you get an idea of what to show.
The whole statistical measure of what is ‘abnormal’ vs. a value level is something that will require constant tweaking. I think it took us 2 years of normal operations tweaking settings for various alarms set/read mismatches and read only vs. active read only. (long story) Which then defined the events that should stand out in alarm handlers (or abnormal event reports).
Key goal in my mind on this dashboard is if there is a sudden shift in DAI either in activity (moving) vs. static we should see that immediately. The dashboard should also give us at a glance where this DAI moved from and to. If particular wallets stand out in terms of total activity (I’d say .1-1% or more of outstanding is probably something to watch).
Anway apologies for length. I simply don’t have time to edit this one down. I will see if I can generate a simple view of the rows/columns pie approach to a dashboard display based on what you are presenting and then you can try to make one - and we all can look and see what we think.
In the end I wanted to thank you for doing this work. It is something along with vault and liquidation activity analysis (as a kind of dashboard/report) I have been wanting to see for a long time and I can’t wait to see how this evolves.
Thank you again for doing the work, and listening.