A Product Meta-Checklist

-
So you’re building a product. I assume you’ve got everything under control? You know what you’re building, what stages it needs to be delivered in, when they are due, and so on, right? Most importantly, you have all of the things that you are doing — and need to do! — documented, right?
Well, for those of you whose To-Do list is some variation of the above, herewith an actual list (•) of all the things that you should have covered. Take this as a starting point — at the very least you should have some idea around each of the following. You can flesh it out as you go on, with the amount of fleshing depending completely on your circumstances.
Without further ado.
  • • Scope: The Business and Technical requirements, probably some set of epics, user stories, and whatnot. This includes requirements for everything below.
  • • Schedule: Prioritizing everything. Everything. This ranges from the Big(Ideas, Epics, …) to the Small (Tasks, Feature Points, …)
  • • People: Who is working on stuff? Mind you, this is orthogonal to the what(Scope) and when (Schedule)
  • • Resources: All the things that are going to be involved — software, hardware, platforms, services, .., basically everything that isn’t People.
  • • Finances: All the monetary issues — and boy howdy, are there a lot! They include things like expected vs actual versions of budget, costs, ROI, IRR, allocations, and more. Your CFO will be more than happy to go over all of this with you (after they burst into tears when they realize you actually give a s**t about it)
  • • Quality: The acceptance criteria associated with the Scope. As quantifiable as possible (“I know it when I see it” might actually be ok in some cases, but keep it rare).
  • • Risks: Things that can go wrong, with some measure of likelihood, and some plan for dealing with them.
  • • Vendors: Where do we get Resources from? What are we going to pay (Finances!) for them? How will we monitor their performance, and mitigate Risk?
  • • Change: Everything above will change, from the Scope on down. How will this be discussed, agreed upon, and documented?
  • • Communications: What are all the required types of communications, collaboration, and reporting? This should (will!) range from stand-ups, to status reports, to retrospectives and more.
Yes, all of the above is remarkably obvious stuff. And you already know all of it. The question is — does everybody else also know this? In fact, does what they know correspond to what you know? Write it down, and make sure that everybody agrees!
(•) Read the Checklist Manifesto. It’s a good thing!

Comments

Post a Comment

Popular posts from this blog

Erlang, Binaries, and Garbage Collection (Sigh)

-
Image
The nice thing about garbage-collection is that it is makes memory management absolutely transparent to you Of course, the above is true right up to the point when it stops being transparent, at which point it does a phase change from nice to clusterf**k of biblical proportions .  There are entire posts, books, and suicide notes that have been written about this, and I have no great desire to add to them, save with the minor comment that paranoia about garbage-collection is still justified , albeit only in the edge-cases for most people. That said, I'll give you that Erlang GC is in many ways much, much better positioned in this regard than, oh, Java, but it still rears up and bites you in the butt when you least expect it. ( More information about Erlang's GC vis-a-vis Java here , and Jesper's truly excellent description of Erlang's GC here ).  A story from the past should serve to illustrate this. Once upon a time, in a magical land far far away - well, Her...
Read more

Spot The Difference — Deep Learning Edition

-
Image
You’ve played  Spot The Difference  at some point, right? (Of course you did. We  all  did  ). Think about what you actually did when you were trying to Spot The Difference — in fact, just do it again with SpongeBob juggling above. You’re probably doing something like 1. Quick glance to the left. 2. Quick glance to the right 3. “ Spatula on the left. Wonder if there is one on the right? ” 4. “ Yup, there is. Sriracha on the right. Is that on the left? ” 5. “ Nope! It’s a ketchup bottle on the left! And there is nothing on the plate below it! ” etc. To summarize, what you’re basically doing is looking at each image alternately, identifying objects in each image, and trying to find the same object in the other image. As it turns out, what most Deep Learning systems do is something quite different. They basically do something like this 1. Figure out everything in the first image (“ ketchup bottle at 1 o-clock, empty plate at 3 o-clock, spatula at 1...
Read more