Super easy project planning and estimation
geon.github.io
geon.github.io
I have been working on this as a hobby project for a few weeks now, and it's starting to look decent. It is barely an early alpha yet, so please forgive any catastrophic data loss etc...
It is a tool for breaking down projects into manageable pieces, and to estimate the total time of the project. Pretty useful. I've been dogfooding during the development, and it is a lot better than my usual method of indented lists in a text file.
* Click the button to create a new project.
* Type in your project title.
* Click the "+"-button to add a task.
* Hover over a taks to see the button for adding subtasks.
* Drag&drop task to reorder them or move them up/down the hierarchy.
* Open the edit-dialog on a task to set an estimated time.
* When you enter the first estimate in a task, you get projected estimates for all other tasks.
It is desktop-only at the moment. Some of the stuff works on mobile, but don't count on it. None of the drag&drop works, for example, and it relies on mouse hover.
* I think hovering to change the task is fine when you are adding smaller things, but if you are putting in a bunch of tasks it would be nice if you could just keep them there (like an edit mode).
* I think the time entry part could use some work, obviously alpha here, but I could see things like a default time for each task, and a button to add/remove increments of time in a quick way.
* Having some sort of bubbling surrounding or highlighting for each task group might be nice from a visual standpoint.
You mean like having the description and estimated time editable from the tree-view? It adds clutter...
> * Having some sort of bubbling surrounding or highlighting for each task group might be nice from a visual standpoint.
Hmm. It can't be there the whole time since the bulles would add borders-around-borders-around-borders for as deep as your tree is. The clutter adds up fast.
Also would be great to tag other people. Would also be awesome if there is a way to tell if there is any relationship between the two or not.
Looks super killer dude! Good job!
Any specific things you would have changed?
> Would also be awesome if there is a way to tell if there is any relationship between the two or not.
Could you expand on that?
- Clickable items are better with a `cursor: hover` on those elements. In that case, you know where you can click in a better way.
- It's a productivity task, so make some things dead-obvious. For example, the fact that you can drag tasks around should not be discoverable by accident. You might want to add an icon or a small text on the bottom of the screen to make it obvious.
Otherwise, really cool app!
I even removed the mobile-friendly responsive design I had for the landing page to not imply it will work on mobile...
But it shouldn't be a big issue to get the drag&drop working. Trello does it great already. I might have to rethink the hover-reveal icons, though.
Otherwise, excited to see this unfold!
I have a task already for the `cursor: hover` and `cursor: move`. I'll move it up in the priority.
I can't tell if this a straight up adaptation of PERT 3-point estimates or not. That's essentially what I was trying to develop. It's taught in project management courses but there're no simple tools for it.
I'm wary of projecting from a few tasks to all tasks. The strength of the PERT 3-point method is that it can provide a projected cumulative distribution of outcomes based on expert opinion.
There's a lot of PM and ops research literature about the PERT 3-point technique. My suspicion though is that it actually works less because of the quasi-statistical side of things, and more because of what psychologists called "the unpacking effect".
The unpacking effect is simple: ask someone to estimate a task ("how long will it take to prepare for a flight across the country?"). The estimate will probably be low. If, instead you ask them to enumerate subtasks -- to unpack the task -- subsequent estimates become more accurate.
I use this at work when estimating story points. See a story like "as a user, I can add a phone number to my profile", then speculate aloud what will be required. "We need a database field, to update the model, controller and view, we need some styling and documentation; does this need to be part of the analytics backend too?"
Suddenly the 1 point story is 2 points, or 3.
Thanks for mentioning some theory behind this. What is lost by doing a simple best/worst/likely time estimate of all sub tasks, as compared to doing the full blown statistical analysis? The simple approach can be achieved relatively easily with a spreadsheet. For small-ish projects, does the full blown approach provide any significant benefit?
I work mostly on small projects, implementing new server/network infrastructure for small/medium businesses. Time estimation is always a crap shoot, and the only approach I know to combat it is to pad the estimate with generic line items like "testing" and "troubleshooting". If the statistical analysis would help create a better estimate of time, I would spend time developing or contributing to an estimating tool.
I'm not sure I understand you, but I'm just going to talk at you anyway.
In the 3-point estimate you break the estimate down into smaller parts, then have experts assign best/likely/worst case values to each part. Then they are rolled up into a single CDF.
The thing is that the formulae used are basically made up. They give a "triangular distribution", which superficially resembles a normal distribution at low precision. But lots of things don't resemble a normal distribution. You can hope that through the central limit theorem your estimate will improve towards resembling a normal distribution ... except that humans persistently underestimate everything.
A lot of the Ops Research / PM literature is about fiddling with the formulae, or introducing adjustments based on historical data, which all helps. But by itself the 3-point method improves outcomes simply because you bother to enumerate stuff.
The other secret is that if you do it a few times, you tend to look at previous estimates and you begin to remember things that are frequently forgotten. A common cause of underestimation is leaving off common tasks. For example, software developers can often give a reasonable estimate for the core work they're doing (code and tests), but tend to forget to account for everything else that's needed before a feature can be considered done done: merging, discussion with others, integration, deployments, documentation and so on.
Well, frontend is my thing, so... The estimation is a total hack, though. But it can easily be ripped out.
> I can't tell if this a straight up adaptation of PERT 3-point estimates or not.
It's probably not. I skimmed through some papers I found, but only to confirm the basic Idea I had to begin with. There is lots of room for improvement.
> I'm wary of projecting from a few tasks to all tasks.
Yes. This is intentionally just bullshitting. You are often very unsure of how big a task is going to get, and this bullshat number is sometimes as good as any number I can think of.
And, sometimes the best way of getting the right answer is to give a wrong one.
> My suspicion though is that it actually works (...) more because of what psychologists called "the unpacking effect".
This is what I have noticed at work, and what I have (tried to) optimize the UI for.
* The automagical guessing of missing estimates. Propagating the estimate for a subtask to other subtasks at the same level makes a lot of sense for a first guess, if I'm any good at task breakdown. The propagating up to the "aunt/uncle" tasks (i.e. siblings of the parent) is a bit stranger - seems like it should dramatically underestimate most top-level tasks, and I'd worry about the anchoring effect. Still, it makes it very convenient and quick.
Have you thought about visually distinguishing autoguessed estimates from manually entered ones? At least for leaf tasks, I'd like a reminder of what I have left to estimate. (You could propagate up the "degree of guessedness" to parent nodes, but you probably wouldn't want to, or it would undermine the usefulness of guessing in the first place.)
* The visual tree structure is nice. I like how the horizontal arrangement puts a natural limit on how deeply you can nest, and therefore discourages overplanning :)
http://s12.postimg.org/xth7k6fi5/Screenshot_from_2015_02_01_...
Time is propagated to siblings, if they have no estimates from their own children.
Un-estimated siblings will be given the average time of the siblings with estimates.
Time will also propagate down the chain, and will be split equally over the children.
In the end, it is mostly bullshit, but then again, so are all estimates...
> Still, it makes it very convenient and quick.
Exactly. Sometimes, the best way of getting the right answer is to give the wrong one...
> Have you thought about visually distinguishing autoguessed estimates from manually entered ones?
Oh, they are. See the icon in front of them in the tree view?
Bulls-eye: Your own estimate
Checkmark: Actual time
Arrow: Auto-generated projection
They all have a title-attribute with their type in case you forget.
> I like how the horizontal arrangement puts a natural limit on how deeply you can nest
:)
It doesn't though. Still, you can fit like 8 levels deep on a normal desktop screen, but in practice, I've never found a need for so much nesting.
You're basically competing with Excel here. One of the strengths of Excel is the excellent support for keyboard. That is, easy entry of new cells and navigating between them by only using keyboard.
Your application's support for keyboard is nonexistent. If I have to enter lines of text and I have to continuously click (+), I will close the browser pretty fast.
I have keyboard navigation planned already, but in low priority. I'll move it up.
See how, for example, Trello has implemented keyboard input. User can add multiple items to a list without raising hands from keyboard.
Should you find yourself developing this tool further, these books will give you an edge that most other tools lack -
http://www.amazon.com/Critical-Chain/dp/B002LHRM2E/
The icons distinguishing guessed from manual estimates are rather meaningless to me. I suppose the manual icon is supposed to represent a set "target"? The guessed estimate could be something with a question mark in it to represent the guess.
As mentioned already, the "Delete" button is where a "Save" should be, I've found myself automatically moving towards it after editing a task.
The tasks could be slightly smaller, so that more fit on a screen (I can see only 6 in a column at most, though my screen is only 1366x768).
Overall it seems like a great tool and I'd be interested in using it. The front page would certainly benefit from a "email when it's beta/ready" box, as my email would be in there now.
Hmm. Any idea how to make it more clear? (Apart from just stating it... I need a manual, obviously.)
> The lack of feedback requires you to guess what's going to happen when you drop the task.
Right! I have plans for that, but it's the kind of think that takes a lot of work, with relatively low bang-per-buck. At least so early in development.
> The tasks could be slightly smaller
I experimented a bunch with that, and picked readability over space saving. But yes, as the project grows it gets harder to get an overview. I like the [CMD]+[-]... :)
Be nice if you could use the enter / return key when inputing task titles to move to a new task. I think the delete button is strangely placed. This would normally be an accept button. Maybe just have a trashcan icon or something on the task itself.
In a nutshell, the key to making such an effort very effective is just really good knowledge of and experience with all the parts of the project to be done.
Below in (1) -- (5) I give an overview of parts of the field.
(1) Importance of Experience.
Here some examples where a lot of experience is crucial:
A kitchen/bath remodeling firm can give a good estimate of time and cost because they have already done, say, one such job a week for five years, that is, 250 jobs; so, essentially they have already seen it all, that is, all the possibilities of what can go wrong and how much there is to do. Similarly for an auto body shop, a residential HVAC company, a plumber or electrician, a landscaping company, an asphalt paving company, a residential housing general contractor, etc.
(2) Software Projects and Experience.
One means of project planning and estimating for software projects looks at each of the parts of the work and starts with the experience level of the team for that part.
For parts of the work where the team has no experience, that is, is doing such work for the first time, no estimates are made!
So, the project planning works only for projects where there is good experience for all the parts of the work.
Alas, often software projects need to do some things for the first time.
(3) Critical Path.
Some US DoD projects made use of Gantt charts,
http://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd...
and in particular the concept of a critical path. As I recall, this work can make good use of linear programming which can identify the critical path.
Intuitively the critical path is a sequence of tasks such that, if any task in that sequence takes one minute longer, then the whole project will take one minute longer. So, the tasks on the critical path have no slack.
So, to speed up the whole project, must at least speed up the projects on the critical path.
Next, then, of course, is the issue of where to put more resources to speed up the projects on the critical path. This, then, is a resource allocation problem, another optimization problem.
(4) Alternatives and Uncertainty.
One of the biggest problems in getting projects done on time and within budget is handling uncertainty, e.g., the effects of unpredictable, outside influences, that it, exogenous random inputs.
And, there can be some alternatives in how to execute the projects; then during the project might select different alternatives depending on how the project has gone so far, that is, the then current state of the project.
State -- Essentially the situation or status of the project at some particular time, and generally want enough information in the state (vector or collection of information) such that the past and the future of the project are conditionally independent given the state, that is, want to satisfy the Markov assumption so that in planning the future can use just the current state and f'get about all the rest of the past.
One such state is always the full past history of the project, but commonly much less information is also sufficient to serve as the state.
Commonly we can be drawn into the applied mathematics of stochastic optimal control, say, at least discrete time stochastic dynamic programming, e.g.,
Stuart E. Dreyfus and Averill M. Law, 'The Art and Theory of Dynamic Programming', ISBN 0-12-221860-4, Academic Press.
Dimitri P. Bertsekas and Steven E. Shreve, 'Stochastic Optimal Control: The Discrete Time Case', ISBN 0-12-093260-1, Academic Press.
Wendell H. Fleming and Raymond W. Rishel, 'Deterministic and Stochastic Optimal Control', ISBN 0-387-90155-8, Springer-Verlag, Berlin, 1979.
E. B. Dynkin and A. A. Yushkevich, 'Controlled Markov Processes', ISBN 0-387-90387-9, Springer-Verlag, Berlin.
So, a lot of quite serious applied math research has been done, and a lot is known.
Broadly stochastic dynamic programming makes the best decisions that can be made making use of only information available at the time each decision is to be made.
Nicely enough from the Markov assumption and just a simple application of Fubini's theorem, we can say a little more about being best possible.
Interesting here, and a way to get some massive speedups of some software, is the concept of certainty equivalence in the case of LQG, that is, linear, quadratic, Gaussian control as in
http://en.wikipedia.org/wiki/Linear-quadratic-Gaussian_contr...
So, the system is linear (as in a linear operator or, for an important special case, matrix multiplication); the exogenous random variables are Gaussian; and the quantity to be controlled, say, minimized, is quadratic (which also includes linear).
(5) Spreadsheets.
Sometimes a spreadsheet is used for project planning, and there is an interesting observation to be made here:
So, suppose we are doing financial planning for five years and develop a spreadsheet with one column for each month, that is, 60 columns, maybe 61, and one row for each variable.
So, some of the spreadsheet cells represent exogenous random variables, and some cells represent decisions to be made.
(A) We can fix the decisions and recalculate the spreadsheet, say, 500 times and, thus, do Monte Carlo simulation for the random cells and get an empirical distribution and expected value of the money made at the end of the project.
(B) We can fix the values of the exogenous random variables and then use some optimization to find the values of the decisions that maximize the money made at the end of the project. Spreadsheet software has long, often had some optimization, from linear programming or L. Lasdon's generalized reduced gradient software, version 2 -- GRG2.
This approach, in terms of football, say, the Superbowl later today, would be like the quarterback on first and ten calling the next four plays without considering the extra information he will have after each of the plays. Quarterbacks wouldn't do that, and business planners should not either.
(C) But what about making the best decisions with the random exogenous random variables not fixed? Then usually we want to maximize the expected value of the money made at the end, but the form of the decisions is special: At each period, the decisions are in terms of the state of the project as of the end of the last period.
So, such optimization is called discrete time stochastic dynamic programming, Markov decision theory, etc.
So, nicely enough, computer spreadsheet software has enabled some millions of planners to specify in very precise terms some nearly complete formulations of problems to be solved with stochastic dynamic programming.
For a reasonably large spreadsheet, such optimization would be a super computer application -- nicely, there really is a lot of parallelism that can be exploited.
At one time I pursued just this direction at the IBM Watson lab in Yorktown Heights. Had the semi-far sighted management let me continue, by now there should be a good business for cloud sites to do such problems, say, use a few thousand cores. Ah, IBM has missed out on several much larger opportunities!
There are various approaches to making the computations faster, say, using multivariate splines to approximate some of the functions (tables) to be generated, the R. Rockafellar idea of scenario aggregation, and more.
My guess is that the OP has in mind something simpler.
As I recall, there is some project planning software. Right, a simple Google search shows, e.g., Microsoft's Project 2013.
Yes.
Not to dismiss the actual research that has been done, but... Estimates are mostly bullshit anyway.
This tool helps you to bullshit more accurately than nothing, while still being "super simple" to use.
The projection algorithm I use is extremely basic so far. There is a ton of improvements I have in mind already, and I haven't even bothered to more than skim read the research papers I found yet.
I did have plans for some simple Monte Carlo sampling to get a nice probability distribution graph, though.
Right, but in some cases you can know fairly well or quite well. E.g., say you are planning and one of the exogenous random variables is the number of people, or customers, who arrive during the plan. Then with just a few assumptions, that mostly can be checked just intuitively, that number of people will have Poisson distribution and all that have to estimate is the arrival rate parameter. One of the random variables might have to do with weather, but there is a lot of data on the probability distribution of what the weather can do.
But generally, yes, that applied math is a lot of theorems and proofs about what the heck to do if you had a lot more data than you do have. Or, in the South Pacific, it is an airline service from island A to island B, terrific if you are at A and want to get to B but no good if there's no chance of getting to island A.
As I recall, long in some major US DoD projects, keeping track of the critical paths and adding resources to those was regarded as doing a lot of good.
A related part of project planning is the subject, often pursued in B-schools, of materials requirements planning -- in practice there can be a lot to that. And closely related there is supply chain optimization, that is, when the heck will the critical parts arrive for our poor project?
Also related is constraint logic programming or how the heck to load all those 18 wheel trucks, each with 40,000 pounds of boxes of fresh pork, from our only three loading docks where each truck gets what its scheduled deliveries need and the boxes are ready from the kill and cut operation when the truck is parked at the loading dock? Real problem. Such problems are commonly looking for just a feasible solution, that is, not necessarily an optimal solution, to some constraints that might have been for an optimization problem. Well, then, in such optimization, just finding a first feasible solution is in principle as hard as finding an optimal solution given a feasible solution, so that constraint logic programming gets into optimization. At one time, SAP, C-PLEX, etc. got heavily involved.
Another planning problem is dial-a-ride bus scheduling -- one of my Ph.D. dissertation advisors tried to get me to pursue that problem as a dissertation, but I avoided it like the Big Muddy Swamp full of huge alligators and poisonous snakes and picked another problem, right, in stochastic optimal control, a problem I could actually get some clean results in.
Did I mention, project planning is a big field?
Your software looks like it has a user interface a lot of people will like a lot, but with enough usage some users will still encounter some of the challenging aspects of project planning.
Good luck with your software.
- When I mark a task as "Done", I would assume its sub-tasks to be marked as done too.
- When I mark a task as "Done", it would be nice if it somehow went out of my way. Like if all of the subtasks collapsed into the parent or something.
Right. Didn't think about that. Thanks! I did plan to mark the parent as done when all children are done.
> collapsed into the parent or something
Exactly what I have in mind.
Likewise your quick instructions should not be here in your intro, put them somewhere in the flow once someone lands on your site.
> quick instructions should not be here in your intro
Yes. I'm not yet sure how much of it is self explanatory, but I'm getting an idea of it.
Also not exactly sure how to use the tool... I created a project and added some tasks but not quite sure what to do next/ how to use it
jQuery, underscore, backbone.....
Plus a minimalistic REST api in Node, with Postgres.
Actually, all source in on Github.