Karmona Pragmatic Blog

Don't get overconfident… Tiny minds also think alike

Karmona Pragmatic Blog

Managing Engineers is like Herding Cats

October 4th, 2008 by Moti Karmona | מוטי קרמונה · 2 Comments

When “The Moscow Cats Theater” came to New York, the Russian clown Yuri Kuklachev was interviewed:  the secret of training them is realizing that you can’t force cats to do anything […] If the cat likes to sit you can’t force her to do anything else […] Each cat likes to do her own trick […] Maruska is the only one who does the handstand. I find the cat and see what they like to do and use that in the show […] I have a cat now that loves to be in the water…”

REUTERS, 2006

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Personally, I think that managing engineers is much more complicated than herding cats (although I didn’t have the twisted pleasure to herd a cat yet)

When you go out of your way to hire the best people around than soon enough you will find yourself herding a superior, class A, hyper-developed mutant Ligers* who are much more knowledgeable than the herder (a.k.a. you)

In this environment you have to learn to simply trust your people (although this is not simple at all :), mark the vision, let them loose and only help to get rid of the stones in their way (this concept was best described as the Open Kimono** policy in Peopleware)

Well…. Managing the Delver Engineers is like Herding Legendary Ligers and you need to make a superior effort to see what these ligers “likes to do” and run fast enough to set the Vision and move the rocks out of the way.

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* The Liger, is a (huge) hybrid cross between a male lion and a female tiger

** Open Kimono Attitude: You take no steps to defend yourself from the people you have put in positions of trust.

By the way, The best answer I found on the origin of the term “Herding Cats” was in Google Answers

→ 2 CommentsTags: Delver · Development · Leadership · Management · People · Project Management · Software Management

Back from the Rabbit hole

April 12th, 2008 by Moti Karmona | מוטי קרמונה · No Comments

Speeding

* My daughter first words were ‘Aaa…Baa’ :-)

* The Delver Alpha was released and deployed – Want an invite?

* Ron Gross, Ofer Egozi and Tal Shiri have joined Delver’s R&D team.

* Video Bitz is a striking success story

→ No CommentsTags: Delver · Recruiting · Software Management

Software Release On-Time

February 22nd, 2008 by Moti Karmona | מוטי קרמונה · No Comments

The British merchant ship Madagascar

“The British merchant ship Madagascar set sail from Melbourne in August 1853, headed for London and carrying 60,000 ounces of gold dust. – She was never seen again…” (http://www.futilitycloset.com/2008/01/29/overdue/)

Well… Saying “no more gold dust” is the only way I know to close a software release on-time…

P.S. Did you noticed that the Mona Lisa has no eyebrows. (http://www.futilitycloset.com/2008/02/12/trivium-16/)

→ No CommentsTags: Management · Planning · Project Management · Software Management

The Software Chaos

February 22nd, 2008 by Moti Karmona | מוטי קרמונה · No Comments

The Chaos Theory

1st Warning: Chaotic post below

Software project are chaotic system and are highly sensitive to their initial conditions (a.k.a. the butterfly effect) and dynamics (e.g. wrong design, vague requirements, team professionalism etc.).


To master (/control) a software project you must be able to breathe (/smoke ;-) the project – inhale the chaotic butterfly movements around you and exhale with the needed adjustments or you will be crushed on the nearest project failure shore with zillions of butterfly excuses.

2nd Warning: Smoking software project is bad for you health

After a decade of software projects smoking I find myself easily doing a background-surfing on the chaotic edges of my projects like I drive my car in the same daily well known route back from work but since I am part of the same chaotic system I am trying to control, I know that my background-surfing is like forgetting my own butterfly wings.

Software project smoking isn’t a social event and can’t be easily shared but it is also one of the key factors in projects surfing – If you will not be able to share your surf experience with your team, your own butterfly wings will bring the next tsunami.

3rd Warning: Don’t practice management if you don’t like the butterflies

→ No CommentsTags: Development · Management · Project Management · Software Management

Pragmatic Time Estimation

November 8th, 2007 by Moti Karmona | מוטי קרמונה · 1 Comment

Software Project Management Life CycleMy rough estimation is that the number of software project managers in the world is smaller in (at least) one scale from the conceived time-estimation techniques and this post is my humble four-cents contribution on how to do pragmatic time estimation for software projects (just finished one in Delver).

  • Start with the mother of all lists to store your Product Manager wish list– We use eScrum Product-Backlog to store our work-items
  • Prioritized them – We use 0-Yesterday; 1-Must; 2-Important; 3-Nice-to-Have and 4-“Forget-About-It”… ;-)
  • Get relative estimations on all items
    • Granularity is the bronze-bullet for time estimations – Strive to the finest grained possible in reasonable time-frame  e.g. We usually aim for 2-5 days granularity in 2-3 days of time-boxed-estimation-period since the finest granularity in planning without reasonable time-box might take twice the time of doing the planned work (a.k.a. The Estimation Paradox)
    • Experience can turn your bronze bullet into silver one (ye ye, a silver one) – Relative estimation is calculated relatively upon a common scale of known work items from the team history e.g. We use Scrum “Story Points” and constantly measure the team velocity for time estimation adjustments
    • Fibonacci sequence (0, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89 etc.) can be used to “embed” the complexity and risk of rough (with insufficient drilldown) estimations e.g. if your estimation granularity for specific task reach ~40 days then your pragmatic estimation should be around 55 days (= the closest Fibonacci sequence) since it is reasonable to believe your (insufficient) granularity conceals risk, complexity and unknowns issues which requires Fibonacci-like-“buffering”
    • Strive to synchronize your time estimation techniques into very simple one – different time estimation conventions in the same development team is the 2nd reason for time delays. (I will give 0.95$ grant if you can guess what the 1st reason)
    • I know I am different but personally, I do prefer to have “pragmatic hours” vs. the normal Agile “ideal hours” and to start the project when 1 “Story Point” =  1 “Pragmatic Day” so long everyone understand this will change as soon as you start the project and then you need to return to velocity tracking to calculate the end
    • Don’t be naïve (a.k.a. “Ideal  Days”) with two known flavors:
      • Optimistic time estimations,  assuming 24*7 of concentrated programming ability with no outside interference (a.k.a. no such thing)
      • “Stupid” hand-waiving time estimations a.k.a. It is only 10 min to code this (but ~5 days to Integrate, Review, Design, Test, Schema and DAL changes, I18N support, Styling etc.)
  • Get the rough project estimation = Sum of all product backlog story points / 22 (work days in month) / Number of relevant people
    • Usually this calculation will show you don’t have enough time for the project (even without project dependencies buffer which can be added later)
    • Start the “Tradeoff Game” – Try to cut items (content) based on the relative ROI
    • Revalidate your priorities since they will be the main tool (beside dependencies) for creating the project work plan.

As I see it, estimating software projects in a realistic time-frame is a statistic prediction of chaotic, time-delay-series of events and will never be straightforward nor easy so you can only do your best in the estimation and then track the project as it goes and make the needed adaptation on the way upon crystal clear project priorities.

Good Luck!

→ 1 CommentTags: Agile · Delver · Development · Management · Planning · Project Management · Scrum · Software Management