Shipulski On Design

One of the biggest mistakes I know is to get too little done by trying to do too much.

In high school we got too comfortable with partial credit. Start the problem the right way, make a few little mistakes and don’t actually finish the problem – 50% credit.  With product development, and other real life projects, there’s no partial credit.  A project that’s 90% done is worth nothing.  All the expense with none of the benefit.  Don’t launch, don’t sell. No finish, no credit.

But our ill-informed focus on productivity has hobbled us.  Because we think running projects in parallel is highly efficient, we start too many projects.  This glut does nothing more than slow down all the other projects in the pipeline.  It’s like we think queuing theory isn’t real because we don’t understand it.  But to be fair to queuing and our stockholders, queuing theory is real.

Queues are nothing more than a collection of wayward travelers waiting in line for a shared resource.  Wait in line for fast food, you’re part of a queue.  Wait in line for a bank teller (a resource,) you’re queued up.  Wait in line to board a plane, you’re waiting in a queue.  But the name isn’t important.  Line or queue, what matters is how long you wait.

Lines are queues and queues are lines, but the math behind them is funky.  From firsthand experience we know longer queues mean longer wait times. And if the cashier isn’t all that busy (in queuing language – the utilization of the resource is low) the wait time isn’t all that bad and it increases linearly with the number of people (or jobs) in the queue.  When the shared resource (cashier) isn’t highly utilized (not all that busy), add a few more shoppers per hour and wait times increase proportionately. But, and this is a big but, if the resource busy more than 80% of the time, increasing the number of shoppers increases the wait time astronomically (or exponentially.)  When shoppers arrive in front of the cashier just a bit more often, wait times can double or triple or more.

For wait times, the math of queueing theory says one plus one equals two and one plus one plus one equals seven.  Wait times increase linearly right up until they explode.  And when wait times explode, projects screech to a halt.  And because there’s no partial credit, it’s a parking lot of projects without any of the profit.  And what’s the worst thing to do when projects aren’t finishing quickly enough?  Start more projects.  And what do we do when projects aren’t launching quickly enough?  Start more projects.

When there’s no partial credit, instead of efficiency it’s better to focus on effectiveness.  Instead of counting the number of projects running in parallel (efficiency,) count the number of projects that have finished (effectiveness.)  To keep wait times reasonable, fiercely limit the amount of projects in the system.  And there’s a simple way to do that.  Figure out the sweet spot for your system, say, three projects in parallel, and create three project “tickets.” Give one ticket to the three active projects and when the project finishes, the project ticket gets assigned to the next project so it can start.  No project can start without a ticket.  No ticket, no project.

This simple ticket system caps the projects, or work in process (WIP,) so shared resources are utilized below 80% and wait times are low. Projects will sprint through their milestones and finish faster than ever.

By starting fewer projects you’ll finish more.  Stop starting and start finishing.

Image credit – Fred Moore

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