Stop Wasting Money: The Simple Truth that Could Save Your Engineering Budget Millions

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Stop Wasting Money: The Simple Truth that Could Save Your Engineering Budget Millions

And today's topic is measuring performance at every step.

Now, rather than give you some theory on this, I'm going to give you a practical example.

As a software engineer, I was responsible for a feature in one organization where every time a problem report showed up, I would solve it within one day.

And the way I would do that would be that I knew for a fact that the filter algorithm was, you know, finicky.

And so I would point to the files that have been modified in that feature, and I would search for another software engineer who I knew was interacting with my software and in some interface fashion, and I would find the problems very quickly.

As bad as that sounds, I would search for those two things and within one day I would solve the issue.

But I guarantee you, now that I no longer work at that organization, my successor probably spends weeks solving the same problem.

So one day turned into probably weeks if those problems were ever solved.

And the reason is the data and the insights that I had working there for several years are gone.

The 20th century solution to that problem is when it shows up again and I'm long gone, we're going to throw 3 bodies at that problem, we're going to throw 10 bodies at that problem, we're going to throw an offshore team at that problem and it'll get resolved at extreme cost.

The 21st century solution to this problem is capture the insights of your lead engineers, store them, get that data and put learning algorithms and point the next engineer in the right direction.

That removes the critical path of one person within the success of your entire product development life cycle.

Now this extends well beyond code.

I mean, did the HR team deliver on staffing needs for the engineering manager and how long did that take?

How many interviews occurred?

That's very important information to know as a part of your development program.

Did the marketing requirement spec change multiple times and is there or is your R&D team constantly spinning their wheels waiting on that?

Is there even a marketing requirement spec or a system requirement spec?

Did the cost of the program differ significantly from the proposal cost, and how, by how much, and in what capacity all that data is digitally available?

Ultimately, as the CTO or the head of engineering of your organization, if you don't have that information, you're making calls in the blind.

But if you do have that information, you're unlocking the critical path and you're removing top constraints for your organization.

So if you're an organization stuck with escalating engineering costs compounded by quality issues and returns and warranties, and you're trying to figure out how to get out of it without constant firefighting, measure your performance at every step and use the 21st-century data and data analytics to do that.

If you like this video, go ahead and subscribe and like and comment and maybe we could start a forum where we share information on the topic.

That's your $1,000,000 minute.

Thanks for listening.