Manufactured certainty

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“So often people are working hard on the wrong thing. Working on the right thing is probably more important than working hard.”
Caterina Fake

In his blockbuster book, Atomic Habits, author James Clear talks about how changing habits is less about setting goals and more about focusing on your system. “Goals are about the results you want to achieve. Systems are about the processes that lead to those results.”

The current processes for modernization—often under the politically safer label of “digital transformation”— are faulty: documented failure rates range from 55 percent to 79 percent. What’s more concerning is that there seems to be little appetite, besides some general hand waving in the direction of Generative AI, to break the patterns of failure, to look deeply at the system that perpetuates the processes that lead repeatedly to sheepish apologies and half-finished projects.

In our collective experience, we’ve noticed that social considerations—project champions, uncodified expertise, user reactions—feature as strongly as technology considerations. We’ve also noticed that the habit to overcome these considerations is to manufacture certainty where little certainty exists: detailed project roadmaps with Gantt charts, impressive numbers of developers, and budget numbers that inevitably bear only a passing semblance to final costs.

So, what is the process that needs to change to lead to better results?

We need to let go of the Master Digital Transformation Plan security blanket. Success doesn’t come sweeping in at the end of the project. Success has to be proven at each step: incremental evidence of making progress toward the ultimate goal of continuous modernization.

We might be creatures of habit, but it’s time to kick this one.

News and Views

The inimitable Leda expounds on the fragility of legacy systems—and the yawning gap between “not dying” and doing something useful in the present decade. Quote to note: “Maintaining your tech estate is not an exercise in bravery, but rather an exercise in risk management.”  

Gergely of The Pragmatic Engineer wrote about the week-long outage at Sella Bank in Italy (subscription required for the entire analysis). Something to do with Oracle systems now approaching their third decade: sound familiar? Reuters reports on resolution.

Gen AI in legacy modernization hype continues unabated (Gartner, McKinsey). While most of these cover the magic and wonder of AI for coding, GIGO still prevails: garbage in, garbage out. In fact, successful modernization relies more on understanding the system’s behavior rather than the code alone.

From the Orchard

Mechanical Orchard CEO Rob Mee met with The New Stack’s Jennifer Riggins to talk platform engineering, the joys of incremental modernization, and the applicability of Conway’s Law to both legacy modernization and the open source movement. Read the full article.

To our pleasant surprise, CB Insights included us in their AI 100, a yearly selection of the 100 most promising private AI companies in the world. We’re listed in their DevOps category. Thanks, CB Insights!

According to McKinsey, GenAI tooling can help reduce costs by 70%, delivering value faster. But how much can you trust your AI? Mechanical Orchard’s Jeff Schomay discusses.

Lead Software Engineer and original member of the Cucumber project Matt Wynne is conducting two workshops at Domain Driven Design Europe 2024 this May: Example Mapping (How to Slice Any Story into Testable Examples), and with co-speaker Diana Montalion on how to use systems thinking (particularly, the Iceberg Model). If you’re there, say hello!

What happened in Vegas (at the Google Cloud Next 2024 breakout session on GenAI in mainframe modernization, where VP, R&D Dan Podsedly presented) is available for your viewing pleasure.

Curious to learn more? Say hello@mechanical-orchard.com.

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Issue first published on April 30th, 2024.

Conversation

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