Unclear if this is isolated to a few or widespread. Looking for clarity.
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How do you flatten layers filled with Secret Love Children with jobs in perpetuity? They "earned it", of course. But what person with legitimate qualifications would want to work for those people?
The primary reasons behind these layoffs include:
- Organizational Restructuring and Flattening
• Reducing the "Manager Ratio": Data from recent tech contractions highlights a major push to flatten corporate hierarchies. Private software companies often realize they have too many "managers of managers." Consequently, middle-management and director-level PM roles are frequently consolidated or eliminated to create a leaner organization.
• Correcting Post-Pandemic Over-Hiring: Many private software companies over-hired during the software bo-m of 2020–2022. As market demand stabilized, companies ended up with bloated product teams relative to the number of engineers available to actually build the software.
- Redefining the Product Management Value Proposition
• The "Feature Factory" Correction: During flush economic times, the PM role at some companies devolved into administrative tasks—such as formatting user stories, managing roadmaps, and scheduling meetings. When budgets contract, executives often scrutinize these "process-heavy" PM roles and cut them if they aren't directly driving customer value or revenue.
• Merging PM and Product Marketing (PMM): To reduce overhead, companies frequently eliminate specialized niche roles and return to a combined PM/PMM model, requiring a single individual to handle both product strategy and go-to-market execution.
• Increasing Engineering-to-PM Ratios: Tech companies are actively widening their engineering-to-PM ratios. Instead of assigning one PM to a single small engineering pod, companies are restructuring so that a single experienced PM supports multiple technical teams or larger engineering orgs.
- Strategic Pivots and Technological Disruption
• The AI and Automation Transition: Companies are actively reallocating budgets to prepare for the next era of technology. This often means reducing headcount in legacy or maintenance product lines to fund highly specialized talent in artificial intelligence and data science.
This only affects the people we don't like.
The beatings (layoffs) will continue until morale (margins) improve.
@OP I haven't heard a whiff of any such layoffs. That doesn't mean there weren't or were. I'm not a terribly good grapevine.