Month in review: February 2025
This is a literal scarf model. Read more to find out about SCARF models.
This monthly newsletter is a simple way to catch up or refresh your memory on events, new members, and conversations from the Enrich community - here's February’s month-in-review.
🚀 Join Us in Slack!
In February we moved our always-on community space from WhatsApp to Slack! We hope this transition enables a smoother onboarding experience, better member profiles, even more async conversations, and easier 1:1 messaging with fellow Enrich members.
🗣️ Enrich Conversations
Our curated conversations are a great way to learn how your peers are tackling the same challenges and questions you face. Here's the quick takeaways from February’s conversations.
Implementing DORA/SPACE metrics:
Platform costs & switching: while many teams use strong tools/platforms for capturing DORA metrics, rising costs often lead to switching to new tools/platforms, causing disruptions.
Managing cross-team dependencies: a common bottleneck in implementation is how to manage dependencies across teams and ensure smooth collaboration.
Value estimation: DORA captures deployment frequency, but lacks a direct measure of value delivery.
Gaming the metrics vs. true impact: one risk is that teams may optimize for hitting numbers rather than driving real business impact.
Sharing DORA metrics beyond engineering: leaders want to demonstrate high-performing teams outside of engineering. Sharing DORA broadly without executive support (“air cover”) can backfire—requires careful time and alignment. Clear expectation-setting and communication are essential to avoid misalignment. And drilling down into the details can provide valuable clarity.
Justifying your spend to your organization:
Turn challenges into opportunities: never let a crisis go to waste! Use crises as catalysts to justify fixing long-standing issues that were previously deprioritized. Urgency can drive buy-in as part of a broader change management strategy. Leverage regulatory and security needs to position infrastructure investments as essential rather than optional.
Communicate tech spend to leadership by making it tangible: find real customer testimonials online (e.g., LinkedIn/Twitter) to advocate for UX and product investments. Frame with analogies: Explain infrastructure investment like building a highway before driving faster—laying a foundation before scaling. Present clear trade-offs: Provide multiple options with consequences rather than just asking for budget.
Balancing tech debt vs. innovation: a common split is 75% tech debt, 15-20% new development, and 5-10% innovation—ensuring sustainability while still pushing forward.
Build credibility first: start with quick wins or proof of concepts to gain trust before seeking larger investments.
Understand your audience: align investment requests with company strategy, leadership priorities, and personal credibility to drive approval. Justify operational costs: Position running costs (e.g., cloud, production support) as necessary infrastructure rather than just expenses.
Frameworks to Consider: SCARF Model is a useful approach for understanding stakeholder motivations (Status, Certainty, Autonomy, Relatedness, Fairness).
AI In Your Product: What Works, What Fails, What Sells (in-person panel):
Risk presented by AI is not to the technology, but on the business side. SaaS margins will go from 80% to 20%.
People don’t want immense personalization - they want shared experience that they can talk to their friends about. E.g. you like watching a TV show and experiencing that with your friends!
Fundamentally, we’ve had risks before that people worry about and we’ve overcome them (think about nuclear power, etc.).
How to meaningfully implement AI into your product:
AI is reshaping businesses. Fewer employees, rise of the no-code movement, and fundamental shifts in operations.
Honesty is key. AI affects customers at both micro (tactical) and macro (strategic) levels, requiring transparency for both internal and external stakeholders.
Executive buy-in is easy, but execution is tough. Numbers make AI adoption compelling, but achieving real impact requires more than just out-of-the-box solutions.
Currently there is no universal approach. AI must be tested and adapted for different use cases; it presents both massive opportunities and significant challenges. Everyone is still experimenting, but a major divide exists between companies embracing AI innovation and those hesitant to adapt.
AI-driven efficiency shifts: productivity and efficiency gains are becoming clearer, but B2B SaaS margins may shrink as AI commoditizes certain aspects of software.
Tools & tactics for improving cross-functional collaboration:
Communication & relationships over tools: effective cross-functional collaboration starts with communication centered around people rather than just tools.
Empathy & trust: leading with empathy helps bridge gaps between teams. Trust isn’t built overnight; consistent check-ins help strengthen collaboration over time.
1:1 meetings as a foundation: 1:1s are one of the most impactful ways to build strong relationships, especially during times of change. They can also be strategically planned around major corporate shifts.
Understanding pain points: building personal relationships helps uncover friction points and challenges within teams.
Less tech, more human connection: a key takeaway was that to truly step into someone else’s shoes, we have to take ours off. Technology should support not replace meaningful human interaction.