This content originally appeared on HackerNoon and was authored by Anurag Jindal
\ Why OBS (Outcome-Based Services)?
Enterprises don’t buy kubernetes clusters or model weights, they buy outcomes. The OBS playbook encodes those outcomes before work begins. We tie SLAs and KPIs to ROI with a cadence that never goes out of date:
- Daily Ops Reviews keep services green.
- Monthly Business Reviews (MBR) connect tech health to cost and CX.
- Quarterly Business Reviews (QBR) rebalance investment to what’s working.
At my firm, this approach helped scale from a 50-person boutique to a 700-employee, 15-location enterprise serving 150+ clients—with run-ops costs down 25–35%, availability at 99.9%+, CSAT at 80%+, and $10M+ in renewals and expansions.
Step 1: Encode Outcomes
- Define business outcomes: time-to-value, churn reduction, NRR lift, cost-to-serve.
- Translate into SLOs and error budgets per service.
- Document DoD (definition of done): tests, data quality, security, explainability, and acceptance criteria.
Step 2: Standardize the Ways of Working
- Reference architectures that 80/20 your stack decisions.
- Migration runbooks with traffic-shift and rollback plans.
- Analytics accelerators for common use cases (e.g., personalization, operational dashboards).
- FinOps guardrails: rightsizing, autoscaling, lifecycle policies, reservations—reviewed monthly against value, not just cost.
Step 3: Operate, Review, Reinvest
- Ops telemetry rolls up into green/yellow/red summaries the CFO understands.
- MBR/QBR focus on: What proved value? What missed? What do we stop, start, scale?
- Funding shifts follow evidence, not opinions.
Field Notes from Real Programs
- Iconic global motorcycle manufacturer: Unified customer data + use-case analytics cut time-to-insight from weeks to days, enabling targeted personalization and new revenue plays.
- Top-5 U.S. academic medical center: GCP modernization shrank data syncs 24h → 4–6h with 0 data-load failures and 99.9%+ availability, improving research reporting and grant compliance.
- Global remittance & payments network: Portfolio SRE habits reduced MTTR and stabilized CX; reliability became a board-level dial through error budgets and change policy.
Avoid These Traps
- Model Theater: fancy demos without DoD gates for data quality, drift, and cost.
- SLA Soup: commitments that don’t affect behavior. If your SLA doesn’t change how you staff, deploy, or approve changes, it’s noise.
- One-off Savings: FinOps is a habit. Guardrails + monthly cost-to-value reviews convert 15–20% savings into the new baseline.
What Good Looks Like
- An executive dashboard showing SLOs, error budgets, MTTR, CFR, unit economics, and a top-3 ROI narrative.
- A catalog of outcome-priced services with clear acceptance criteria.
- A culture where teams celebrate deleting unused resources as much as shipping features.
Bottom line: OBS is how you make AI/Data/Cloud pay rent. Encode outcomes, standardize how you work, and run the cadence. The rest is commentary.
This content originally appeared on HackerNoon and was authored by Anurag Jindal
Anurag Jindal | Sciencx (2025-11-03T04:58:00+00:00) The OBS Playbook: How to Turn AI, Data & Cloud Into P&L Results. Retrieved from https://www.scien.cx/2025/11/03/the-obs-playbook-how-to-turn-ai-data-cloud-into-pl-results-2/
Please log in to upload a file.
There are no updates yet.
Click the Upload button above to add an update.