Let me start where my recent role does. The “product” here isn’t an app — it’s a device with hardware and software that also talks to the cloud: a typical AIoT product. And the discipline that keeps it alive in the field, long after the launch confetti settles, is Product Operations.
Broadly, Product Operations does three things. It supports engineering and go-to-market counterparts to improve alignment, communication, and process around development, launch, and iteration. It arms product management with the right quantitative and qualitative data to decide well. And it acts as the bridge between product engineering, field support, cloud infrastructure, quality, the production plant, commercial, legal, and sales.
01Why it matters
In agile development, almost all the gravity pulls toward “ship a usable product.” That’s necessary — but customer-centricity is just as much about what happens after the product ships.
- A product exists for a defined period — sometimes its entire lifetime — depending on the engagement model, B2B or B2C.
- The mandate is to reduce customer churn and hold a high Customer Satisfaction Index (CSI).
- Everything that determines renewal happens in operations, not in the launch demo.
02What it actually covers
The surface area is wider than most teams expect. It spans the physical device, both layers of software, and the cloud it depends on.
Hardware
Handle warranty claims on the device’s hardware component. And where a function relates to the safety of human life, an appropriate recall process has to exist and work.
Software
| Device software | Ship updated software to fix field issues on the device itself. |
|---|---|
| Application software | Run it through DevOps / DevSecOps practices for safe, continuous delivery. |
Cloud operations
- Manage pre-production and production environments.
- Track and manage software licences, including open-source (OSS) evaluation.
- Manage third-party apps — integration, contracting, and SLAs.
- Handle subscription management where applicable.
- Use the data sitting in the cloud to generate business insight — an additional revenue stream.
03How to set it up
Operations doesn’t bolt on at the end — it earns its leverage by getting involved early.
Write the ground rules
Jot down the operating rules before anything goes live, so the team isn’t improvising under pressure later.
Get in early
Engage at the product’s early stages to factor in scope and complexity — read the contracts and coordinate across every relevant function.
Map stakeholders & engagements
Build a stakeholder matrix and detail the customer engagements it implies.
Establish SLAs
Define SLAs for the SaaS elements as applicable — they’re the contract your support model is measured against.
Run support as managed services
Install and handle support tickets as managed services — web and mobile app issues, cloud infrastructure, and security incidents.
Maintain the device database
Keep a database of every product/device with all its key information — the single source of truth for operations.
04Where data analytics earns its keep
This is where Product Operations stops being a cost centre and starts paying for itself. The analytics split cleanly into customer-facing wins and internal efficiency.
Customer obsession
- Address pain points — predictive, descriptive, prescriptive
- Lower customer churn rate
- Improve Customer Satisfaction Index (CSI)
- SLA tracking via time-series analysis of tickets
Profitability
- Reduce operations cost
- Predict cloud downtime before it bites
- Detect anomalies in warranty claims
- Reuse returned field (hardware) parts
Beyond that, operations data feeds market study — product improvement suggestions and competitor analysis — closing the loop back into the next iteration of the product.