Importance of Product Operations in AIoT products

Let me start with a topic which is related my recent role as Product Operations Head. My reference to product here is the one which has hardware + software components and also communicates to Cloud, a typical AIoT product.

Broadly Product Operations,

- Supports engineering and go-to-market counterparts to improve alignment, communication and processes around product development, launch and iteration

- Assists Product management decisions by churning appropriate data both quantitative and qualitative

- Act as Bridge between Product engineering-Field support team-Cloud infrastructure-Quality-Production plant-Commercial-Legal and Sales functions

Why?

- In this Agile mode of product development most of the focus seems to be on "shipping usable product"

- Keeping customer centricity equally important is what happens after the product is shipped

- Normally the product will be in existence for a definite period of time or even life long for that matter also depends on business model of engagement (irrespective of B2B / B2C)*

- We need to reduce customer churn-outs and maintain a high CSI*

2. What?

- Hardware :

Handle warranty claims of the Hardware component of the device.

*If the functionality is related to safety of human life, then appropriate recall also has to happen.

- Software

- Device SW : Provide updated software to fix field issues on device

- Application SW : DevOps / DevSecOps (more information can be found online)*

- Cloud Operations

Pre-prod and production environments

- SW license management and tracking

OSS software evaluation*

3rd party apps management (integration, contracting,SLA etc)*

- Subscription management (as applicable)

- Using data analytics, provide business insights from data stored on cloud (additional revenue stream)

3. How?

- Jot down the ground rules for Operations to begin

- Get involved at early stages of product to factor in the scope, complexities (read the contracts and coordinate with all relevant functions)

- Create stakeholder matrix and detail out customer engagements

- Establish SLA (SaaS) as applicable*

- Install and handle support tickets as “Managed Services”

- Web application and mobile app related

- Cloud infrastructure related

- Security incidents

- Maintain database of device (product) including all key information

4. Data Analytics in Product Operations

Customer obsession

- Address pain areas of customer : predictive, descriptive and prescriptive

Customer churn rate

- Customer satisfaction index improvement

- SLA tracking (time series analysis of tickets)

- Profitability

Reduced Operations cost

Cloud operations - predictive downtime

Anomaly detection in Warranty claims

Reusability of returned field (hardware) parts

- Market study / inputs

Product improvement suggestions

Competitor analysis

*

· AIoT – Artificial Intelligence of Things

· OSS – Open Source Software

· SLA – Service Level Agreement

· SaaS – Software as a Service

· CSI – Customer Satisfaction Index

· B2B – Business to Business service

. B2C – Business to Consumer marketing