R&D Management 11 min read

Three Stages of Technical Colleagues and How to Drive Business

The article outlines three developmental stages for engineers—from merely implementing PRD specifications, to understanding business and selecting appropriate technical solutions, and finally proactively contributing business ideas—while describing practical methods for demand exploration, project initiation, management, and data‑driven iteration within a mobile development context.

DataFunTalk
DataFunTalk
DataFunTalk
Three Stages of Technical Colleagues and How to Drive Business

Authors Fang Jun, Feike, Cola, and Da Xun from the E‑commerce Mobile department present a framework of three stages for technical colleagues.

Stage 1 – PRD Translator: Engineers follow the PRD strictly, complete tasks, and consider the work finished once acceptance passes, without concern for business background or value.

Stage 2 – Business‑Aware Technologist: Engineers begin to understand the business, discuss PRD with product managers, choose suitable technical architectures, and prioritize MVP features under tight schedules.

Stage 3 – Proactive Business Thinker: Engineers actively generate business ideas, draft product proposals (background, value, feasibility, roadmap), and collaborate with product managers to drive implementation.

The authors then describe how their team explored business‑driven development in H1 2020, including:

Contacting frontline roles (sales, operations, service) to experience merchant pain points.

Using data analysis to uncover needs (e.g., conversion rates of PC vs. App marketing plugins).

Interviewing merchants directly or shadowing product managers.

For project initiation, they emphasize leveraging OKRs to align cross‑department goals, thorough pre‑work (e.g., feasibility studies of mobile marketing plugins), and preparing clear business cases before engaging product teams.

Project management is presented as an opportunity for engineers to act as project managers, gaining a holistic view of all roles and stages, and learning to handle mid‑project changes and inter‑project dependencies.

Data analysis and iteration are highlighted as essential: define measurable indicators, build dashboards, and conduct descriptive, diagnostic, predictive, and prescriptive analyses. Good metrics should be comparable, understandable, and ratio‑based.

In the concluding “Harvest” section, the team reflects on the benefits of stepping beyond pure development—gaining broader business insight, improving requirement reasoning, and continuously delivering value after launch.

mobile developmentR&D managementProject Managementdata analysistechnical growthbusiness thinking
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DataFunTalk

Dedicated to sharing and discussing big data and AI technology applications, aiming to empower a million data scientists. Regularly hosts live tech talks and curates articles on big data, recommendation/search algorithms, advertising algorithms, NLP, intelligent risk control, autonomous driving, and machine learning/deep learning.

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