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Career 05 · Dec 2023 – Present

Singlife

Senior Data Analyst / Distribution Sales Analytics

Enterprise Analytics

2023 – Now
analytics

MY STORY

在 Singlife，我的核心工作不是單纯做報表，而是把分散的銷售資料變成業務可以使用的管理視圖。 At Singlife, my core work is not simply producing reports; it is turning scattered sales data into management views that the business can actually use.

OVERVIEW

這段經歷是我目前最重要的職業階段。我負責支持銷售表現追蹤、目標進度分析、歷史資料整理和業務差異解釋。相比內部系統名稱，更重要的是：我學會了如何把複雜資料、業務規則和跨部門反饋整理成清楚、穩定、可追蹤的分析流程。 This is my most important career chapter so far. I support sales performance tracking, target progress analysis, historical data organization and business variance explanation. More important than internal system names, I learned how to turn complex data, business rules and cross-functional feedback into clear, stable and trackable analytical processes.

量化工作成果與核心能力 Quantified Impact & Core Capabilities

  • speed

    每週報告準備時間從 15 小時縮短到 20 分鐘，效率提升超過 97%Weekly reporting prep time reduced from 15 hours to 20 minutes — efficiency improved by over 97%

    將每週報告流程結構化，減少 stakeholder 手動整理、核對與彙整資料的時間，讓團隊能把更多時間放在業務回顧、差異分析與後續行動上。Structured the weekly reporting workflow to reduce manual consolidation, verification and compilation for stakeholders, freeing the team to focus on business review, variance analysis and follow-up actions.

  • schedule

    月度報告準備時間從 48 小時縮短到 1 小時，turnaround time 改善約 98%Monthly reporting prep time reduced from 48 hours to 1 hour — turnaround improved by ~98%

    優化月度報告流程，將原本需要約 2 天的準備工作縮短到約 1 小時，加快 month-end review 節奏，提升管理層取得關鍵資訊與做出決策的速度。Optimized the monthly reporting process, compressing ~2 days of prep work into ~1 hour, accelerating month-end review cadence and helping leadership access key insights and decisions faster.

  • monitoring

    建立多渠道業務表現追蹤與歷史回看機制Built multi-channel performance tracking and historical lookback

    參與 Heatmap / sales performance dashboard 與 monthly archive 設計，支援不同渠道、公司與產品類別的 daily / monthly tracking，讓 business team 能更清楚掌握目標進度、渠道表現、歷史趨勢與 month-over-month comparison。Contributed to Heatmap / sales performance dashboard and monthly archive design, supporting daily and monthly tracking across channels, companies and product categories so business teams can track targets, channel performance, historical trends and month-over-month comparisons.

  • account_tree

    設計 Convention Data Model，將複雜業務規則系統化Designed Convention Data Model to systematize complex business rules

    參與 Convention data model 設計，將多渠道、多產品、多條件的獎勵規則拆解成可維護的資料結構，支援 policy-level、advisor-level、qualification 和 next-tier progress tracking，讓原本複雜且依賴人工判斷的規則可以被系統化追蹤、驗證與維護。Contributed to Convention data model design, breaking down multi-channel, multi-product, multi-condition incentive rules into maintainable data structures supporting policy-level, advisor-level, qualification and next-tier progress tracking — enabling rules that were complex and manual to be tracked, validated and maintained systematically.

  • storage

    優化資料量、查詢成本與備份流程，提升資料流程穩定性Optimized data volume, query cost and backup workflows for pipeline stability

    在 Heatmap / Convention 相關資料流程中，參與資料結構優化、歷史資料保存與備份設計，降低不必要的資料處理與重複查詢負擔，提升資料流程的穩定性、可追溯性與長期維護效率。In Heatmap / Convention data pipelines, contributed to data structure optimization, historical retention and backup design, reducing unnecessary processing and duplicate query load while improving stability, traceability and long-term maintainability.

  • verified

    提升報表數字可信度與 stakeholder 信任Improved report credibility and stakeholder trust

    多次追查並解釋不同報表或不同時間點之間的數字差異，協助判斷問題來自時間點、資料來源、mapping 變動，還是業務規則調整。透過清楚拆解差異原因，讓 Distribution Sales、Dops、Finance 等 stakeholder 更安心使用 dashboard 結果做業務回顧與管理決策。Repeatedly investigated and explained numeric differences across reports or time points, helping determine whether issues came from timing, data sources, mapping changes or business rule adjustments. Through clear variance breakdowns, helped Distribution Sales, Dops, Finance and other stakeholders use dashboard results with confidence for business review and management decisions.

  • groups

    展現 cross-functional PM 能力，協調不同部門分歧並推動共識Demonstrated cross-functional PM skills — aligning departments and driving consensus

    在 Heatmap、Archive 和 Convention projects 中，協調 Dops、Data Engineer、Distribution Sales、Finance 等不同團隊，釐清需求、對齊資料定義、確認業務規則，並在數字差異或邏輯分歧時推動各方達成一致，確保專案可以持續往前推進。Across Heatmap, Archive and Convention projects, coordinated Dops, Data Engineering, Distribution Sales, Finance and other teams to clarify requirements, align data definitions, confirm business rules, and resolve numeric or logic disagreements — keeping projects moving forward.

  • dashboard

    將分散資料、人工流程與複雜規則轉化為可持續使用的管理工具Turned scattered data, manual workflows and complex rules into sustainable management tools

    過去的工作成果不只是產出一次性報表，而是把分散的業務資料、複雜規則、人工追蹤流程整理成 dashboard、archive table、data model 和 reusable tracking logic，讓 business 可以長期追蹤、回看、比較與改善。Outcomes go beyond one-off reports: scattered business data, complex rules and manual tracking were organized into dashboards, archive tables, data models and reusable tracking logic so the business can track, review, compare and improve over the long term.

我協助建立了什麼 What I helped build

  • check_circle我協助把銷售資料整理成更清楚的管理視圖，让團隊可以看到目标进度、渠道表現和歷史趨勢。I helped turn sales data into clearer management views so teams can see target progress, channel performance and historical trends.
  • check_circle我參與設計可以持續更新的 dashboard 和資料表，減少每次都從头整理資料的人工工作。I helped design dashboards and data tables that can be refreshed continuously, reducing manual work that would otherwise be repeated from scratch.
  • check_circle我把業務規則整理成更結構化的邏輯，讓後續分析可以更容易複用和維護。I structured business rules into clearer logic so future analysis can be reused and maintained more easily.

我解決過什麼問題 Problems I solved

  • check_circle當不同報表數字不一致時，我會追查差異來源，並把原因解釋成業務可以理解的語言。When numbers differ across reports, I investigate the source of variance and explain the reason in business language.
  • check_circle當業務規則改變時，我會把影響拆解到資料邏輯、報表結果和後續使用方式。When business rules change, I break the impact down into data logic, reporting results and future usage.
  • check_circle當需求不夠清楚時，我會先厘清問題，再决定該做資料、報表、解釋，還是流程改善。When requirements are unclear, I clarify the problem first, then decide whether the solution should be data, a report, an explanation or a process improvement.

我是怎麼工作的 How I work

  • check_circle我通常會先確認業務問題，再確認資料來源，接着建立邏輯，最後用 dashboard 或解釋帮助業務行动。I usually start by clarifying the business question, then confirm data sources, build the logic and finally use dashboards or explanations to support action.
  • check_circle我會在技術準確性和業務可理解性之間做平衡，让結果不只正確，也能被使用。I balance technical accuracy with business readability so the output is not only correct, but also usable.
  • check_circle我習慣和不同團隊對齊定義、時間點、口徑和最終使用場景。I am used to aligning definitions, timing, logic and final use cases across different teams.

這段經歷為我準備了什麼 What this prepared me for

  • check_circle我更能處理跨部門、多規則、多來源的資料問題。I became better at handling cross-functional, multi-rule and multi-source data problems.
  • check_circle我更懂得如何把重複性的人工分析流程系統化。I learned how to systemize repetitive manual analysis processes.
  • check_circle這也讓我更適合往 operations analytics、process improvement 和 global logistics transformation 方向發展。This also prepares me for operations analytics, process improvement and global logistics transformation.

What I Took Away

Singlife 這段經歷讓我最大的成長，是從“會做分析”變成“能把分析變成業務管理工具”。我學會了用資料說明問題、用結構降低重複工作、用溝通讓不同團隊對同一個結果達成共識。 My biggest growth at Singlife is moving from “doing analysis” to “turning analysis into business management tools.” I learned to use data to explain problems, use structure to reduce repeated work and use communication to align different teams around the same result.

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