219 lines
7.4 KiB
JSON
219 lines
7.4 KiB
JSON
{
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"projectTitle": "人咧 PeoplePing 智能出勤系統",
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"overallScore": 82.5,
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"totalPossible": 100,
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"grade": "A-",
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"performanceStatus": "表現良好",
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"recommendedStars": 4,
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"analysisDate": "2024-10-27",
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"criteria": [
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{
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"name": "應用實務性",
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"score": 8,
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"maxScore": 10,
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"weight": 30,
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"weightedScore": 24,
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"feedback": "系統設計貼合實際出勤管理痛點，流程清晰，具備可行性。但缺乏更詳細的實際案例佐證。",
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"strengths": [
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"解決了主管無法即時掌握團隊出勤和員工查詢繁瑣的問題",
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"清晰的流程圖展示了系統的運作方式",
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"整合了常用的工具如Dify和MySQL"
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],
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"improvements": [
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"提供更多實際應用案例，例如導入公司後產生的數據結果",
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"說明系統在不同網路環境或設備下的兼容性"
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]
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},
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{
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"name": "創新性",
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"score": 7,
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"maxScore": 10,
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"weight": 25,
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"weightedScore": 17.5,
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"feedback": "利用對話式介面和Dashboard整合提升效率，具有一定創新性，但整體概念在市面上已有類似產品。",
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"strengths": [
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"結合Dify Chat Flow實現自然語言互動出勤登記",
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"使用Dashboard提供即時KPI和趨勢分析",
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"API設計方便與其他系統整合"
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],
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"improvements": [
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"更深入地探討系統的獨特性和優勢，與競品區隔",
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"考慮加入更創新的功能，例如異常狀況自動告警或預測分析"
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]
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},
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{
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"name": "成效與效益",
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"score": 9,
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"maxScore": 10,
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"weight": 25,
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"weightedScore": 22.5,
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"feedback": "數據呈現明確，效率提升數據具有說服力。但缺乏數據來源和計算方法說明。",
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"strengths": [
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"量化了時間節省的效益，例如出勤登錄時間從3分鐘縮短到30秒",
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"清晰地展示了效率提升的百分比",
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"系統錯誤率控制在1%以下"
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],
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"improvements": [
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"說明數據來源和計算方法，提升數據的可信度",
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"加入使用者滿意度調查結果，更全面地評估效益"
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]
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},
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{
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"name": "擴散與可複用性",
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"score": 8,
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"maxScore": 10,
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"weight": 20,
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"weightedScore": 16,
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"feedback": "API設計良好，具備一定的擴散性和可複用性。但缺乏跨部門應用案例或模組化設計的說明。",
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"strengths": [
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"提供清晰的API清單，方便與其他系統整合",
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"後續優化規劃中包含功能擴充和智能整合",
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"系統架構相對清晰，理論上具備可複用性"
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],
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"improvements": [
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"提供更詳細的模組化設計說明，方便其他部門套用",
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"提供跨部門應用案例，說明系統的可擴展性"
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]
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}
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],
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"overview": {
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"excellentItems": 1,
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"improvementItems": 3,
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"overallPerformance": 82.5
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},
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"detailedAnalysis": {
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"summary": "人咧 PeoplePing 智能出勤系統在解決實際問題和呈現效益方面表現良好，但創新性和擴散性方面仍有提升空間。建議加強數據佐證、更深入地分析競品優勢，以及提供模組化設計和跨部門應用案例。",
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"keyFindings": [
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"系統功能完善，解決了實際的出勤管理痛點",
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"數據呈現清晰，但缺乏數據來源和計算方法說明",
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"創新性有待提升，需要更深入地探討系統的獨特性"
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]
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},
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"chartData": {
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"barChart": [
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{
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"name": "應用實務性",
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"score": 8,
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"maxScore": 10,
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"percentage": 80
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},
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{
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"name": "創新性",
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"score": 7,
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"maxScore": 10,
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"percentage": 70
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},
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{
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"name": "成效與效益",
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"score": 9,
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"maxScore": 10,
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"percentage": 90
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},
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{
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"name": "擴散與可複用性",
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"score": 8,
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"maxScore": 10,
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"percentage": 80
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}
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],
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"pieChart": [
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{
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"name": "應用實務性",
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"value": 24,
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"weight": 30
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},
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{
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"name": "創新性",
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"value": 17.5,
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"weight": 25
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},
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{
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"name": "成效與效益",
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"value": 22.5,
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"weight": 25
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},
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{
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"name": "擴散與可複用性",
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"value": 16,
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"weight": 20
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}
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],
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"radarChart": [
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{
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"subject": "應用實務性",
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"score": 8,
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"fullMark": 10
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},
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{
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"subject": "創新性",
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"score": 7,
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"fullMark": 10
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},
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{
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"subject": "成效與效益",
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"score": 9,
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"fullMark": 10
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},
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{
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"subject": "擴散與可複用性",
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"score": 8,
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"fullMark": 10
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}
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]
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},
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"improvementSuggestions": {
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"overallSuggestions": "加強數據佐證，完善模組化設計，深入分析競品優勢，並提供更多實際應用案例和跨部門應用經驗。",
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"maintainStrengths": [
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{
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"title": "清晰的系統架構和流程",
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"description": "系統架構和流程圖清晰易懂，方便理解系統的運作方式。應繼續保持這項優勢，並在後續優化中持續完善。"
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},
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{
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"title": "數據驅動的效益呈現",
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"description": "通過量化數據清晰地呈現了系統帶來的效率提升，這對於說服使用者至關重要。應繼續完善數據的來源和計算方法。"
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}
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],
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"keyImprovements": [
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{
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"title": "提升創新性",
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"description": "目前系統概念在市面上已有類似產品，需要進一步挖掘系統的獨特性和優勢，例如加入更智能化的功能，如異常狀況自動告警或預測分析。",
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"suggestions": [
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"研究市場上其他類似產品的不足之處，並以此作為創新點",
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"加入更個性化的功能，例如根據不同部門或員工的需求提供定制化服務",
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"探索AI技術的更多應用，例如利用機器學習進行缺勤預測"
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]
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},
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{
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"title": "加強數據的可信度",
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"description": "目前數據雖然清晰，但缺乏數據來源和計算方法的說明，這會影響數據的可信度。",
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"suggestions": [
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"提供數據來源和計算方法的詳細說明",
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"加入使用者滿意度調查結果，更全面地評估效益"
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]
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},
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{
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"title": "提升擴散性和可複用性",
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"description": "雖然API設計良好，但缺乏跨部門應用案例或模組化設計的說明。",
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"suggestions": [
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"提供更詳細的模組化設計說明，方便其他部門套用",
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"提供跨部門應用案例，說明系統的可擴展性",
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"考慮開發可視化工具，方便使用者快速理解和使用系統"
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]
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}
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],
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"actionPlan": [
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{
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"phase": "短期目標（1-2週）",
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"description": "完善數據來源和計算方法說明，補充實際應用案例"
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},
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{
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"phase": "中期目標（1個月）",
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"description": "研究市場競品，制定創新功能規劃，初步設計模組化架構"
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},
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{
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"phase": "長期目標（3個月）",
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"description": "完成創新功能開發，實現模組化設計，並在其他部門進行應用測試"
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}
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]
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}
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} |