Belajar Program Manager - Program Analytics & Data

#Pendahuluan

Setelah di episode 22 kita mempelajari AI & technology programs, pada episode ini kita fokus pada program analytics & data — bagaimana menggunakan data untuk mengambil keputusan program yang lebih baik.

#Program Data Framework

#Data Sources

Source	Data Type
Project tools (Jira)	Progress, velocity, cycle time
Financial systems	Budget, actuals, forecast
HR systems	Capacity, utilization, satisfaction
Benefits tracking	KPIs, outcomes, ROI

#Analytics Maturity

Level	Deskripsi
Descriptive	What happened?
Diagnostic	Why did it happen?
Predictive	What will happen?
Prescriptive	What should we do?

#Program Dashboard

Program Dashboard

Program Health: 7.8/10
 
Schedule: [=========>  ] 65% (On Track)
Budget:   [========>  ] 60% (On Track)
Benefits: [======>    ] 45% (Improving)
Risks:    [====>      ] 4/10 (Managed)
 
AI Insights:
- Predicted completion: On schedule
- Budget forecast: $1.1M (within 5% of plan)
- Benefits forecast: 85% realization by year-end

Tip

Program analytics harus actionable. Setiap metric harus menjawab: "Apa yang harus saya lakukan berbeda berdasarkan data ini?" Jika tidak ada aksi, metric tidak perlu ditampilkan.

#Praktik: Program Dashboard

Buat program dashboard:

Program Dashboard Template

1. Overall health score
2. Key metrics (schedule, budget, benefits)
3. Risk profile
4. Stakeholder satisfaction
5. AI insights (jika available)
6. Action items

#Penutup

Inti yang harus dibawa pulang:

Program data framework harus mengintegrasikan data dari berbagai source.
Analytics maturity: dari descriptive sampai prescriptive.
Dashboard harus actionable, bukan hanya informatif.

Di episode 24 selanjutnya kita akan membahas global & distributed programs — bagaimana mengelola program lintas region dan budaya.