🎯
Executive Summary | 執行摘要
📦 Total Inventory Value | 總庫存價值
$25,629,325
📊 Total Units | 總單位數
265,668 units
🏆 Highest Value Category | 最高價值類別
橄欖油 (Olive Oil): $10,758,430
⚠️ Value at Risk (< 180 days) | 風險中的價值
$805,828 (3.1%)
❌ Expired Inventory Value | 過期庫存價值
$419,701 (15 items)
✅ Safe Inventory (> 180 days) | 安全庫存
$24,823,497 (86 items)
Key Insights | 關鍵洞察：
1️⃣ Inventory is predominantly safe (96.9% > 180 days remaining). The company has strong liquidity management.
2️⃣ Class A items represent 80% of inventory value (29 items), indicating high concentration risk. Recommend tighter monitoring.
3️⃣ Potato Flakes category has critical expiration issues (-152.5 avg days). Immediate liquidation action required.
4️⃣ Top 10 items account for ~$9.4M (36.7% of total value). Focus control measures on high-value SKUs.
⚙️ Dynamic Data Filter Panel | 動態資料過濾器
📈 Key Performance Indicators | 關鍵績效指標
Filtered Total Value | 過濾後總金額
$0
Total capital tied up
Safe Assets | 安全資產
$0
> 180 days remaining
At Risk | 中等風險
$0
91-180 days remaining
Critical Status | 危急狀況
$0
< 0 days (expired)
Total Items | 總項目數
0
Filtered SKUs
Avg Shelf Life | 平均效期
0d
Days remaining
📊 Interactive Analytics & Visualizations | 互動式分析與視覺化
🎯
Urgency Matrix: Value vs. Shelf Life | 庫存急迫性矩陣
Visualization Guide | 視覺化指南：
Bubble size = Inventory quantity | 泡泡大小 = 庫存數量
Bubble color = Risk level | 泡泡顏色 = 風險等級
Position = Days remaining (X-axis) vs. Value at stake (Y-axis)
Medium Risk 91-180D (中風險)
📊
Capital Distribution by Category | 類別資本分佈
⚠️
Risk Distribution | 風險分佈圓餅圖
🏆
ABC Inventory Classification Analysis | ABC分級分析
The Pareto Principle (80/20 Rule) applied to inventory: 80% of value is typically held in 20% of items (Class A).
| Class | 級別 |
Items | 項目數 |
Value | 金額 |
% Total | 佔比 |
Avg Days | 平均天數 |
| Data loading... |
🔄
Top 10 Highest Value Items | 前十高價值項目
📅
Expiration Timeline Analysis | 效期時間線分析
🧮 Mathematical Models & Analytical Framework | 數學模型與分析框架
⚡
Model 1: FEFO Urgency Index (UI) | FEFO急迫性指數
First-Expire-First-Out (FEFO) Principle
Used in industries where product freshness matters (food, pharmaceuticals). The Urgency Index quantifies how quickly inventory needs to be liquidated based on capital at risk and shelf life.
$$UI = \frac{V}{d + \delta}$$
Where:
• $V$ = Inventory Value (庫存金額)
• $d$ = Remaining Days to Expiration (剩餘天數)
• $\delta$ = Small constant (e.g., 1) to prevent division by zero
Interpretation: Higher UI = More urgent action needed. Items with UI > 100 require immediate liquidation strategies.
📦
Model 2: Economic Order Quantity (EOQ) | 經濟訂單量
Balancing Holding Costs vs. Order Costs
For high-value inventory (Class A items), EOQ determines the optimal reorder quantity that minimizes total inventory costs. Critical for olive oil, sauces, and pasta categories.
$$EOQ = \sqrt{\frac{2 \cdot D \cdot S}{H}}$$
Where:
• $D$ = Annual Demand (年需求量)
• $S$ = Fixed Cost per Order (每次訂購固定成本)
• $H$ = Annual Holding Cost per Unit (每單位年持有成本)
Application: For olive oil ($10.7M, 38,019 units): Calculate optimal batch sizes to minimize warehousing + ordering costs.
📈
Model 3: ABC Segmentation & Pareto Analysis | ABC分層與帕累托分析
Cumulative Distribution Function (CDF)
The Pareto Principle (80/20 Rule) states that approximately 80% of inventory value is held in roughly 20% of items. ABC segmentation operationalizes this principle.
$$\text{Class A}: \sum_{i=1}^{n_A} V_i \approx 80\% \text{ of Total Value}$$
$$\text{Class B}: 80\% \text{ to } 95\% \text{ of Cumulative Value}$$
$$\text{Class C}: 95\% \text{ to } 100\% \text{ of Cumulative Value}$$
Your Current Distribution:
• Class A: $20,500,631 (80.0% of value) - 29 items (25.7% of SKUs)
• Class B: $3,890,803 (15.2% of value) - 25 items (22.1% of SKUs)
• Class C: $1,237,891 (4.8% of value) - 59 items (52.2% of SKUs)
Implications:
1. Focus 70% of control efforts on Class A items (frequent cycle counts, tight thresholds)
2. Moderate monitoring for Class B items
3. Minimal control for Class C items (periodic counts sufficient)
💰
Model 4: Financial Impact of Expired Inventory | 過期庫存財務影響
Total Cost of Obsolescence
When inventory expires, the entire capital is at risk. This model quantifies the financial impact and opportunity cost.
$$C_{obsolete} = V_{expired} + (V_{risk} \cdot r \cdot t) + H_{disposal}$$
Where:
• $V_{expired}$ = Value of expired inventory = $419,701
• $V_{risk}$ = Value at risk (< 180 days) = $805,828
• $r$ = Annual opportunity cost rate (assume 10%) = 0.10
• $t$ = Time in holding (assume 1 year) = 1
• $H_{disposal}$ = Disposal/liquidation costs (assume 5% of value)
Calculation:
$C_{obsolete} = 419,701 + (805,828 \times 0.10 \times 1) + (419,701 \times 0.05)$
$C_{obsolete} = 419,701 + 80,583 + 20,985 = \mathbf{\$521,269}$
Insight: The financial impact of expired/at-risk inventory exceeds $521K annually, representing 2.0% of total inventory value.
🎯 Risk Analysis & Strategic Recommendations | 風險分析與戰略建議
🚨
Critical Issues Identified | 識別的關鍵問題
1. Potato Flakes Category Liquidation Crisis
Issue: 6 items in Potato Flakes with -152.5 avg days (mostly expired)
Value at Risk: $368,297
Action: Immediate liquidation, donation, or disposal
2. Class A Concentration Risk
Issue: 29 Class A items = 80% of value
Risk: Supply chain disruption = major financial loss
Action: Diversify sourcing, increase safety stock thresholds
3. Top 10 Items Concentration
Issue: Top 10 items = $9.4M (36.7% of total)
Risk: Quality issues or recall on 1-2 items = major impact
Action: Enhanced quality checks, supplier contracts
✅
Strategic Recommendations | 戰略性建議
✓ Strengthen FEFO Controls
Implement automated rotation systems. Current 96.9% safe inventory is excellent but requires discipline to maintain.
✓ Optimize ABC Thresholds
Set safety stock levels: Class A (40 days), Class B (25 days), Class C (10 days) to balance availability + turnover.
✓ Implement JIT for Low Performers
Slow-moving Class C items should use Just-In-Time (JIT) model: order only when demand confirmed, to reduce holding costs.
📋
Problem Items Requiring Action | 需要採取行動的問題項目
| Product Name | 產品名稱 |
Category | 類別 |
Days Left | 剩餘天數 |
Qty | 數量 |
Value | 金額 |
Status | 狀態 |
| Data loading... |