Inventory Management and Risk Pooling Flashcards
(29 cards)
Why hold inventory?
- Hedge against uncertainty in supply & demand
- Economies of scale
- Hedge against lead time
- Capacity limitations
Order costs
Product cost, transportation cost (straightforward computation)
Holding costs
Capital tied up, physical costs: warehouse space, storage tax, insurance, breakage, spoilage
Other inventory costs (other than order and holding costs)
Component devaluation costs (life cycle dependent)
Price protection costs (supply contract dependent)
Product return costs (operational cost)
Obsolescence cost (FG inventory + components in pipeline + probable discount)
Out of stock costs (difficult)
Tendency to overstock (diagram)
Cost of stock outs high, cost of obsolescence low
Tendency to understock (diagram)
Cost of stock outs low, cost of obsolescence high
Balancing act
Cost of stock outs high, cost of obsolescence high
Forecasting methods
Quantitative - moving average, exponential smoothing
Qualitative methods
Principles of forecasts
- Forecasts always wrong
- Longer the horizon, the worse the forecast
- Aggregate forecasts always more accurate
Three types of inventory
Raw-materials
WIP
Finished goods
Four main methods to keep track of inventory and differences
- General of average rules
- ABC analysis
- MRP or APS systems
- Multi echelon inventory system
MRP APS - demand uncertainty
Multi echelon - capacity considerations
ABC analysis
Split products in to A, B, C
A - 80% revenue 20% inventory space
B - 15% revenue 30% inventory space
C - 5% revenue 50% inventory space
Cycle service level
Fraction of replenishment cycles
with no stock out
Fill rate
Fraction of demand satisfied from stock on hand
Prediction Methods
Judgement, market research, time series, causal methods
Judgement methods
Opinion of experts
Delphi method - panel of experts share opinions independently over several rounds
Marker research methods
Qualitative forms - Base predictions solely on behaviour of consumers
Time series
Data from the past used to predict the future, quantitative method. Moving average or exponential smoothing
Causal methods
Predictions based on basis of sales data and how it differs from predictions. Relies on external factors
Economic lot size model characteristics
Demand is known and constant Order quantity fixed at Q per order Balance fixed cost K and inventory holding cost h No lead time No discounts No stock outs
Single period model
Data from the past, uses this data to make predictions and future scenarios. Only one order moment with no backorders
Multiperiod model
Several orders with order thresholds and order sizes
R, Q), (s, S
(R, Q) policy
Fixed order quantity Q, once reorder point triggered R.
Reorder point = avg demand during lead time + safety stock
Periodic checks without fixed costs (S-1, S)
S represents order up to point. Inventory placed each check - order up to certain amount. r is the review period time between two periodic checks