Exam 1

• logistics is the movement and storage of product
• logistics starts with marketing and the place in the 4 p's
• types of logistics: event, passenger, military, service, humanitarian
• strategic value of logistics for companies: reduce amount of unnecessary inventory and reduce stockouts
• strategic value of logistics to customers: reduce lead time for orders and ensure favorite item will be available when customer wants it
• logistics is a part of SCM
• we are now in an era known as the age of the consumer
• "last mile" is the most expensive leg
• more product variations - good for customers, bad for logistics
• global markets increase lead time
• customers are demanding faster delivery
• good SCM: valuable, rare, inimitable, non-substitutable
• tradeoffs: product variety/inventory, lead time/transportation, inventory/transportation
• waste reduction (DOWNTIME): defects, overproduction, waiting, not utilizing staff talent, transportation, inventory, motion, excess processing
• order fulfillment (7 R's): right product to the right customer at the right time in the right condition in the right quantity at the right price for the right cost
• 4 components of order fulfillment: availability, delivery, transparency, recovery
• availability: analyze tradeoff between inventory and stockout costs
• delivery: customers care about speed, consistency, flexibility
• PIIS = # SKUs in stock/total SKUs we sell
• fill rate: what is in stock compared to demand
• calculating stockout costs: evaluate customer response, estimate consequence costs, calculate expected stockout costs
• lead time: time between when an order is placed and arrives
• perfect customer order: every order is expected to contain all 7 R's
• ways of classifying supply chain risk: known-knowns, known-unknowns, unknowns-unknowns
• the further out in time you're trying to predict demand, the more error there will be
• there will always be error in forecasting
• as you look at more specific products, the probability of forecasting errors increases
• components of demand data: demand levels, trend, seasonality
• approaches to demand forecasting: quantitative, qualitative
• approaches to time series forecasting: moving average, weighted average, exponential smoothing
• forecast error = actual demand - expected demand forecast
• approaches to IBP (integrative business planning): internal and external
• the further out in time you're trying to predict demand, the more error there will be