Enterprise Business Processes and Applications

(

IS 6006

) Masters in Business Information Systems 18 th Nov 2008

Fergal Carton Business Information Systems

Last week • • • • • • • • BOM example iPhone Product names (sales) versus model #’s (Mfg) Build to plan model Process versus discrete manufacturing – Process manufacturing produces batches in larger volumes that are undifferentiated (eg. Coke, milk, oil, …) – Discreet manufacturing is characterised by separate unit production from outset of process (eg. toys, medical equipment, computers, cars) ERP modules (Sales, Finance, Logistics, Procurement, Manufacturing) ERP is single instance Key benefit for IT is common platform – simplifies skills required (development and support) – simplifies operations (release management, interfaces, security, …) Production planning: iPhone production planning – Many sources of demand – How can production be planned?

This week • Sample BOM’s • Bullwhip effect • Push – Pull strategies • SIT case study and assessment

BOM: a definition • A list that specifies the parts used to build a product – materials and components used in its creation. – BOM included with the product when shipped • BOM similar to a recipe – Every ingredient used is listed in the bill of materials – No item can be skipped – Essential for service (replacement parts / repairs)

Sample BOM

Sample BOM

Sample BOM: Screaming Circuits

Sample BOM

iPhone and competitor sales Model Prepay Bill

iPhone 3G (O2 Store Patrick St)

– 16Gb €569 – 8Gb €480 €49-229 – Lead time : order Saturday AM, deliver Tuesday (O2 in Dublin) – Nov 07 huge sales, Nov 08 very low (eg. 10 units sold per week) – Key is having product in stock, otherwise sale is lost

Blueberry Storm (Vodafone Store, Patrick St)

– 1Gb €159.98 – No orders placed locally – Head office in Dublin monitors sales and delivers according to inventory

What are the Causes….

• Promotional sales • Volume and Transportation discounts – Batching • Inflated orders • Demand Forecast • Long cycle times • Lack of Visibility to demand information

Consequences….

•

Increased safety stock

•

Reduced service level

•

Inefficient allocation of resources

•

Increased transportation costs

The Bullwhip Effect: Managerial Insights

• Exists, in part, due to the retailer ’ s need to estimate the mean and variance of demand.

• The increase in variability is an increasing function of the lead time.

• The more complicated the demand models and the forecasting techniques, the greater the increase.

• Centralized demand information can reduce the bullwhip effect, but will not eliminate it.

Coping with the Bullwhip Effect in Leading Companies

• Reduce Variability and Uncertainty - POS - Sharing Information - Year-round low pricing • Reduce Lead Times - EDI - Cross Docking • Alliance Arrangements – Vendor managed inventory – On-site vendor representatives

Suppliers From Make-to-Stock Model….

Configuration Assembly

Push-Pull Supply Chains

The Supply Chain Time Line

Suppliers

PUSH STRATEGY Low Uncertainty

Customers

PULL STRATEGY High Uncertainty

Push-Pull Boundary

….to Assemble-to-Order Model Suppliers Configuration Assembly

Matching Supply Chain Strategies with Products Demand uncertainty (C.V.) Pull H I Computer II III Push L L Pull IV Push H Delivery cost Unit price Economies of Scale

Locating the Push-Pull Boundary

Organizational Skills Needed Raw Material Push Low Uncertainty Long Lead Times Cost Minimization Resource Allocation Customers Pull High Uncertainty Short Cycle Times Service Level Responsiveness