Supply Chain

SCM (Supply Chain Management)

The active management and coordination of supply chain activities and trading partners to maximize customer value and achieve a sustainable competitive advantage.

Basic Supply Chain Structure

Supplier → Manufacturer → Customer, facilitated through logistics.

Upstream / Backward Side of Supply Chain

The supplier side of the supply chain.

Downstream / Forward Side of Supply Chain

The customer side of the supply chain.

Inbound Logistics

Movement from suppliers toward the manufacturer.

Outbound Logistics

Movement from the manufacturer toward customers.

Tier 1 Supplier

A supplier with a direct relationship with the manufacturer.

Tier 2 Supplier

A supplier one additional step removed from the manufacturer, often supplying a Tier 1 supplier.

Product / Service Flow

The movement of products or services through the supply chain toward customers.

Information Flow

The movement of requirements, orders, confirmations, shipping notices, invoices, and other information throughout the supply chain.

Payment Flow

The flow of money generally moving from customers back toward suppliers.

Return Flow

The movement of products backward from the customer toward the point of origin.

Main Goals of SCM (Supply Chain Management)

Increase customer service while simultaneously reducing inventory and operating expenses.

Logistics

The movement and storage of products and materials; it is one component of Supply Chain Management.

Five Transportation Modes

Truck, Rail, Air, Water, and Pipeline.

Service Supply Chain

Service companies still have supply chains even though the service itself is intangible.

Intangible Product or Service

Something that cannot be physically touched.

SCOR Model

Plan → Source → Make → Deliver → Return, with Enable supporting the processes.

PLAN (SCOR)

Establishes the strategy and parameters for how resources will be used to satisfy customer requirements.

SOURCE (SCOR)

Identifying and managing suppliers that provide required materials and services.

MAKE (SCOR)

Converting materials into finished products through manufacturing operations.

DELIVER (SCOR)

The logistics phase involving the forward flow of products and related information to customers.

RETURN (SCOR)

Reverse logistics involving product movement from the point of consumption back toward the point of origin.

ENABLE (SCOR)

Systems, technology, measurements, standards, training, and other tools that support Plan, Source, Make, Deliver, and Return.

Reverse Logistics

The process of moving goods from the point of consumption back to the point of origin for repair, reclamation, remanufacturing, recycling, or disposal.

Efficient Supply Chain Model

A model focused on high volume, high utilization, and low cost; best for functional products.

Responsive Supply Chain Model

A fast and flexible supply chain model designed to respond quickly to changing demand; best for innovative products.

Functional Products

Common products with stable, predictable demand that do not change much over time.

Innovative Products

Rapidly changing products with short life cycles, high variety, and unpredictable demand.

MTS (Make-to-Stock)

Producing finished products for inventory based on anticipated or forecasted demand before an actual customer order is received.

MTS (Make-to-Stock) is also called

Make-to-Forecast and the Push Model.

Push Model

Product is produced based on forecasted demand before an actual customer order is received.

MTO (Make-to-Order)

Producing a finished product only after an actual customer order is received.

MTO (Make-to-Order) is associated with

The Pull Model.

Pull Model

Actual customer demand pulls the product through the supply chain.

Economies of Scale

The more units produced, the lower the cost per unit may become.

JIT (Just-in-Time)

A philosophy based on eliminating waste and providing only what is needed when it is needed.

JIT (Just-in-Time) main inventory idea

Avoid carrying unnecessary inventory.

TRUE or FALSE: Service companies do not have supply chains because their services are intangible.

FALSE. Service firms still have supply chains.

TRUE or FALSE: MTS (Make-to-Stock) is a Pull Model.

FALSE. MTS is a Push Model.

TRUE or FALSE: Functional products are best suited for Responsive Supply Chains.

FALSE. Functional products are best suited for Efficient Supply Chains.

TRUE or FALSE: Innovative products are best suited for Responsive Supply Chains.

TRUE.

TRUE or FALSE: Logistics and SCM are exactly the same thing.

FALSE. Logistics is one component of SCM.

Forecast

A prediction or estimate of future demand.

Forecasting

The process of developing an estimate of future demand using historical data, mathematical techniques, judgment, and insight.

Demand Planning

The process of combining forecasting techniques and judgment to create demand estimates used for supply chain planning and execution.

Independent Demand

Demand for an item that is unrelated to demand for another item.

Independent Demand is

Forecasted.

Dependent Demand

Demand for an item that depends on the demand for another item or finished product.

Dependent Demand is

Calculated.

Short-Term Forecast Horizon

Less than 3 months.

Medium-Term Forecast Horizon

3 months to 2 years.

Long-Term Forecast Horizon

Greater than 2 years.

Forecast Horizon Principle

The farther into the future you forecast, the less accurate the forecast generally becomes.

Forecast Granularity

The level of detail contained in a forecast.

Granularity Principle

The more granular or detailed a forecast becomes, the less accurate it generally becomes.

Qualitative Forecasting

Forecasting based primarily on opinion and intuition.

Quantitative Forecasting

Forecasting using mathematical models and historical data.

Personal Insight

A qualitative forecast based on the opinion of the most experienced or knowledgeable person.

Jury of Executive Opinion

A qualitative forecasting technique where knowledgeable managers or experts discuss the forecast and reach consensus.

Delphi Method

A qualitative method where experts provide input separately through multiple rounds until a consensus forecast is reached.

Historical Analogy

A forecasting method using the history of a similar product or situation to estimate demand for a new one.

Customer Survey

A qualitative forecasting technique that directly asks customers about their opinions or future requirements.

Trend Variation

A general movement in demand over time.

Random Variation

Short-term unpredictable changes caused by unexpected events.

Seasonal Variation

A repeating pattern of demand that occurs within one year and can repeat from year to year.

Cyclical Variation

A wavelike pattern of variation lasting longer than one year.

Naïve Forecasting

Using the previous period's actual demand as the next period's forecast.

SMA (Simple Moving Average)

A forecast calculated by averaging a selected number of recent historical demand periods equally.

Longer Moving Average

Provides more smoothing.

Shorter Moving Average

Responds to trends more quickly.

WMA (Weighted Moving Average)

A moving average in which historical periods receive different weights.

WMA (Weighted Moving Average) Rule

The weights must total 1.00 or 100%.

WMA (Weighted Moving Average) common practice

More recent data usually receives greater weight.

Exponential Smoothing

A forecasting technique using the previous actual demand, previous forecast, and a smoothing factor.

Exponential Smoothing Formula

New Forecast = (Actual × S) + [Old Forecast × (1 − S)].

Smoothing Factor

A number greater than 0 and less than 1 used in exponential smoothing.

Linear Trend Forecasting

Fitting a line of best fit to historical demand and extending the line into the future.

Simple Linear Regression

Uses one independent variable to predict a dependent variable such as demand.

Multiple Linear Regression

Uses multiple independent variables to predict a dependent variable such as demand.

Fundamental of Forecasting: Forecast Accuracy

Your forecast is most likely wrong.

Fundamental of Forecasting: Granularity

The more granular the forecast, the less accurate it generally becomes.

Fundamental of Forecasting: Complexity

Simple forecasting methods can outperform complex forecasting methods.

Fundamental of Forecasting: Correct Forecast

A correct forecast does not prove the forecasting method is correct; it could have been luck.

Fundamental of Forecasting: Data

If data is not regularly used, trust it less when forecasting.

Fundamental of Forecasting: Trends

All trends eventually end.

Fundamental of Forecasting: Bias

It is difficult to completely eliminate bias from forecasts.

Fundamental of Forecasting: Technology

Technology alone is not the solution to better forecasting.

Forecasting is a blend of

Art and Science.

Forecast Error

The difference between actual demand and forecast demand.

Forecast Error Formula

Actual Demand − Forecast Demand.

Absolute Deviation

The absolute value of forecast error, ignoring whether the original error was positive or negative.

MAD (Mean Absolute Deviation)

The average of the absolute forecast errors over a number of periods.

MAD Formula

MAD = Σ|Actual − Forecast| ÷ Number of Periods.

MAD measures

Forecast error magnitude, not forecast bias.

MAPE (Mean Absolute Percentage Error)

The average absolute forecast error expressed as a percentage of actual demand.

MAPE Formula

MAPE = Σ(|Actual − Forecast| ÷ Actual) ÷ Number of Periods.

MSE (Mean Squared Error)

The average of the squared forecast errors.

MSE Formula

MSE = Σ(Actual − Forecast)² ÷ Number of Periods.

MSE effect on large errors

Large forecast errors are magnified because the errors are squared.