Managing Operations Flashcards
3 Management Processes in Operations
- supplier relationship
- internal management
- customer relationship
Goal of Operations Management
Make the operations as efficient as possible
Inputs (materials, capital) –> Operations –> Outputs (products, services)
Productivity
Efficiency is measured in Productivity which = output/input
Output always measured in dollars
Find out what resource is scarce or expensive and focus on it (measure their productivity)
Productivity in Different Countries
- US is the leader
- Why does productivity in countries matter? You can only consume what you produce - standard of living is dependent on productivity.
- e.g. highway - can drive 70 mph…in US takes one hour, in a country where you can only drive 35 miles per hour, will take 2 hours
- highly concentrated countries are more productive (e.g. Japan)
US employment by Sector
Services, Manufacturing, Government, Agriculture
- productivity of manufacturing has gone up dramatically
- manufacturing jobs have gone down
Manufacturing vs. Service
M - physical, durable output, S - intangible, perishable output (you can’t store service)
M - easily measured, S - not easily measured
M - low customer contact, S - high customer contact
M - long response time, S - short response time
Factors Affecting Productivity (11)
- Investments in plant and equipment. Newer equipment = higher productivity
- R&D Spending. higher spending = more innovations = higher productivity
- Patent Laws - better patent laws, people will invest in R&D in those countries
- Regulations - increase costs
- Taxation - serious problem - US are taxed on global income (not just their income from the US)…not favorable for companies earning high proportions of incomes from foreign countries
- Metric System - US follows Foot Pound Second (FPS)
- Health Care Costs
- in the US, health care is paid by the employer (part of the cost of production)
- outside the US, paid by taxes - Price Earning Ration (earnings per share) - higher ratio = higher competitiveness. e.g. if you’re P/E is 20, you can raise $20 from $1 in the market. Companies should try to have as high a P/E as possible
- Education - matters because if you don’t have high paying jobs to pay people with the highly educated people
- US values college education versus vocational education - Hourly Wages
- Value-Added = price - cost of inputs
Challenges the US is facing (6)
- High Trade Deficit (the good news is, most of the imports into the US is energy and energy use is going down)
- Rising Current Account Deficit - almost 95% of the world’s savings coming into the US
- Falling dollar reducing the standard of living
- Rising entitlement spending - social security payments, fewer and fewer people working in the US
- Dramatic growth in China and India increasing costs of raw materials and energy
- Loss of competitiveness - everybody else has started building up better infrastructure and becoming more competitive
Production Systems (4)
- Job - e.g. printing press. high customization, high variety, volume low and unique, every job is unique - one extreme*
- Project - building shopping centers. high customization, low volume
- Batch - e.g. mcdonalds - low variety, standardized product, high volume - the other extreme*
- Line - between batch and continuous process - refineries, little inventory held between processes
America’s Race to the Bottom
- making less money today than in 1985, MBAs rarely get union jobs and those pay highly, unions have been going down
- less unions
Wages as a proportion to the GDP
60’s-70’s - 51/52%
Today - 42% (GDP is rising but wages are not)
Retirement Plans
- defined contribution is like 401K plan (depends on the stock market return) - this has been rising in the past 30 years
- defined benefit - take final salary, each year give you 2% of your final salary (if you work for 30 years, you get 60% of your ending salary) - this has been falling in the past 30 years
- less defined contribution
H1-B Visa Issuance Cap
- employer sponsored
- after 9/11, outsourcing went up - employees had worked in the US but were sent back, so companies outsourced the work and paid the local currency
- large number of jobs outsourced
Trends in Ops: Yield Management
- Simply by charging different prices to different segments based on their likelihood for payment, you don’t have to spend any more money on resources (in Atlantic City example - bus, gas, etc) but you fill the bus and maximize your profit
- Ideal for perishable items - (airline seats have no value after the plane takes off, hotel rooms have no value for that night after the night is over, etc.)
Success in Yield Management - The trick is to segment your customers and know how much they are willing to pay
- fixed costs high, variable costs low
- product can be sold in advance
Trends in Ops: Modular Design
- use standard components to produce a variety of products
- e.g. Lego Set
- customization and standardization can be achieved simultaneously
- trend - instead of nuts and bolts, use adhesives
Trends in Ops: Profit Pool
- profits rather than revenue
- considers both revenue and profit margin
- usual example is computers - hardware, processor, operating system, assembly, financing, trading, etc. By examining profit pools, company identifies deepest pool that will make max profits
- walmart will make larger items (destination product) less expensive but then charge more for cords, etc.
Trends in Ops: Winner Takes All
- many industries have high competition so their income depends on your rank
- if you’re not #1, there is no use (90% market share versus 10%)
Trends in Ops: Microprocessors
- in cars, etc
- build logical designs
Steps in Long Term Planning
- Forecasting
- Capacity Planning
- Location
- Facility Layout
- Process Design/Time Measurement
Forecasting
- The first (and fundamental) step in long term planning - vital function and impacts every management decision
- Used by all departments (accounting, marketing, production, etc.)
- Forecasting: What will happen
- Planning: What you want to happen
- Schedule: when to do the plan (starting and completion dates)
- Forecast effort should be proportional to the magnitude of the decisions made
- There will always be some error in forecasting
Four Types of Forecasting (4)
- time-series analysis (based on the idea that data relating to past demand can be used to predict future demand)
- casual relationships
- qualitative
- Simulation
Product Life Cycle
- R&D (innovators)
- Introduction (early adapters)
- Growth (early majority)
- Maturity (late majority)
- Decline (laggards)
Time Series Decomposition
- chronologically ordered
- may contain one or many of the following elements:
trend, seasonal, cyclical, autocorrelation and random - identifying these elements and separating the time series data into these components is known as decomposition
Components of Demand (6)
- Average demand for a period of time
- Trend
- Seasonal Element
- Cyclical elements
- Random variation
- autocorrelation
Trends
Identification of trend lines is a common starting point when developing a forecast
- common trend lines: linear, S-curve, exponential, asymptotic
Time Series Analysis
Using the past to predict the future (you’re assuming what happened in the past will happen in the future)
- short-term (less than 3 months) - mainly tactical decisions
- medium term (3 months to 2 years) - used to develop a strategy will be implemented over the next 6-18 months e.g. in response to demand
- long-term (greater than 2 years) - detecting general trends and major turning points
Model Selection for Forecasting
Choosing an appropriate model depends on:
- time horizon to be forecast
- data availability
- accuracy required
- size of forecasting budget
- availability of qualified personnel
Simple Moving Average
- Forecast for the short term (weeks are often used for data) when the data is pretty fixed
- takes the average of a fixed number of past periods
- removes some of the random fluctuations from the data
- longer periods provide more smoothing, shorter periods react to trends more quickly
= Ft = A(t-1) + A(t-2) + A(t-3)…A(t-n)/n
A(t-2) = actual 2 periods ago
Weighted Moving Average
- allows for unequal weights depending on the time (usually more recent gets more weight)
- the sum of the weights must be equal to one
- when selecting weights, experience or trial-and-error are the best approaches
Exponential Smoothing
- a weighted average method which includes all past data in the forecasting calculation
- more recent weights are weighted more heavily
- most used of all the techniques
- surprisingly accurate, easy (with computers), user can understand it, little computation required, tests for accuracy easy to compute
Ft = Ft-1 + alpha(At-1 - Ft-1)
alpha = the smoothing constant
At-1 is actual one period ago
Choosing Alpha & Beta
- usually a range between .1 - .3
- alpha depends on how much random variable is present
- beta depends upon how steady the trend is
Linear Regression
- regression is used to identify the functional relationship between two or more correlated variables, usually from observed data
- one variable (dependent) is predicted given values of the other variable (independent)
- assumes relationships can be explained with a straight line
Y = a +bt
Seasonal Variation
can be either additive or multiplicative
Forecast Errors
- difference between the forecast value and what actually occurred
- sources of error: bias (consistent mistake), random (unexplained)
Measures of Forecast Error (3)
- Mean absolute deviation (MAD) - ideally will be zero
- Mean absolute percentage error (MAPE) - scales the forecast error to the magnitude of demand
- Tracking signal - indicates whether forecasting errors are accumulating over time
Casual Relationship Forecasting
- uses independent variables other than time to predict future demand (the variable must be a leading indicator)
- care must be taken in selecting variables - some are just correlated events
Multiple Regression Techniques
- often, more than one independent variable may be a valid predictor of demand
Qualitative Forecasting Methods
- generally used to take advantage of expert knowledge
- useful when judgment is required
e. g. market research
Capacity
- the maximum rate of output of a process or system
- all departments need capacity information to make decisions
- done in the long-term and short-term
Capacity Utilization
average output rate/max capacity
- should not go beyond .65 (or long wait times)
Factors Affecting Capacity (5)
- Economies of Scale
- Diseconomies of Scale
- Economies of Scope
- U-Shaped time-capacity cost curve
- Focus Factory
Economies of Scale
the greater the quantity of a good produced, the lower the per-unit fixed cost because these costs are shared over a larger number of goods
- spreading fixed costs
- reducing construction costs
- cutting costs of purchased materials
- finding process advantages