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Terms in this set (100)
HP Problems with Supply Chain
Japanese Earthquake and Tsunami messed with supplier factories, good that Japan's markets are mature, fine for semiconductors but issue for chips, move towards just-in-case mentality
Apple Watch Problem
Supplier of taptic sensors created defective, slowed rollout, highlights potential downside of Apple's lean supply chain, Apple can produce mass quantities at little waste and excess supply, but can experience shortages when a prob arises with key part
Corp level strategic planning
What busi am I? What am I better at? Mission statements, core competencies
Core competency
essential capabilities that create a firm's sustainable competitive advantage, PROCESSES NOT TECH
ex/ American airlines with reservation sys, scheduling, distribution
ex/ Fedex- delivery, tracking, etc
Business level strategic planning
How to position firm? Competitive priorities?
order winners and qualifiers, market analysis
Porter's Five Forces: Market Analysis
1. Potential Entrants
2. Suppliers
3. Substitute products
4. Buyers
5. Rivals among existing firms
--> Industry competitors
Order qualifier
Something that makes a product or service qualify for consideration for purchase
Order winner
something that makes you choose one product over its rival, may become order qualifiers over time
Specific order Qualifiers/Winners
Cost:Low production cost
Quality: design quality, product reliability, product durability, post-sale service
Delivery: speed and dependability
Flexibility: product, vol, process flex
CANT BE BEST AT ALL OF THESE
Functional Strategic Planning
1. Finance Strat
2.Operation Strat
3. Marketing
How can i implement my strategic directives? support strategic positioning and competitive priorities
Four basic operations strategies
1. Cost
2. Quantity
3. Delivery
4. Flexibility
Competing on Cost
-Continually reduce costs in materials, labor, inventory, transportations
ex/ Southwest
Competing on Quality
-delivering higher performance/consistent product
-product development with high durability, superior features
-service
-error reduction
-variability reduction (Six Sigma a disciplined, data-driven approach and methodology for eliminating defects (driving toward six standard deviations between the mean and the nearest specification limi)
ex/ Mercedes Benz
Competing on Delivery
-continually reduce processing time (scanning rather then processing)
-no wasted time (redesign for linear workflow sequence)
Ex/ FedEx
Competing on Flexibility
Being better able to adapt to changes in customer needs
-product variety through flexible manufacturing sys, component commonality, mass customization
-volume flexibility through temp labor, outsourcing
Ex/ Dell
Key Strategic Decisions
Primary factor- product type/mix (variety, vol, custom)
similar: critical resource (labor/capital)
org of resources--process flow
produce to order or to forecast?
type of equip and degree of automation (Process choice)
INTERRELATED AND DEPEND ON MARKET POSITIONING
Job Shop Process
Production
-small batches
-unique set or sequence of processing steps
-labor intensive
Products:
-customized
-one of a kind
HIGH VARIETY LOW VOLUME
Batch Process
Production
-periodic, medium sized batches
-multiple standardized routings
-relatively labor intensive
Products:
-limited product line
-as per forecast or customer order
MEDIUM VARIETY MEDIUM VOLUME
Assembly Line process
Production
-high vol
-fixed routings
-relatively capital intensive
Products
-standard (limited modular) product
-produced to forecast for inventory
LOW VARIETY HIGH VOL
Continuous Process
Production
-continuous flow of product
-fixed equipment sequencing
-capital intensive
Products
-commodity product
-typically not discrete units
SUPER LOW VARIETY AND SUPER HIGH VOL
Process/Product Matrix
see desktop, diagonal denotes effective process choice for product characteristics
- match process choice to order winners
-eval new market opportunities
Can a firm be successful if it competes off the drag? Theoretically no, but yes
Boeing Challenges
-Ramp up issues (new composite site therefore diff mfg process)
-Managing dream liners supply chain (more than 300 global suppliers, outsourcing vs designing and producing in house
Tesla*
- needed to find way to get people to plant, made it ahead of schedule to match demand for their car
-their position is to be on the forefront of tech, so they need to be the first
Examples of Poor Forecasting
Cisco- $2.2 write down for excess inventory
Ford-$1 bill of palladium
GM- 40000 sales lost due to shortage
Time Series Forecast Assumption
Past history is best predictor of future, based on time series (pre observed values) of variable to be forecasted
Demand Notation
At
Forecast (made in period t) of demand for period t+1
Ft+1
Basic Time Series about Constant mean
Demand=mean +random fluctuation
1. fluct can be pos or neg
avg fluc= 0
estimate MEAN LEVEL DEMAND
Naive Method
Simplest approach to forecasting, use the demand of the current period for the forecast of the next
Simple Average
Ft+1= (A1+A2+...At)/t
total cumulative
uses all the history of demands to generate forecast for next period
assumption: all periods are equally informative
The Simple Moving Average
-uses only the most recent n period demands to generate forecast
-treats all n recent demands equally, generating the forecast for the next period
F4=(A1+A2+A3)/3
assumption: only last n periods are important (equally)
Weighted Moving Average
weights each of the n most recent demands differently in generating the forecast for the next period
F4=0.2(A1)+0.3(A2)+0.5(A3)
Assumption: (not all recent periods equally important)
Exponential Smoothing Forecast Formula
Ft+1=a(At) + (1-a)(Ft)
-forecast for period 1 will be given or use naive
assumption: importance of data declines smoothly (in expo fashion)
What reacts faster?
smaller n and larger A
Why not use extremely responsive forecast?
may skew data due to random fluctuations
stability
ability of forecast to ignore random variations
responsiveness
ability of forecast to respond quickly to a true change in mean level demand
Forecast error formula:
et=At-Ft
Mean Forecast Error
avg error all weighted equally
Mean Absolute Deviation
Avg of abs value of errors
Mean Absolute Percentage Error
|Error|/Demand*100
MAD vs MSE
MSE penalizes large errors while MAD treats all errors equally
MSE
avg of each error^2
Forecast of Level: Double Exponential Smoothing
St=aAt+(1-a)(St-1+Tt-1)
Forecast of Trend: Double Exponential Smoothing
Tt= B(St-St-1)+(1-B)(Tt-1)
Forecast of Next period: Double Exponential Smoothing
FITt+1=St+Tt
*note: use S and T from previous period!!
Double Expo Smooth
responds to trends better
Casual Forecasting Assumption
variable we want to forecast is related to other variables in the environment
Forecasting with Seasonality
1. Perform a linear regression
2. Calculate seasonal index (actual/forecast)
3. Calculate mean seasonal index
4. Get regression forecasts ignoring seasonality
5. Multiply regression forecasts by average seasonal forecast
Forecasting demand for families of products is _______ than for members
easier
Forecasting for a month is ______ accurate than for a week
more
the further into the future you want to forecast demand the ______ accurate you are likely to be
less
Danger of using sales as estimate of demand
there may have been a shortage
Danger of using sales targets as forecasts
often generated in diff parts of the company, marketing likely to make higher estimate
CUSTOMER DEMAND _____ EQUAL TO SALES
MAY NOT BE
Why capacity planning is difficult (manufacturing)
-building capacity (esp in manufacturing busi) can take long time
-forecast of demand is often uncertain at the level of capacity is decided
-typically diff to add capacity in smooth increments
-cheaper to expand in lumps less set up costs
Why capacity planning is difficult
Staffing- to meet peak, avg, or daily demand?
throughput
avg number of units actually ebbing processed per unit time
capacity
max avg throughput that a sys can maintain under normal conditions
**throughput is less than or equal to this
utilization formula
throughput/capacity
cycle time
time interval bt completion of t2 successive units of output
cycle time for a task
equivalent to the processing time for the task (if no setup)
cycle time for a process
inverse of process capacity
throughput time for process
total time a unit of product spends in the process
Why would throughput time be greater than actual processing time?
Because of time a product spends waiting as Work-In-Process (WIP) inventory
throughput time doesn't count
before it starts the process while other are going thru
Determine Process/Sys Capacity
1. Choose a sys-wide measure of capacity to be used for all tasks (units/hr, arrivals/min)
2. Find capacity of each individual task in these units
3. Identify bottleneck
4. determine sys capacity (capacity of bottleneck)
bottleneck
step in production/service delivery process that has the lowest capacity when measured using same uni too measure, limits overall output
Expected cycle time
percentage of R1(time it takes) +percentage of R2(time it takes) +percentage of R3(time it takes)
Inventory turns formula
CGS/Inventories
Raw Materials
basic inputs to the manufacturing process
WIP
inventories of goods that have been partially process but not yet completed
FG
completed units that are awaiting shipment to customers
Companies use inventory to
-take advantage of economies of scale (quantity discounts)
-buffer against uncertainty
-speculate price changes
-smooth production in anticipation of peak demand to avoid max capacity
continuous review
inventory level is continuously monitored, when it reaches reorder point, order is placed
periodic review
i level monitored at certain times, if at or below reorder point, place order
Economic Order Quantity Assumptions
-Demand rate known and constant, can forecast perfectly and is the same for every period
-lead time known and constant, time bt placing and receiving the order is always the same
-not allowed to run out of items, all demand must be met,
-FC to ordering
-constant unit price (no quant discount)
TC
total annual relevant cost
TC formula
TC= (D/Q)Co+ (Q/2)Ch
Number of orders in a year
D/Q
Annual Ordering Cost
D/Q(Co)
Annual Holding Cost
Q/2(Ch)
Frequent orders
-small size
-incur fixed cost frequently
-low avg inventory level
infrequent orders
-large size
-incur FC infer
-high avg inv level
EOQ Formula
Q*= sq rt(2DCo/Ch)
Avg inventory
Q/2
time between orders
Q/D
TC using EOQ
TC(Q*)= sq rt (2DCoCh)
Robustness of EOQ
flat TC cost curve means if you have to change q not too bad
Reorder Point Formula
R=D*L
**Pay attention to units!!
Safety Stock
extra stock held bc of uncertainty
Reorder Point with Uncertain Demand
R=d*L+z(s.d.)sqrtL
SS with variable demand
SS=z(s.d.)sqrt(L)
z
1-a, a is probability of there being a stockout
Safety stock only affects
the reorder point, NOT EOQ
Products that incur majority of inventory control need _____ attention re: inventory
tighter
A items
very tight control, complete records, frequent/continuous review, no more than 20% of items
B items
less tightly controlled, good records, large inventories, less regular review
C items
simple controls, minimal records, large inventories, less regular review, no less than 50% of items
Procedure for ABC Inventory Analysis
1. Calculate annual dollar usage (volume) (demand*price)
2. List items in descending orde based on annual dollar vol
3. Calculate the cumulative annual dollar vol
4. classify items into groups
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