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7/29/2019 WH science 1415
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W A R E H O U S E P E R F O R M A N C E M E A S U R E S
C H A P T E R S 1 4 - 1 5
Warehouse and Distribution
Science
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C H A P T E R 1 4
Activity Profiling
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ABC Analysis
80-20 Rule
Ranking by $-volume is financial
Ranking by labor or space needs is operational
Often find surprises in examining warehouse activity
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ABC Profiling
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Statistical Analysis
Data Needs
Sku data
Order data
Warehouse location data
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Sku data
May reside in different databases
When in doubt get it all
ID, description, product family, address of storage
locations, dimensions, packing, date introduced,maximum inventory level
Sku data
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Order Data
Order ID, Skus, customer, special handling,date/time order picked up, quantity shipped
Order data is financial information and usually
accurate, but Not necessarily operations focused, e.g. date ordered,
not date picked
Validate with lines shipped each day
Very large quantity of data
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Warehouse Layout & Location
Least standardized
Blueprints, sketches, CAD files
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Issues with Profiling
Getting the data
Data mining
Discrepancies in the data
Validating Interpreting patterns
Beware of small numbers
Beware of sample biases E. TuftesThe Visual Display of Quantitative
Information
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C H A P T E R 1 5
Benchmarking
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Benchmarking
What to measure?
With whom to compare?
How to improve?
Compare a warehouse with similar warehouses. Examine its facilities and processes to adopt if better
performing.
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Performance Measures
Units of output achieved/Units of input required
Operating cost (cost as % of sales)
Operating productivity (picklines, orders, etc. per
person hour) Response time (order-cycle time)
Order accuracy (% of shipments with returns)
Advantages/disadvantages of these measures?
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Benchmarking
Comparing warehouse with other warehouses
Internally or externally
Ratio-based benchmarking
Aggregate benchmarking Data Envelop Analysis
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Efficient Frontier
Convex combination
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Regression Line
Pick rates at
similar
warehouses
Fit a regression line forsize versus averagepicks per person-hour.
Generally, larger
warehouses are lessefficient
Larger warehouses havemore travel time
Figure 15.5
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Conclusions of GT Study
There was no difference between union and non-union warehouses.
Warehouses with low capital investment tended to
outperform those with high capital investment.Inflexible automation.
Smaller warehouses tended to outperform largerwarehouses.
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Are smaller warehouses more efficient?
Pure size hurts efficiency
Size requires process changes
E.g. Walmart
Changed the smallest quantity handled, from eaches tocartons, etc.
Utilize cross-docking to eliminate double handling.