Warehouse Activity Profiling

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RightChain™ Warehousing Insights Warehouse Activity Profiling and Data Mining

Edward H. Frazelle, Ph.D. President and CEO RightChain™ Incorporated

“Buy truth, and do not sell it; buy wisdom, instruction, and understanding. “ - Solomon

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• The Power of Profiling

• Quick revelation and elimination.

• The Payoff of Profiling

• Purpose driven participation.

• The Purpose of Profiling

• You can drown in a lake that’s two feet deep.

The P’s and P’s of Profiling

• The Principle & Principal of Profiling • Alfred Pareto • The Practice of Profiling

• Wallowing in data stimulates fact-based thinking.

• The Picture of Profiling

• A picture is worth one thousand words.

• The Peril of Profiling • Paralysis of analysis.

Dangerous Averages

Purpose of Profiling

50%

50%

10% 15% 20% 25% 30% 35% 40% 45% 50%

The average is 2, but there aren’t any 2s.

0% 5%

0%

1

2

3

Items per Order

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Participation in Profiling

Involves key stakeholders

Facilitates design collaboration

Catalyst for cooperation

Encourages objectivity

Puts skin in the game

Raises results accountability

Leverages know-how

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Principal of Profiling

• Applied to gardening…

• 20% of the bees do 80% of the pollination.

• Applied to wealth…

Vilfredo Pareto, 1848-1923

• 20% of the people have 80% of the wealth.

• Applied to sales…

• 20% of the sales people yield 80% of the sales.

• Applied to SKUs…

• 20% of the items yield 80% of the sales.

• Applied to warehousing…

• The majority of the picking activity stems from a minority of the items. • The majority of the inventory cube stems from a minority of the items. • The majority of the shipping volume stems from a minority of the customers. • The majority of receipts come from a minority of suppliers.

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Perspectives of Profiling

Interactive Data Simulation

Interactive Data Visualization

Two-Dimensional Simulation

Three-Dimensional Animation

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• Paralysis of analysis is the paralyzing of a decision-making process due to over analyzing data and options related to the decision. • Stop analyzing and start solving the problem. • What’s the minimum amount of analysis required to make the decision? • What decision are we trying to make? • What questions require answers for making the decision? • What information is required to answer the questions? • What data is required for that information

Paralysis of Analysis

RightChain™ Warehousing Perspectives

Buyer or Planner

Supply Chain Role Raw Material, WIP, Finished Goods

Value and Velocity ABCD SKUs/Customers

Geography International vs Domestic Specific Location

Source Supplier or Carrier Commodity

INVENTORY PERSPECTIVES

Time Product Maturity Planning Horizon

Supply Chain Echelon Supplier, Factory, Warehouse, DC, Depot

Classification and Variability Seasonal, Fashion, Basic

Supply Chain Role Lot Size, Safety Stock, Pipeline, Build

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RightChain™ Warehousing Insights

Raw Transaction Data

SKU Insights

Picking Insights

Shipping Insights

Receiving Insights

Putaway Insights

SKU Profiles include SKU ABCs, SKU Pick Profiles, SKU Affinities, SKU Volumetrics, and Calendar Clock Profiles.

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SKU Master

RightChain.ai

Location Master

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RightChain™ Warehousing Insights Structure

Perspective 1

Source 1

Perspective 2

Source 2

RightChain™ Warehousing Database

RightChain™ Warehousing Insights

Perspective 3

Source 3

Perspective n

Source n

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SKU ABCs | Lines

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ABCD SKU Classification

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SKU Affinities | SKU Demand Correlation

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Demand Correlation Profile

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Item-Order Completion Profile

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Order Mix Distribution Family Mix

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Order Mix Distribution Handling Unit Mix | Pallet/Case

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Order Mix Distribution Handling Unit Mix | Broken/Full Case

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Order Increment Distribution Pallet Portion Profile

Half Pallets

Quarter Pallets

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Order Increment Distribution Layer Portion Profile

• A layer of cases on a pallet is a common customer order quantity. • An example from a food and beverage client is illustrated below. • Note that 80 percent of the order lines are for full-layer increments. • Our strong recommendation was that case layer picking be implemented. • A dramatic increase in productivity and throughput capacity resulted.

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Order Increment Distribution Case Portion Profile

Half Carton Inner Packs

Full Carton Round-Up

Order Increment Distribution for a Pharmaceutical Company

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Lines per Order Distribution Type I: Consumer Direct

DOUBLES Correlated assignments make doubles picking highly productive.

SINGLES Single line orders

are batched together for high pick efficiency.

MULTIs are picked in large batches with pick-pack carts.

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Lines per Order Distribution Type II: Retail/Grocery/Dealership Replenishment

Another common lines per order distribution is the mirror image of the previous figure. The peak is around ten plus lines per order. This is common in retail/grocery/dealer distribution where the customer is a retail store/grocery store/dealership. In that case, there is typically enough work to do within an order so that the order itself represents an efficient workset. Or, the order may be so large that it may be split across multiple order fillers for zone-wave picking. Another strategy is to work multiple picking policies in the same facility.

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Cube per Order Distribution

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Lines & Cube per Order Profile Type I: Consumer Direct

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Lines and Cube per Order Distribution Type II: Replenishment

MEDIUM ORDERS Medium sized orders are picked with carts holding 2 to 5 orders.

Order by Cube/Lines

12.00%

10.00%

SMALL ORDERS Picked with special pick-pack carts holding 10 to 20 orders per picking tour.

8.00%

LARGE ORDERS Picked one order at a time on large pick carts.

%Orders

6.00%

4.00%

2.00%

<1 1 - 4.99 5 - 14.99 15 - 29.99 30 - 59.99 60 - 89.99 90 - 149.99 150 - 500+

90 - 149.99

0.00%

30 - 59.99

1

2 -5

5 - 14.99

6 - 10

Cube per Order

10-50

<1

51-100

Lines per Order

100-200

200-300

300+

Lines & Cube Profile for a Major Retailer

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Cube Movement Profile

25%

20%

20%

15%

15%

15%

12%

10%

10%

8%

10%

% Items

5%

3%

5%

2%

0%

<0.1

1,000+

0.1 to 0.5

.5 to 2

2 to 5

5 to 10

10 to 50

50 to 100

100 to 250

250 to 1,000

Cube per Month

Cube Movement Profile for a Major Valves & Fitting Distributor

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Handling Unit Inventory Profile

0.0% 10.0% 20.0% 30.0% 40.0% 50.0% 60.0% 70.0% 80.0% 90.0% 100.0%

Cum % of SKU's Cum % of Pallets

Lane Depth Optimized Floor Storage

Two-Deep

Push-Back

Single Deep

Pallet Rack

Decked

Racking

Three-Deep

Push-Back

Number of Pallets on Hand

Inventory Activity Profile for a Major Office Machines Company

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Month-of-the-Year

Non Cross-Trained Staffing Requirement

Cross-Trained Staffing Requirement

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Week-of-the-Month

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Weekday Activity Profile

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Hour-of-the-Day

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Exercises • Profiling Practice

Name three inventory activity profiles that you don’t have, would like to have, the decisions they would influence, the required sources of information, and associated queries. • Profiling Priorities List and prioritize the ten most important data elements to support inventory planning for a particular item. • Units of Measure List the pros, cons, and applications for measuring inventory levels in turns, days on-hand, leadtimes on-hand, $value on-hand, cube, and weight. • Pareto on Profiling Name as many examples as you can for how Pareto’s Law might work in inventory management.

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