Developing an Internal Supply Chain Analytics Competency · internal supply chain analytics...
Transcript of Developing an Internal Supply Chain Analytics Competency · internal supply chain analytics...
Developing an Internal Supply Chain Analytics Competency
A Case Study
Preview
• Topic Description
In this session we will discuss the process of developing an internal supply chain analytics competency through the lens of a major retailer’s recent initiatives. – What elements need to be considered before and during
development of an internal supply chain analytics competency?
– What challenges are commonly experienced?
– What conditions are necessary, and what practices lead to long-term retention of a competency in supply chain analytics?
Agenda
• Introduction and Background
• Elements of a Supply Chain Analytics Competency
• A Framework for Development
• Common Challenges Experienced
• Necessary Conditions and Best Practices
Agenda
• Introduction and Background
• Elements of a Supply Chain Analytics Competency
• A Framework for Development
• Common Challenges Experienced
• Necessary Conditions and Best Practices
• Timeline: Major Retailer
Background
Green light for enhancement
of internal supply chain
analytics competency
Chainalytics engaged for
technology RFP and Selection
Services
Chainalytics engaged for Competency Development
Services
Joint rollout of new Analytics,
Processes, Tools, Data, and Team
Organization
Newly instantiated
Competency is now beginning to embed and
grow
2009 2010 2011 2012
Motivation
• Common Drivers – Margin growth; path forward to get to next level
– Increased complexity; old approaches no longer sufficient
– Budget pressure; external services spend too high
– Agility desire; increase ability to react and respond faster
– Risk mitigation; preparedness and contingency planning
• For This Retailer – Primary motivation for enhancing and expanding an internal supply chain
analytics competency was Increased Complexity, but all of the above were part of the decision to proceed
– Use of external services to help develop the competency was not without careful consideration; balancing cost vs. value and likelihood of success
Agenda
• Introduction and Background
• Elements of a Supply Chain Analytics Competency
• A Framework for Development
• Common Challenges Experienced
• Necessary Conditions and Best Practices
Team Data
Elements
Process Technology
Analyses
Framework
Define the specific supply
chain questions to
answer
Determine the Analyses
required to answer the questions
Understand the inputs,
outputs, owners, form, and frequency
Choose an approach and Technology to support each
analysis
Learn the usage rules of the approach
and technology set selected
Establish the detailed
Process and workflows to be executed
Map the Data elements,
definitions, sources, and specific uses
Design, create, test, and
implement supporting
architecture
Identify the skills needed to execute all elements of the process
Align the Team staffing to the resulting mix of skills and roles
required
List of Analyses to Support (Partial)
Strategic Network Design: Open/Closed/Location; and Territory Assignment Decisions
Velocity-Based Analysis: This process identifies vendors and vendor-ship points with fast-moving product from a company-wide perspective rather than per buying group.
Inventory Safety Stock Analysis: This process determines the necessary safety stock required to be on hand at a node based on supply lean time, lead time variability, product service level, demand, and demand variability
Forward Buy Analysis: This process is performed when a product’s price will be increased in the near future and there is the ability to purchase an increased amount of the product in advance. This process determines the lowest average cost per product unit given shelf life restrictions, max. quantity of product the vendor will allow to be purchased, and any OTB constraints.
Evaluate Import Opportunity: The purpose of this analysis process is to evaluate the different landed costs associated with importing a product or sourcing domestically.
Evaluate Inbound Consolidation Analysis: The purpose of this analysis is to determine if there are cost benefits with using a consolidation center prior to bring a truck to the DC.
Prepaid or Collect Delivery Analysis: This process is performed when the Buying/Planning Team needs to determine if there is a cost advantage of taking responsibility of transporting product to the vendor. This process can be used to evaluate a proposed reduction in list prices and allowances or to determine the amount of reduction that would be necessary from the vendor in order to make Pickup economically advantageous.
Plant-Direct Shipment: The purpose of this analysis process is the evaluate picking up a product at a vendor’s manufacturing plant. This is possible when the Vendor uses its own distribution center not co-located with the manufacturing plan and will allow picking-up products from the DC.
Evaluate X-Dock, Warehouse, or Combo at RSC: The purpose of this analysis is to provide a method to evaluate the different DC and transportation costs associated with either cross-docking a product, combo’ing the product, or warehousing the product. This analysis does not have to be determined for every product, but can be used as a guide to understanding the associated costs.
Analyses
Technology Network Design/Product Flow Capabilities Weight
1 Model Structure 20%
2 Sourcing Rules/Contraints 20%
3 Cost Elements Included/supported 20%
4 Historical (Baseline) Modeling 10%
5 Data Development/Manipulation 15%
6 Technical 15%
Inventory Optimization Capabilities Weight1 Product Segmentation 10%
2 Life-cycle Parameter Maintenance 10%
3 Inventory Planning 50%
4 Service Level Targets 15%
5 Exception based workflow 15%
Transporation Modeling Solution Capabilities Weight
1 Ease of Use 10%
2 Rating Capabilities 20%
3 Load Building Capabilities 20%
4 Scheduling 20%
5 Reporting 10%
6 Scalability 20%
Area Sub Area Must Haves Weight
Mentioned
in RFP
Response
Verified in
Demo
Mentioned in
RFP
Response
Verified in
Demo
Multi echelon Ability to skip echelons
Product Flow forward and reverse
Multiperiod Models open/close decisions, and associated costs
by period with ability to respect prior period
decisions.
Inventory modeling Carry inventory from period to period
Cycle stock, safety stock, and in-transit
inventory
Safety stock varying in a non-linear manner
as facility throughput changes
Days on hand/weeks on hand requirements
Capacity constraints Transporation, facility, process, and product
levels
Processes/
Resources
Service Level
requirements
Constraints across
model entities
20% 5-Excellent 1-Unacceptable 5-Excellent 1-Unacceptable
Model Structure
Vendor 1 Vendor 2
Process
Data
6 Supply Planners 80% Merchant Support 20% Internal SC Analysis MS Excel (MS Access)
3 Supply Planners 80% Merchant Support 10% Internal SC Analysis 10% Data Preparation MS Access MS Excel Network/Flow Path Tool Inventory Optimization Tool
2 Supply Chain Analysts 20% Merchant Support 60% Internal SC Analysis 20% Data Preparation MS Access MS Excel Network/Flow Path Tool Inventory Optimization Tool
1 Data Analyst 0% Merchant Support 0% Internal SC Analysis 100% Data Preparation MS Access MS Excel SQL Server/SQL Scripting Data Systems
Current State
Future State
Product Category Focus Network/Capacity Focus
Team
Agenda
• Introduction and Background
• Elements of a Supply Chain Analytics Competency
• A Framework for Development
• Common Challenges Experienced
• Necessary Conditions and Best Practices
Common Challenges Experienced
• Team
– Specific mix of skills is rare (business + data + analytical) – hard to hire
– Long-term retention vs. career growth is tough – hard to keep
– Line between IT and supply chain ownership blurs – hard to manage
• Data
– Supply chain analytics require vast breadth of data – hard to gather
– Efficiency requires repeatability and “refreshability” – hard to maintain
• Analyses
– Analyses can be new and complex – hard to communicate the value
• Process
– Processes can be very different – change management is significant
Necessary Conditions and Best Practices
• Must Have – Sponsorship willing to champion internally
– Stakeholders able to commit to a multi-year effort
– Budget sufficient to support the development and upkeep
– Data needed to support the Analyses, Tools, Processes
• Best Practices – Launch new processes through expert-assisted, phased, hands-on joint execution and
rollout, rather than a “train on the tool and then try on your own” approach
– Primary data sources and prep must be owned and accessible by supply chain team members; reliance on outside resources will jeopardize the effectiveness of the team
– Spend the time to carefully map out the holistic considerations on Data, Team, and communication of inputs/outputs to stakeholders and customers of the Analyses
Questions and Discussion