Developing an Internal Supply Chain Analytics Competency. A Case Study

Transcription

1 Developing an Internal Supply Chain Analytics Competency A Case Study

2 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?

3 Agenda Introduction and Background Elements of a Supply Chain Analytics Competency A Framework for Development Common Challenges Experienced Necessary Conditions and Best Practices

4 Agenda Introduction and Background Elements of a Supply Chain Analytics Competency A Framework for Development Common Challenges Experienced Necessary Conditions and Best Practices

5 Background Timeline: Major Retailer 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

6 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

7 Agenda Introduction and Background Elements of a Supply Chain Analytics Competency A Framework for Development Common Challenges Experienced Necessary Conditions and Best Practices

8 Elements Analyses Technology Process Data Team

9 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 Align the Team staffing to the resulting mix of skills and roles required Identify the skills needed to execute all elements of the process Design, create, test, and implement supporting architecture Map the Data elements, definitions, sources, and specific uses Establish the detailed Process and workflows to be executed

10 Analyses 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.

11 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 Weight 1 Product Segmentation 10% 2 Life-cycle Parameter Maintenance 10% Area Sub Area Must Haves Weight 3 Inventory Model Planning Structure Multi echelon Ability to skip echelons 50% 4 Service Level Targets Product Flow forward and reverse 15% 5 Multiperiod Models open/close decisions, and associated costs Exception based workflow by period with ability to respect 15% prior period decisions. Inventory modeling Carry inventory from period to period Transporation Modeling Solution Capabilities Cycle stock, safety stock, Weight and in-transit 1 Ease of Use inventory 10% Safety stock varying in a non-linear manner 2 Rating Capabilities 20% as facility throughput changes 3 Load Building Capabilities Days on hand/weeks on hand 20% requirements 4 Scheduling Capacity constraints Transporation, facility, process, 20% and product levels 5 Reporting Processes/ 10% 6 Scalability Resources Service Level 20% requirements Constraints across model entities Mentioned in RFP Response Vendor 1 Vendor 2 Mentioned in Verified in RFP Demo Response Verified in Demo 20% 5-Excellent 1-Unacceptable 5-Excellent 1-Unacceptable

12 Process

13 Data

14 Team Current State 6 Supply Planners 80% Merchant Support 20% Internal SC Analysis MS Excel (MS Access) Future State 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 Product Category Focus Network/Capacity Focus

15 Agenda Introduction and Background Elements of a Supply Chain Analytics Competency A Framework for Development Common Challenges Experienced Necessary Conditions and Best Practices

16 Common Challenges Experienced Team Data 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 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

17 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

18 Questions and Discussion