Developing an Internal Supply Chain Analytics Competency. A Case Study

Similar documents
Model, Analyze and Optimize the Supply Chain

11 Key Questions When Adding a Distribution Center

Business Challenges. Customer retention and new customer acquisition (customer relationship management)

Software for Supply Chain Design and Analysis

Supply Chain Design and the effects on shipping

Integrated Sales and Operations Business Planning for Chemicals

Global Enterprise Business Management Platform Interactive, Intelligent with Controls to Ensure Profit

BI STRATEGY FRAMEWORK

Supply Chain development - a cornerstone for business success

Logistics Management SC Performance, SC Drivers and Metrics. Özgür Kabak, Ph.D.

Strategic Framework to Analyze Supply Chains

BUILDING A DEMAND-DRIVEN SUPPLY CHAIN THROUGH INTEGRATED BUSINESS MANAGEMENT FROM EXECUTION TO OPTIMIZATION ADVANCED EXECUTIVE EDUCATION SERIES

Four distribution strategies for extending ERP to boost business performance

QA Engagement Models. Managed / Integrated Test Center A Case Study

About Inventory Optimization

Integrated Fulfillment: Modern Warehouse Management

Supply & Demand Management

Webinar: The Three Cornerstones for Effective Supply and Demand Planning

Building an Internal Supply Chain Design Competency with External Support. June 19, & CHAINalytics. Presented by:

Focused Metrics. Tom Vander Weide G-3 Enterprises and Tom Patterson Saddle Creek Corporation

White Paper February IBM Cognos Supply Chain Analytics

How to Cheat and Make Better Decisions with Predictive Analytics. Track 1 Session 3

E-Logistics Successes and Failures

Transportation Management

NCOE whitepaper Master Data Deployment and Management in a Global ERP Implementation

Value Creation Through Supply Chain Network Optimization To Address Dynamic Supply Chain

Supply chain intelligence: benefits, techniques and future trends

PLANNING FORECASTING & PROCESS OPTIMISATION. Caleb Nicolson General Manager Group Supply Chain

Electronics Components Manufacturing: The Path to Excellence

LOGISTICS & SUPPLY CHAIN MANAGEMENT

Optimizing Inventory in Today s Challenging Environment Maximo Monday August 11, 2008

Moving Away from Legacy Systems and Choosing the Right ERP Solution

DESIGNING AND WHOLESALING

Supply Chain Management

IT Cost Reduction. Doing More with Less. Anita Ballaney, Vishwanath Shenoy, Michael Gavigan. Strategic IT cost reduction - Doing More with Less

Logical Modeling for an Enterprise MDM Initiative

Supply Chain Management Build Connections

Planning & Allocation vs. Replenishment: When is Each the Best Strategy?

Transportation. Transportation decisions. The role of transportation in the SC. A key decision area within the logistics mix

Planning an ERP Implementation Small and Medium Enterprises

Building a Business Case for Supply Chain Execution in the Cloud

Supply chain network optimization

Operations/Inventory Excellence

26/10/2015. Enterprise Information Systems. Learning Objectives. System Category Enterprise Systems. ACS-1803 Introduction to Information Systems

BI4Dynamics provides rich business intelligence capabilities to companies of all sizes and industries. From the first day on you can analyse your

Chapter Introduction. Distribution Strategies. Traditional Warehousing Intermediate Inventory Storage Point Strategies

Contact Center Consolidation and Centralization: Building a Plan to Get There

The Network Approach to Inventory Management

Your Trusted Supply Chain Partner. We Teach. We Consult. We Do.

SCALING UP RFID FOR RETAIL CHAINS

The fact is that 90% of business strategies are not implemented through operations as intended. Overview

The Training Material on Logistics Planning and Analysis has been produced under Project Sustainable Human Resource Development in Logistic Services

Enhancing Sales and Operations Planning with Forecasting Analytics and Business Intelligence WHITE PAPER

Who s your Big Data? Big Data Metrics, what it is, how it works and who benefits.

PART 1: THE WHAT, WHO, AND WHY OF MSP BY JENNIFER SPICHER

Making Strategic Decisions with Oracle Advanced Planning. An Oracle White Paper September 2006

MSD Supply Chain Programme Strategy Workshop

Certification in Humanitarian Supply Chain Management (CHSCM) Competence Model. Final Version 2007

Product Documentation SAP Business ByDesign Supply Chain Setup Management

Positioned for Growth: SAP Update / Supply Chain Optimization

<Insert Picture Here> Oracle Retail Data Model Overview

Unifying the Private Fleet with Purchased Transportation

OVERCOMING FIELD SERVICE & REVERSE LOGISTICS CHALLENGES WITH AN INTEGRATED, BEST OF BREED ENTERPRISE SERVICE MANAGEMENT SYSTEM

Becoming a Business Analyst

Date : Max. Marks :100 Time : a.m. to 1.00 p.m. Duration : 3 Hrs.

College of Engineering, Technology, and Computer Science

Supply Chain. cinagement. IStlGS USO OS.S. Fourth Edition. Donald J. Bowersox David J. Closs M. Bixby Cooper John C. Bowersox.

Big Data Analytics Valuation Methodology and Strategic initiatives

ACS-1803 Introduction to Information Systems. Enterprise Information Systems. Lecture Outline 6

Retail 2020 Challenges: Collaborating for Growth through Supply Chain Efficiencies. Jeff Holmes Managing Director, Retail and Consumer PwC

Oracle Value Chain Planning Inventory Optimization

Business Intelligence (BI) Data Store Project Discussion / Draft Outline for Requirements Document

Segmentation in Demand Planning for Enhanced Forecast Accuracy

What s Trending in Analytics for the Consumer Packaged Goods Industry?

Delivering Smart Results

Visibility in the Supply Chain

Is it Time to Purchase a Fashion Enterprise Solution?

Scaleable cloud-based warehousing & delivery for South Africa

Vancouver Chapter Study Group. BABOK Chapter 1 Introduction. Jorge Vega

Strategic Network Design. Focus Topic Paper. Supply Chain Management Logistics & Distribution. Value Chain Excellence. Strategy to Results.

Leveraging Continuous Auditing / Continuous Monitoring in internal audit April 10, 2012

PwC The Path Forward for Data Analysis and Continuous Auditing May 2011

Transforming Enterprise

Supply Chain Management Seminar at Bangalore Dec. 6, 2003

Today, the world s leading insurers

LDAP Authentication Configuration Appendix

3.7 Logistics Execution

1) A complete SCM solution includes customers, service providers and partners. Answer: TRUE Diff: 2 Page Ref: 304

RedPrairie > Retail > White Paper. The Bottom Line Benefits of Workforce Management in Retail Distribution

SOLUTION OVERVIEW SAS MERCHANDISE INTELLIGENCE. Make the right decisions through every stage of the merchandise life cycle

Business Forecasting and Analytics Forum

Logistics / Supply Chain Management. Industry Overview and Statistical Profile

How To Use Ecommerce With Ecommerce (Edi)

Improve the Agility of Demand-Driven Supply Networks

SCM. Logistics, Service, and Operations Management

Understanding Gross Margin Impacts on Profitability

Huawei Managed Services Unified Platform (MS UP) v1.0

ELA Standards of Competence on the Supervisory/Operational Management Level

Investing in an Internet of Things (IoT) Solution: Asking the Right Questions to Minimize TCO

Transcription:

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

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 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

Elements Analyses Technology Process Data Team

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

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.

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

Process

Data

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

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 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

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