TABLE 4-3 How Analytics Benefits Inventory Visibility Business Benefit from Applying Analytics Data Owner Data Sources
Example Metrics
Improve inventory visibility
Procurement
Buying director
Manager
B2B integration platform
ASN timeliness
Improve supplier management
Operations director
Manager
ERP Delivery timeliness
Improve inventory management
Transportation
Logistics director
Manager
Accounts payable/ receivable
Quantity variance
Implement vendor managed inventory
CFO
Financial director
Warehouse management system (WMS)
Delivery count and frequency by trading partner
Reduce logistics costs
Operations
Logistics
Transportation Management System (TMS)
Count of nodes by SKU/order
Reduce LWOE write-offs
Operations
Logistics
ERP/MRP Percentage of units wasted due to expiration
Reduce warehouse/ distribution center carry costs
Operations
Logistics
ERP/WMS/TMS Total logistics cost per SKU/RMC
CHAPTER 4 Use Cases for Supply Chain Analytics 35
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that don’t provide good service and value. You can make sure that you’re getting what you’re paying for, and quickly make adjust- ments where that isn’t happening. Table 4-4 highlights how the quality reporting process in relation to trading partners can bene- fit from the use of analytics, who benefits in the organization, and the sources of information that are used as part of this particular use case.
TABLE 4-4 How Analytics Benefits Partner Performance Reporting
Business Benefit from Applying Analytics Data Owner Data Sources
Example Metrics
Improve supplier management
Procurement
Buying director
Manager
B2B integration platform
Returned product count and frequency
Improve supply chain management
Product director
Manager
ERP/B2B integration platform
Delivery On-Time and In-Full (OTIF)
Improve renegotiating & bargaining position
Supply chain director
Manager
Third-party trading exchanges
Order and price accuracy
Develop strategic supplier relationships
Operations director
Manager
Accounts payable/ receivable
Invoice accuracy against PO and contracted price
Reduce procurement costs
Quality team ERP/quality reporting System
Track supplier compliance and quality resolution speed
Improve customer experience
Compliance officer
Product management
B2B integration platform
Top SKU/RMC with quality issues
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Procurement Reporting Procurement reporting provides the information foundation improving the procure-to-pay process. It provides a clear idea of the amount of business the company is doing with each of its suppliers and how well each supplier is performing. Imagine a large organization that has recently completed an acquisition and now has thousands of new suppliers. If it can’t quickly find out the exact spend with these suppliers, supply chain costs are likely to mount significantly. Table 4-5 highlights how the procurement reporting process benefits from the use of analytics, who benefits in the organization, and the sources of information used in this use case.
TABLE 4-5 How Analytics Benefits Procurement Reporting Business Benefit from Applying Analytics Data Owner Data Sources
Example Metrics
Reduce supply chain spend
Procurement
Buying director
Manager
B2B integration platform
Top trading partners by spend
Improve supplier management
Product director
Manager
ERP Price variance against contracts
Improve sourcing strategies
Supply chain director
Manager
Accounts payable/ receivable
OTIF rates
Reduce procurement costs
Operations director
Manager
ERP/B2B integration platform
Order acceptance
Improve bargaining position
CFO
Financial director
Marketing
Product management
ERP/B2B integration platform
Top products by invoiced amount
CHAPTER 4 Use Cases for Supply Chain Analytics 37
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Business Benefit from Applying Analytics Data Owner Data Sources
Example Metrics
Improve negotiation leverage
Operations
Procurement
ERP/B2B integration platform
Volume of transactions by trading partner
Reduce procurement costs
Transport
Logistics director
Manager
ERP/B2B integration platform
Top trading partners by spend
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CHAPTER 5 A Six-Stage Approach to Getting Started 39
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A Six-Stage Approach to Getting Started
For most organizations, analytics has traditionally consisted mainly of looking at historical data in spreadsheets. Decisions have been as much about gut feel as they were about intelli-
gent analytics. What could possibly go wrong? (You already know the answer to that, right?) Supply chain analytics can help an organization move from being a gut feel kind of company to an analytics-driven one.
It all starts by answering a few questions: What do I need to mea- sure? Where’s my data? Who should be involved? What software do I need? How can I measure success? I try to help you find those answers in this chapter.
Step 1: Identify the Business Problem Start Step 1 by identifying the business problem and the KPI met- rics that will be used to analyze and address the problem. Per- haps you need to release more cash from your supply chain, or reduce inventory levels, or address challenges you’re having with on-time, in-full orders that are affecting your customer relation- ships. This step is about fully understanding the problem. Conduct
Chapter 5
IN THIS CHAPTER
» Planning and building an analytics initiative
» Measuring the success of an initiative
» Discovering a short list of things to avoid
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a thorough root cause analysis to discover why the problems are occurring and what actions to take to reduce inefficiencies and waste.
From there, you can begin to structure your analytics program, setting in place the KPI levels you want to reach and the metrics you need to measure to get there. After that’s in place, it should be obvious which transactions are of interest.
Just because you can doesn’t mean you should. Many companies get new analytics tools and jump straight into measurement. They don’t stop to consider the business problems they’re trying to solve. These are the companies who struggle to justify their analytics investment.
When planning a supply chain analytics strategy, a good place to start is to determine the maturity level of your current activities so that a baseline operational state can be determined. Luckily, a number of services are available to help. Many organizations, like analytics training company TDWI, have developed Analytics Maturity Models. These models help an organization understand the phases of maturity in analytics, interpret assessment scores, and provide best practices to move forward.
