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SCOR helps address, improve, and communicate supply chain management decisions within a company and its trading partner community. Breaking down the supply chain by using the SCOR

 

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CHAPTER 3 Understanding the Basics of Metrics and KPIs 25

These materials are © 2017 John Wiley & Sons, Ltd. Any dissemination, distribution, or unauthorized use is strictly prohibited.

model allows an organization to apply metrics to business activi- ties at each of five stages: plan, source, make, deliver, return.

Benchmarking Benchmarking enables an organization to compare its analytics performance with aggregated data from other companies within a specific industry sector, including the sector’s best performers. This provides valuable context, helping to set meaningful targets, gain insight into trends occurring across the industry, and find out how a company is doing compared to its competition.

It’s good to benchmark and compare yourself against others, but don’t be tempted to set benchmark results as targets. If others in your industry sector are doing much better, don’t set matching them as a goal. Rome wasn’t built in a day. Set achievable targets for your business and develop at a pace your business can sustain.

Applying Goals to the Supply Chain Reference models like SCOR can help apply analytics to the dif- ferent parts of a supply chain process, as shown in Figure 3-3. It enables decision makers to focus on the supply chain activities to be measured and improved to achieve corporate goals. By identi- fying a series of related activities at each stage of the process, a company can drill down to work out the KPIs. Defining and mea- suring these KPIs will help create a useful overall picture of the changes needed in order to improve and grow.

FIGURE 3-3: Example supply chain activities within the SCOR reference model.

 

 

26 Supply Chain Analytics For Dummies, OpenText Special Edition

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What to Measure After identifying the supply chain activities you wish to improve, the next step is to create a series of KPIs to ensure that perfor- mance targets are being achieved. Here is a short list of the types of KPIs commonly used within supply chain organizations.

» Average customer order delivery time (in days)

» Average service delay (in days)

» Share of perfect orders delivered/received

» Cash-to-cash cycle time (in days)

» Days of sales outstanding (DSO) (in days)

» Invoice processing time

» Price per unit trend over time

» Order volumes and associated change orders

Next, assign the metrics that will be measured to ensure the KPIs are met. A vast array of metrics is available, and there is no one-size-fits-all solution. Some metrics  — such as invoice accuracy, quantity variance, and purchase costs — can apply to every business. Other metrics have more value for specific indus- tries. For example, Advanced Shipping Notices (ASN) timeliness is important within the automotive industry, where JIT and Kanban manufacturing processes demand that parts be delivered exactly where and when required.

For the purpose of this book, I’ve broken down the metrics into three types:

» Business metrics: Business metrics measures an activity that delivers value to the business. Examples include

• ASN timeliness: The number of timely ASN creation instances as a percentage of total ASNs for a time period

• Delivery timeliness: The number of “on-time” deliveries as a percentage of total number of deliveries for a time period

• Invoice accuracy: Measures whether invoices accurately reflect orders placed in terms of product, quantities, and price by supplier, during a specified period of time

 

 

CHAPTER 3 Understanding the Basics of Metrics and KPIs 27

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• Price variance: The actual invoiced cost of a purchased item, compared to the price at the time of order

A price variance exists if the price on the purchase order (PO) doesn’t match with the invoiced price.

• Order acceptance rate: Fully acknowledged POs as a percentage of total number of POs within a given period of time

• Quantity variance: The difference between the quantity delivered and the quantity invoiced for goods received for a purchase order

A quantity variance exists if the quantity entered into the invoice doesn’t match this open quantity.

• Top partners by spend: The top trading partners by the economic spend over a period of time

• Top products by invoiced amount: The top products by invoiced amount over a period of time

» Operational metrics: Operational metrics look at how well your supply chain is performing every day. Examples include

• Transaction volume by document type: The number and type of documents sent and received over a period of time (days, months, years)

• Transaction volume by trading partner: The number and type of documents sent and received, ordered by the top ten and bottom ten partners

» Custom metrics: These are developed specifically to address a business need that may be unique to your business. Examples include

• Average invoice $ value by customer/supplier: Used to consider the cost of processing a deal in comparison to its dollar value. If a partner is sending frequent invoices for $10 and your processing cost is $25, this would be an opportunity to improve the process.

• Total spend with strategic customers/suppliers: The amount of spend associated with a trading partner based on invoices; may be compared to POs to understand where lost sales opportunities.

After the KPIs and metrics are in place, it’s time to plan the reports.

 

 

28 Supply Chain Analytics For Dummies, OpenText Special Edition

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Looking at Reports Chapter 1 states that there are three categories for supply chain analytics: descriptive, predictive, and prescriptive. While that is broadly true, there are different levels of report types that strad- dle these categories. Figure 3-4 shows a more complex view of these categories, with eight levels.

Here’s a quick explanation of the reports at each level:

» Level 1: Standard reports. What happened? When did it happen? Think of a quarterly financial report. Standard reports tell you where you are but aren’t very useful as a basis for long-range planning.

» Level 2: Ad hoc reports. How many? How often? Where? Ad hoc reports answer very pointed questions about limited datasets. They are useful for gathering the quick facts needed to make limited-scope decisions.

» Level 3: Drilldown. Where exactly is the problem? How do I find the answers? Drilldown enables you to look behind a summary value to see the data underneath it. For example,

FIGURE 3-4: Types of reports for supply chain analytics.

 

 

CHAPTER 3 Understanding the Basics of Metrics and KPIs 29

These materials are © 2017 John Wiley & Sons, Ltd. Any dissemination, distribution, or unauthorized use is strictly prohibited.

whereas a standard report might provide the overall sales for a particular month, a drilldown might show you a list of individual sales transactions included in that total.

» Level 4: Alerts. When should I react? What actions are needed now? An alert is a pre-set query — driven by business rules — that lets you know when something happens — good or bad. For example, you might set an alert to let you know when the inventory for a particular part number falls below a certain level.

» Level 5: Statistical analysis. Why is this happening? What opportunities am I missing? This is a deep dive into a particular dataset to enable frequency, trend, or regression analysis to see why things are happening.

» Level 6: Forecasting. What if these trends continue? How much will be needed, and when? Forecasting is one of the hottest markets — and hottest analytical applications — right now. Effective forecasting can help supply just enough inventory, so you don’t run out or have too much.

» Level 7: Predictive modeling. What will happen next? How will it affect my business? Predictive modeling suggests the likely outcomes for a certain set of actions under a specific set of circumstances.

» Level 8: Optimization. How do we do things better? What is the best decision for a complex problem? Optimization is a type of prescriptive analytics that takes resources and needs into consideration and helps find the best possible way to accomplish goals.

Levels 1 through 4 are concerned mainly with descriptive analyt- ics, while the mid-section, levels 5 through 7, are predictive. At the top end — levels 7 and 8 — are prescriptive reports.

Never underestimate the value of data visualization to help the story of how analytics resonates with your audience. To conclude this chapter, I quickly review a couple of descriptive reports. The reports shown in Figures 3-5 and 3-6 were obtained from Open- Text’s cloud-based supply chain analytics solution. Figure 3-5’s report highlights a business metric known as invoice accuracy. This metric analyzes whether suppliers are invoicing correctly. In the example shown in Figure 3-5, the line chart automatically updates when a different date range is selected.

 

 

30 Supply Chain Analytics For Dummies, OpenText Special Edition

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Figure 3-6 shows an example of the document volume by type met- ric. This metric summarizes the top 20 document types by total volume. These transactions could be any of a variety of types, including purchase orders, invoices, or advanced ship notices.

Think of your supply chain as a journey. Sit down and sketch it out. Look at the different processes and the systems that support them. Consider all the datasets you’ll need to collect to improve any part of any of those processes. (You look at this further in Chapter 5.)

FIGURE 3-5: An example of the business metric invoice accuracy.

FIGURE 3-6: The operational metric Document Volume by Type.

 

 

CHAPTER 4 Use Cases for Supply Chain Analytics 31

These materials are © 2017 John Wiley & Sons, Ltd. Any dissemination, distribution, or unauthorized use is strictly prohibited.

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