What Are the Top 7 KPIs Metrics of a Supply Chain Visibility Platform Business?

Apr 6, 2025

As small business owners and artisans, it's essential to have a clear understanding of how your supply chain is performing. Key Performance Indicators (KPIs) are the heartbeat of any successful supply chain visibility platform, and in the unique world of artisan marketplaces, they play a critical role in driving growth and profitability. In this blog post, we'll delve into the seven industry-specific KPIs that are essential for monitoring and optimizing your marketplace's performance. By understanding these KPIs, you will gain valuable insights into your supply chain, enabling you to make informed decisions that will elevate your business to new heights. Get ready to unlock the potential of your marketplace and take control of your success!

Seven Core KPIs to Track

  • Order Tracking Accuracy Rate
  • Supplier On-Time Delivery Rate
  • Inventory Turnover Ratio
  • Forecast Accuracy
  • Freight Cost Per Unit
  • Customer Order Cycle Time
  • Rate of Return Due to Supply Chain Errors

Order Tracking Accuracy Rate

Definition

The Order Tracking Accuracy Rate KPI measures the percentage of correctly tracked orders within the supply chain visibility platform. It is critical to measure this ratio as it directly impacts the reliability and efficiency of the supply chain. In today's fast-paced business environment, accurate tracking of orders is essential to meet customer expectations, ensure timely deliveries, and minimize disruptions. A high order tracking accuracy rate signifies a well-organized and responsive supply chain, while a low accuracy rate can lead to customer dissatisfaction, increased operational costs, and potential loss of business.

How To Calculate

The formula for calculating the Order Tracking Accuracy Rate KPI is:

(Number of Correctly Tracked Orders / Total Number of Tracked Orders) x 100

Where: - Number of Correctly Tracked Orders: The total count of orders that were accurately tracked throughout the supply chain. - Total Number of Tracked Orders: The overall count of orders tracked within the supply chain visibility platform.

Example

For example, if a company successfully tracked 800 out of 1,000 orders within its supply chain visibility platform, the order tracking accuracy rate would be:

(800 / 1,000) x 100 = 80%

Benefits and Limitations

The benefits of maintaining a high order tracking accuracy rate include improved customer satisfaction, streamlined operations, and better decision-making based on reliable data. However, a potential limitation is that manual errors or outdated tracking systems can lead to inaccuracies, which may require additional resources to rectify and monitor.

Industry Benchmarks

According to industry benchmarks, a typical Order Tracking Accuracy Rate in the US manufacturing sector ranges between 85% to 90%, with above-average performance levels reaching 90% to 95%, and exceptional organizations achieving 95% or higher.

Tips and Tricks

  • Implement automated tracking systems to reduce manual errors and improve accuracy.
  • Regularly audit tracking data to identify and address any discrepancies.
  • Integrate the supply chain visibility platform with reliable and real-time data sources for enhanced accuracy.

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Supplier On-Time Delivery Rate

Definition

Supplier On-Time Delivery Rate is a key performance indicator that measures the percentage of deliveries that meet their scheduled arrival time. This ratio is critical to measure as it directly impacts a company's ability to maintain production schedules, manage inventory levels, and meet customer demand. In the business context, this KPI provides insight into the reliability of suppliers and their impact on the overall supply chain performance. A high on-time delivery rate is crucial for maintaining operational efficiency and meeting customer expectations, while a low rate can lead to production delays, increased holding costs, and customer dissatisfaction.

How To Calculate

The formula for calculating the Supplier On-Time Delivery Rate is:

(Number of On-Time Deliveries / Total Number of Deliveries) x 100

The number of on-time deliveries represents the deliveries that arrive at their scheduled time, while the total number of deliveries includes all shipments within the specified timeframe. By dividing the on-time deliveries by the total and multiplying by 100, the percentage of on-time deliveries is obtained.

Example

For example, if a company received 90 deliveries from a supplier within a month and 80 of these deliveries arrived on time, the calculation for the Supplier On-Time Delivery Rate would be (80 / 90) x 100 = 88.9%. This means that the supplier had an on-time delivery rate of 88.9% for the given period.

Benefits and Limitations

An effective Supplier On-Time Delivery Rate KPI allows businesses to identify reliable and consistent suppliers, optimize inventory levels, and minimize the risk of production disruptions. However, it's important to note that this KPI may not account for external factors such as transportation delays or unforeseen events. Additionally, it does not provide insights into the quality of the delivered goods or the supplier's communication and responsiveness.

Industry Benchmarks

According to industry benchmarks, the average Supplier On-Time Delivery Rate in the US manufacturing sector ranges between 85% to 95%, with exceptional performance levels reaching over 95%. In the retail industry, on-time delivery rates of over 90% are considered above average. These benchmarks reflect typical performance levels for this KPI in relevant industries.

Tips and Tricks

  • Implement clear and enforceable delivery terms in supplier contracts
  • Establish open communication channels with suppliers to address potential delivery issues proactively
  • Utilize supply chain visibility platforms to track and monitor delivery performance in real time
  • Diversify suppliers to mitigate the impact of potential delays

Inventory Turnover Ratio

Definition

The inventory turnover ratio is a key performance indicator that measures the number of times a company's inventory is sold and replaced over a specific period. It is critical to measure this ratio as it provides insight into how efficiently a company is managing its inventory. A high turnover ratio indicates strong sales and effective inventory management, while a low ratio may indicate excessive inventory or insufficient sales, leading to potential financial strain. This KPI is essential to measure as it impacts working capital management, cash flow, and profitability, making it a crucial metric for assessing overall business performance.

How To Calculate

The formula to calculate the inventory turnover ratio is:

Cost of Goods Sold / Average Inventory

Where the cost of goods sold represents the total cost of manufacturing or purchasing the products that have been sold during the period, and the average inventory is the average of the beginning and ending inventory levels for the same period.

Example

For example, a company has a cost of goods sold of $500,000 and an average inventory value of $100,000. The inventory turnover ratio would be calculated as follows: $500,000 / $100,000 = 5. This means the company's inventory is turning over 5 times within the specified period.

Benefits and Limitations

The advantage of a high inventory turnover ratio is that it indicates efficient inventory management and can lead to reduced carrying costs and increased cash flow. However, a potential limitation is that a very high turnover ratio may indicate stocking out of inventory and lost sales opportunities.

Industry Benchmarks

According to industry benchmarks, the average inventory turnover ratio in the retail industry is approximately 8-12 times annually, while for manufacturing companies it ranges from 6-8 times. Exceptional performance in the retail industry would exceed 20 times annually, and in manufacturing, it would exceed 10 times.

Tips and Tricks

  • Regularly review inventory levels and adjust purchasing accordingly to optimize turnover.
  • Implement lean inventory management strategies to minimize excess stock.
  • Analyze slow-moving inventory and consider discounting or other strategies to improve turnover.

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Forecast Accuracy

Definition

Forecast Accuracy is a key performance indicator (KPI) that measures the accuracy of a company's demand forecasting. It reflects the ability to predict future demand for products or services, which is critical for effective supply chain management. This KPI is important in the business context because it directly impacts inventory levels, procurement decisions, and overall operational efficiency. By measuring forecast accuracy, businesses can identify areas for improvement, reduce excess inventory, and better meet customer demand. It matters because inaccurate forecasts can lead to stockouts, excess inventory, and ultimately impact customer satisfaction and business profitability.

How To Calculate

Forecast Accuracy can be calculated using the formula:
(|A - F| / A) x 100
Where: - A = Actual demand - F = Forecasted demand This formula compares the absolute error between actual and forecasted demand and expresses it as a percentage of actual demand.

Example

For example, if the actual demand for a product is 1,000 units and the forecasted demand is 900 units, the forecast accuracy would be: (1000 - 900) / 1000 x 100 = 10% This indicates a 10% forecast accuracy for the specific timeframe and product.

Benefits and Limitations

Effective measurement of forecast accuracy allows businesses to optimize inventory levels, reduce carrying costs, and minimize stockouts. However, it's important to note that forecast accuracy is influenced by factors such as seasonality, market trends, and unforeseen events, making it challenging to achieve consistently high accuracy levels.

Industry Benchmarks

In the US context, typical forecast accuracy benchmarks range from 75% to 90% across industries such as manufacturing, retail, and e-commerce. Achieving accuracy above 90% is considered exceptional performance.

Tips and Tricks

  • Regularly review historical forecast accuracy to identify patterns and trends
  • Utilize advanced analytics and machine learning algorithms to improve forecasting precision
  • Collaborate closely with suppliers and customers to gather accurate demand insights

Freight Cost Per Unit

Definition

Freight Cost Per Unit is a Key Performance Indicator that measures the average cost of transporting a single unit of a product within a company's supply chain. This KPI is critical to measure because it directly impacts the overall cost of goods sold and can significantly affect a company's profitability. By understanding the freight cost per unit, businesses can identify opportunities to optimize transportation expenses, negotiate better rates with carriers, and streamline their supply chain processes to minimize costs and improve operational efficiency.

Freight Cost Per Unit = Total Freight Costs / Total Units Transported

How To Calculate

The formula for calculating Freight Cost Per Unit involves dividing the total freight costs incurred by the company by the total number of units transported within a specific time period. The total freight costs should include expenses related to shipping, handling, and any other logistics-related costs. By dividing this total by the number of units transported, businesses can determine the average cost of transporting each unit throughout their supply chain.

Freight Cost Per Unit = Total Freight Costs / Total Units Transported

Example

For example, let's assume that Company XYZ incurred total freight costs of $50,000 within a month, and during the same period, they transported 10,000 units of their products. To calculate the Freight Cost Per Unit, we would divide the total freight costs by the total units transported:

Freight Cost Per Unit = $50,000 / 10,000 units = $5 per unit

Benefits and Limitations

Effectively measuring and managing Freight Cost Per Unit allows businesses to identify cost-saving opportunities, enhance their competitive position, and improve their bottom line. However, it's important to note that this KPI may not account for variations in product size or transport distances, which can limit its accuracy in certain scenarios.

Industry Benchmarks

Industry benchmarks for Freight Cost Per Unit in the US context can vary across different sectors. However, typical benchmarks range from $3 to $10 per unit, depending on the specific industry and product characteristics. Above-average performance can be seen at levels below $3 per unit, while exceptional performance may achieve costs as low as $1 to $2 per unit.

Tips and Tricks

  • Negotiate long-term contracts with reliable carriers to secure preferential rates
  • Optimize packaging to minimize dimensional weight and reduce transportation costs
  • Implement advanced route optimization and load consolidation strategies to improve freight cost efficiency
  • Regularly review and benchmark your freight rates against industry standards for cost-saving opportunities

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Customer Order Cycle Time

Definition

Customer Order Cycle Time is a key performance indicator (KPI) that measures the time it takes for a customer's order to be processed, fulfilled, and delivered. This ratio is critical to measure as it provides insights into the efficiency and effectiveness of a company's supply chain operations. In the business context, a shorter order cycle time indicates faster delivery to customers, improved customer satisfaction, and reduced carrying costs for inventory. On the other hand, a longer order cycle time can result in customer dissatisfaction, increased carrying costs, and potential loss of business to competitors. Therefore, measuring and optimizing Customer Order Cycle Time is critical for maintaining a competitive edge in the market.

How To Calculate

The formula for Customer Order Cycle Time is the total time taken to fulfill an order, from the moment it is placed by the customer to the moment it is delivered, divided by the total number of orders processed within the same period. The total time includes processing time, production time, and delivery time. By dividing this total time by the number of orders, you can calculate the average Customer Order Cycle Time.

Customer Order Cycle Time = Total time to fulfill orders / Total number of orders

Example

For example, if a company takes a total of 300 hours to fulfill 100 customer orders in a month, the calculation for the Customer Order Cycle Time would be: Customer Order Cycle Time = 300 hours / 100 orders Customer Order Cycle Time = 3 hours per order

Benefits and Limitations

The benefits of measuring Customer Order Cycle Time include improved customer satisfaction, reduced inventory carrying costs, and increased operational efficiency. However, the limitation of this KPI is that it does not capture the entire order fulfillment process, such as any delays in production or shipping that may impact the overall cycle time.

Industry Benchmarks

According to industry benchmarks, the typical Customer Order Cycle Time in the manufacturing industry is around 15-30 days for standard products. Above-average performance in the retail industry indicates a cycle time of 1-2 days, while exceptional performance can achieve a cycle time of under 24 hours.

Tips and Tricks

  • Implement lean production and inventory management techniques to reduce cycle time.
  • Optimize transportation routes and methods to expedite delivery.
  • Leverage technology such as IoT and real-time tracking to monitor and streamline order fulfillment processes.

Rate of Return Due to Supply Chain Errors

Definition

The Rate of Return Due to Supply Chain Errors is a key performance indicator that measures the financial impact of errors, delays, and disruptions in the supply chain. This KPI is critical to measure as it provides insights into the direct impact of supply chain inefficiencies on the overall profitability of the business. By understanding the financial implications of supply chain errors, businesses can prioritize areas for improvement and allocate resources more effectively. This KPI is important in the business context as it directly impacts the bottom line by highlighting the costs associated with supply chain disruptions, and provides a clear indication of the potential return on investment for implementing improvements.

How To Calculate

The formula for calculating the Rate of Return Due to Supply Chain Errors is:
Rate of Return Due to Supply Chain Errors = (Cost of Errors / Total Revenue) x 100
In this formula, the cost of errors refers to the total financial impact of supply chain errors, including the costs associated with delays, inventory shortages, and customer dissatisfaction. Total revenue represents the total income generated by the business within the specified time period. By multiplying the ratio by 100, the result is expressed as a percentage.

Example

For example, if a business incurs $500,000 in costs due to supply chain errors and has a total revenue of $5,000,000, the calculation for the Rate of Return Due to Supply Chain Errors would be: Rate of Return Due to Supply Chain Errors = ($500,000 / $5,000,000) x 100 = 10% In this hypothetical scenario, supply chain errors result in a 10% financial impact on the business's total revenue.

Benefits and Limitations

The benefit of measuring the Rate of Return Due to Supply Chain Errors is that it provides a clear understanding of the financial implications of supply chain inefficiencies, allowing businesses to prioritize improvements and allocate resources effectively. However, the limitations of this KPI lie in its focus on quantifiable costs, potentially ignoring non-financial impacts such as reputation damage or customer churn.

Industry Benchmarks

According to industry benchmarks within the US context, the typical Rate of Return Due to Supply Chain Errors ranges from 5% to 15%, with above-average performance falling below 5% and exceptional performance achieving less than 3%.

Tips and Tricks

  • Implement proactive supply chain monitoring and predictive analytics to identify potential errors before they occur.
  • Strengthen relationships with key suppliers to minimize disruptions and errors in the supply chain.
  • Regularly review and update supply chain processes to reduce the likelihood of errors and delays.

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