Today’s world has no shortage of data. In fact, seemingly everywhere we look, there’s an endless stream of metrics and numbers helping measure anything and everything.
With so many data points buzzing around, keeping track of what matters can be daunting for supply chain managers. And if you’re one of those supply chain managers with a pounding headache, don’t worry, you’re not alone.
Knowing what matters to a team, department, or company is a constantly moving target. Worse yet, what matters to one person might not matter to another.
So, what metrics do we care about and why do we want/need to measure them?
The truth is that all data is important, but some data is more important.
Understanding what industry standard metrics are and how they relate to you goes a long way. While we’d all love to monitor everything, it’s impossible.
Despite every department in a company striving toward the same overall goals, they care about different things. Tracking everything and anything can easily become overwhelming. Worse yet, tracking the wrong numbers can mask more important information, including potential warning signs.
We can break down most metrics into one of several buckets – macro, daily/weekly, or micro:
Macro – These are high-level stats for business decisions.
Daily/Weekly – These department or team-level data points measure performance against SMART goals.
Micro – Individual goals we can measure in real-time. Typically, each person will have a few, but not too many.
The three layers of data work together to provide a 360-degree view of company performance. When businesses use those metrics to improve, customers eventually notice.
Let’s face it, supply chains have plenty of moving parts and data sources.
For most people, tracking everything at once can be overwhelming. But the truth is, while every metric plays a role in overall success, some might not be critical to you or your team.
Still, being familiar with specific key performance indicators (KPIs) helps decision-makers make more confident decisions.
When we use the phrase “top-tier,” we’re referencing crucial supply chain operations data. These keystone metrics directly impact financial performance and customer satisfaction.
Demand Forecast – This metric uses supplier data, historical trends, and sales information to predict customer demand. Accurate demand forecasts use both quantitative (historical data, moving averages, etc.) and qualitative data (market research, industry expert interviews) to develop metrics.
Perfect Order Measurement – Also known as OTIF (on time, in full), or Perfect Order Rate. This metric includes customer data, including on-time delivery, complete orders, damage, documentation, and accuracy.
Supply Chain Management (SCM Cost) – The total cost of moving a product from raw material to final delivery. Data includes procurement, manufacturing, and warehousing costs, along with transport, fulfillment, IT, and return costs.
If our top-tier metrics are Beyoncé, the middle-tier ones are the rest of Destiny’s Child.
Although they don’t provide the most critical business information, these data points contribute to top-tier performance.
Days Payable Outstanding (DPO) – How long it takes a company to pay suppliers, measured in days. A high DPO means a company holds onto cash longer. Lower DPOs mean the company pays suppliers fast but may have little cash on hand for investments.
Days Sales Outstanding (DSO) – This is the number of days it takes to collect payments after making a sale. A low DSO means the company receives money quickly, whereas a high DSO can be a sign of poor collection processes.
Cash-to-Cash (C2C) Cycle – Also known as the Cash Conversion Cycle, this metric measures how long it takes to convert cash paid for materials or goods into cash from sales. A low C2C cycle (measured in days) is generally a good indicator of strong financial health.
Inventory Total – Inventory metrics measure the cost of your on-hand inventory. It includes finished and unfinished goods.
Inventory Average – How much inventory do you typically have over a certain amount of time? This data helps determine inventory carrying costs, inventory turnover ratio, and C2C cycle.
Customer Satisfaction – Are your customers happy? This metric includes order and shipping accuracy data, lead times, issues or returns, and customer communication.
Foundational metrics may not carry as much weight as top-tier ones, but they’re still important.
These metrics help us find efficiencies in the supply chain. They’re the building blocks for middle and top-tier metrics to determine overall health.
Supplier Quality – How good are the partners your company is working with? This metric measures defects, manufacturing ability, delivery, and communication. When supplier quality is poor, it results in lost sales, returns, and higher scrap costs.
Supplier On-Time – What percentage of orders from the supplier arrive early or on time? High percentages mean companies receive the inventory they need when they need it and maintain adequate inventory levels.
Raw Material Inventory – How many materials do you have available to make your products? If you don’t have enough raw materials, you can’t make anything. However, excess raw material inventory leaves cash tied up.
Purchasing Costs – Also known as procurement costs, this data highlights how much a company spends on materials. Inputs include base costs, tariffs and taxes, transport, and administrative spending.
Direct Material Costs – How much do you pay for raw materials? Within this are the base purchase price, transport costs, including tariffs, and waste and scrap losses. Knowing what the direct material costs are leads to better product or service pricing.
Cost Detail (Labor, Overhead, etc.) – This process breaks down specific expenses into smaller parts. By analyzing individual components, it’s easier to find savings.
Production Schedule Variance – The difference between how much a company wanted to produce and how much it actually did. A positive variance means production exceeded plan. Negative variances highlight production shortfalls.
Plant Utilization – How well is the company utilizing its equipment, employees, and facility? When utilization rates are high, it lowers production costs per unit. When they’re lower, it could be a sign of weak product demand or resource issues.
WIP (Work in Progress) and FG (Finished Goods) Inventory – These metrics cover unfinished products and those ready for sale.
Order Cycle Time (Internal Order Processing) – How long does it take a product to reach the customer after they order it? Short order cycle times highlight efficiencies in order processing, pick/pack, and shipping.
Perfect Order Detail (Component Breakdowns) – Similar to the perfect order metric, but breaks down the metric into smaller parts. It includes product accuracy, quality, and quantity alongside pick/pack accuracy and shipping metrics.
New Product Development (NPD) Time and Forecast – How long does it take to bring a product idea to market? Also known as “Time to Market,” this metric measures how quickly a company responds to market trends.
Just when you thought you had finished learning about supply chain metrics, here come some more!
They may not directly impact the bottom line, but these stats give us a glimpse behind the curtain. If we used them with other metrics, we’d have a 360-degree view of our supply chain health.
Fill Rate (Line, Order, and Case) – What percentage of a customer’s order was shipped from on-hand inventory? High fill rates typically result in a strong supply chain, avoiding stockouts and other issues.
Supply Chain Cycle (End-to-End) – This is a holistic supply chain process data point. It includes planning, sourcing, making, delivering, and returns, and follows product flow through its journey. The supply chain cycle helps improve visibility, risk management, and efficiency.
Days of Supply – How many days’ worth of stock do you have available without purchasing new stock? This metric highlights inventory efficiency, product forecasting, and reduces stockout threats.
Average Payment Period (APP) – How long does it take a company, on average, to pay its suppliers? At base level, APP shows how strong a company’s working capital is.
On-Time Delivery – What percent of orders arrive at the customer on or before the agreed-upon delivery date? High on-time delivery rates often lead to higher trust, reliability, and customer loyalty.
Product Turnover Rate – How often do you sell through your inventory over a certain timeframe? High turnover rates mean strong sales. Weaker rates could denote potential overstocking issues or poor sales.
Days to Sell Inventory (DSI) – DSI is part of the cash conversion cycle, measuring the time it takes to turn inventory into cash. A low DSI could mean a company has high sales and low inventory costs. Higher DSIs could indicate poor forecasting or weak sales.
Lead Times (Supplier, Production, Delivery) – Lead times measure the time it takes to manufacture an item or complete a process. Long lead times lead to slower development or manufacturing. Shorter lead times result in faster development.
Customer Return Rate – How often are products sent back to the company? Low return rates dictate high customer satisfaction and quality. The data can also determine a company’s reverse logistics performance.
Holding Costs – How much are you spending to maintain your inventory? Holding costs are dollars tied up in products on the shelf. When costs are too high, they eat into profitability and available money.
Stockouts – How often does a company run out of certain products? Stockouts highlight several potential issues, including poor forecasting or inventory management, logistical issues, or delays.
Inventory Accuracy (Physical vs. ERP) – How close is your recorded stock to your actual floor counts? ERP systems measure on-hand stock using real-time sales data. Physical counts tell you the actual inventory on hand.
Freight Costs (In and Out) – Expenses tied to bringing materials or goods in (from suppliers) or sending them out (to customers). This metric helps companies with accurate costing, pricing, and profitability work.
On-Time Pickups – Measures how often freight companies pick up scheduled goods on time. If the on-time pickup percentage is low, it’s a sign to potentially replace the carrier.
But what’s the point of having all this great data if you don’t know what to do with it?
In the right hands, supply chain metrics are like the Rosetta Stone. Good data makes it possible to easily spot problems, fix them, and prevent them from happening. It also helps companies find ways to constantly improve systems without relying on hunches, feelings, or vibes.
At the end of the day, facts tell stories, not anecdotal information, and definitely not emotions. But how do we put that information to work?
Failing to understand their metrics is a recipe for disaster. When we don’t act on the data we collect, it creates several problems, including:
Accurate data is a safety net for supply chain managers. With it, they can address concerns early, fix them quickly, and limit bad decisions.
Strong, well-maintained supply chain data boosts our ability to see both the bigger picture and the details.
Think of foundational metrics like levers that control top-line data. When we pull the levers and improve one or more smaller metrics, they influence larger ones. Over time, those incremental changes lead to more efficient operations, boosting the bottom line.
What does that mean for the average company? Better efficiency leads to stronger inventory controls, reduced stockouts, and fewer overstocks. It also reduces waste, lowers the amount of cash held in inventory and warehousing, and improves logistics.
From cradle to grave, optimizing metrics improves performance.
Strong supply chain metrics don’t end on the production floor. Good metrics also make ordering and shipping a lot easier.
When companies read the tea leaves and make changes, everything improves, including the ordering process. Customers get what they need, when they need it–without delays or incorrect orders. Additionally, companies can use the valuable data they collect to anticipate trends and pinpoint seasonal runs.
As ordering improves, customers are happier, more loyal, and much more satisfied. Over time, those relationships lead to fanatics who tell others about your company.
Early monitoring systems also improve, allowing supply chain managers to pull the ripcord on potential issues like slipping quality, slow lead times, or poor service.
Nothing surprising here; better metrics = more money.
Strong data points lead to lower operations costs, thanks to more efficient and effective processes. The extra money is then available for capital expenditure projects like new machines, product development, or other ventures.
As supply chains become more complex, so does the data they collect.
The best businesses rely on accurate supply chain data to meet customer demands. Becoming a data-led operation requires effort, investment, and time. Once companies achieve that goal, it’s crucial to maintain those efforts.
Monitoring supply chain performance is crucial. For those who do it well, they’ll develop stronger customer service, demand planning, and supply chain programs. And what will happen to companies that don’t?