You Can’t Improve What You Don’t Measure: Why Supply Chain OKRs Are the Key to Success (Part 1 of 7)

It was a chilly February night in 1980, with four feet of snow blanketing the outside world. There was no way to reach a hospital. Deep into the night, walls echoed with the cries of a newborn, but the next morning, those cries faded. Sensing something was wrong, the grandmother discovered the baby was bleeding because its umbilical cord hadn’t been tied properly. She immediately fixed it, ensuring no further blood loss, and over the following week, she kept a close eye on the little one. But something still seemed off: the baby’s legs weren’t moving as strongly as they should.

Undeterred, the grandmother tested, observed, and measured the baby’s reactions for several days. Alarmed by the results, she urged the family to see a doctor. Indeed, the doctor diagnosed a risk of polio, and treatment began right away. If she hadn’t acted so quickly—measuring each symptom, focusing on each detail—it could have led to severe complications down the road. Thankfully, the baby recovered and went on to live a healthy life.

Rest in peace grandma...That baby was… me.

“If you don’t measure it, you can’t improve it.”?This principle doesn’t just apply to lifesaving moments; it’s also a guiding philosophy in Supply Chain Management, where a single oversight can ripple through entire operations.

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2. So, What Are OKRs, and Why Do They Matter in the Supply Chain?

With that personal insight into why measurement matters, let’s explore how to systematically apply it in supply chains. OKRs—Objectives and Key Results—are a goal-setting framework originally popularized by tech giants like Google and Intel. They consist of:

??? Objective: A qualitative ambition you want to achieve (e.g., “Enhance Demand Forecasting accuracy for better product availability”).

??? Key Results: Quantifiable markers that track progress toward your Objective (e.g., “Increase forecast accuracy to 99%—a super ambitious goal,” “Reduce backorders by 25%,” etc.).

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2.1 Why OKRs in Supply Chain?

??? They align teams around shared, impactful goals.

??? They define ‘success’ with measurable Key Results.

??? They foster continuous improvement, allowing regular checks on progress and dynamic course corrections.

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A Quick Note on OKR Visibility

Building robust OKRs is far easier when you have real-time visibility into every node of your supply chain. A Control Tower setup provides historical and intraday data, along with heat maps and drill-down capabilities. This allows you to quickly spot bottlenecks, track unexpected spikes or dips in demand, and fix issues before they cascade. In other words, a well-designed Control Tower turns your OKRs from theory into actionable insights.

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3. Before We Dive into Supply Chain OKRs: The Main Objective of Supply Chains

Moving products from Point A to Point B safely and optimally, ensuring the right quantity of the right product is available at the right time.

Everything we do in the supply chain—whether it’s demand planning, warehousing, transporting, or fulfilling customer orders—ultimately serves this goal. Within that overarching mission, five core areas ensure operational excellence:

1. Safety & Compliance: Keep associates, customers, and the environment safe, above all else.

2. Right Product, Right Place, Right Time: Deliver the correct goods promptly, meeting demand without delays or shortages.

3. Cost Optimization & Waste Reduction: Minimize operational expenses (including transportation, inventory holding, etc.) and resource wastage to maximize profitability.

4. Quality Assurance & Traceability: Ensure every product meets the highest standards, with full visibility from source to delivery.

5. Risk Management & Resilience: Anticipate disruptions, maintain continuous operations, and adapt swiftly to unforeseen challenges.

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4. Demand Planning: The First Step Toward Supply Chain Mastery

Being a Demand Planner and implementing demand planning systems have been some of my most fulfilling roles—I love it! However, it’s not always smooth sailing. Back in 2009, I remember a time when I had to upload mass forecasts for hurricane-stricken stores—last minute, under intense pressure. I had just one hour to figure it all out.

I ended up sending multiple trucks to various stores, adjusting huge forecast numbers. On Monday morning, I found the VP of Inventory waiting at my desk, questioning the surge in shipments. Thankfully, those stores did need the extra inventory due to the hurricane situation. It turned out to be a fortunate mistake, but it taught me a valuable lesson about measuring, validating, and communicating forecast changes. Even experienced planners can misstep when working with incomplete data or under tight deadlines.

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4.1 Main Objective of Demand Planning

Accurately predict future customer demand so that a company can optimize inventory levels—producing or procuring exactly the right amount of goods to meet demand without overstocking or running out—ultimately maximizing efficiency and minimizing costs.

Demand Planning merges art and science, especially when AI and advanced analytics enter the picture—factoring in everything from seasonal patterns to social media trends. Yet true success starts by setting clear Objectives and Key Results that pinpoint where and how to improve.

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4.2 How Demand Planning Builds Upon Demand Forecasting

Demand planning builds upon demand forecasting by involving multiple stakeholders—finance, sales, marketing, operations, and more. This collaborative approach:

??? Allows teams to view, analyze, and modify forecasts in real-time.

??? Enables proactive adjustments to meet sales and profit goals or accommodate supply constraints.

??? Fosters an enterprise-wide consensus plan, ensuring a single version of the truth.

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To measure the effectiveness of your forecasts, there are multiple metrics you could track—such as forecast error, monthly product category forecast error, bias, or MAPE—without going into extensive detail on each. While numerous measures exist (e.g., MAE, SMAPE, WMAPE, MSE, RMSE, etc.), Bias and MAPE often prove simple and scalable. They effectively highlight systematic errors (Bias) and overall magnitude of forecast deviations (MAPE), making them excellent starting points for organizations refining their forecasting process.

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5. Focusing on Demand Planning with OKRs

Objective Example

“Optimize Demand Forecasting to Minimize Stockouts and Excess Inventory”

Potential Key Results

1. Improve Forecast Accuracy to X%

Rationale: Higher forecast accuracy reduces emergency procurement, minimizes obsolete inventory, and boosts customer satisfaction.

Measurement Tip: Track how close your forecasts are to actual demand weekly or monthly, using metrics like MAPE and Forecast Bias.

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2. Maintain (or Reduce) Safety Stock to Y% of Baseline

Rationale: While forecast accuracy is a major factor in lowering safety stock, other elements—such as lead time variability and service levels—also play a role.

Measurement Tip: Compare current safety stock levels to your established baseline, noting how changes in forecast accuracy affect safety stock decisions.

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3. Optimize Backorder and Inventory Holding Costs

Rationale: Forecast accuracy significantly impacts both backorder cost and inventory carrying costs, but production cycles, minimum order quantities, and logistics constraints also affect these expenses.

Measurement Tip: Track backorder costs (lost sales, customer dissatisfaction) and inventory holding costs (storage, insurance) over time, correlating them with forecast accuracy gains to identify where further process improvements are needed.

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Pareto Principle in Demand Planning

Typically, 80% of your forecasting issues come from 20% of your SKUs—often high-revenue or high-volatility items. Setting a Key Result like “Cut forecast errors by 50% for top 20 revenue-driving SKUs” can yield an outsized impacton overall performance. Furthermore, having company-wide visibility into forecast accuracy—with the ability to drill down and generate actionable insights—ensures each department can rapidly identify which products or locations need extra attention. Integrating these insights with demand planning systems closes the loop between measurement and improvement.

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6. Conclusion: Laying the Foundation with OKRs

“You can’t improve what you don’t measure” isn’t just a catchy phrase—it’s the driving principle behind a high-performing supply chain. By defining clear Objectives and quantifiable Key Results for Demand Planning, you establish a solid foundation to pinpoint inefficiencies and adapt quickly when market conditions shift.

??? Objective: “Improve Forecasting Accuracy to Minimize Stockouts and Excess Inventory”

??? Key Results: “Improve Forecast Accuracy to X%,” “Maintain (or Reduce) Safety Stock to Y% of Baseline,” “Optimize Backorder and Inventory Holding Costs”

Once you know where the problems lie—be it forecasting blind spots, suboptimal safety stock, or ballooning carrying costs—you can take swift action to optimize and stay ahead of evolving customer demands.

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7. What’s Next?

This article is the first in a series exploring OKRs across the supply chain spectrum. Stay tuned for insights on:

1. Distribution: Ensuring products flow safely and seamlessly from warehouses to end customers.

2. Fulfillment: Perfecting on-time, in-full delivery for ultimate customer satisfaction.

3. Supply Planning: Coordinating resources, production schedules, and inventory levels at scale—ensuring synchronized operations and minimal downtime.

4. Transportation: Optimizing routes, carrier performance, and costs.

5. SC Strategy: Building a cohesive, future-proof infrastructure for sustained growth.

6. SC System Health: Ensuring real-time, accurate data availability and system reliability for swift, informed decisions across the entire supply chain.

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Get ready to transform your supply chain, one OKR at a time—and remember, measurement is the key to saving not just supply chains but sometimes even lives!

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