In the workshops, distilleries, and forges across the Sword Coast, production rarely fails because of a single dramatic event like a broken enchantment or collapsed furnace. Instead, loss arises from small pauses, slow runs, spoiled batches, and quiet rework that never clearly reaches the ledger. A half hour here, a failed batch there, and suddenly the quarterly margins tell a different story than the production logs promised.

The Waterdeep Trading Company recognizes this truth. To see what truly happens on the shop floor, rather than what should happen according to plan, the company employs a measurement discipline known as Overall Equipment Effectiveness, or OEE. This metric does not judge the skill of artificers or the dedication of laborers. Instead, it measures how well equipment turns planned time into sellable goods. It captures time, speed, and quality in a single actionable metric that reveals the hidden costs of production.

OEE matters because it connects the reality of the workshop to the expectations of the counting house. It indicates whether delays are attributable to bad luck, poor maintenance, inadequate training, or systemic issues that require investment. For guild masters, production supervisors, and finance scribes alike, OEE transforms vague impressions into clear data.

This article explains OEE in plain terms, shows how it applies to Faerûnian production environments, and walks through worked examples using a heated cauldron line operated by the Waterdeep Trading Company.

What OEE Is

OEE is a single measure built from three distinct components. Each component represents a different approach, which can result in lost planned production time. Together, they answer one essential question: Of all the time we planned to produce, how much became a good product ready for sale?

The three components are Availability, Performance, and Quality. Each is expressed as a percentage, and their product yields the overall OEE score.

The Three Components Explained

Understanding each component separately is essential before combining them into the full OEE calculation.

Availability

Availability measures time lost to stoppages. If a cauldron is scheduled to run but sits idle due to cleaning, repair, missing ingredients, or equipment failure, that time is lost availability. Availability only checks whether the equipment is running. It does not matter how fast the equipment runs or whether the output is good. It simply asks: Was the equipment operating when it should have been?

Common causes of availability loss in Faerûn include arcane instability requiring recalibration, material shortages from delayed caravans, mechanical failures in gears or seals, and unplanned cleaning due to contamination.

Performance

Performance measures lost speed. If a cauldron is running but heating more slowly than expected, pausing briefly between batches, or operating at reduced output due to worn components, the slowdown reduces performance. Performance is measured by comparing the actual output rate to the ideal output rate. Even if the equipment never fully stops, running at 80% of expected speed results in a 20% performance loss.

In Faerûnian workshops, performance loss often comes from aging enchantments, inexperienced operators, inconsistent ingredient quality, or temperature fluctuations in the workshop environment.

Quality

Quality measures lost output. If a batch fails inspection, requires rework, or must be discarded entirely, that loss reduces quality. Quality looks only at usable output. Even if availability and performance are perfect, quality loss means that production time was spent creating goods that cannot be sold at full value.

Typical quality issues include failed enchantments, contamination from improper cleaning, incorrect ingredient ratios, or structural defects in the finished product.

The OEE Formula

The formula for OEE is straightforward. It multiplies the three components together.

OEE equals Availability multiplied by Performance multiplied by Quality.

Each value is expressed as a percentage, and the result is also a percentage. An OEE of 85 percent means that 85 percent of planned production time resulted in good output. The remaining 15 percent was lost due to downtime, slow speed, or defective products.

Worked Example 1: Single Heated Cauldron, One Shift

For example, OEE can be illustrated by a single heated cauldron operated by the Waterdeep Trading Company over an eight-hour shift.  The cauldron produces alchemical potions in batches, each requiring a defined heating and cooling cycle.

The shift begins with a plan. The following table shows how the planned shift time is allocated before any actual production begins.

The planned production time of 420 minutes represents the time available for actual manufacturing after subtracting scheduled breaks, shift handovers, and routine inspections. This is the baseline against which OEE will be measured.

During the shift, several events occur that affect production. A seal failure causes a 30-minute stoppage while repairs are made. The cauldron runs slower than expected for part of the shift due to inconsistent heat from a weakening enchantment. One batch fails quality inspection due to improper mixing and must be discarded.

Now we calculate each component of OEE step by step.

Step 1: Calculating Availability

Availability compares the time the equipment operated to the planned production time. The following table breaks down the calculation.

Availability equals operating time divided by planned production time. This gives us 390 ÷ 420, which equals 92.86%. The cauldron was available to produce for just under 93 percent of the planned time.

Step 2: Calculating Performance

Performance compares actual output to the ideal output based on the equipment’s design speed. The cauldron is designed to produce one batch every 20 minutes when running at full capacity.

With 390 minutes of operating time, the ideal output is 390/20, which equals 19.5 batches. However, the actual output before quality checks is 18 batches.

Performance equals actual output divided by ideal output. This gives us 18 ÷ 19.5, which equals 92.31%. The cauldron ran at just over 92 percent of its expected speed.

Step 3: Calculating Quality

Quality compares good output to total output. Out of the 18 batches produced, one fails inspection and must be discarded. This leaves 17 good batches.

Quality equals good batches divided by total batches. This gives us 17/18, which equals 94.44%. Just over 94 percent of production met quality standards.

Step 4: Calculating OEE

We now multiply the three components to compute the overall equipment effectiveness.

OEE equals 92.86% × 92.31% × 94.44%, which gives approximately 80.9%.

This means that just over 80% of the planned production time resulted in sellable output. The remaining nineteen percent was lost due to downtime, reduced speed, and quality failures. Each of these losses represents real cost to the company, whether in wasted materials, wasted labor time, or lost revenue from goods that could not be sold.

Worked Example 2: Comparing Two Cauldrons

The Waterdeep Trading Company operates two heated cauldrons in parallel, both using the same recipe and running for the same shift length. While both produce the same product, their performance characteristics differ significantly. The following table compares their OEE components.

The results reveal an interesting pattern. Cauldron B stops more often, resulting in more downtime and lower availability. However, when it runs, it runs faster and produces cleaner output. Cauldron A runs more consistently with fewer stoppages but loses effectiveness through slower speed and more quality issues.

Despite their different loss patterns, both cauldrons deliver nearly identical overall effectiveness, approximately 80%. This informs the production supervisor and the finance scribe that both lines require attention, but for different reasons. Cauldron A may require improved training or maintenance to enhance speed and quality. Cauldron B may need more reliable components or better preventive maintenance to reduce stoppages. Focusing solely on total output would obscure these differences. OEE reveals where improvement efforts should focus.

Why OEE Matters to the Ledger

OEE connects the shop floor to finance without guesswork or assumptions. Each component of OEE has direct financial implications that are reflected in the cost accounting system.

Low availability increases labor cost per unit because workers are paid for time when the equipment sits idle. It also increases per-unit overhead allocation because fixed costs, such as workshop rent and lighting, are spread across fewer units of output.

Low performance hides capacity loss. A workshop that believes it has space to take on more orders may be running its existing equipment at reduced speed. OEE reveals this hidden constraint before the company overcommits to customers.

Low quality creates scrap, rework, and delayed revenue. Materials are consumed but produce no sellable output. Labor is spent twice on the same batch. Delivery promises are broken because good output arrives later than planned.

By linking OEE trends to cost and margin analysis, the Waterdeep Trading Company avoids the common mistake of blaming weak demand for execution issues. When revenues fall short, OEE data can show whether the problem is market conditions or internal capacity utilization.

Using OEE the Right Way

OEE is a signal, not a weapon. When used properly, it guides continuous improvement and reveals systemic issues. When used improperly, it becomes a tool for blame that drives workers to hide problems rather than solve them.

Good use of OEE focuses on patterns over time rather than on single shifts. A bad day tells you little. A trend of declining performance over weeks indicates that something fundamental requires attention. OEE should be reviewed with operators, not against them. The people closest to the equipment often know exactly what is wrong and simply need permission and resources to fix it.

The goal of tracking OEE is to remove friction from the system, not to punish those working within it. Equipment that consistently exhibits low availability may require investment in improved maintenance or replacement parts. Low performance may indicate the need for improved training, clearer work instructions, or enhanced capabilities. Low quality may indicate issues with ingredient sourcing, inadequate inspection tools, or process design flaws.

OEE works best when it is transparent, regularly discussed, and used to justify investments in improvement rather than to assign blame for shortfalls.

Realms Aware Considerations

Production in Faerûn faces unique challenges that are less common in purely mechanical manufacturing environments. Some losses are specific to the magical and logistical realities of the Sword Coast.

Magical instability affects quality. Enchantments can fade, interfere with each other, or behave unpredictably during storms or planar convergences. Quality losses from arcane sources require different solutions than mechanical defects.

Ingredient variance affects performance. Raw materials sourced from different regions or different seasons may behave differently in the same process. A potion recipe that works perfectly with Cormyrian herbs may run slower or produce inconsistent results with substitutes from Amn.

Enchantment maintenance affects availability. Unlike purely mechanical equipment, magical apparatus requires periodic recalibration, attunement, or recharging. These maintenance activities may be less predictable than oiling gear or replacing worn belts.

Despite these unique factors, the losses are still losses. OEE allows them to be measured, discussed, and planned for, rather than accepted as inevitable. By quantifying the impact of magical instability or ingredient variance, the company can make informed decisions about whether to invest in better enchanters, source more consistent materials, or adjust customer delivery promises.

Final Thoughts

OEE does not promise perfection. No production system will ever achieve 100% effectiveness. Equipment breaks, people make mistakes, and materials vary. OEE clarifies where production time is spent and why planned output differs from actual results.

For the Waterdeep Trading Company, OEE turns the shop floor into a reliable source of truth. Time, speed, and quality cease to be narrative elements in shift reports and become metrics that inform better decisions. Finance scribes can calculate true production costs. Operations supervisors can prioritize improvement projects. Guild masters can set realistic expectations for capacity and delivery times.

In a competitive market where margins are measured in units per copper piece, the difference between 80% and 90% OEE can determine whether a product line thrives or fails. OEE makes that difference visible, measurable, and actionable.

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A Grateful Salute to Our Patrons.  To all those who stand behind the vision, thank you for helping bring this world to life. Our Benefactors, Andre Breillatt and Eryndor Fiscairn^‡, your boundless generosity fuels the arcane core of this project. Without your magic, the weave would falter. Our Apprentices, the spell engines turn, and the training labs thrive thanks to our current Apprentices: Michael Ramirez and Andreth Bael’Rathyn^‡. Special thanks to our past Apprentices, whose contributions helped us get here: Ralf Weber, Wendy Rijners, Shashi Mahesh, Julia Tejera, Ben Ekokobe, Tiago Xavier, Naveen Boyinapelli, Marcos Tadeu Wolf, Kathryn Greene, Jason Brown, Mark Christy, and Ashish Singh. Our Initiates, Jesper Livbjerg, Peter Lorre, Gregory Brigden, and Martin Grahm, your commitment marks the start of the deeper path, stepping beyond mere observation into the active shaping of this realm. Our Followers, your steady presence along the journey is a beacon of encouragement: Rusty Cavalier, Eric Shuss, Sunil Panchal, Sarah D. Morgan, Nick Ramchandani, Daniel Kjærsgaard, and Tomasz Pałys. And our Voyeurs, Harry Burgh, Abdelrahman Nabil, and Basil Quarrell, ever watching from the shadows, clearly intrigued… but not enough to part with a single gold piece. Your silent curiosity is noted and mildly judged.

Want to design your own economic models in Faerûn?  Get your own AD&D365 Environment and guides at adnd365.com/start, and request access to the public view of the current database at https://public.adnd365.com – Login npc@adnd365.com, Password N0nPl@yC#822!

The Waterdeep Trading Company oversees forges, breweries, tanneries, butcher halls, and alchemical works from the Sword Coast to the Moonsea. Each site produces goods needed by guilds, caravans, and settlements. To control these flows, the company relies on two core production models: input-driven manufacturing and output-driven manufacturing.

Choosing the correct method shapes cost, supply, and worker activity across the company. It is a key skill for any planner or foreman in Faerûn.

What Is Input-Driven Manufacturing

Input-driven manufacturing begins when materials arrive. The trigger is the availability of raw goods, not a customer request. Production cycles are set by supply rhythm, which may depend on weather, caravans, or seasonal harvests.

This method suits operations that must consume materials before spoilage or where bulk goods are expected to flow in steady waves.

Examples include:

• Breweries working with incoming grain.
• Tanneries receiving hides after large hunts.
• Butcher halls where livestock arrives from nearby farms.

What Is Output-Driven Manufacturing

Output-driven manufacturing begins when a customer asks for something. A work order is created only when demand is confirmed. Goods are produced with accuracy, often following custom instructions or strict material controls.

This method suits operations where materials are rare or high cost, or where final goods require specialized work by artificers or master smiths.

Examples include:

• Enchanted gear production.
• Noble house commissions.
• Custom alchemical batches.

Why These Approaches Matter

Both approaches determine how goods and coins move across the company.

They influence:

• Inventory levels.
• Cash flow.
• Labor planning.
• Resource allocation.

Selecting the right method ensures smooth trade across regions such as Waterdeep, Baldur’s Gate, and Calimport.

Worked Example One: Input Driven Example: Frostroot Ale in Silverymoon

When Frostroot Barley arrives from Icewind Dale, the Copperleaf Brewery begins a new brewing cycle. Barley cannot remain in storage for long, so production is triggered by shipments.

The table below shows how incoming material drives production volume.

This method keeps taverns supplied but increases storage during heavy harvest seasons.

Worked Example Two: Output Driven Example: Enchanted Shields in Waterdeep

The Arcane Smiths Hall starts production only when a signed order arrives. Mithral Dust and Phoenix Plume are tracked tightly by the Artificers Union, which makes this method ideal.

The table shows how materials are allocated only after orders are logged.

This approach protects rare resources and ensures predictable delivery.

Worked Example Three: Input Driven Example with Variable Outputs: Whole Animal Disassembly in Daggerford

When local farmers bring cattle to the Daggerford Butcher Hall, production begins immediately. This is input-driven because the animal itself is the trigger. One animal, however, can be broken into multiple cut profiles, each requested by nearby markets.

The final output varies because cutters choose different profiles based on condition, size, and planned sales.

The table below shows how three animals can produce different cut mixes.  Each cut type has a standard yield range, but the actual yield depends on the animal’s size and the chosen breakdown pattern.

How This Works in Practice

The Butcher Hall begins work as soon as animals arrive. The cutters select the breakdown style based on:

• Market demand in Waterdeep or Baldur’s Gate
• Condition and age of the animal
• Local festival needs
• Storage space and salt levels
• Order patterns from nearby taverns

This produces variable outputs and makes production unpredictable.
It is a classic input-driven scenario because cutters respond to the arrival of livestock rather than to a fixed customer order.

This method is standard across Faerûn, where livestock flows depend on weather, harvesting, grazing conditions, and the health of nearby herds.

Realms Aware Considerations

Faerûn’s regions shape the choice of method.

• Livestock production in Daggerford follows input cycles tied to farm supply.
• Wandering herds in Amn cause irregular arrivals for local butcher halls.
• Enchanted workshops in Waterdeep use output cycles to protect rare essence materials.
• Coastal trade houses in Calimport favor output cycles for high-value seafood that must be allocated by order.

Final Thoughts

Input-driven manufacturing converts available goods into stock as soon as materials arrive. Output-driven manufacturing produces only when the market demands it. The Waterdeep Trading Company uses both across Faerûn to keep trade stable, predictable, and profitable.

Animal disassembly adds an extra layer of complexity, since a single input can yield many different outputs. This makes the method valuable for regions with active livestock markets and diverse customer needs.

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Support the AD&D365 Project on Patreon.  To grow this world, we’ve launched an official Patreon where supporters can gain access to exclusive content, tools, training labs, and even influence the future of the project. Your support fuels more than just development ,  it expands the guildhall, forges new scrolls, and empowers the next generation of configuration wizards.  Begin your journey: https://www.patreon.com/adnd365/

A Grateful Salute to Our Patrons.  To all those who stand behind the vision, thank you for helping bring this world to life. Our Benefactors, Andre Breillatt, and Eryndor Fiscairn^‡, your boundless generosity fuels the arcane core of this project. Without your magic, the weave would falter. Our Apprentices, the spell engines turn and the training labs thrive thanks to our current Apprentices: Michael Ramirez and Andreth Bael’Rathyn^‡. Special thanks to our past Apprentices, whose contributions helped us get here:  Ralf Weber, Wendy Rijners, Shashi Mahesh, Julia Tejera, Ben Ekokobe, Tiago Xavier, Naveen Boyinapelli, Marcos Tadeu Wolf, Kathryn Greene, Jason Brown, Mark Christy, and Ashish Singh. Our Initiates, Gregory Brigden, and Martin Grahm, your commitment marks the start of the deeper path, stepping beyond mere observation into the active shaping of this realm. Our Followers, your steady presence along the journey is a beacon of encouragement:  Eric Shuss, Sunil Panchal, Sarah D. Morgan, Nick Ramchandani, Daniel Kjærsgaard, and Tomasz Pałys. And our Voyeurs, Harry Burgh, Abdelrahman Nabil, and Basil Quarrell, ever watching from the shadows, clearly intrigued… but not enough to part with a single gold piece. Your silent curiosity is noted, and mildly judged.

Want to design your own economic models in Faerûn?  Get your own AD&D365 Environment and guides at adnd365.com/start, and request access to the public view of the current database at https://public.adnd365.com – Login npc@adnd365.com, Password N0nPl@yC#822!