The queue you can’t walk past

Every Monday somebody asks engineering where the job is. Engineering says it is close. Both people are telling the truth, and neither of them has a number.

This is not a discipline problem. Production inventory is visible. You can walk the floor and see the parts stacked against the wall, and nobody has to be told if the shop is behind. Office inventory takes up no space. A drawing waiting for an approval, an RFI sitting in somebody’s inbox, a job that is ninety percent detailed and has been for two weeks: all of it occupies exactly zero square feet. You cannot walk past it, so you manage it by asking, and the answer you get back is always some version of busy.
Busy is not a measurement. It is the same answer whether engineering is two days behind or five weeks behind, and by the time the difference shows up on the floor, the release date has already moved.

What INNERGY already tracks 

Engineering time is measurable, and most shops never measure it. In INNERGY, drafting is a work order phase, the same as Production and Installation, so every drafting work order carries a start date, a critical date, a duration and a progress figure.

Date Management is where that stops being a per-job question. It is a single grid of every work order milestone across every project, and it separates four things most shops keep in one column: the Target Date the system calculates, an Override Date a human typed in on purpose, the Actual Date the milestone was really hit, and the Prevailing Date, whichever of those currently governs. Two columns beside them, Days In Step and Days Overdue, do the work of the Monday meeting without anyone having to answer for themselves.

Sorting that grid by Days In Step is the uncomfortable part. The jobs that surface are rarely the ones anybody was worried about. The loud job has been loud for a reason and somebody is on it. The job sitting in the same step for nineteen days is quiet, which is exactly why nothing has happened to it.

One number for the month

Individual milestones tell you where a job is. They do not tell you whether the month is going to make it. That is the Released % metric: released hours divided by total hours, measured against a release step you configure. It answers one question, which is how much of the work in front of you is clean and gone to the floor, versus still being drawn.

The Bottlenecks dashboard puts that in context. Its Workflow and PM in Workflow tabs cross-tabulate hours, cost and margin against time ranges, so you can see whether the engineering queue is a spike this month or the shape of your operation. The Throughput and Slippage widgets sit alongside it, and Slippage drills down to which project managers contributed to the move.

There are honest limits. The measurement is only as good as the release step you set, and if that step does not match what your shop actually treats as released, Released % will be precise and wrong. There is also the question of what counts. Across INNERGY platform data, a cross-tenant rollup built in August 2026, 54.2% of hours attributed to engineering are being worked and 45.8% are waiting, and the largest single waiting bucket is work out for approval. Whether that time should count against engineering at all is a judgment call worth roughly four points either way. Your leadership team makes that call, not the software.

Why we are going to Bonita Springs 

This is a hard conversation to have in a group webinar but an easy one to have across a table, which is the real reason we go to the AWI Annual Convention.

INNERGY will be at the 2026 convention, October 21 to 23, at the Hyatt Coconut Point in Bonita Springs, Florida. Jillian Klinar, Garin Trimble and I are making the trip. Find us at the Product Fair: two six-foot tables side by side, two screens running, no theater presentation on a loop.

Fifteen minutes is enough to see what the measurement looks like on a real operation: how long a job sits between award and released shop drawings, how much of a month is actually released, and what the grid surfaces when you sort it by the jobs nobody was worried about.

What we will not do at that table is tell you the software fixes a throughput problem. It makes the constraint visible, and visible is where a team can finally act. The deciding is still yours, and any vendor promising otherwise is selling you the easy version of a hard year.

Register for the event here and come see us in Bonita Springs. We will be the ones with two screens and too much coffee.

Ask a millwork owner where the company loses money and most will point at constraints they see on the floor. The machine that went down. The crew that ran long on install. The panel that came back wrong three days before delivery.

 

Then look at the numbers. AWI Cost of Doing Business Survey data puts the engineering productivity multiplier at roughly $15.35 of downstream shop labor and materials output for every $1 of drafting and engineering corporate cost. Engineering is the highest-return dollar in the building, which makes a backlog in engineering the most expensive delay you have.

 

Nine out of ten shops named the same constraint

 

In August 2026 we surveyed 124 woodworking shops across the United States, Canada, and Australia and New Zealand about their current CAD/CAM tools. 85% named the time it takes to detail or engineer a job as a pain point. It was the number one answer in every region, and nothing else came close.

 

The pressure is building from both sides. With increased renovation and retrofit rather than new construction, and existing buildings do not cooperate: nothing is square, dimensions have to be field-verified, and phasing around an occupied space means more one-off pieces and fewer repeatable runs. Same contract value, more drawings. Meanwhile a shortage of skilled engineers pulls design windows in. More drawings, less time, in the exact place where speed decides profitability.

 

What the margin gap is actually made of

 

AWI Cost of Doing Business Survey data shows an 11-point operating margin gap between top-quartile firms and the median. Same machines, same lumber, same labor market. For a $10 million shop, that is roughly $1.1 million more EBIT every year.

 

Here is the part that surprises people: top-quartile firms spend less on engineering payroll than bottom-quartile firms and still win. The advantage is not more engineers. It is the ability to release clean work early and know where every job stands. When we polled owners at an INNERGY Summit on what that would be worth, complete shop drawings four weeks early with all materials staged, 64% said their profit would more than double.

 

“Profitability is made prior to the sawdust, in estimating, engineering, and the flow of information long before a single part is cut.”

Marc Sanderson, CEO, INNERGY

 

The instinct is to hire. The constraint is usually the waiting.

 

When engineering runs behind, the default move is another drafter. Sometimes that is right. But capacity added to a serial process is still a serial process, and in a file-based desktop tool the hours go somewhere other than engineering:

• One person per job. A second drafter means a second file and a merge at the end. 

• Crashes on custom work, which is the work that pays best. 

• Performance that degrades as job size grows, on the projects the schedule can least absorb. 

• A recut loop that routes through whoever has the file open. 

None of that is engineering. It is waiting, redoing, and hand-carrying. You cannot hire your way out of a backlog whose real cause is that only one person can be in the room.

 

What we built, and why

 

INNERGY Engineering launched on August 19, 2026: cloud-native CAD/CAM built inside INNERGY ERP, developed and hardened alongside Early Adopter shops. It aims at one outcome above all others. Get engineering done faster, because faster engineering is more throughput, and throughput is margin.

 

Several people can design and engineer in the same project at the same time, with no file locking and no waiting for a colleague to close a file. Work saves continuously, so a crash no longer costs a morning. It runs on the hardware your team already owns, and updates arrive automatically instead of as manual installs. Because engineering lives inside the platform, drawings, bills of materials, and CNC output flow through to production and purchasing instead of being re-keyed.

 

It makes its in-person debut at IWF Atlanta 2026, August 25 to 28 at the Georgia World Congress Center.

 

Three questions before you buy anything

 

You do not need new software to find out whether engineering is your constraint. You need three numbers.

 

• How many days pass between award and released shop drawings, and how much of that is work versus backlog?
• How many people can be inside your largest active job right now, at the same time?
• How many times last week did an engineer stop engineering to unblock someone else?

 

If the answer to the second is “one” and the answer to the third is a number you do not like, capacity is not your problem. Access is. That is fixable, and worth fixing upstream while the margin is still there to protect.

 

See INNERGY Engineering in action. Request a walkthrough at innergy.com/demo, or find us at IWF Atlanta 2026, August 25 to 28.

Nobody sold you the system you run on now. Somebody in your shop built it.

 

It usually starts as one workbook. An estimator wants a faster way to price a job, or a PM gets tired of walking out to the floor for a status update. It works, so it grows. Now there is a tab for labor rates, a Google Sheet the field updates from their phones, a whiteboard that is the actual production schedule, and a folder of saved emails doing the job of an RFI log. Every piece of that solved a real problem the day it got built.

 

Most software companies get this wrong about millwork. The alternative to an ERP is almost never somebody else’s ERP. It is the thing your own people made.

 

It does not break. It stops keeping up.

 

An estimator emails an RFI and the answer lands in their inbox, so a month later the PM asks the same question again. Cut lists get rebuilt from scratch per job. Installers write percent complete on paper and turn it in at day’s end, so the earliest a PM can respond is tomorrow morning. You find out late, then rearrange the month around it. That is not a discipline problem. It is what happens when people carry the information instead of a system.

 

Ask who else can actually run it

 

The person who built your pricing workbook understands the logic inside it. Who else does? Not the formulas, the reasoning. Why that waste factor, why that markup on that GC, why the tab nobody touches is still there.

 

If the answer is one name, that name cannot take a real vacation and cannot be promoted out of the job. Quitting would be worse. You never hired a software maintainer, and you have one anyway. Never be too good at the job you do not want.

 

Schlaegle Design Build ran on spreadsheets until they became a blocker

 

Casey Schlaegle started Schlaegle Design Build Associates in his Pittsburgh basement on April Fool’s Day in 2011, on $30,000 of revenue and whatever work he could get, from countertops to construction.

 

“I didn’t know how accounting worked, so learning QuickBooks was a crash course.”

 

The business kept growing. By 2018 it ran on Excel and QuickBooks, and scaling got harder every year. That got concrete during COVID, when Casey took over purchasing himself for a stretch and saw what a paper system costs from the inside. He came across INNERGY through his peer group in 2021, and he was skeptical at first.

 

Today it is roughly 45 employees and about $10 million, with work at Carnegie Mellon, PNC Park, and Nemacolin. Two things changed, and neither one is a software feature. Workload meetings went from hours to 45 minutes. And the number he manages by moved from revenue volume to contribution margin per hour, which is what put the shop in high-profit territory. He builds his own dashboards on top now through API calls, but the order matters: standardize the data first, automate second.

 

Mission Bell started in exactly the same place

 

Mission Bell has been around since 1959. Jason Neff joined in 1998 and is now COO of roughly 250 people in the Bay Area. Where did a company that size begin? Lotus 1-2-3. Then Excel. Then an internal database of their own that handled rudimentary scheduling and stayed, in his words, very disconnected from the rest of the organization.

 

Same road as the basement in Pittsburgh, started half a century earlier. They got further down it than most shops ever will, and then they ran the math on finishing.

 

“We were evaluating the cost of maintaining the system, the cost of hosting the system, the cost of ensuring redundancy and connectivity and uptime. And an extremely long list of features and functionality that we needed to get coded into the system. It would have probably taken us two years, if not more.”

 

Most millworkers are in the same boat, he figures. They are not software developers and they do not have software developers on the team. Two years or more to finish building what they had started. They signed with INNERGY two months after the first conversation, and went live four months after that.

 

We bring that timeline up because implementation is the objection we hear most, usually some version of not being able to afford the disruption. One detail explains how Mission Bell moved that fast. They did not rebuild the old system inside the new one. Rather than mimic what they had, they changed their standard work toward the best practice path, which is the opposite of what most shops ask for on day one.

 

Forecaster and the Bottleneck Report now show them what is coming and where the holes are, far enough out to expand into life sciences and plan the team for it.

 

Two signals it is time

 

Casey’s test is the shorter one. Enter the same data more than twice and it is time to look at an ERP. Jason’s takes longer to say: once the shop needs a dedicated estimator, dedicated project management, and dedicated engineering, you have built barriers information has to cross.

 

Neither test mentions revenue. Both are about handoffs.

 

Your homegrown system is not the villain here. Somebody smart built it under pressure, and it carried the shop further than anyone expected it to. The question is whether it can carry the shop you are trying to become, and whether the person maintaining it should still have that job.

 

Casey has advice for anyone sitting where he sat in 2018.

 

“Do it sooner rather than later. The longer you wait, the more you’ll wish you had started earlier.”

 

More Resources:

• How Schlaegle Design Build went from Excel bottlenecks to contribution margin per hour
• Mission Bell on exposing bottlenecks and planning further out
• See all five stages side by side, and what changed at both shops

Last year’s benchmarking headline was simple. High-profit shops out-earned the industry average by a wide margin, and the interesting question was what they did differently. That relationship held in 2026. What changed is the ground both groups are standing on.

 

The multiple held. The floor dropped.

 

In the 2025 US report, the average shop posted 9.88% EBITDA and the top quartile posted 24.10%. In 2026, those numbers are 7.47% and 17.83%. Divide either pair and you get roughly 2.4x both years, so the ratio survived intact.

 

The absolute gap did not. It narrowed from 14.2 points to 10.4, because the top quartile fell almost three times as far as the middle did. Average shops gave up 2.4 points of margin. High-profit shops gave up 6.3.

 

The cutoff moved with it. Qualifying for the top quartile in the US took 14.47% EBITDA in 2025 and 11.53% in 2026. Worth remembering that the IIBT force ranks the top 25% every year, so high profit is a rank rather than a fixed standard. A shop that held margin flat may have moved up a quartile without changing a thing.

 

 

The best shops now win more of what they bid

 

Last year the data supported an appealing idea, that the healthiest shops bid selectively and won less of what they chased. US high-profit firms converted 34% of bid value against 37% for all firms.

 

In 2026 that flips hard. High-profit firms convert 46%, all firms convert 35%. Whatever the top quartile is doing on the estimating side, they are winning noticeably more of what they put out, not less.

 

Software satisfaction and AI interest both jumped

 

Engineering software satisfaction in the US moved from 50% to 64% of firms reporting satisfied or very satisfied, the largest single-metric jump anywhere in the report.

 

AI automation as a stated 12-month priority went from 30% to 42%. Still last on the list of seven improvement areas, and still nowhere near profitability at 97%, but a twelve point move in one year says the conversation has shifted from novelty to something shops are budgeting attention for.

 

The bottom line

 

The rankings held their shape while the whole field slid down. That makes 2026 a year where your quartile position is a weaker signal than the margin behind it, and where clearing the high-profit bar says less than it did twelve months ago. If you want one number to work on before the next survey, make it contribution margin, where the 2026 US spread still sits at 38.00% for all firms against 41.59% for the top quartile. These metrics only scratch the surface of the data covered in the IIBT, if you want to have the full report sent to you next year, please make sure you participate!

 

See the 2025 vs 2026 comparison in one graphic, with every movement above, US and Canada side by side, on a single page.

How do we make money? Are we doing better than last year? And what should we be measuring against to know the business is actually healthy? Every shop owner runs on some version of those three questions, and none of them can be answered in isolation. A score only means something when there’s another score next to it.

That’s the whole point of the IIBT (INNERGY Industry Benchmarking Tool). It’s free, it’s anonymous, and it’s built specifically for millwork and custom woodworking businesses. This year set a record: 148 shops across the U.S., Canada, and Australia/New Zealand submitted their 2025 numbers. In the U.S., median revenue came in at $6.5 million, down slightly from last year, with a median of 31 years in business. Here’s what stood out.

 

Trend 1: High-profit shops earn almost 2.5x the margin, and it has nothing to do with wages

 

The median U.S. shop keeps $7.50 of every $100 in operating EBITDA. The top 25% keep $17.80.

 

The easy explanation would be that high-profit firms pay their people less, but the data says no. Across every role surveyed, pay between average and upper quartile firms lands within about 4% of each other, which is noise. The gap comes from productivity: how much work moves through the shop with the team they already have.

 

Trend 2: Most shops still lose money on installation. The best shops profit from it

 

For the median U.S. firm, installation brings in $12.70 of every $100 in revenue and costs about $13 to deliver. That’s a 3% loss on every install. Installation has historically run at break-even for this industry, so most shops aren’t even losing sleep over it.

 

Upper quartile firms are running install at nearly 23% margin. Not break-even. Profitable. The data doesn’t say the top firms found some install trick nobody else knows about, but it does prove install can carry margin instead of eating it. If install is still the part of the job nobody wants to look at, that’s exactly where to look.

 

Trend 3: Revenue per employee separates the shops that are keeping up from the ones falling behind

 

Here’s a 30-second self-check. Multiply your headcount by $226,000 and compare it to your actual revenue. That’s the U.S. benchmark for a 40-person shop (the number climbs slightly as firms get larger), and upper quartile firms run about 13% above it per person.

 

One more thing the data killed: the idea that bigger shops are automatically more productive. Doubling in size only adds about 2.5% in revenue per person, so if the number above surprised you, the fix probably isn’t hiring.

 

Want to see where your shop stands?

 

The 2026 IIBT goes deeper than three trends: income statements by shop type, performance by revenue quartile, and where profit is actually made across plant-processed work, buyout, and install. The shops in this data get to answer those three questions at the top with real numbers instead of gut feel. When the next IIBT opens, participate. Less than an hour of your time buys you a benchmark you can’t get anywhere else.

Nobody wakes up wanting to buy an ERP. You start looking because something specific finally got old: retyping the same job details into three different places, guessing whether the last job made money, or admitting that the whole office runs on spreadsheets only one person understands.

 

That last one comes up more than anyone admits. A lot of shops are run by an owner who bought or inherited the business years ago, kept the systems that came with it, and is now thinking about what the next owner gets handed. A folder of read-only Excel files and a QuickBooks login is not much of an inheritance.

 

That’s the real reason to look at an ERP. What you’ve built deserves to outlive the workarounds holding it together.

 

What is an ERP for woodworking, actually?

 

An ERP (enterprise resource planning system) is one system that runs the business side of your shop: estimating, project management, scheduling, purchasing, inventory, invoicing, and job costing. Instead of a quote in one file, a cut list in another, materials in your head, and billing in QuickBooks, everything about a job lives in one place and talks to everything else.

 

For a woodworking shop specifically, that matters more than it does for most businesses. Every job is a one-off blend of custom dimensions, materials, finishes, and hardware. Generic software treats that like a nuisance. A woodworking ERP treats it as the whole point.

 

The competition isn’t other software. It’s your spreadsheet.

 

Most ERP marketing gets this wrong. The thing you’d be replacing is the homegrown system you or someone before you built, one workbook at a time, over years.

 

And let’s be fair to that system: it was free, it was clever, and it carried the business this far. The person who built it understood the shop better than any software vendor ever will.

 

The problem is what it costs you now:

• Every estimate, invoice, and material decision routes through one person. When they’re out, the office stops.
• Nobody can say, today, which active jobs are making money and which are quietly bleeding it.
• Inventory lives in memory. Hardware gets reordered that’s already on the shelf, or a job stalls because it isn’t.
• When ownership changes hands, the next person inherits files, not a system. The knowledge walks out the door with the founder.

 

None of that shows up as a line item, but all of it lands in your margins.

 

Five things to evaluate in a woodworking ERP

 

If you’re comparing options, here’s what actually separates them for a shop like yours.

 

1. Was it built for this industry, or adapted to it?

Generalist ERPs can be configured to handle a cabinet shop. The catch is who does the configuring. You’ll either pay an implementation partner to build custom workflows, or you’ll do it yourself and hope you modeled the business right. An industry-specific ERP comes with millwork workflows already built in: bids, work orders, change orders, finishes, submittals. You pay more for the license and less for the surgery.

 

Neither answer is automatically right. But be honest about whether you have the time and technical appetite to build your own system inside a generic one.

 

2. Inventory that understands materials, hardware, and finishes

A woodworking shop’s inventory isn’t widgets on a shelf. It’s sheet goods, edge banding, hinges, slides, and pulls, each with sizes, finishes, and costs that flow into what a job actually costs you and what you should charge. Look for a materials library you can set up your way, and inventory that decrements when materials get consumed on a job, so what the system says matches what’s on the rack.

 

3. Job costing you’d bet the business on

This is the difference between knowing you had a good year and knowing which jobs made it good. Real job costing ties labor, materials, and purchases back to each project while it’s still running, not three months after it closed. If a system can’t show you contribution margin per job, keep looking.

 

4. It should work with your design software, not fight it

You shouldn’t have to abandon the CAD/CAM tools your shop already knows. Ask any vendor exactly which engineering systems they import from, and get specifics: which file formats, whether parts map to materials and labor automatically, and what happens when a design changes mid-job. INNERGY’s Engineering Sync, for example, imports from Microvellum and a range of other supported CAD/CAM systems, mapping parts to materials and labor so engineering data drives purchasing and production instead of getting retyped. If your design tool isn’t on a vendor’s supported list, ask what the workflow looks like before you sign anything.

 

5. Support and education that outlast the demo

Software vendors are great at demos. The question is what happens in month three, when the honeymoon is over and your team hits the messy middle of implementation. Look for structured onboarding, training your whole team can access, and a vendor that teaches business fundamentals, not just button clicks. Owners who’ve been through it tend to describe it the same way: implementation took real time and brainpower, and now they wonder how they ever functioned without it. Both halves of that sentence are true, and a good vendor will say so.

 

The part nobody wants to hear: implementation is on you

 

There’s a piece of shop wisdom we’d frame in a poster and hang in our office: software is no silver bullet. It’s just tools. Time, effort, and consistency get you over the hump, no matter what you choose.

 

That’s true, and we sell the software.

 

Any ERP, ours included, asks something of you. Someone in your shop has to own the rollout. Your processes have to be defined well enough to put into a system, which for a lot of shops means defining them for the first time. Data has to move over clean. If nobody on your team can be that point person, fix that before you buy anything, because no ERP survives an implementation nobody owns.

 

What a good vendor changes is how much of that hill you climb alone. Structured onboarding, industry-specific templates, and a support team that has watched dozens of shops make this exact transition won’t make the work disappear, but they make it survivable.

 

The results can be dramatic when a shop commits. Taber Company grew from $3M to $44M on INNERGY, and buying software was the smaller part of that story. The growth came from finally seeing where the money was made and lost on every job, then acting on it.

 

Frequently asked questions

 

What does ERP stand for in woodworking? ERP stands for enterprise resource planning. In a woodworking context, it’s one system that handles estimating, project management, purchasing, inventory, scheduling, and invoicing for custom work, so job information doesn’t live in disconnected spreadsheets and inboxes.

 

Does a woodworking ERP replace design software? No. A good woodworking ERP connects to your CAD/CAM system and pulls engineering data into purchasing and production. You keep designing where you design today, as long as the ERP supports importing from that system.

 

How is a woodworking ERP different from QuickBooks plus Excel? QuickBooks tracks money after the fact. Excel tracks whatever someone remembers to type into it. An ERP connects estimating, production, purchasing, and invoicing while jobs are live, so you can see problems before they become losses instead of discovering them at year end.

 

Where to start

 

You don’t have to decide on software this week. Start by writing down how a job actually moves through your shop, from first phone call to final invoice, and mark every spot where the information lives in one person’s head. That list is your requirements document, and it’s useful no matter which direction you go.

 

When you’re ready to see how an industry-built ERP handles that list, book a demo with INNERGY.

By: Marc Sanderson

 

Transparency is one of the few competitive advantages available to every leader. It doesn’t require venture capital, breakthrough technology or a patent—yet remarkably few companies consistently practice it.

 

We all value transparency when we receive it. We expect it from our leaders, our colleagues and the companies we buy from. But valuing transparency and practicing it—especially when it’s uncomfortable—are two very different things.

 

In business, transparency feels risky because it exposes imperfection. Yet, that’s precisely when it matters most. At INNERGY, transparency isn’t just something we try to do. It’s one of our core values. We expect every employee to pursue it—with one another and with our customers. We’ve learned that transparency doesn’t weaken relationships; it strengthens them by reducing uncertainty, building trust and accelerating learning.

 

Over time, I’ve come to think about transparency through three distinct forms of trust:

 

1. Operational Trust: People believe you’ll tell them what’s happening.

2. Relational Trust: People believe it’s safe to tell you what’s happening.

3. Strategic Trust: People understand why decisions are being made.

 

Those three forms of trust reinforce one another and become a lasting competitive advantage. Here’s how they play out practically:

 

1. Build Operational Trust: Show the bruised side of the apple.

 

Every company celebrates wins. Few celebrate bruises. Yet bruises are where learning happens. Our team often talks about showing the “bruised side of the apple.” If leaders only share victories, people quickly learn that mistakes aren’t acceptable. Problems get hidden instead of solved.

 

I intentionally admit my own mistakes, big and small, because every time a leader goes first, someone else gains permission to speak up. Research by Harvard Business School professor Amy Edmondson found that the best-performing teams weren’t making fewer mistakes, they were reporting them more openly. Their advantage wasn’t perfection. It was faster learning: fail fast, fix fast.

 

The bruises aren’t the problem. Hiding them is.

 

2. Build Relational Trust: Go first with vulnerability.

 

Transparency requires vulnerability, and someone has to take the first step. Make it you.

 

Many people don’t struggle with transparency because of the current experience, they struggle because of their previous one. They’ve worked in organizations where admitting mistakes meant embarrassment, blame or even termination. They bring that baggage with them.

 

I’ve learned that building a transparent culture isn’t simply telling people it’s safe. It’s proving it over and over again. I seek to model it consistently, in all aspects of my life. I protect people when they tell difficult truths. I don’t punish honesty (bad news doesn’t get better with age). Over time, people believe what they experience instead of what they hear.

 

When leaders go first, innovation follows because people feel safe enough to keep swinging.

 

3. Build Strategic Trust: Make your motives known.

 

People rarely question decisions as much as they question intentions. Every decision tells a story. If you don’t explain the “why,” people will often write their own version.

 

I recently spent an hour with a customer who was convinced we intended to raise prices simply because we could. He was new to our company through an acquisition and didn’t yet understand who we are. I explained that we can demonstrate that an average customer using our platform operates with about 4.5 fewer employees than similar businesses in the industry.

 

Share the Journey (Not Just the Victory)

 

Relational trust is the hardest to build and sustain. People can handle slow progress. They struggle with hidden progress. Transparency isn’t simply announcing the breakthrough. It’s about being open about the process and what it takes to improve.

 

I recently spent significant time in Australia meeting with customers because of technical support challenges. Those conversations led us to identify an AI solution that will dramatically improve support with the focus on achieving RAVING FANS. It would have been easy to announce the exciting part and stop there.

 

Instead, we also need to explain the harder truth. Deploying AI is only one step. Fully solving the problem requires planning, implementation, change management—and time. Transparency sometimes means asking customers or colleagues for patience while you earn back their confidence.

 

The Trust Equation

 

We experienced this firsthand during an unexpected company-wide outage. What stood out wasn’t the outage—it was our culture. Before anyone assigned responsibilities, employees instinctively ran toward the problem. One person launched a communication channel, another rerouted our support line, many others contacted customers, and we published updates every ten minutes.

 

We didn’t need a detailed disaster recovery playbook. We had a shared commitment to creating RAVING FANS, and everyone knew that taking care of customers came before protecting appearances.

 

During our planned product release two business days later, we addressed the outage head-on. Customers thanked us—for communicating openly, acting quickly and demonstrating that we cared. They knew we were running to the problem and respected our transparency.

 

That experience reinforced an important lesson: Transparency isn’t valuable because it makes people feel better. It’s valuable because it reduces uncertainty. And when uncertainty declines, trust grows. Every transparent conversation is another deposit into the trust account.

 

Trust behaves like compound interest. Every transparent conversation adds a small amount. Every mistake that’s hidden withdraws a much larger amount. Over time, organizations—and leaders—with high trust move faster because they spend less time overcoming skepticism.

 

Transparency isn’t always comfortable. It isn’t always convenient. But it’s always worth it because it is a competitive advantage.

 

Marc Sanderson is the CEO of INNERGY and former President/Owner of Wilkie Sanderson. He began in the millwork industry 20 years ago with a small cabinet shop and built it into one of the most profitable operations in the country. A Harvard MBA and 2024 Wood Industry Market Leader, Marc is known for transforming complexity into clarity through data-driven strategy and culture first leadership. Equal parts analytical operator and motivator, he’s just as comfortable refining strategy as he is rallying a room around a shared vision.

Every shop produces sawdust. The ones pulling ahead are producing something more valuable: data they actually use.

 

That was the core idea behind INNERGY’s recent webinar, Data Is the New Sawdust, where our team sat down with two operators who have made data a central part of how they run their businesses — Casey Schlaegle, owner of Schlaegle Design Build Associates (SDBA) in Pittsburgh, PA, and Jason Neff, COO of Mission Bell Manufacturing in California.

 

Between them, they represent two very different shops: SDBA runs about 45 employees and $10M in revenue doing commercial architectural woodwork nationally; Mission Bell operates at roughly 250 employees and $70M in revenue focused on commercial architectural millwork and casework. Different in scale. Very similar in what they’ve learned.

 

Here’s what stood out.

 

Most Shops Are Flying Blind — Until the Job Is Done

 

Casey put it plainly: before INNERGY, his team used QuickBooks and could see where they landed at the end of a project. But they never knew in real time where they were.

 

“We kind of just hoped for the best. We would do a guesstimate of cost to complete to see where we thought a project would end. And then at the end of the day we would evaluate it and say, was that a win or a loss?”

 

The problem with that approach: you can’t fix a job that’s already finished. And you can’t improve your estimates if there’s no reliable feedback loop from actuals back to your bidding process.

 

The shift for Casey came when he started tracking shop floor labor against work orders daily, so he could see estimate versus actual in real time — not after the fact.

 

 

The Three Numbers That Change Everything

 

The team walked through what INNERGY calls the foundation of operational data: three numbers at the work order level.

 

1. Revenue released — what you’re billing for that work order
2. Actual labor — what it actually cost you in hours and dollars
3. Actual material — what you spent on materials

 

These three numbers form what he called the “three-legged stool.” Together, they give you a real picture of job health and contribution margin. The industry benchmark for contribution margin in woodworking is 40%. If you’re not tracking these three at the work order level, you don’t have enough information to know whether you’re hitting it — or why you’re not.

 

For more mature shops, we introduced the concept of the “six column game” — adding work order number, project name, and description to the three financial columns above. It’s a simple structure, achievable in a spreadsheet, that creates an analytical foundation for better decisions down the road.

 

The Capacity Revelation at Mission Bell

 

One of the most compelling moments in the conversation came from Jason. His team made a significant shift in how they think about the business: away from chasing revenue numbers and toward filling capacity.

 

“We used to rely heavily on our revenue number. We were not focused on filling the plane to capacity.”

 

When Mission Bell started measuring labor utilization daily and weekly, something surprising happened: they had more capacity than they thought. And by managing work flow and work-in-process more intentionally, their effective capacity grew 30 to 50 percent — without adding headcount.

 

Casey added a detail worth sitting with: every percentage point of labor utilization above your estimate translates into real margin improvement. If you’re estimating jobs at 85% utilization and your team actually runs at 90%, the difference goes straight to contribution margin. “It’ll blow your mind,” Casey said. “And it’ll make you want to keep increasing that.”

 

Data Doesn’t Fix Itself: The Change Management Problem

 

Both operators were honest about the messiest part of getting here: getting consistent data into the system in the first place.

 

Casey’s approach at SDBA was direct. He started auditing specific data points daily — were employees clocking in to the right work orders? Were materials being job-costed correctly? And then he sent targeted messages to whoever was responsible when something was off.

 

“I would check that every single day and I would send a message, whether it was an @ or a chat, to whoever is responsible and say, ‘hey, this is off.'”

 

Over time, he built a simple scorecard for employees — a 1 or 0 each day for data accuracy — that was posted publicly each week. No one was called out by name, but everyone could see how the shop was performing. Timekeeping accuracy improved steadily until they reached a point where they actually trusted the data.

 

The principle he described: identify the problem, identify the data point that reveals it, audit that data until the behavior changes, then move to the next one. He started with about 20 audit points; he’s now back down to about five, with most of them automated.

 

Jason’s approach at Mission Bell centered on a daily labor utilization rate. The target: above 85%. The metric was tracked daily, reviewed weekly, and used to drive continuous process improvement. They also track Cost of Quality (COQ) — rework and remake — separately, so it doesn’t contaminate the productivity numbers.

 

What Data-Driven Decisions Actually Look Like

 

Both Jason and Casey shared examples of decisions that data made possible.

 

For Jason, the clearest example came at the end of 2024 and into early 2025. Looking at work on the books plus high-probability forecasted projects, Mission Bell could see they had a constraint coming in their finishing team. Not a gut feeling — visible data.

 

“We made the decision to spend a couple hundred thousand dollars in CapEx [on a new finishing booth and infrared cure ovens]. It’s paid off tremendously. Finishing has traditionally been a bottleneck in our organization. We’re in a place right now where we can turn things around in finishing within a day or two.”

 

That decision was made using three to five years of historical data plus the forward-looking work pipeline. Without that visibility, it would have been speculation.

 

For Casey, data has become a tool for continuous improvement at the process level. When labor hours started trending in the wrong direction, he compiled the data, identified the specific areas of the shop where efficiency was slipping, built a targeted improvement plan, and implemented it.

 

“Now we’re trending under estimated hours in those areas.”

 

He also used data to evaluate a capital equipment decision: variable-speed versus fixed-speed compressor. He ran the numbers using AI, factoring in runtime, location, and a 15-year horizon. It’s a small example, but it illustrates something important: when your data is clean and your processes are analytical, every decision gets better.

 

AI Amplifies Good Data (and Can’t Fix Bad Data)

 

Both operators have internal AI task forces. Both are building dashboards, automating workflows, and using AI to aggregate and analyze operational data faster than any manual process could.

 

Casey described an automated daily view for his warehouse team that surfaces every work order coming in the next two weeks, with materials and kitting requirements, refreshed at 5:00 AM every morning.

 

“They can’t even break it. If they delete it, the next day it’ll repopulate.”

 

Jason described layering AI over the data in INNERGY to get more precise views at both the job level and the business level.

 

But both were clear about the limits. “AI does not replace the human, and it definitely does not replace bad data. Hygiene still requires really good data and it still requires that creative, subject matter expertise to really make it all come to life.”

 

The principle is simple but easy to forget: AI is a multiplier. If your data is accurate and your processes are disciplined, AI gives you meaningful leverage. If the underlying data is a mess, AI gives you garbage faster.

 

Where to Start

 

The session closed with a practical framework for shops that are just beginning this journey.

 

Step one: Start with the three numbers. Revenue released, actual labor, and actual material — tracked at the work order level. Build that habit before you try to do anything more complex.

 

Step two: Move to the six column game. Add work order number, project name, and description to create a foundation for trend analysis and estimating improvement.

 

Step three: Find your sweet spot. Analyze which types of projects drive your best contribution margin per production hour. Identify what fits in that upper-right quadrant of right-fit, right-margin work — and get disciplined about pursuing more of it.

 

Casey’s advice for anyone starting from scratch: begin with job costing at the work order level.

 

“That gives you such rich data of where you’re succeeding, where you’re failing, where you need to basically know what you need to do.”

 

And his reminder on data hygiene: “Garbage in, garbage out. That’s easier said than done. But I would urge everybody to figure out a way to audit.”

 

The Bottom Line

 

Your shop produces data every single day. It lives in the hours your team clocks, the materials you purchase, the work orders you close. The question is whether you’re capturing it consistently, trusting it enough to act on it, and using it to make better decisions.

 

The shops that win long-term are the ones that treat that data as a business asset — not an afterthought.

 

If you want to see how INNERGY helps woodworking and millwork shops get control of their operational data, schedule a conversation with our team.

 

Casey Schlaegle is Owner of Schlaegle Design Build Associates in Pittsburgh, PA. Jason Neff is COO of Mission Bell Manufacturing in California.

A shop takes a job. The crew builds it clean, the install goes fine, the client is happy. Months later someone finally pulls the numbers on it and the room goes quiet. The work was good. The bid was wrong. By the time anyone caught it, the money was already gone.

 

That is the quiet way shops bleed. It almost never shows up as one dramatic loss. It’s a slow drip of jobs that looked fine and quietly came up short, and it traces back to one moment: the day the estimate went out the door.

 

Profitability is made prior to the sawdust. The price you can charge, the margin you get to keep, the cushion you have when a job goes sideways, all of it is mostly set before a single part is cut. The saw doesn’t decide whether a job makes money. The estimate does.

 

Why estimating is harder in millwork than almost anywhere else

 

Most manufacturing runs the same part a thousand times. You estimate it once and you’re done. Millwork doesn’t work that way. Every job is a one-off blend of custom dimensions, finishes, and joinery, and every one of those choices carries a cost. Butt joints price differently than miters. Paint grade prices differently than veneer. A run of casework with full-extension soft-close slides is a different number than one without, and that’s before you’ve touched the install.

 

Then there’s labor, which is the part that wrecks most estimates. Material you can look up. Labor you have to know, and it lives in the hands of your shop foreman and your installers, not in a price book. Guess high and you lose the bid. Guess low and you win a job that costs you money to deliver. Either way the spreadsheet doesn’t warn you. It just adds up whatever you typed.

 

What good estimating actually requires

 

Here’s the part nobody selling software likes to admit: there is no button that estimates a custom job for you. Anyone promising that is selling you a fantasy. A real estimate gets built from your shop’s real numbers, your material price points, your labor rates, your install costs, your overhead. Knowledge that already lives in your shop, just scattered across people and files.

 

The job of estimating software isn’t to invent those numbers. It’s to hold them in one place and run the math the same way every time, so the bid doesn’t depend on which estimator built it or how tired they were on Friday. That job is what INNERGY’s Estimating feature is built for, and it’s worth walking through what it actually does.

 

Get the takeoff and the markup in one place

 

Most estimating starts as a scavenger hunt across a PDF plan set, a spreadsheet, and an email chain, and somewhere in that shuffle a measurement gets keyed in wrong. INNERGY puts the plan markup, the product placement, and the cost calculations on one screen, so the takeoff and the number stay connected.

 

• PDF annotations, measurements, and smart tags
• Each, linear, and area takeoff methods
• Scale verification with multi-scale page support
• Locations for instant room-by-room breakdowns

 

Put real math behind every item

 

This is where the price points live. Behind every product you place sits its actual assemblies, parts, labor operations, and material pricing, and the cost reflects how your shop actually builds, not some generic average. Change a material price and the whole bid recalculates. You’re not retyping numbers, you’re adjusting the logic once and letting it ripple.

 

• Material and labor cost roll-ups on every item
• Product logic you customize for how your shop works
• Margin controls with instant recalculations
• Bulk edits that update an entire bid in seconds

 

Make your assumptions visible to the whole team

 

Half the cost overruns in a shop come from a finish or a spec that one person assumed and nobody else knew. Material legends and global groups put those assumptions out in the open. Now the estimator, the PM, and engineering are all reading from the same page from day one.

 

• Define PLAMs, veneers, and finishes upfront
• Share long-lead items with PMs and vendors
• Keep estimating consistent with repeatable SOPs

 

Turn the estimate into a proposal without rebuilding it

 

The estimate is done and now somebody has to turn it into something the client will sign. Usually that means rebuilding it by hand in another document, which is how scope and pricing quietly drift apart. INNERGY pulls the proposal straight from the estimate instead, so what you bid is what you send.

 

• Customizable scope and summary options
• Automatic location and product breakdowns
• Built-in clarifications and conditions
• Export to PDF, Excel, or JSON

 

The estimate is the highest-leverage number in your shop

 

Notice that these four things aren’t really separate. The takeoff feeds the cost math, the cost math carries your assumptions, the assumptions flow into the proposal. It’s one chain, and it’s your numbers moving through it from the plan to the signature.

 

That’s the whole point. Tighten the estimate and everything downstream gets easier, because every schedule, every material order, and every margin report is built on top of it. Get the bid right and you’ve protected the job before it ever reaches the floor. Get it wrong and no amount of good work in the shop will earn that money back.

 

If your shop is still estimating out of a spreadsheet that one person understands, it’s worth seeing what the alternative looks like. Book a demo and see how estimating works when the markup, the math, and the proposal all live in one place.