By Marc Sanderson
Every CEO eventually faces an uncomfortable reality: the strategy that once made sense is no longer delivering results. Revenue stalls. Margins shrink. Your team works harder, but the business isn’t moving forward.
The instinct? Push harder. More sales activity. More accountability. More operational discipline. Maybe even make changes to the team. Sometimes that’s the answer. But sometimes you’re executing a strategy that no longer makes sense.
In woodworking manufacturing where capital investments are significant, skilled labor is scarce and competitive pressures are evolving, knowing the difference is critical.
The question isn’t simply, “Why isn’t our strategy working?” It’s “What did we get wrong, and what are we willing to change?”
Here are five moves every CEO should consider when their business strategy stops delivering results.
1. Challenge the context before changing the course.
Has the world changed around us?
When a strategy fails, leadership teams typically revisit the plan. They adjust priorities, reset targets and push harder on execution. The better move is to revisit the assumptions behind the plan. Strategy is built on context. When the context changes, the strategy may no longer be valid.
Earlier this year at INNERGY, we revisited our competitive environment through the lens of artificial intelligence (AI). Using Porter’s Five Forces framework, we examined how AI was changing customers, competitors, suppliers and potential new entrants.
One question stood out: What happens when customers can use AI to do more themselves? A customer who once needed a complete software solution may now use AI to fill certain gaps. That changes our value proposition—and potentially what customers are willing to pay.
The same principle applies to woodworking manufacturers. Automation changes production economics. Overseas competition reshapes pricing expectations. Technology expands what customers can do internally. Labor constraints challenge existing business models.
A strategy that made sense yesterday may not make sense tomorrow. Strategic planning isn’t an annual event. It’s a continuous response to reality. If the world changes in January, don’t wait until October’s planning retreat to respond.
Change can arrive suddenly (like AI) or be a slow boil (like overseas competition). The magnitude and speed of the change should determine the response. Major contextual changes require faster actions and extensive strategic review. Minor changes still require attention, but the moves tend to be more tactical.
2. Confront your assumptions before committing to ambitions.
Did we get it wrong from the start?
Sometimes the market hasn’t changed. We simply misunderstood it. Perhaps we overestimated our competitive advantage, misunderstood customer needs or pursued a market where the economics were never in our favor.
Consider a woodworking firm serving the hospitality industry. About 75% of its business comes from large hotel projects—competing against overseas manufacturers. The remaining 25% comes from specialized, high-end boutique properties. The company is one of the last domestic fabricators serving this market.
That sounds like a competitive advantage. But is it?
In standardized hotel projects, the fabricator faces Asian manufacturers with significant structural cost advantages. In boutique properties, however, customization, engineering, responsiveness—and the advantages of proximity and shorter lead times—create opportunities to differentiate. The problem isn’t necessarily only that the market changed. It did. It manifested slowly over 20 years. The real issue is the company failed to recognize the slow boil and distinguish where it could create and capture value.
The strategic question isn’t how to work harder at winning the 75%. It’s whether the company should shift toward segments where its capabilities truly matter. That requires validating the opportunity, rethinking its customer mix, aligning operations and potentially walking away from unprofitable work.
It’s difficult. We become attached to the businesses we’ve built and the investments we’ve made. It can feel personal. But, holding on isn’t a strategy. You cannot grab the next trapeze bar without letting go of the first.
3. Get closer to customers before claiming to know them.
Do we truly understand the problems our customers are trying to solve?
One of the biggest strategic mistakes is assuming we understand customers better than we do. In woodworking, we often default to four dimensions of value: cost, quality, delivery, and service. Of course they matter. But they’re starting points, not a differentiated value proposition.
What problem is the customer actually trying to solve? And how can we solve it better than the alternatives?
A cabinet manufacturer may believe its competitive advantage is quality, while its dealer’s biggest frustration is unpredictable lead times. A commercial millwork customer may emphasize price but place greater value on engineering support that prevents expensive field problems.
Talk directly with customers. Conduct interviews and focus groups. Understand their operations, frustrations and unmet needs.
At INNERGY, we reinforce customer intimacy through education, engagement and a high-level of direct executive participation. We bring customers into our events and create opportunities for leaders throughout the organization to build relationships.
Customer intimacy must become part of the organization’s DNA—not simply a sales department responsibility. You cannot build a differentiated strategy around customers you don’t deeply understand.
4. Run the numbers instead of relying on your gut.
Do the numbers validate our growth strategy?
Experienced leaders often rely on intuition—and for good reason. But gut instinct is no substitute for good math. I’ve seen companies pursue ambitious growth plans without answering basic questions about market size, competitive share or the capacity needed to achieve their goals.
You don’t need a sophisticated financial model. Sometimes one spreadsheet is enough.
At INNERGY, we distilled our long-term ambition into 10 key variables. That exercise clarified what the business could become over the next five to seven years. The numbers made the opportunity tangible—and exposed the constraints.
Imagine a woodworking firm planning significant growth within a 100-mile radius. Before investing in equipment or facilities, the CEO needs to understand the addressable market, competitive landscape, current market share and share required to reach the target. What if the local market simply isn’t large enough? That’s a strategic problem—not an execution problem.
I like using simple two-dimensional market maps to visualize segments, market potential, current position and growth opportunities. They reveal where to pursue new customers, cross-sell products or capture additional share. They often become our visual game board for growth.
The goal isn’t more spreadsheets. It’s finding simplicity on the other side of complexity. The numbers don’t need to be perfect. They need to be credible enough to expose assumptions, identify constraints and guide decisions.
They also make an ambitious strategy believable. People commit more readily when they can see a clear path to the goal. The biggest mistake isn’t using imperfect numbers. It’s refusing to use them at all.
5. Turn strategic choices into sustainable success.
Are we capturing the value we create—and aligning the organization to deliver it?
Sometimes the strategy is sound, customers see the value and the market opportunity exists. Yet the economics still don’t work.
Consider a woodworking manufacturer investing significant estimating time into detailed, room-by-room quotations. Customers appreciate the transparency. But it also allows them to cherry-pick components and award the remaining work elsewhere. The company creates value but weakens its ability to capture it.
Before resetting the strategy, test how you package, price and deliver that value. Experiment with bid formats, bundled offerings and pricing. Measure win rates, margins and customer response. Sometimes the problem isn’t the strategy. It’s how you monetize the value proposition.
Even the right value proposition fails without organizational alignment. If customization is your competitive advantage but production is optimized for standardized runs, there’s a disconnect.
At Wilkie Sanderson, we focused on one operational measure: the percentage of work released by the first of the month. It aligned the organization around throughput and on-time delivery.
Translate strategic choices into measurable behaviors. Context drives strategy. Strategy drives structure. Structure drives behavior. And behavior determines results.
Context → Strategy → Structure → Behavior → Results
The Toughest Call: Knowing When to Let Go
Not every missed target requires a new strategy. Sometimes better execution, clearer priorities or a sharper value proposition will get you back on track. But you can’t execute your way out of a fundamentally flawed strategy.
As CEOs, we’re expected to have conviction. We set direction, make investments and ask people to follow us. Admitting we got it wrong takes courage. When your strategy stops working, challenge the context. Confront your assumptions. Get closer to customers. Run the numbers. Align your organization to create—and capture—value.
Above all, be willing to change.
The numbers provide a mirror. They may not show you what you want to see, but they’ll reveal what you need to confront. The objective isn’t to prove your original strategy was right. It’s to build a business that can keep winning when the world changes.
Frequently Asked Questions About Business Strategy
1. How do you know when a business strategy isn’t working?
A business strategy may need reassessment when revenue stalls, margins decline, growth targets are consistently missed or increased effort fails to produce better results.
The key is distinguishing poor execution from a flawed strategy. Start by examining whether the market, customer needs or competitive environment has changed—or whether your original assumptions were wrong. If the economics no longer support your business model, working harder won’t solve the underlying problem.
2. When should a CEO change strategy versus improve execution?
A CEO should focus on execution when the market opportunity remains attractive, customers value the offering, and the business model is economically sound—but organizational performance falls short.
A strategic change may be necessary when customer needs shift, competitive advantages erode, or the market cannot support profitable growth.
The distinction is critical: Execution problems require better performance. Strategic problems require different choices. Before changing direction, validate the assumptions, examine the numbers and determine whether the organization is aligned to deliver the strategy.
3. How can woodworking manufacturers improve their competitive advantage?
Woodworking manufacturers can strengthen their competitive advantage by identifying customer segments where their capabilities create meaningful differentiation.
Rather than competing solely on price, manufacturers should evaluate opportunities in customization, engineering expertise, delivery reliability, customer service and specialized markets.
or example, a domestic manufacturer competing against lower-cost overseas suppliers on standardized hotel projects may find greater opportunity in high-end boutique hospitality, where customization and responsiveness carry greater value.
The goal isn’t to compete everywhere. It’s to compete where your capabilities matter most—and where you can capture the value you create.
4. What financial metrics should CEOs use to validate a growth strategy?
CEOs should evaluate a focused set of financial and operational metrics that connect market opportunity to profitable growth.
Key measures include:
· Total addressable market (TAM): Is the market large enough to support our growth ambitions?
· Market share: What percentage of the available market must we capture to reach our targets?
· Revenue growth: Are we gaining traction in our chosen customer segments?
· Gross margin: Are we capturing sufficient value from the products and services we deliver?
· Production capacity and throughput: Can our operations support the planned growth?
· Win rates and profitability by segment: Are we pursuing the right customers and projects?
A simple spreadsheet connecting these variables can reveal whether growth targets are achievable before committing significant capital or resources. The numbers don’t need to be perfect. They need to be credible enough to expose assumptions, identify constraints and guide better decisions.
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.
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.
- Revenue released — what you’re billing for that work order
- Actual labor — what it actually cost you in hours and dollars
- 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.
By Marc Sanderson
Most companies use data to explain results. The best use it to change them.
High performers don’t just ask, “What happened?” They ask, “What’s coming next and what do we do about it? They use context, leading indicators and disciplined decisions create an edge.
When I ran a mid-size millwork company, I could look at one number at the first of the month and predict—with remarkable accuracy—where profitability would land at month end. If that number was running at 60-70 percent, I knew we were positioned to hit our target. If it dropped to 30 percent, we had work to do—and time to intervene, recalibrate and protect profitability before the month was lost. The ultimate indicator was percentage of work released to the shop floor.
It sounds simple, but early signals lead to better moves. That’s the advantage: not more data, but using it to outperform. Here how companies turn insight into a strategic weapon:
ADVANTAGE 1:
Compare to Compete
Think of a scoreboard: If your team scores three goals, is that good? You don’t know until you see the other side: Did the opponent score zero or four goals? Your team’s number doesn’t change, but the meaning does.
Business works in the same way. A 42 percent win rate, a $5-million backlog, or an average wage all sound informative—until you compare them. When grounded in industry benchmarks, your strategy, or your targets, they either signal strength or expose risk.
One company believed it was performing well until it benchmarked against peers using industry tools and surveys. The comparison revealed they were underprepared for a downturn and misaligned on pricing. That insight changed their decisions immediately.
Without context, data is noise. With it, data becomes direction. This is why INNERGY offers industry benchmark reporting on both financial and operational performance in real-time – for free. (You can check it out here).
Here’s a look at the three lenses of context most often applied in business:
| Lens | What It Answers | When to Use It | What It Tells You | Risk If Used Alone |
|---|---|---|---|---|
| Industry Benchmarks | How do we compare to others? |
|
Where you stand relative to the market | Can drive wrong decisions if your strategy is different |
| Company Targets (Internal Benchmarks) |
Are we improving? |
|
Whether you’re getting better and hitting your plan | Can create complacency if targets are too low |
| Strategy Alignment | Are we winning at the game we chose? |
|
Whether your model is working as intended | Can justify poor performance if not grounded in reality |
The real advantage is using them together:
• Start with industry to understand the baseline.
• Track against targets to drive ongoing improvement.
• Adjust for your strategic focus to ensure relevance.
Takeaway: Benchmark your top 3 metrics across industry, internal targets and your strategic focus—then change one decision this week based on what you learn.
ADVANTAGE 2:
Move Up the Maturity Curve
Organizations want to use data better, but what does that look like? That’s where the data maturity curve comes in. It’s a simple way to understand how organizations evolve in their use of data—from reporting what happened to actually shaping what happens next and the impact they can have.
At the initial level, companies track results. More advanced organizations diagnose why those results occurred. The best go further—predicting what’s likely to happen and prescribing what to do about it.
A shop floor team began using real-time data to monitor workflow across stations and quickly spotted a pattern—work orders were stacking at one point in the process. Instead of waiting for delays to show up in missed deadlines, they acted immediately. They reallocated labor to the bottleneck, adjusted upstream inputs and workflow before it became a problem. The result was clear: lead times dropped, throughput increased, and the team avoided the typical cycle of firefighting.
Most companies operate at stage 1 or 2, but the real advantage comes when they can reach stage 4:
Stage 1: Descriptive → What happened?
Stage 2: Diagnostic → Why did it happen?
Stage 3: Predictive → What will happen?
Stage 4: Prescriptive → What should we do?
Descriptive data explains the past. Prescriptive data drives the future.
Takeaway: Pick one recurring problem, trace it from “what happened” to “why,” then define one leading signal to monitor and one action to take before it happens again—and review it weekly.
ADVANTAGE 3:
Shift from Lagging to Leading Indicators
How much time are you spending looking at lagging vs. leading indicators? In business, we naturally gravitate to lagging indicators, like EBITDA and revenue. Yet, these show history that you can’t change. Competitive advantage comes from leading indicators that show whether they’re on track and where to intervene.
A common example:
Rework or margin loss (lagging) → Percentage of work released to shop floor (leading)
When used correctly, leading indicators enable organizations to fix problems before they happen—turning unpredictable results into controlled outcomes. This is the leading indicator that predicted our profitability each month and I know it is the case for others.
At INNERGY, we have distilled down the “Perfect Release” to three elements: complete information, materials ready and time needed for the shop execute. When I survey CEOs and ask what happens if all three are consistently met, 64% say profitability would more than double. This shows the power of leading indicators—they don’t just improve operations, they make EBITDA more predictable.
Here’s a look at the leading indicators INNERGY’s insights have identified as the closest thing to a silver bullet in our industry and why they matter:
- Engineering Completeness at Release → Rework percentage, labor overruns
Most downstream problems are rooted in the office and engineering is the choke point. Quality assurance becomes critical and allows you to prevent issues prior to fabrication. - Material Readiness Before Production → On-time delivery, downtime
Missing materials stop everything. This is one of the fastest ways to improve flow. - Time for the Shop to Complete → Lead time, throughput
This exposes bottlenecks early, before delays show up. It allows you to make sure the floor has the time needed to complete, in the midst of interruptions.
Start with these three and you will uncover leverage in the organization that you did not know existed.
As teams and organizations mature, they hone in on leading indicators more often and with greater depth. The result is that they can tell in the short-term—daily, weekly or monthly— what’s working and what needs attention.
Takeaway: Audit your dashboard this week—identify your top lagging metrics, then assign one leading indicator to each and start reviewing it daily with your team.
ADVANTAGE 4:
Make Data Your Identity
Culture is the multiplier. You can install systems to drive data, but high-performing organizations need to go further. They embed data into identity to make data a mindset and a part of the culture:
- Individuals know how they impact the bigger picture
- Teams understand how they’re performing
- Leaders act consistently on insights
Everyone needs to understand data and keep score so they can assess and improve. Without this, data becomes passive and decisions revert to instinct.
A mid-sized millwork company had the right systems in place, but results were inconsistent because data stayed in dashboards—not in daily decisions. They shifted to a simple mindset: everyone keeps score. Operators tracked labor vs. estimate, team leads reviewed performance daily, and leaders acted on issues in real time. Within months, labor overruns dropped, rework declined, and margins stabilized. The system didn’t change—the behavior did.
Takeaway: Make data everyone’s job—define the score, show the impact and act on it daily.
Time to Act
At scale, companies don’t compete on effort. They compete on clarity of information, speed of decision-making and alignment of execution. Data drives all three.
That leads to the ultimate truth: Two companies can have the same people, the same strategy and the same market. But the one with better data discipline will win. Not occasionally. Systematically.
Your 2026 IIBT Prep Checklist
The 2026 INNERGY Industry Benchmarking Tool is open, and the payoff is real: you’ll see exactly how your profit margins, labor costs, and business outlook compare to other shops across the industry.
The whole survey takes most people about 45 minutes, but only if you’ve got the right numbers in front of you before you start. Pull these together first and you’ll cruise right through it.
Section 1 — Your Company
The basics. Should take about two minutes.
✅ Company name, address, and contact info
✅ Your role
✅ Number of full-time employees (FTEs)
✅ Years in business
✅ Primary source of revenue
✅ Whether you’re an INNERGY ERP or Microvellum customer
Section 2 — Business Sentiment
No numbers here, just your honest read on the business. The CEO or owner answers a few dropdown questions about the past six months and the next six.
✅ Economic conditions
✅ Sales pipeline
✅ Cash flow
✅ Labor availability
Section 3 — Operations
A mix of numbers and quick selections. Pull these from your accounting system and estimating software:
✅ Bid win rate (by dollar value, past 12 months)
✅ Current backlog (contracted work not yet invoiced)
✅ Current AR and AP balances
✅ Total assets as of 12/31/25
✅ Total long-term debt
You’ll also answer a few quick questions about your software, what equipment you’re planning to buy, and where you want to improve in the next year. Dropdowns and checkboxes throughout.
Section 4 — Income Statement
This is the meatiest section. You need a full-year P&L from your accounting system. Here’s what to pull:
Revenue
✅ Plant-processed sales (casework, millwork, stairs, doors, panels, countertops)
✅ Non-plant sales (products you resell without touching on the floor)
✅ Installation sales
Direct Material
✅ Plant material cost
✅ Non-plant material cost
Labor — fully loaded (base pay + payroll taxes + benefits)
✅ Direct factory staff
✅ Installation wages (in-house and outsourced)
✅ Indirect factory staff (plant manager, purchasing, quality, maintenance)
✅ SG&A staff (CEO, estimators, sales, accounting, HR, admin, PMs, engineers)
Fixed Costs
✅ Other direct costs (bonding, insurance, sales tax, project general conditions)
✅ Overhead (rent, utilities, equipment leases, software, accounting fees, repairs)
Tip: The survey includes a position chart to help you sort each employee into the right bucket. If you don’t track benefits by department, just prorate your total benefits cost across the labor lines.
Section 5 — Workforce
Pull from payroll. For each role, you need headcount and average hourly rate:
✅ Estimator
✅ Engineer / Drafter
✅ Project Manager
✅ Machine Operator
✅ Journeyman / Custom Assembler
✅ Casegood Assembler / Production Worker
✅ Material Handler
✅ Finisher
✅ Installer
✅ Plant Manager / Foreman
You’ll also answer a few quick questions about turnover, what’s hardest to hire for, and what your team values most.
Tip: If payroll is outsourced, ask your provider for a headcount and average hourly wage report by role. If someone is salaried, divide their annual salary by 2,080 to get an hourly equivalent.
A few things worth knowing
This survey is administered by Inverra, an independent third party. INNERGY does not see your individual responses, only aggregated benchmark data. And everyone who completes the survey receives a $50 gift card from Inverra as a thank-you.
That’s the whole list. Once you’ve got these numbers gathered, the survey itself moves fast. And when results are published, you’ll have something most shop owners never get: a real, apples-to-apples look at how your business compares to the industry.
By: Marc Sanderson
Most companies treat data like exhaust—something left over after the real work. That is backwards. The best companies run on data and it’s the difference between scaling and stalling.
In the late ’90s, I bought a woodworking company with only four computers—not one on my desk. It didn’t prevent us from understanding our data. We mapped the entire business on whiteboards: every form, every handoff, every step—all connected with string. What looked simple turned into a web.
The breakthrough wasn’t technology. It was visibility.
We followed a single data point—like a customer name—and saw it touch everything. That’s when it clicked. We weren’t just looking at information. We were seeing how the business actually worked—and where it broke.
That one exercise changed how our company thought about data, how our team used it day to day and quickly improved our processes. The result? We did not just meet industry benchmarks. We used data to outperform them.
Here’s where companies go wrong—and how to fix it:
Step 1: Measure What Actually Drives Outcomes
Most leaders fall into the same trap: If data is valuable, more must be better. It’s not. I have learned this the hard way. Most companies today track too much—and trust too little.
The differentiator with data is not volume. It’s hierarchy. Recognizing the pecking order based on the DNA of your organization is essential to success.
Start with what directly drives profit:
- Revenue accuracy at the work order level
If what you sell doesn’t match what you build, nothing else matters. - Actual labor hours spent on that order
This is where margin lives or dies. - Cost of materials used on that order
This is the silent killer of profitability when unmanaged.
Forget budgets early on. Focus on actuals.
The lesson: Track a few key metrics that drive outcomes.
The Case: Cost of Tracking Everything
One company tracked a long list of data—machine utilization, micro-task timing and dozens of operational metrics peppered across the organization. They could measure multiple parts of the process, but they trusted nothing. Why?
- Data entry became inconsistent.
- Teams didn’t understand why they were collecting it.
- Leaders couldn’t connect it to decisions.
Then, they scaled back to a handful of critical metrics—and performance improved. Clarity beats complexity.
Step 2: Use Data to Drive Decisions, Not Reports
Data doesn’t create value. Decisions do. When looking at data at any level of an organization, the key question to ask is: What does this metric impact?
There are three layers at play in any given organization:
| Layer | Typical Company | High-Performing Company |
|---|---|---|
| Data | Collects | Curates |
| Insight | Reports | Interprets |
| Action | Delayed | Immediate |
The lesson: Data without action is useless.
The Case: Data-Rich, Action-Poor
A $40-million manufacturer had dashboards, reviews and an ERP system—yet margins slipped. The problem wasn’t access to information. It was action on the right data.
Then, they cut their metrics, focused on a few that mattered and pushed them to frontline teams. Teams reviewed daily and corrected issues mid-process, not after.
Within months, labor overruns dropped and margins stabilized. The shift was simple from reports to real-time decisions.
Step 3: Build Trust Through Discipline
Data integrity is rarely a systems problem. It’s a people problem. If team members do not understand why data matters, see how it’s used and trust leadership to act on it, then your data will degrade.
That’s why high-performers operationalize data:
- Operators input data daily
- Team leads review it daily
- Finance audits it weekly
This creates a feedback loop: Input → Review → Correction → Trust → Better Input
Break the loop and data decays.
The lesson: Audit data—or no one will trust it.
The Case: Reliability through Routine
A manufacturer invested in a new ERP system, expecting better visibility and control. Instead, leaders questioned every report. Numbers didn’t match what was happening on the floor, so teams defaulted back to gut decisions and spreadsheets.
The issue wasn’t the system—it was the lack of consistent auditing. Operators entered data inconsistently, supervisors reviewed it sporadically, and finance only checked it at month-end for their needs rather than for organization-wide, operational outcomes. Errors compounded and trust eroded.
Then, they implemented a simple discipline within the ERP system: daily input, daily review and weekly audits. Within a short time, discrepancies dropped and confidence in the data improved. Once leaders trusted the numbers, they started using them—and decisions got faster and better.
From Data to Control
Data is not a support function. It is the operating system of the business. When done right, it allows you to:
- Spot problems early
- Allocate resources precisely
- Eliminate hidden inefficiencies
- Scale without losing control
Without data discipline, growth breeds breakdown—more complexity, more noise, more bad decisions.
You can start taking steps today to build control—and see what I’ve seen with so many across the woodworking industry: faster execution, tighter control and more predictable performance.
What Comes Next
Control is only the beginning. At INNERGY, we’ve found the real advantage comes with tackling the harder question: Are you using data to actually outperform? Because the difference between average and elite isn’t better dashboards. It’s knowing what your numbers mean, what’s coming next and acting before everyone else does. In the next article, I will breakdown how to turn insights into 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.
What is the IIBT (INNERGY Industry Benchmark Tool) and Why You Should Participate
At INNERGY, we believe that numbers tell a story —but only when you know what to compare them to. In today’s competitive landscape, running a woodworking business without good data is like driving blindfolded. You might get somewhere-but chances are, you won’t like where you end up.
For years, I’ve relied on benchmarking data to help guide business decisions—whether it was to measure productivity, evaluate our margins, or understand if we were investing in the right areas. With data, you have a roadmap.
That’s why we created the INNERGY Industry Benchmark Tool (IIBT)—a free, anonymous benchmarking survey built for woodworking businesses in the US, Canada, Australia, and New Zealand.
If you’re wondering whether it’s worth your time, let me be clear: this is one of the most valuable tools you’ll use all year.
Why Benchmarking Matters
When you look at your backlog, your labor costs, your revenue per employee—what are you comparing them to? Most companies guess. The IIBT removes the guesswork.
The IIBT is INNERGY’s benchmarking tool capturing essential business performance metrics across operations, financials, workforce and sentiment and giving you something every leader needs: perspective. In short: it gives you context. And once you have that, you can start driving meaningful, focused improvement.
We’re offering a snapshot of the industry that breaks down key performance data across geographies, company sizes, and business types—so you can finally answer questions like:
- Is our profitability above or below average?
- Are we paying our team competitively?
- How do our operations stack up against peers in our region?
- What’s the average backlog or AR across the industry?
What’s In It for You
You won’t get fluff or generic “industry insights.” The IIBT is focused on real, actionable data, including:
- Wage and compensation benchmarks
- Bid success rates and backlog analytics
- Income statement breakdowns (including margin and EBITDA)
- Turnover trends and staffing ratios
- Sentiment around cash flow, labor, and sales pipeline
- Peer comparisons by region, company size, and market (e.g. commercial vs. residential)
I’ve used this kind of data for 20+ years to drive continuous improvement—and we want to make it accessible to every shop in our industry.
Fast, Free, and Anonymous
Here’s what you need to know:
- It’s completely free.
- It’s 100% anonymous. INNERGY never sees your individual submission.
- It takes less than 45 minutes. If it takes longer, you’re doing the wrong survey.
- You do NOT have to be an INNERGY customer to participate!
We partnered with Inverra, the same trusted firm behind the AWI’s benchmarking study, to make this fast and frictionless.
How to Participate
- Download the Excel survey at https://offer.innergy.com/2026iibt
- Submit your completed survey to iibt@inverra.com
- Deadline: May 1, 2026
Note: You’ll need a Windows machine this year. We kept it simple and spreadsheet-based for speed—but we’ll be going online in the future.
Final Thought
If you’re serious about improving your business, you need to know how you stack up. The IIBT is your chance to get honest, regional, and relevant benchmarks—so you can make sharper decisions with confidence.
As always, thank you for being part of this community. I hope you’ll join us in shaping the future of this industry—together.
Marc Sanderson
CEO, INNERGY