Why founders misread their own balance sheet

Oksana D — Fri, 13 Nov 2026 15:57:59 +0000

Most founders can quote their revenue to the dollar. Very few can actually say what their company is worth. Their wealth is generally in a few places: the company itself, the real estate associated with it, their retirement accounts and insurance (which they bought years ago for some reason they can't now recall).

That concentration makes it easy to overlook value. Some of it is embedded in the business itself (buyers will pay for things the owner would consider entirely routine). Some of it is in personal assets which are simply stashed away rather than actively managed. Both of those value categories tend to come to light at the same time, which is when the owner begins to think about an exit.

What buyers see that owners don't

Austin Hartley, Managing Partner at Parkland Capital Partners, a Dallas based M&A advisory firm working with privately held companies, says the business itself often has value that the founder has ceased to see.

Founders will value their company on last year's profit and nothing else. Buyers will look further. Recurring contracts, a team that can run the business day to day without the founder, clean financials, documented processes and long-standing customer relationships all affect what a private equity firm or a strategic buyer will pay. Many owners will just treat those as the normal cost of doing business and so they don't factor them into their own valuation at all. The gap between what the founder thinks the company is worth and what a properly run, competitive sale process can actually achieve is invariably in those very things. The time to go out and find those and document them is a year or two prior to a sale, not during due diligence.

The policy in the drawer

Outside the company one of the most underappreciated assets is life insurance. Founders will often take out policies to fund a buy-sell, to cover a key person or to protect a family as the business is still in its infancy. Jay Jackson, Chairman and CEO of Abacus Global Management (NYSE: ABX), says those policies are rarely looked at again once the original reason for having them has gone.

A life insurance policy is a financial asset but most people treat it as a liability. If you're selling the policy or your circumstances have changed in some way then the cover may no longer be relevant and the normal thing to do is just to let it lapse or surrender it to the insurer. There's a third option though. In the secondary life insurance market the policy can be valued and sold and the value is to do with the individual rather than the average. At Abacus we've spent over 20 years building up mortality and medical records data to price that exact thing. Before you allow a policy to lapse you should know what it's actually worth.

A short inventory before any exit

Neither of the sources suggests an owner can do that on their own. The common thread is the same habit: list everything first, then make your decision.

Inside the business: recurring contracts, customer tenure, management depth, documented processes and the financials that a buyer can verify.
Real estate and equipment: property which the company uses but which is held personally by the owner and whether it is part of the deal.
Insurance: buy-sell, key person and personal policies. What each one was purchased for and whether that purpose still exists.
Retirement and other accounts: how they fit in with the proceeds of the sale.

The review is cheap and has a real effect on what an owner brings to the table. A founder who understands what they actually have will make better decisions about when to sell, what to keep and what to let go.

This article is for general information and is not investment, tax or legal advice.

Beyond Automation: How AI Is Creating New Opportunities in Technical Industries

Oksana D — Fri, 13 Nov 2026 15:12:41 +0000

Most of the discussion around AI and jobs has been about office work: writing, coding, customer service, data entry. The technical trades are either cited as the 'safe' exception or as the next frontier for automation depending on who you ask. Neither of those is what's actually happening on the job sites.

In plumbing, roofing and engineering the AI is moving into the planning, the diagnostic and the paperwork aspects of the work. The actual work still gets done in the crawlspaces, on the roofs and along the riverbanks. The result to date is not fewer skilled tradespeople. It's a redefinition of what 'skilled' means and it's opened up a whole new space for people who can bring their practical judgement to bear in conjunction with better tools.

Where AI is actually showing up

The adoption pattern is pretty much the same across all the trades. AI tends to go in first where there's a lot of visual and/or textual information to wade through:

Design and engineering: generating and comparing design options, running load scenarios and the associated documentation that all of that requires.
Inspection and diagnostics: drone imagery of the roofs, camera footage down the sewer lines and software that will flag up the likely problems for the technician to look at.
Operations: scheduling, routing the crews, drawing up the estimates and dealing with the normal run of customer queries.

What they all have in common is that they accelerate the work on the physical job. None of them in any way replaces the person who has to go through the software's flags, make the call and do the actual repair.

Engineering: faster desk work, same site judgment

Engineering is frequently cited as the domain where AI will have the most impact, as so much of it is screen based. In the world of custom construction though the screen is only half the story. Every site has its own soil, its own water, its own access and its own environmental constraints and it's those that dictate how the building is actually going to be constructed.

People think engineering is the bit of construction that AI will be first to take over and some of that will go faster. In my 15 years at YBC (including my time running the field ops) I've learned that no two bridge sites are the same. A crossing through a wetland, a golf course creek and a trail over a ravine all have different soils, different water levels and different wildlife to protect. The decision of how to build there with as little impact as possible and the choice of timber that will last for 50 years etc. that's the bit that takes people who have actually been on that bank. If AI is doing all the desk work then it's going to free up time for the bit that the client actually pays us to do; getting it right on site.

Brian Kennedy, Head of Bridge Consultancy at York Bridge Concepts (YBC)

Plumbing: better diagnostics, same 2 a.m. emergency

Plumbing have been using diagnostic tech for years and AI is just making that tech work faster at interpreting what it sees. The decision to repair and the actual repair is still the technician's.

In drain work the technology has already changed the way we find problems. We've got sewer cameras now which will show you the inside of the line and the software is getting better and better at flagging roots, cracks and build up in that footage. That's obviously useful. A flagged image doesn't however clear a line that's backed up at 2 a.m. and it doesn't tell you whether a pipe is suitable for a CIPP lining or not. Those calls come from years of experience on the homes and the soil conditions around here. The place where I see AI being most useful is in the conversation with the customer. With clearer footage and clearer explanations you can actually go in and show the customer what's going on and how they can prevent it next time rather than just selling them a quick fix.

Walter Nance, Owner of Discount Drain Cleaning LV

Roofing: sharper photos, same need for an honest call

Roofing is probably the clearest example of AI improving the documentation process without actually replacing the inspection. Aerial imagery can cover a roof in a very short space of time but storm damage is often only visible (or only verifiable) up close. Given that so much of the roofing work will be going through an insurance claim, someone has to be there to validate what's been recorded.

From the driveway the roof under hail will typically look okay. Drones and AI image analysis tools are getting better at identifying likely damage from above and will speed up the post-storm inspection process in DFW. The bruising in the mat and the soft spots you find with your thumb still require someone to be on the roof and a claim needs to be backed by a person who's made the call. After 30 years of working roofs in Rockwall and Rowlett that's the one thing I would never delegate to software. The honest call to a homeowner that there simply isn't enough damage to warrant a claim. The technology can make the photos better, it can't make the recommendation credible.

John Bacon, President at Bacon Roofing

The new opportunities

Taken together, these perspectives highlight where new opportunities are emerging:

Hybrid skill sets are increasingly valuable.
For example, a technician who can analyze camera footage, interpret flagged images, and communicate findings to customers is more valuable than one with only a single skill. The same applies to estimators and project managers who can use AI-assisted design and documentation tools.

Inspection and documentation are becoming specialized roles.
As imagery becomes less expensive to collect, value shifts to those who verify, contextualize, and stand behind the information, whether for insurance adjusters, permitting offices, or clients. to the work that needs judgment. When scheduling, paperwork and first-pass analysis take less time, experienced people spend more of their day on site decisions, complex repairs and client conversations. Those are the parts of the job that are hardest to automate and the ones customers value most.

Trust remains a human asset.
Licensing, liability, and accountability continue to rest with individuals and companies, not software. In trades where customers grant access to their homes, roofs, or land, reputation built over years is still the deciding factor. AI can enhance transparency and support that reputation, but it cannot establish it.

Beyond automation

For technical industries, the question is not whether AI will replace jobs, but which tasks it will accelerate and how skilled professionals will use the additional time and information. For plumbers, roofers, and engineers, the answer is clear: tools are becoming smarter, but judgment, expertise, and accountability remain essential.

DEV Community: Oksana D