The True Cost of a Bad Engineering Hire: SEK 1.8M. Here's Every Line.

Most companies count salary when they think about the cost of a bad hire. Some add the recruitment fee. Almost none add the full picture: the management time invested in trying to make it work, the team productivity lost, the deferred roadmap, the rehiring cost, and the ramp-up for the replacement. When you add it all up for a senior data engineer in Stockholm, you reach SEK 1.8M. Here is every line of that calculation.

The Full Cost Breakdown

The SEK 1.8M figure is a midpoint across six categories. Each category has a range. The ranges reflect real variation in outcomes: how long the mis-hire lasted, how contentious the exit was, how long the role sat vacant before being filled, and how long the replacement took to reach full productivity.

The Category Most Companies Forget: Lost Productivity

Salary and recruitment fees are visible in financial systems. Lost productivity is not, which is why it's almost never counted. When a mis-hire is in a role, several things happen simultaneously: the person is producing at below-expected output (we assume 40–60% of the productivity a successful hire would deliver); other team members spend time managing, compensating for, or repairing their work; and the engineering lead or CTO invests management time — typically 3–5 hours per week during the performance management phase — that could have been spent on strategic work.

At SEK 70K/month for the mis-hire and an employment period of four months, the direct salary cost is SEK 280K. But if two other engineers are absorbing 20% of their capacity covering the gap, that's an additional SEK 112K in diverted capacity. And if the engineering lead spends four hours per week on performance management for four months, at an imputed rate of SEK 1,000/hour, that's SEK 64K in senior management time. Add those together and the "4 months of salary" line becomes SEK 456K before we've touched recruitment or severance.

"The line item every CTO misses is team morale tax. When you're managing someone out, the rest of the team knows it's happening. Velocity drops. People start updating CVs. It's not in a spreadsheet, but it's real — and it usually costs more than the legal fees." — Aashijith, Head of Engineering, Indpro AB

The Rehiring Cycle: Where the Cost Doubles

After a mis-hire exits, most companies make the same mistake: they repost the same job description. The job description that produced the wrong hire. In a market with 187 days average time-to-hire, starting over means another four to six months of vacancy. The second recruitment cycle incurs comparable fees to the first (SEK 150K–280K for agency or internal HR), and the role is now harder to fill — candidates who passed on the first posting saw the quick exit and factor that into their perception of the company.

Some companies accelerate the second cycle by broadening the criteria — accepting more risk to fill the seat faster. That increases the probability of a third cycle. The compounding nature of mis-hire cost is why the range goes up to SEK 2.4M: a company that makes a fast, desperate second hire after a first mis-hire, and that hire also exits, is looking at a number well above the midpoint.

The Ramp-Up Cost That Extends Beyond Start Date

A new senior data engineer in Stockholm doesn't reach full productivity on day one. The realistic ramp-up to full output is eight to twelve weeks. During that period, they are producing at roughly 50–70% of their eventual output while consuming 20–30% of a senior colleague's time for onboarding, code review, and context transfer. For a SEK 70K/month engineer, eight weeks of partial output and onboarding overhead costs approximately SEK 200K–350K — this is a real cost that accrues even from a successful hire. It's included in the SEK 1.8M because it's part of the cost cycle that a mis-hire resets.

How to Calculate Your Own Exposure

The SEK 1.8M figure is a midpoint for a senior data engineering role in Stockholm. It will be different for your situation based on seniority, salary level, employment duration, and the specifics of the exit. Here's a simplified model you can run:

Input	Your Number	Multiplier	Cost Line
Monthly salary + employer costs (SEK)	e.g. 95,000	× months employed	Salary cost
Recruitment fee (% of annual salary)	e.g. 20%	× annual salary	Recruitment cost
Team size covering the gap	e.g. 2	× 15% of monthly salary × months	Coverage cost
Management hours/week × weeks	e.g. 4h × 16wks	× SEK 1,000/hr	Management cost
Second recruitment fee	Same as above	—	Rehire cost
Replacement ramp-up weeks	e.g. 10 weeks	× 40% of monthly salary	Ramp-up cost

Most CTOs who run this model reach a number that surprises them. The typical response: "I knew it was expensive. I didn't know it was that expensive." The model is available as a spreadsheet — ask us and we'll send it over.

Frequently Asked Questions

Is SEK 1.8M based on published research or Indpro's own data?

It's built from Indpro's client data (conversations with 30+ CTOs about their actual hiring costs), published benchmarks for Swedish employment costs, and recruitment fee market rates from Stockholm staffing agencies. Each component of the model has a source. It's not a generic "1–2× annual salary" rule of thumb — it's a line-by-line build.

Does this apply to mid-level engineers as well as senior?

The number scales with salary and seniority. For a mid-level engineer at SEK 55K/month, the equivalent midpoint is approximately SEK 1.2M — lower on salary and recruitment fees, but the same structure of lost productivity, management time, and ramp-up costs applies. The percentage of annual salary (the "multiplier" approach) usually underestimates because it doesn't capture the rehiring cycle.

What defines a "bad hire" in this model?

A bad hire is defined as an engineering hire who exits — voluntarily or involuntarily — within 12 months of starting, and where the exit was due to poor fit (skills, culture, or performance) rather than external circumstances. The model doesn't count voluntary exits for clear career-advancement reasons — those are a different risk category.