01
Workaround payroll.
The hours your business units burn working around data products that do not fit how they operate. I call it FTE Debt. It appears on no cloud invoice, yet it consumes real salaries every week.
You review every budget line. Except this one.
Your data budget has a payroll problem, not a technology problem.
Lior Barak is an author and strategic advisor specializing in Data Capital Allocation, helping CEOs and CFOs treat data spend as auditable capital.
The hours your business teams spend compensating for data they can't rely on are a real payroll cost, even though they appear on no technology invoice. I help CEOs and CFOs price those hours against payroll and decide what to keep, fix, and retire.
Numbers your CFO can audit. A method your team runs independently after I leave.
2 min · who this is forLior Barak
140 hours per week
of senior workforce capacity found vanishing into manual data workarounds in one portfolio
250 data products
audited and trimmed to 48 core capabilities in another
€145,000
in annual carrying costs recovered
From client engagements. Anonymized. Measured against the client's own payroll rates and cloud bills.
The unvoiced margin leak
Every data product your company ever shipped is still on the payroll.
Compute bills, storage maintenance, engineering support hours, and frontline workarounds: every product your company ever deployed keeps costing something. The ones nobody looks at anymore do not stop billing you. They just stop appearing in active conversations.
This is the Data Zombie Tax: dead products quietly eating budget, live products costing far more than they return, and a core team too busy keeping legacy pipelines alive to build what should actually replace them. It compounds silently, which is why it is rarely named during a budget review.
The tax arrives through three doors:
02
Carrying weight.
The full cost of keeping every data asset alive: infrastructure, incidents, and the engineering hours lost to maintenance, whether the asset moves margins or not.
03
Decisions that wait.
The data exists, but a strategic decision waits days while someone validates the number by hand. Waiting has a payroll cost and a market cost. Neither appears on any invoice.
The calculator below gives you the first rough number for what you're paying.
None of this shows up as a line item. Here is roughly what it is costing you.
Three inputs. Adjust to your situation. Most leaders have never had this number before.
People touching data
Anyone in the business who builds, uses, fixes, or waits for data. Not just the data team.
30
Time lost to friction
Share of their time spent fixing, waiting, reconciling, or working around data rather than using it.
35%
Avg annual cost per person
Fully loaded: salary, benefits, employer taxes, tools. Not just gross salary.
€85k
~10.5 FTEs
locked in friction every month
€893k
estimated annual cost of wasted capacity
Directional estimate. We measure yours precisely in the first engagement.
The true run rate of data friction.
In a high-growth environment scaling from 15 to 90 employees, an organization expanded its data capability to fuel a new AI roadmap, bringing the total annual department budget to €1.2 Million across tools and salaries.
- The Structural Gap: Because data products were built based on request volumes rather than business-validated yields, the organizational infrastructure became flooded with unverified data models.
- The Leakage: A portfolio audit isolated 140 hours per week of senior workforce capacity vanishing into manual workarounds and shadow validation checks, including the CFO independently reconstructing financial metrics via raw banking transcripts.
- The Operational Load: Despite investing heavily in automated observability tools, 80% of the engineering team's incoming support volume was driven entirely by business trust issues rather than server downtime. The alerts were simply not translated into the language of the financial margin.
Built data functions from the inside at
Zalandoidealo
Author of What Data Really CostsData portfolios are corporate capital. It is time they are managed like it.
You run capital allocation conversations every week: with product, with marketing, with sales. Each one starts with what a bet returns and what it costs to maintain. Then the data budget arrives, and the conversation shifts to uptime, pipelines, and tooling vendors.
The fix is a flipped sequence: value first, team capability second, technology last. The conversation about tooling does not disappear; it gets easier, because by the time it happens, everyone knows exactly what the work is for.
Value first: what decision does this serve and what is it worth.
Capability second: can we actually capture it.
Technology last: the shortest conversation of the three.
You don't need to speak engineering to lead this. You need the correct sequence.
See how the method works →Start here
The Data Cost Baseline
Three weeks · €12,000 fixed50% to start, 50% at the readout.
Most companies can tell you what their data team costs. Almost none can tell you what it costs them to run data. In three weeks you get that number, and the list of what to stop.
What’s included:
- →The baseline: total annual cost of running data, split into three layers: infrastructure, the hours absorbed across the business preparing and reconciling data, and the carrying cost of everything already built
- →Cost per product for the top 20 items in the portfolio
- →A ranked keep / kill list with the annual recovery attached to each candidate
- →The template and method, so the team can rebuild the number next quarter without me
- →A 60-minute readout with the CFO and the data lead in the same room
What you provide:
Access to six to eight people for 45 minutes each, cloud and tooling invoices, and a headcount list.
Where is your data portfolio today?Building or Migrating Running and Tracking Institutional Transformation
Three ways in.
Each product ends with your team running the instruments. Not me. Not sure which one fits? 30 minutes. No slides. Bring the number you can't explain.
The Prevention Blueprint
You are about to commit capital to an infrastructure migration, a stack overhaul, or an AI-agent rollout. Before your engineers write a single line of code, we install the financial rules that govern what earns a place in the new architecture.
+ Explore the program →1-Month Rule Foundation + Ongoing Strategic Steering Cycles · CEO + CFO
What stays when we are done:
- →A clear financial bar every data product must pass before it enters the new stack.
- →Keep-or-kill decisions governed by structural rules, not political capital.
- →An honest assessment of what your team can carry before you add technical weight.
The Hidden Cost Recovery
Your data budget grows every quarter, yet frontline teams are still fixing numbers by hand in spreadsheets. Those manual hours run on your payroll. I locate them, calculate them, and isolate the exact leakage.
+ Explore the program →4-Week Capital Diagnostic + Multi-Month Capacity Verification · CEO + CFO
What stays when we are done:
- →A precise euro figure for the hours your business teams spend compensating for data gaps.
- →A monthly operational review your own people keep running after the engagement ends.
- →An actionable roadmap with the first three months fully mapped for your team to execute.
The Data Capital Program
Your data lead reports in sprint velocity and engineering metrics. Your CFO tracks margin contribution and capital efficiency. Neither can make an allocation decision together. This program installs a single, unified financial language.
+ Explore the program →6 to 8-Month Embedded Integration · Executive Board
What stays when we are done:
- →One set of numbers connecting boardroom strategy directly to weekly engineering tasks.
- →A live view of what every data asset costs to carry against its explicit business return.
- →Structured validation cycles that test value before major engineering capital is deployed.
Not sure which one fits?
30 minutes. No slides. No sales pitch.
Bring the portion of your data spend you cannot explain. We will decide together which product fits your situation, or whether the timing isn't right.
Book an alignment call
Founder statement
"Most data functions were never asked the one question that decides everything else: what should we stop paying for? Engineering was hired to build. Finance was hired to total the bill. Nobody was hired to sit in between and ask what's actually earning its keep."
Fifteen years running data teams inside scaled organizations like Zalando and idealo, and the same gap kept showing up: engineering owns delivery, finance owns the total, and the space in between, where each product either earns its keep or quietly stops, belonged to no one.
Impact Operations is what I built to close it: a method that gives the CEO and CFO the numbers and the rhythm to run data as the capital investment it already is. I sit in your boardroom until your team runs it without me.
The Reality Check
See what the workarounds cost you.
Answer a few questions about how your teams handle numbers today. You get a figure in payroll terms, the hours behind it, and one sentence you can say in your next leadership meeting.
About 4 minutesNo email needed to see your numberAnonymous
Start the Reality Check →Would rather just talk? or message me on LinkedIn.