Bingo Consulting
You run Bingo Consulting, a mid-sized energy auditing firm with 45 employees. Twenty-two of them are engineers - the best you've ever hired. The rest handle project management, data analysis, and admin work. You've built something solid here, a team you trust completely.

It's Friday morning when the call comes in.

"I'm looking for your Managing Director," the voice says. "This is Peter from Metallurgy."

Your posture straightens immediately. Metallurgy. The country's largest steel manufacturer. Over 50 facilities nationwide. £185 million in annual energy costs. This is the kind of client that can define a year.

"This is Johanssen," you say, adjusting your tone. "I'm the Managing Director. How can I help?"

Peter gets straight to it. They want a comprehensive energy audit across all their facilities. You walk him through your process, your team's expertise, how you've handled similar projects. 

Twenty minutes later, you've got a verbal agreement. Contract details to follow by email. Work starts Monday.

You cancel your afternoon and call an emergency planning meeting. By 3 PM, your team is assembled. You assign six engineers to the project - your strongest people.

The contract is worth £850,000. If you deliver well, this could open doors to their entire industry network.

Everyone leaves energized. This is what you built the company for.

Your advanced team of four arrives at Metallurgy's headquarters at 8 AM. They're meeting with Serah, the Energy Manager, who's been with the company for 15 years.

She walks them to a conference room. On the table: 14 cardboard boxes.

"This is everything we could pull together," Serah says. "Utility bills, equipment logs, maintenance records. Some of it is digital, most of it is... well, you'll see."

Your lead engineer, Marcus, opens the first box. Inside are utility bills - hundreds of them, organized by facility but in no particular order. Some are printed PDFs. Others are actual paper bills from the utility company. A few are photocopies of photocopies, the text barely legible.

"We've got 47 facilities," Serah explains. "Each one has multiple meters - electricity, gas, sometimes more than one account per site. Different utility companies, different formats. We've been meaning to digitize everything but..." She trails off with a shrug.

Marcus does quick math in his head. Forty-seven facilities. Twelve months of bills. Multiple meters per site. He's looking at close to 900 electricity bills alone. Then there's gas.

"What about equipment data?" asks Jennifer, one of the other engineers.

Serah pulls out a USB drive. "We've got spreadsheets. Fifteen files, I think. Each facility manager keeps their own records - motors, compressors, furnaces, all the major equipment. The formats are... different."

"Different how?"

"Different column names, different units, some in metric, some not. We've tried to standardize but it never quite stuck."

Jennifer takes the USB drive. She already knows what she's going to find.

Back at the office, the team divides the work. Marcus takes the utility bills. Jennifer handles equipment data. Two other engineers, David and Priya, split the production records and historical audit reports.

Marcus starts with electricity bills from Metallurgy's largest site - an integrated steel mill that consumes 1.8 TWh per year. He opens the first bill. It's a PDF from Northern Power Company. He needs to extract the:

• Account number
• Meter ID
• Billing period
• Total consumption (kWh)
• Peak demand (kW)
• Total cost
• Tariff breakdown

The PDF is scanned, so he can't copy-paste the text. He types each field manually into the Excel template. Twelve minutes later, he's done with one bill. He has 11 more months for this meter. And this site has six meters.

He looks at the stack of bills on his desk. This is going to take a while.

Across the room, Jennifer is wrestling with the equipment spreadsheets. She opens the first file: "Site_03_Motors_2025.xlsx"

The columns read: Equipment_ID | Type | HP | Efficiency | Hrs/Day | Notes

She opens the second file: "Facility_12_Equipment.xlsx"

The columns read: Asset# | Description | Power(kW) | Daily_Runtime | Status | Comments

Same data, completely different structure. She's going to have to manually reformat everything into a master spreadsheet. She counts 1,847 pieces of equipment across all the files.

At 8 to 10 minutes per entry - checking for duplicates, converting units, standardizing names - she's looking at 250 hours of work. Just for the equipment database.

By the end of week two, you notice something's off. You stop by the project room to check in.

All six engineers are at their desks, headphones on, staring at spreadsheets. No one's talking. No one's sketching ideas on the whiteboard. No one's reviewing technical drawings or running energy models.

They're just... typing.

You pull Marcus aside. "How's it going?"

He exhales slowly. "We're making progress on the data. But it's slow. Really slow."

"What's the holdup?"

"The utility bills are a mess. Seven different utility companies, seven different formats. Some bills have the data in tables, some have it in paragraphs. A bunch of them are scanned images, so I have to type everything manually. I've done about 340 bills. I've got 550 to go."

"How long per bill?"

"Twelve to fifteen minutes. Depends on how clear the scan is."

You do the math. Five hundred fifty bills at fifteen minutes each. That's 137 hours. Just for one person. Just for utility bills.

"What about the others?"

Marcus glances back at the team. "Jennifer's been reformatting equipment data for a week and a half. David's trying to pull production data from their SAP system, but the exports are formatted weird - dates are inconsistent, units keep changing. Priya's re-entering data from their 2020 audit report because it's a 450-page PDF and half the tables are images, not text."

You feel something tighten in your chest.

"When do you think you'll start the actual analysis?"

Marcus looks at his screen, then back at you. "Honestly? Another month. Maybe five weeks. We need clean data before we can do anything useful."

A month in, you sit down with your project manager to review the budget.

You allocated 3,200 hours for this project. So far, the team has logged 1,100 hours. Of those, 715 hours, 65% of the time, has been spent on data entry and data cleaning.

At your blended labor rate of £50 per hour, that's £35,750 in costs. For work that has produced exactly zero insights, zero recommendations, zero value for the client.

Your engineers - people with master's degrees in mechanical and electrical engineering, people you're paying £55,000 to £75,000 per year - have spent the last month doing work that a high school graduate could do with an hour of training.

Worse, you can see it wearing on them. Jennifer used to be the first one in the office every morning, excited to tackle complex problems. Now she drags in at 9:15, puts her headphones on, and zones out in Excel for eight hours.

David asked to be moved to a different project last week. You convinced him to stay, but barely.

This isn't what they signed up for. It's not what you built this company for.

Two months into the project, you finally have clean data. The team can start the real work - building energy models, identifying inefficiencies, calculating ROI on potential upgrades.

But you're already behind schedule. The client expected a preliminary report by now. You've had to push deadlines back twice.

And your profit margin? You projected 28% on this project. You're now tracking at 12%. If anything else goes wrong, you'll barely break even on the biggest contract you've ever landed.

You sit in your office late one night, staring at the project timeline on your screen.

Fourteen hundred hours. That's how much time your team spent on manual data entry. Fourteen hundred hours of engineering talent, reduced to copying and pasting.

If you'd known, you would have hired temps. You would have outsourced it. You would have done anything except waste your best people on work that a computer should have done in minutes.

But you didn't know. And now you're here.

Here's the thing: Bingo Consulting isn't unique. This story plays out in engineering firms every single day.

Energy audits. Construction projects. Environmental assessments. Manufacturing optimization. It doesn't matter the industry - if your engineers are working with data from multiple sources, they're spending a massive chunk of their time on manual data entry.

And most firms have no idea it's happening.

Why? Because it's invisible. It doesn't show up as a line item in your budget. Your engineers don't complain because they think it's just part of the job. And by the time you realize how much time has been wasted, the project is already underwater.

The numbers are staggering:

• Studies show engineers spend 30-50% of their time on data collection and entry

• For a mid-sized firm with 20 engineers at an average salary of £65,000, that's £390,000 to £650,000 per year in wasted labor costs

• That's not counting opportunity cost - the projects you can't take on, the innovations you can't pursue, the clients you can't serve

But the financial cost is only part of it.

Talk to any engineer about data entry and you'll see their face change. It's boring, it's demoralizing.

They didn't spend four years studying thermodynamics and fluid mechanics to type numbers into spreadsheets. They didn't get into engineering to be glorified data entry clerks.

And when you waste their talent on mindless work, they notice. They disengage. They start looking for other jobs.

You will lose your best talent because "I wasn't doing engineering work anymore" - exit interviews will reveal.

Replacing them will cost you £45,000 in recruitment fees and lost productivity. And the new hires? They will walk into the same data entry trap.

So why do engineering firms keep falling into this trap?

Most clients have decades of records scattered across filing cabinets, hard drives, and legacy systems. They assume you'll "figure it out." And you do - by brute force.

Data entry happens quietly at individual desks. There's no dramatic moment where you realize it's a problem. It just slowly drains resources until a project is over budget.

Many firms treat manual data entry as an unavoidable cost of doing business. It's just how things work. Except it doesn't have to be.

Engineers know automation exists. But between project deadlines and client demands, there's never time to implement it. So they keep doing it manually, promising themselves they'll fix it "next time."

Spoiler: next time never comes.

The Metallurgy project eventually finishes - five weeks late, with a final margin of 11%. The client is satisfied with the findings (£28 million in identified savings), but their satisfaction score is 6.5 out of 10. They cite "slow turnaround" and "communication delays."

You know the real problem. Your team spent so much time on data entry that they'd barely had time to communicate with the client, refine their models, or deliver the level of insight they were capable of.

The project that was supposed to be a showcase becomes a cautionary tale.

But here's the good news: it doesn't have to be this way.

The technology to automate data extraction, cleaning, and entry exists right now. And Kawibot is at the forefront, tackling this problem for you.

We have an end-to-end data extraction pipeline - Marcus and team would have just had to upload all the Metallurgy files once, and let Kawibot handle the rest. We would extract and digitize all the data in, literally a day's work for an audit of that size.

They can edit the data and eventually export to excel or other formats.

We have scripts to standardize spreadsheet formats and are working on APIs that can pull data directly from utility company portals.

The firms that figure this out - that invest in automation and free their engineers to do actual engineering, are the ones that will dominate the next decade.

The firms that don't? They'll keep burning money and talent on data entry, wondering why they can't compete.

So here's the question for you:

If you don't know the answer, you need to find out. Because every hour they spend typing is an hour of problem-solving, innovation, and value creation you're losing forever.

And unlike Johanssen, you still have time to fix it.