I Interviewed 50 Ops Leaders. Here's What They Told Me.

"I'm not drowning in work. I'm drowning in tabs."

That quote came from a Director of Operations at a 200-person SaaS company. She said it casually, almost as a joke. But no one in the room laughed.

Over the past three months, I sat down with 50 Ops leaders across B2B SaaS companies ranging from 30-person startups to 500-person growth-stage firms. The goal was simple: understand how Ops teams actually spend their time, what makes the job painful, and what they wish the rest of their company understood.

The answers surprised me. Not because the problems were unfamiliar, but because of how universal they were. Regardless of company size, industry vertical, or team structure, these leaders described the same friction. The same exhaustion. The same invisible tax on their productivity.

Here's what the data says.

The Numbers That Should Worry Every CEO

Let's start with the headline findings.

67% of Ops time is spent context-switching. Not answering questions. Not solving problems. Not doing the work their title describes. Two-thirds of their day is spent hunting for information across disconnected tools, switching between browser tabs, and reconstructing context that should be at their fingertips.

The average Ops professional checks 5.3 tools per request. A single Slack message asking "What's the renewal status for Acme Corp?" triggers a workflow that touches Salesforce, HubSpot, the billing dashboard, a shared Google Sheet, and Slack DMs with the account manager. Five tools. One answer.

200+ internal requests per week. That's the median across our sample. For Ops teams at companies above 200 employees, the number climbs past 300.

15+ minutes per response. Not because the answer is complex. Because finding the answer requires a scavenger hunt across your entire tech stack.

Do the math. If your Ops team handles 200 requests per week at 15 minutes each, that's 50 hours of labor. Per week. Just responding to internal questions.

"Quick Question" Is the Most Expensive Phrase in Your Company

When I asked Ops leaders to name their most dreaded type of request, the answer was nearly unanimous.

"Can I ask you a quick question about [customer X]?"

This phrase, sent via Slack at 2:47 PM on a Tuesday, is the single most expensive sentence in B2B SaaS. Here's why.

There is no such thing as a quick question in Operations. Every "quick question" requires context. Context lives in tools. Tools require logins, searches, cross-references, and interpretation. The person asking the question sees a 30-second interaction. The Ops professional sees a 15-minute scavenger hunt.

What the requester sees:

• Ask question in Slack
• Wait for answer
• Get answer
• Move on

What the Ops professional actually does:

• Read the Slack message
• Open Salesforce to check account status
• Open HubSpot for recent email history
• Check the billing dashboard for payment status
• Review Slack threads with the account manager for recent updates
• Cross-reference the customer's support tickets in Zendesk
• Synthesize all of this into a coherent two-sentence Slack reply
• Move on to the next "quick question" already waiting in the queue

One Ops leader at a 150-person company told me she tracked this for a week. The result: she spent 12 minutes gathering context for every 2 minutes spent actually typing a response. The ratio is 6:1. Six minutes of searching for every one minute of doing.

The Tool Overload Problem

I asked each leader to list the tools they open in a typical day. The average was 11.2 tools. Here's a representative list:

• Slack
• Gmail
• Salesforce
• HubSpot
• Google Sheets
• Notion
• Linear or Jira
• Zendesk or Intercom
• Stripe or billing dashboard
• Calendar
• Internal admin tools

That's not a tech stack. That's a digital obstacle course.

The problem isn't that any single tool is bad. Most of these tools are excellent at what they do individually. The problem is that operational knowledge is fragmented across all of them. No single tool has the complete picture. Every answer requires assembling a puzzle from pieces scattered across a dozen different places.

How Tool Count Scales With Company Size

One of the most striking findings was how the problem scales.

30-50 employees: 7.4 tools/day, 80 requests/week, 10 min/request

51-150 employees: 10.8 tools/day, 180 requests/week, 14 min/request

151-300 employees: 12.6 tools/day, 260 requests/week, 16 min/request

301-500 employees: 14.1 tools/day, 340 requests/week, 19 min/request

The pattern is clear. As companies grow, everything gets worse. More tools, more requests, more time per request. The complexity doesn't scale linearly. It compounds.

A Director of RevOps at a 300-person company put it bluntly:

"Every time we add a new tool to the stack, my job gets harder. Not because the tool is bad. Because it's another place I have to check."

The Curse of Being Helpful

Here's the finding that hit hardest. The better you are at your job in Ops, the worse your job becomes.

87% of the Ops leaders I interviewed said their request volume increased after they improved their response time. Read that again. Getting faster at your job doesn't reduce your workload. It increases it.

This is what I call the Ops Efficiency Paradox. When you respond quickly and accurately, you become the path of least resistance. Colleagues learn that asking you is faster than looking it up themselves. So they ask more. And more. And more.

One Head of Ops described it this way:

"I spent a month optimizing our processes. Got our average response time from 20 minutes down to 8. My reward? Request volume went up 40% the next quarter. People figured out I was the fastest way to get answers, so they stopped even trying to find things themselves."

The implication is profound. Traditional productivity improvements, faster processes, better documentation, improved workflows, don't solve the Ops bottleneck. They make it worse.

The only way to break the cycle is to change the fundamental model. Instead of making the human faster at context-gathering, you need to eliminate context-gathering as a human task entirely.

What Ops Leaders Actually Want

I closed every interview with the same question: "What do you wish the rest of your company understood about your job?"

The answers clustered into five themes.

1. "We're not a help desk."

"People treat us like an internal Google. But our job isn't to answer questions. It's to make the company run better. Those are very different things."

Ops leaders want to be strategic. They want to design systems, optimize workflows, and drive operational efficiency. Instead, they spend their days as human search engines, pulling data from one tool and pasting it into another.

2. "The real work is invisible."

"My manager sees me typing Slack messages all day and thinks I'm just chatting. She doesn't see the 15 minutes of context-gathering behind every two-sentence reply."

The effort behind each response is invisible to everyone except the person doing it. This creates a persistent perception gap. Leadership sees the output (short Slack replies) and underestimates the input (complex multi-tool research).

3. "We need fewer tools, not more."

"Every quarter, someone proposes adding another tool to 'solve' a problem. I want to scream. The tools aren't the problem. The fact that I have to use 12 of them for every answer is the problem."

This was one of the strongest consensus points. Ops leaders don't want more tools. They want fewer context switches. The ideal scenario isn't a new dashboard. It's a single place where context from all their existing tools comes together automatically.

4. "Hiring more people doesn't scale."

"We hired two more Ops analysts last year. Within six months, request volume absorbed their capacity completely. We were back to the same bottleneck, just with a bigger team."

Headcount doesn't solve a structural problem. If every request requires manual context-gathering across multiple tools, adding people just adds more manual context-gatherers. The bottleneck doesn't shrink. It moves.

5. "We're burning out."

"I love operations work. I love solving problems and making things run. But I can't keep doing this. The constant switching, the endless interruptions, the feeling that I'm always behind. Something has to change."

This was the most consistent and the most sobering response. Burnout isn't an edge case in Ops. It's the norm. And it's driven not by the volume of work, but by the nature of it. Constant context-switching is cognitively exhausting in a way that sustained, focused work is not.

Where Time Actually Goes

Based on detailed time-tracking data from 15 participants who agreed to log their activities for a week, here's how the average Ops professional's day actually breaks down:

• Context gathering (switching tools, searching, cross-referencing): 41%
• Communication (reading/writing messages, meetings): 26%
• Context switching overhead (refocusing after interruptions): 15%
• Administrative tasks (updating records, filing, routing): 11%
• Strategic work (process improvement, planning, analysis): 7%

Seven percent. That's how much time Ops professionals spend on the work they were actually hired to do. The rest is overhead.

Compare this to how leadership perceives Ops time allocation:

• Answering questions and helping teams: 50%
• Process improvement: 25%
• Administrative tasks: 15%
• Meetings: 10%

The gap between perception and reality is staggering. Leadership thinks Ops spends a quarter of their time on strategic work. The actual number is less than a third of that.

The Path Forward

These findings point to a structural problem, not a people problem. You can't fix this by hiring more analysts, adding more tools, or running another process improvement sprint. The fundamental model of "human gathers context from multiple tools to answer each request" doesn't scale.

The solution has to address the core bottleneck: context aggregation.

What if the context from all your tools came together automatically, before you even started typing a response? What if a Slack message asking about a customer's renewal status immediately surfaced the relevant data from Salesforce, HubSpot, Zendesk, and your billing system, synthesized into a ready-to-send answer?

That's the shift from Inbox Zero to what we call Inbox Intelligence. Not an empty inbox. An intelligent one. One where every request arrives with the context already assembled and a suggested response already drafted.

Tools like Runbear are building toward this model, connecting across Slack, email, and calendar while pulling context from 2,000+ services to eliminate the scavenger hunt. But regardless of which tool you choose, the principle is the same: the answer to Ops burnout isn't faster humans. It's eliminating the manual context-gathering that consumes 67% of their day.

What's Coming Next

This article represents the qualitative findings from our interviews. But there's more data coming.

We're currently fielding the 2026 Ops Bottleneck Report, a comprehensive survey of 200+ Ops professionals across B2B SaaS. The full report will include:

• Detailed benchmarks by company size, industry, and team structure
• Correlation analysis between tool count and response time
• ROI modeling for context automation
• Recommendations from the top-performing Ops teams

If you want early access to the report when it drops, keep an eye on our blog. We'll publish a preview with the key findings before the full release.

The Bottom Line

Ops teams aren't slow. They aren't inefficient. They aren't bottlenecks because they lack talent or motivation.

They're bottlenecks because every answer requires a scavenger hunt across a dozen tools. Because "quick questions" are never quick. Because getting better at the job means getting more of it. And because the invisible work of context-gathering consumes two-thirds of every working day.

The 50 leaders I spoke with are some of the most capable, dedicated professionals I've ever met. They deserve better systems. And their companies deserve to unlock the strategic potential that's currently buried under an avalanche of browser tabs.

It's time to stop optimizing the wrong thing.

This is the second post in our "Ops Tax" series. Read the first post: The Ops Tax: The Hidden Cost of Waiting on Your Operations Team.