Teams | Collaboration | Customer Service | Project Management

Move from reactive hiring to proactive workforce planning using data-backed productivity benchmarks.

Running a small business is hard, and building a customer service center from scratch is harder. Almost 50% call center managers cite high agent turnover and absenteeism as their single biggest operating problem. Plus, it’s expensive to replace a well-trained agent, almost $10,000 to $20,000 expensive. Without a clear plan, that investment can spiral before you've handled your first call. This guide walks you through the practical steps of setting up a call center for a small business.

High attrition has been a long-standing challenge in the contact center industry. Many agents leave within months of joining, which creates a constant cycle of hiring, training, and replacing employees. For managers, this can quickly become expensive and disruptive. A call center faces many issues, such as a drop in service quality, increased training costs, and mental pressure on remaining employees when experienced agents leave.

The number one reason projects miss deadlines isn't poor planning. It's poor visibility. Before I joined Teamwork.com, I kept seeing the same pattern: teams had plans, but nobody could see the real-time status of those plans across multiple projects at once. According to Teamwork.com's Sprint to AI research, 58% of professional services teams now use three to five separate tools to manage their work.

Your project management stack is probably held together with duct tape and good intentions. I know because I've seen it firsthand across hundreds of client-facing teams. The pattern is always the same: one tool for task tracking, another for time logging, a spreadsheet for resource planning, and a prayer that nothing falls through the cracks. What we see across Teamwork.com customers is that this tool sprawl isn't just annoying. It's expensive.

Before the doctor walks in, before the diagnosis, before the prescription – there is a form. And more often than we admit, that form is where things start to go wrong. A 67-year-old man sits in a waiting room, clipboard balanced on his knee. He’s here for a pre-surgical consultation. The form asks for his current medications. He pauses, trying to remember the name of the blood thinner he started a couple of months ago. It’s on the tip of his tongue, but not quite there.

If your AI is closing tickets but not solving problems, it’s doing more harm than good.