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InterviewAgent Experience2h · 12:01 BST · 4 min read

The Hidden Cost of Manual Contact Center Scheduling

8x8’s WFM customer base grew by more than 170% since November 2025 as contact centres seek simpler alternatives to spreadsheet-led planning. Lisa Orford explains why AI is changing the work agents handle, and why workforce, quality, and coaching data must increasingly work together.

Workforce management is gaining renewed attention as contact centers face more variable demand, tighter budgets and growing pressure to protect both customer and agent experience.  

In fact, 8x8 reported its WFM customer base had increased by more than 170% since November 2025, pointing to an increasing demand for tools that can replace manual planning without creating another complex technology project.  

To keep up with competition, CX leaders should assess whether their current planning model gives supervisors enough timely, reliable information to prevent service issues. 

In conversation with CX Today, Lisa Orford, Global Vice President for Contact Centre PM at 8x8, discussed why spreadsheet-based workforce planning is becoming increasingly difficult to sustain as AI changes the work handled by human agents. 

“As AI agents take the simple interactions, the humans are left with the harder, longer conversations, and you can’t schedule for that in a spreadsheet.”

Why Spreadsheets Still Persist Despite Manual Friction 

For many contact centers, spreadsheets have remained the default workforce management tool because the alternatives have historically been too expensive and complicated to implement.  

In fact, WFM platforms were originally designed for larger operations, leaving smaller teams struggling to remain ahead amid substantial costs, lengthy deployments, integrations, and training requirements.  

“For the smaller teams around 50 seats plus, that’s a massive project and cost,” Orford explained. 

As a temporary fix, manual planning became the easiest option, despite its obvious operational problems.  

“Spreadsheets won by default, not because anybody necessarily thought they were good, but they just fit,” she said. 

Unfortunately, the costs of spreadsheet-led planning can be difficult to identify, with poor forecasts often leading to understaffing, gaps in coverage, and increased overtime. 

With many supervisors spending too much time resolving scheduling problems instead of supporting agents through coaching, their insight into the daily employee capacity becomes lessened.  

From here, the expenses may become accepted as part of daily operations rather than recognised as consequences of an inadequate planning process.  

“Nobody could see the cost of the spreadsheet,” she said. 

“The overtime, supervisor firefighting instead of coaching, those costs become invisible.”

Without a clear view of these costs, contact center leaders may have little incentive to invest in a dedicated WFM platform. 

Particularly when budgets are tight and implementation requires additional resources, spreadsheets often offer the best practical alternative. 

However, 8x8’s reported 3 times growth in WFM adoption suggests that reducing these barriers can change that calculation, coming almost entirely from existing 8x8 Contact Center customers enabling the capability.  

For smaller operations, this solution can make WFM more accessible by replacing manual processes with more consistent planning, while giving managers greater visibility into staffing requirements and operational performance. 

From Scheduling to Smarter Decisions 

As AI agents take on more routine customer interactions, workforce planning needs to account for the changing nature of the work reaching human agents.  

Rather than handling a predictable mix of inquiries to fit the increasing expectation for proactive work, employees may be moved over to longer, more complex conversations that require human judgment or empathy.  

Historical averages therefore become less reliable as a basis for forecasting demand, particularly if contact centers cannot distinguish between interactions handled by AI and those passed to human teams.  

“The forecast has to understand what’s going on,” Orford emphasized. 

“What is going to AI, what is reaching humans, because humans now get the harder conversations and the more challenging tasks.”

To ensure internal success, workforce management must evolve alongside AI deployment to account for changes in both interaction volumes and the skills required to handle them. 

Forecasting and scheduling can also help contact centers determine when employees are available, but quality insights can indicate where their time and support would be most valuable.  

If performance data identifies an agent struggling with a particular interaction, supervisors need to arrange coaching without leaving the team short-staffed.  

“Quality insights should feed that plan. Struggling agents need to get coaching,” Orford explained.  

Scheduling, quality monitoring, and coaching are often left as separate operational responsibilities. 

As a result, connecting these capabilities allows managers to reconsider their current strategy; how they should improve staffing requirements, agent performance, and development. 

It can also help organizations assess whether AI is directing customers to the right channel or escalating interactions to human agents when necessary. 

With customer satisfaction providing an additional measure of whether the overall approach is working. 

AI can support this process by identifying recurring patterns in operational data and suggesting potential improvements, however, decision-making should remain with human supervisors.  

Orford suggested:

“We can also use AI to spot the patterns and propose the fixes while the supervisor stays in charge of the decision.”

As workforce planning becomes more automated, human oversight remains necessary to interpret those findings within the context of the team and its customers. 

To ensure this strategy is in place, organizations will need to connect operational data to staffing and performance decisions and outcomes. 

Forecasts will need to reflect a clear division between AI and human agents in task responsibility, while quality insights can help managers determine where coaching is needed and when it can take place.  

Check out the full interview with Lisa above to hear more about its recent WFM customer success.

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