Call Center Operations Case Interview: Capacity Case
| Case type | Operations |
|---|---|
| Industry | Travel / Customer Service |
| Difficulty | Hard |
| Firm style | BCG |
The case prompt
Our client is TravelLine, an online travel booking platform. They recently centralized customer service from 12 regional offices into one national call center. The center is overwhelmed — customers face 20-plus minute wait times and satisfaction scores are dropping fast. The CEO needs to understand why and what to do about it.
TravelLine migrated 780,000 active customers from 12 regional offices to a single national call center over 50 weeks. The call center currently has 45 trained agents. Customers are experiencing 20+ minute wait times, and NPS has dropped 25 points. The CEO wants us to diagnose the root cause and recommend solutions.
The exhibits
Exhibit 1
Cumulative Customers Migrated to National Call Center (thousands)
Cumulative customers migrated to the national call center (thousands), by week (weeks 0-50).
Show the data behind Exhibit 1
| Week | 0 | 5 | 10 | 15 | 20 | 25 | 30 | 35 | 40 | 45 | 50 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Customers Migrated (K) | 0 | 50 | 120 | 200 | 300 | 420 | 550 | 650 | 720 | 760 | 780 |
Exhibit 2
Call Center Capacity Driver Tree
Driver tree linking weekly call volume and per-agent capacity to the number of required agents.
Show the data behind Exhibit 2
| Component | Value | Notes |
|---|---|---|
| Average Call Time | 210 seconds | Time on the phone with customer |
| Average Wrap-up Time | 90 seconds | Post-call notes and system updates |
| Total Settlement Time | 300 seconds = 5 min | Call time + wrap-up = 1/12 hour |
| Calls per Customer per Year | 2.5 | Average across all customer types |
| Weeks per Year | 52 | Used to convert annual customer calls to weekly calls |
| Working Hours per Week | 40 hours | Standard full-time schedule |
| Gross/Net Working Ratio | 78% | Net of breaks, meetings, admin |
| Working Time Duration | 55% | % of net time actually on calls |
| Effective Call Hours per Agent per Week | 17.16 hours | 40 x 78% x 55% |
| Seconds per Hour | 3,600 | Used to convert productive hours into call capacity |
| Calls Handled per Agent per Week | ~206 calls | 17.16 hrs x 12 calls/hr |
| Seasonal Peak Factor (Summer) | 1.30 | 30% more calls June-August |
BCGOperations · hard
TravelLine Call Center Optimization
Travel / Customer Service
How a strong candidate structures it
A strong call center operations framework
Question by question
- 1
Case context
Understand the Case
“Can you summarize the situation and what TravelLine needs from us?”
- 2
Clarifying
Clarifying Questions
“What would you like to know before analyzing the problem?”
- 3Drill the structure
Structure
Framework
“How would you structure your analysis of why the call center is overwhelmed?”
- 4Drill the brainstorming
Analysis
Driver Tree Setup
“Looking at Exhibit 2, walk me through the driver tree for calculating how many agents TravelLine needs. What are the key inputs?”
- 5Drill the math
Math
Calculate Required Agents
“At Week 20, TravelLine had 300,000 customers migrated to the call center. Using the driver tree from Exhibit 2, calculate how many agents are needed at that point. Then calculate how many are needed at Week 50 with 780,000 customers. Compare both to the current 45 agents.”
- 6Drill the brainstorming
Analysis
Gap Analysis and Constraints
“The call center has 45 agents but needs 182. Hiring takes 8 weeks per agent and the budget is limited. What are the key constraints, and what categories of solutions should TravelLine consider?”
- 7Drill the math
Math
Quantify Solution Impact
“If self-service tools deflect 25% of calls and better CRM tools increase each agent's capacity by 10%, how many agents would TravelLine need at Week 50? How many do they still need to hire?”
- 8Drill the synthesis
Synthesis
Final Recommendation
“The CEO just walked in. Present your diagnosis and recommendations.”
The worked path
The numbers that decide it
- At Week 20 with 300K customers, TravelLine needs approximately 70 agents but only has 45
- The agent gap of 25 (36% shortfall) explains the 20+ minute wait times
- By Week 50 with 780K customers, the need grows to approximately 182 agents at baseline
- Summer peak season adds 30% more call volume, requiring ~236 agents at peak
- Three levers exist: reduce call volume, reduce settlement time, increase agent productivity
- Self-service tools (IVR, chatbot, FAQ) could deflect 20-30% of simple calls
- Reducing wrap-up time through better tools could cut settlement time by 15-20%
- Part-time agents during peaks could increase effective capacity 10-15%
- Long-term solution requires combination of all three levers plus strategic hiring
Analysis Flow
- 1
Set up the demand equation
Weekly call volume = (Customers / 52 weeks) × Calls per customer per year
At Week 20 (300K customers): 300,000 / 52 × 2.5 = 14,423 calls/week
At Week 50 (780K customers): 780,000 / 52 × 2.5 = 37,500 calls/week
- 2
Calculate agent capacity
Settlement time = 210 + 90 = 300 sec = 5 min = 1/12 hour
Effective hours per agent = 40 × 78% × 55% = 17.16 hrs/week
Calls per agent per week = 17.16 × 12 = ~206 calls/week
- 3
Calculate required agents
Week 20: 14,423 / 206 = ~70 agents needed
Week 50: 37,500 / 206 = ~182 agents needed
Week 50 peak season: 37,500 × 1.30 / 206 = ~236 agents needed
Current staff: 45 agents
- Gap at Week 20: 25 agents (36% shortfall)
- Gap at Week 50: 137 agents (75% shortfall)
- 4
Three solution levers
Lever 1 — Reduce demand (call volume)
- Implement IVR system to handle simple queries (booking confirmation, status checks)
- Build self-service FAQ and chatbot for common issues
- Estimated deflection: 20-30% of calls
- Impact: reduces required agents by 20-30%
Lever 2 — Reduce settlement time
- Better CRM tools to reduce wrap-up time from 90 to 60 seconds
- Pre-built response templates for common issues
- Impact: settlement drops from 300 to 270 sec, ~10% more calls per agent
Lever 3 — Increase capacity
- Hire and train additional agents (8-week ramp)
- Add part-time agents for peak hours and peak season
- Cross-train back-office staff for overflow support
- 5
Combined impact estimate
Self-service deflects 25% of calls: 37,500 × 0.75 = 28,125 calls/week
Better tools increase calls/agent by 10%: 206 × 1.10 = 227 calls/agent/week
Required agents: 28,125 / 227 = ~124 agents (vs 182 without improvements)
- Still need to hire ~79 additional agents beyond current 45
Recommendation
"The root cause is a massive supply-demand mismatch: TravelLine needs 182 agents at full migration but only has 45. Three actions in priority order: First, immediately deploy self-service tools (IVR, chatbot) to deflect 25% of calls — this is the fastest lever. Second, invest in better CRM tools to reduce settlement time by 10%. Third, begin hiring and training 80+ additional agents in waves, starting immediately given the 8-week training cycle. Combined, these reduce the requirement to ~124 agents, making the hiring target achievable."
BCGOperations · hard
TravelLine Call Center Optimization
Travel / Customer Service
Why this case
This travel customer-service case tests capacity planning after centralization, a trap generic operations cases often miss. The 20-plus-minute waits are not just a staffing problem: demand rises with customer migration, call time includes a 90-second wrap-up, and summer adds 30% volume. The industry-specific issue is protecting service quality while scaling a seasonal, distributed customer base.
FAQ
- How do I calculate required agents in this call center case?
- Estimate weekly calls from customers, calls per customer, and 52 weeks, then divide demand by weekly calls handled per agent. At Week 50, 780,000 customers create 37,500 weekly calls. With about 206 calls per agent per week, TravelLine needs approximately 182 agents before seasonal or operational improvements.
- Why is hiring alone not the best answer?
- Hiring addresses capacity but leaves demand and productivity unchanged. TravelLine can deflect 20% to 30% of simple calls through IVR, chatbots, and FAQs, while better tools can reduce wrap-up time and raise calls per agent by about 10%. Those levers reduce the number of agents needed and improve response times.
- What are the three operational levers in this case?
- Reduce call volume through self-service, reduce settlement time through better CRM tools and response templates, and increase capacity through hiring, part-time peak coverage, or cross-training. A strong answer ranks the levers by speed and impact, then combines them rather than presenting staffing as the only fix.
- What should the recommendation say at Week 50?
- State that TravelLine needs about 182 baseline agents but has 45, creating a 137-agent gap. Prioritize self-service, reduce wrap-up time, and hire in waves because training takes 8 weeks. With 25% call deflection and 10% productivity improvement, the requirement falls to about 124 agents, before the 30% summer peak.
BCGOperations · hard
TravelLine Call Center Optimization
Travel / Customer Service