Snapshot

At Lando Interactive, a small management team supports a fully distributed workforce of teachers delivering live after-school classes across hundreds of school sites.

Currently, we operate at roughly a 1:200 manager–frontline staff ratio - not through heroic management, but through deliberately designed systems that remove repeatable coordination, make distributed work observable, and route human attention where judgment actually changes outcomes.

Outcome

• Scaled from ~1:8 to ~1:200 manager-frontline staff ratio

• Maintained class quality and NPS throughout the expansion

• Shifted manager time from logistics to coaching and judgment

Details have been generalized to preserve confidentiality. Specific implementations, thresholds, and internal tools have been intentionally abstracted.

Context

This case study examines how managerial leverage scaled inside operations at Lando Interactive, a distributed after-school enrichment company.

Definitions

• Frontline staff: teachers delivering live after-school classes across school sites

• Managers are accountable for

  • Class quality 

  • Staffing and coverage reliability

  • Teacher performance and development

  • Incident and issue handling involving teachers, schools, and parents

Starting Point
When the organization was small, managers operated at roughly a 1:8 manager–frontline staff ratio, relying on frequent check-ins and hands-on coordination.

Scale Transition
As the company grew, that ratio expanded to approximately 1:100, and eventually to ~1:200, as coordination and visibility became increasingly system-driven.

This expansion was gradual, driven by sustained investment in operational systems.

Problem: Why the Normal Manager Model Breaks

In execution-heavy, distributed organizations, the traditional manager role spans an unusually wide surface area:

• Recruiting and onboarding

• Training and quality review

• Staffing and scheduling

• Performance management

• Incident response and operational support

At a small scale, this model works because managers can apply continuous, hands-on attention. As headcount grows, however, managerial attention does not scale with the work.

Administrative coordination - staffing logistics, onboarding steps, exception handling, information routing - expands to consume the manager’s time. The highest-leverage parts of the role (coaching, judgment, development) are the first to erode, not because they matter less, but because they are crowded out.

The typical response is to hire more managers. This relieves short-term pressure but does not reduce the underlying coordination burden. Instead, it scales cost and organizational complexity roughly in line with headcount.

The result is a fragile system: more managers, more handoffs, and more effort spent moving information around—without meaningfully improving outcomes.

Solution: The System Design That Enabled 1:200

Achieving this level of leverage required redesigning the manager role itself.

The operating model rested on three principles:

• Automate coordination 

• Make work observable

• Route attention to risk

1. Automate Coordination
The fastest way to reduce managerial load was to remove repeatable coordination entirely.

Examples included:

• System-driven staffing and restaffing, handling initial placements and ongoing coverage adjustments without manual triage

• App-led onboarding, with enforced steps, automated reminders, and clear completion tracking

• Targeted trainings, assigned based on detected class issues

Managers were no longer responsible for chasing logistics or enforcing process. Coordination happened by default through the systems teachers already used.

2. Make Work Observable
Once coordination was handled by systems, managers still needed a way to understand how classes were running, without constant check-ins or on-site presence.

Our operational platform makes work observable by default, using data generated through normal day-to-day workflows rather than special reporting or manual updates.

Managers had visibility into class health through two complementary signal types:

• Leading signals: behavioral data generated as part of teaching workflows, such as class check-ins, timing patterns, lesson completion, and attendance consistency

• Lagging signals: structured feedback from teachers, parents, and schools, including post-class reports, surveys, and notes

Together, these signals provided a near real-time view of performance and emerging risk. Managers could quickly see which classes were running smoothly, which required attention, and where trends were forming - without chasing updates or being physically present.

3. Intervention Is Targeted

With coordination automated and work observable, managerial attention became selective, with the operating platform flagging situations that require attention.

Examples:

• Underperformance flags (e.g., frequent callouts, chronic lateness, low lesson completion) prompting investigation and coaching

• Team survey results giving a channel for issues to get flagged

• Incident tracking, allowing patterns to trigger specific actions such as coaching conversations, policy adjustments, etc.

On most days, most teachers required no manager involvement at all.

Impact

• Manager-to-frontline staff ratio increased from ~1:8 to ~1:200

• Class quality and NPS remained stable throughout the ratio expansion

• By moving coordination into systems and making work observable, managers spent less time on logistics and more time on coaching and judgment

Key Decisions & Tradeoffs

This model introduced real constraints and required deliberate tradeoffs.

• Reduced personal touch: frontline staff had a lighter relationship with any single manager

• Emotional load on managers: as systems handled the happy path, managers became disproportionately focused on edge cases and issues rather than everyday successes

• Operational rigor required: The model depended on work happening in-system. Informal, out-of-system exceptions reduced visibility and trust, so exceptions had to be structured and auditable, even when this felt slower in the moment

What I Did

• Led operations from 0→1, designing the operating system and building key tools to scale frontline execution

• Built and shipped core internal tools across frontend and backend - owning full-stack implementation for some components and partnering with the CTO and one engineer on others

This work spanned hiring and onboarding, staffing and coverage, training and performance management, incident handling, and day-to-day operational support.