Adland’s efficiency trap media agencies never saw coming

By Maaz A. Khan, Regional Client Partner (APAC) GroupM

Satya Nadella’s recent tweet about the Jevons paradox sparked an interesting reflection on how this 19th-century economic theory perfectly explains today’s media agency landscape. The paradox, which suggests that increased efficiency leads to higher resource consumption rather than reduction, is playing out dramatically in our industry.

When automation and AI first emerged, we anticipated they would simplify our workload and improve work-life balance. Instead, we’re experiencing quite the opposite. As media planning and buying processes become more automated, the scope and complexity of agency work have expanded exponentially.

The time saved through automation is quickly consumed by more demanding reporting requirements, managing multiple channels, and elevated client expectations for strategic insight.

This paradoxical effect is particularly visible in resource allocation. While automated tools handle routine tasks efficiently, the human element has become increasingly crucial. Teams are now required to provide deeper strategic insights, more sophisticated campaign optimization, and complex data analysis generated by these automated systems.

The proliferation of efficiency tools has created a meta-challenge: we now need platforms to manage other platforms, and meetings to discuss how to manage our efficiency tools effectively. The time saved through automation isn’t reducing workload; instead, it’s being redirected into higher-value activities requiring specialized skills and increased human involvement.

To address these challenges, media agencies need to fundamentally reconsider their resource planning models. Here are key areas to focus on:

Value-Based Planning: Agencies must move beyond the traditional “hours = output” equation. Modern resource planning should incorporate a “complexity multiplier” that accounts for both quantitative metrics (campaign performance, efficiency gains) and qualitative aspects (strategic insight, innovation).

Hybrid Capacity Models: Success lies in finding the right balance between automated capabilities and human expertise. This means clearly defining where AI and automation add value (routine tasks, data processing) versus where human insight is irreplaceable (strategy, creative thinking, relationship management).

Flexibility Frameworks: New planning models must accommodate the expanding scope of work. This might involve maintaining a core team supplemented by specialists for specific projects, ensuring adaptability to changing demands.

Skills Evolution Mapping: Agencies need to plan not just for current resource needs but for future skill requirements. This involves creating development pathways that transform team members from task executors into strategic thinkers.

The focus should shift from purely efficiency-based metrics to those that better reflect the evolving nature of agency work. This includes developing new pricing models based on value creation, incorporating innovation time as a legitimate resource requirement, and establishing clear guidelines for human intervention in automated processes.

Understanding and adapting to this paradox is crucial for media agencies in today’s complex digital landscape. While technological advancement remains inevitable, we must recognize that efficiency gains often lead to expanded scope and complexity. The goal isn’t to reduce work through efficiency but to enable more meaningful work and better client outcomes.

Perhaps the wisdom lies in embracing this paradox rather than fighting it. As Jevons observed about human nature and technological progress, our greatest efficiency gain might come from understanding that advancement brings not less work, but better work. In an industry constantly pursuing technological breakthroughs, this might not be such a bad paradox to live with after all.

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