The perennial pressure on corporate leadership to achieve ambitious goals with reduced budgets often leads to a singular, and frequently misguided, solution: "do more with less." While this directive sounds pragmatic, its common interpretation as a headcount problem solvable by artificial intelligence (AI) is a superficial approach, according to Lisa Heay, Vice President of Business Operations at Heinz Marketing. Heay argues that genuine efficiency gains stem not from simply reducing staff or implementing new technologies in a vacuum, but from a fundamental re-evaluation of workflows. The critical first step, she asserts, is to meticulously map which tasks intrinsically require human judgment and which are repeatable, a foundational analysis that must precede any decisions about AI integration, contractor engagement, or staffing adjustments.
The current economic climate, marked by a persistent drive for fiscal prudence, has intensified this organizational dilemma. Many Chief Marketing Officers (CMOs) report facing a dual mandate from their boards and Chief Financial Officers (CFOs): maintain or increase pipeline generation while simultaneously cutting operational budgets. This familiar challenge has been amplified by the rapid advancement and adoption of AI technologies, which are now frequently presented as the immediate panacea for the "do more with less" imperative. The logic often presented is that if AI can automate tasks such as drafting content or scoring leads, then the human resources dedicated to these functions become redundant. This simplistic equation, however, overlooks the intricate nature of operational processes and the nuanced capabilities of both humans and AI.
The Illusion of "Do More With Less" as a Strategy
The appeal of "do more with less" as a response to budget constraints is understandable. It offers a seemingly straightforward path to cost savings and increased productivity. In some instances, there may indeed be opportunities to streamline existing processes, reallocate budgets more effectively, or optimize team structures. However, when this directive is treated as a strategy in itself, rather than a desired outcome, it often leads to detrimental consequences.
Organizations that rigidly adhere to "do more with less" without a strategic plan typically find themselves in one of two difficult positions: either their teams become profoundly burned out from being stretched too thin, or they resort to filling critical operational gaps with external agencies and freelance contractors. The latter scenario is particularly problematic when these external resources are integrated into existing, unexamined workflows. Without a clear understanding of how these new contributors fit into the overall operational fabric, their effectiveness is severely hampered, and the promised efficiency gains fail to materialize. They are not set up for success, nor are they positioned to drive the substantial results leadership expects.
A true strategy articulates how work itself will evolve to meet new objectives. "Do more with less," in contrast, merely sets a numerical target – a reduction in personnel or budget – without providing a roadmap for achieving it. This disconnect creates a significant gap for most teams. While leadership may readily approve the numerical targets, there is often a profound lack of clarity regarding the actual nature of the work once those targets are implemented. The essential question of how the work will be performed differently remains unanswered, leading to operational inefficiencies and unmet expectations.
Prioritizing Workflow Analysis Over Organizational Charts
As the Vice President of Business Operations at Heinz Marketing, Lisa Heay’s role places her at the intersection of leadership aspirations and the daily realities of team execution. Her observations consistently highlight a critical flaw in the typical response to the "do more with less" directive: the immediate inclination to reduce headcount. Heay contends that the real solution rarely begins with personnel cuts. Instead, it necessitates a granular examination of how work is presently accomplished, step by step. Identifying and rectifying inefficiencies within these processes should precede any adjustments to staffing levels.
The foundational inquiry should not be about how many people are needed, but rather, "What does the team in question actually produce?" From this starting point, one can then ascertain the objectives these outputs serve, the ultimate outcomes for which the team is accountable, and, crucially, which specific components of that production genuinely require the precise actions of a human employee as they are currently performed. Heay notes that this level of detailed process mapping is often conspicuously absent within organizations.
Without this fundamental analysis, decisions regarding staffing reductions are frequently based on arbitrary criteria such as employee tenure, cost to the company, or the perceived ease of parting with an individual. The inevitable consequence of such actions, undertaken without a commensurate adjustment to the workload, is a decline in quality and missed deadlines. The work itself does not diminish; rather, the capacity to perform it is reduced. If employees are terminated without a thorough consideration of the underlying processes they supported, they may have been the linchpins holding together undocumented systems – such as critical approval chains or inter-team handoffs. The work does not evaporate; it lands on the remaining staff, who are then left to improvise and piece together solutions until a breakdown occurs, forcing a reactive scramble to understand and address the new crisis.
The Pitfall of Speed Without Process Integrity
The integration of new technologies, particularly AI, is often framed as a means to accelerate existing processes. However, faster execution does not equate to a fundamentally improved or "fixed" process. The core issue, Heay explains, is that teams are rarely provided with workflows that have been re-engineered to account for the realistic capabilities of AI versus the enduring need for human judgment. The process is not redesigned; instead, human elements are simply removed from a system that was originally architected with their consistent presence assumed.
This is precisely why AI, when implemented without a workflow redesign, so frequently fails to deliver on the "do more with less" promise in isolation. While AI can indeed generate a first draft of content or score leads, these are merely preliminary steps. The critical judgment of whether a draft is ready for publication or the strategic decision of how to act upon a qualified lead are entirely different tasks. AI can expedite the initial stages, but it possesses no inherent capacity for the nuanced decision-making required in the subsequent phases. Consequently, unreviewed drafts and misrouted leads simply traverse a flawed process at an accelerated pace, a process that was never designed to catch the errors or omissions that AI might introduce.
Mapping the Workflow: The Prerequisite to Setting Targets
The logical progression for achieving genuine efficiency gains lies in meticulously analyzing the actual workflow. This involves a careful distinction between tasks that inherently demand high levels of human judgment – such as strategic decision-making, intricate relationship management, creative direction, and complex problem-solving – and those that are repetitive, well-defined, and amenable to automation by AI or other technological solutions without a significant degradation in quality.
Consider a content creation workflow. AI might adeptly generate an initial outline and a first draft. However, a human strategist must then evaluate the angle and relevance of the content to ensure it aligns with market objectives. Subsequently, an editor provides the final crucial assessment of tone, style, and accuracy before the content is released. In this scenario, two of the three steps – drafting and editing – can be significantly enhanced or even automated by AI. The crucial step, however, is the strategic evaluation, which demands human insight and cannot be reliably replicated by current AI capabilities. This is the element that remains essential and therefore warrants continued investment in human expertise.
Only after this comprehensive mapping and differentiation of tasks is completed can a headcount number or budget allocation become a meaningful metric. Without this foundational understanding of how work is performed and where human judgment is indispensable, any numerical targets set are arbitrary and likely to lead to operational disruption.
The Contractor Conundrum: A Symptom of Unaddressed Workflow Gaps
When the critical workflow mapping process is neglected, a common organizational response to perceived staffing shortages or budget cuts is to engage external contractors. This is often perceived as a cost-effective solution, as contractors typically come with lower overheads than full-time employees. While bringing in specialized external expertise can indeed be a strategic advantage, it becomes problematic when implemented as a mere patch to cover immediate gaps without a fundamental re-evaluation of the underlying workflow.
In such cases, contractors are layered onto an existing process that was never designed to accommodate their integration. This leads to escalating costs and significant management challenges. The lack of a well-defined process for onboarding, task assignment, and performance evaluation of contractors can result in inefficiencies, miscommunication, and a failure to achieve the desired outcomes. The problem is not necessarily the use of contractors, but their deployment within a broken or incomplete operational framework.
The Org Chart Follows the Workflow, Not the Other Way Around
The ultimate solution lies in developing a workflow that has been genuinely and thoughtfully constructed. This ensures that regardless of whether the work is performed by a full-time employee, a contractor, or an AI, there is a clear and defined place for them to contribute effectively. The process should be robust enough to integrate various resources seamlessly.
It is important to acknowledge that this is not an argument for perpetuating unnecessary headcount. Many organizations do, in fact, have more personnel than their current operational demands require, and some roles were established for a marketing landscape that has long since evolved. The imperative for efficiency is valid.
However, the answer to the "do more with less" directive cannot be confined to simply reducing the number of boxes on an organizational chart. It must commence with an honest and critical examination of the work itself: identifying precisely which tasks necessitate human involvement and which can be effectively automated or augmented by technology. This is a more challenging conversation, demanding a deeper level of introspection and strategic planning. Yet, it is the only approach that can yield a sustainable and truly effective version of "do more with less." The future of operational efficiency hinges on this fundamental shift in perspective, moving from a focus on headcount to a deep understanding and optimization of workflow.
