The right way to resource a function depends on the shape of its demand over time. Most businesses never actually look at the shape. They just pick a structure and keep it regardless.
A business facing a resourcing decision usually asks “should we hire, outsource, or find some flexible option,” as if the answer were a fixed property of the function itself. It is not. The right answer depends heavily on how that function’s workload actually behaves over time, whether it is flat, seasonal, growing, or spiky, and most businesses never look closely enough at that shape before choosing a structure.
The Problem: One Structure Applied to Every Kind of Demand
A permanent hire assumes constant, ongoing demand. Traditional outsourcing assumes a definable, often standardised scope that can be handed to an external provider. Ad hoc freelance work assumes occasional, disconnected tasks. Each of these structures is a reasonable fit for the specific demand pattern it was built for, and a poor fit for the others.
The trouble is that businesses rarely choose a structure by examining the actual shape of demand first. They choose based on habit, on what the business has always done, or on which option feels most familiar, and then live with the mismatch, whatever form it takes, for far longer than they should.
Why It Happens: Nobody Draws the Curve Before Choosing the Structure
If a business actually plotted a function’s workload over a full year, hours or volume of work required, week by week, the right structure would often become obvious. A sharply seasonal pattern points clearly away from year round permanent staffing at peak levels. A flat, constant pattern points clearly toward permanent hiring being efficient. A growing but still uncertain pattern points toward starting flexible and scaling as the trend confirms itself.
Almost nobody actually draws this curve before making the decision. The resourcing choice gets made first, based on convention, and the workload pattern is discovered only afterward, usually in the form of either idle capacity during quiet periods or a scramble during busy ones. The curve was knowable in advance. It just was not consulted.
The Framework: The Workload Curve
The Workload Curve is a simple exercise: plot the actual volume of a specific function’s work over a meaningful period, commonly a year, and look honestly at its shape. Four shapes recur often enough to be worth naming directly.
The flat curve. Demand stays roughly constant across the period, with limited seasonal or cyclical variation. This shape is the strongest case for permanent hiring, since the underlying assumption behind permanent employment, ongoing, continuous need, actually matches the reality of the work.
The seasonal curve. Demand rises and falls in a predictable, recurring pattern, often tied to a calendar event, a filing deadline, a sales season, an industry cycle. This shape is a poor match for permanent staffing at peak levels, and an equally poor match for staffing at the average, since both leave the business either overstaffed most of the year or understaffed exactly when it matters most. Flexible capacity that scales specifically around the known peak is the structural answer this curve is asking for.
The growth curve. Demand is trending upward, but the pace and eventual scale are not yet confirmed. This shape favours starting with flexible, scalable capacity and converting to more permanent structure only once the trend has generated enough real evidence to commit with confidence, rather than guessing at the eventual scale upfront.
The spiky curve. Demand is unpredictable, arriving in sudden bursts with no clear seasonal pattern, often tied to specific client wins, project starts, or one-off events. This shape is the hardest to staff efficiently with any fixed structure, and it is where on demand, rapidly scalable capacity delivers the most value, since neither a permanent hire nor a standard outsourcing contract can respond at the speed a genuine spike requires.
The value of naming these shapes explicitly is that it turns a vague, habitual decision into a specific, evidence based one. The question stops being “should we hire or outsource this” in the abstract, and becomes “what shape is this function’s actual demand, and which structure was built for that shape.”
What This Looks Like in Practice
An accounting firm’s bookkeeping and filing workload is a textbook seasonal curve, sharply higher around filing deadlines, considerably quieter the rest of the year. Staffing permanently at peak level means carrying real, ongoing cost for capacity that sits underused most of the year. Staffing at the average means a genuinely difficult, error prone peak season every year. Flexible seasonal capacity, brought in specifically around the known peak, is the structural answer the curve itself points toward, once someone actually looks at its shape.
A SaaS company’s customer success function, in the months following a major funding round, is a growth curve. Nobody yet knows how quickly the customer base will actually expand or by how much. Committing to a large permanent support team ahead of that evidence risks significant unused capacity if growth is slower than hoped. Flexible, scalable capacity that expands directly with confirmed customer growth lets the company track the real curve as it emerges, converting to permanent structure only once the shape is actually known.
A consulting firm’s analyst capacity, tied to the timing of engagement wins, is a spiky curve. Two large engagements landing in the same month create a demand spike no amount of careful average based staffing would have anticipated. On demand, rapidly deployable capacity, brought in specifically to handle the overlap, addresses this far more efficiently than either a permanent team sized for the coincidence or a slow traditional hiring process that could never move fast enough to catch it.
Practical Takeaways
Before choosing a resourcing structure for any function, spend the time to actually plot its workload over a meaningful period. This does not need to be a formal exercise. Even a rough, honest sketch of busy and quiet periods over the past year usually reveals the curve’s shape clearly enough to inform the decision.
Match the structure to the shape, not to habit. A flat curve genuinely supports permanent hiring. A seasonal, growth, or spiky curve is telling you something a permanent hiring decision will not respond to well, regardless of how confidently the decision is made.
Revisit the curve periodically, since a function’s demand shape can change as a business evolves. A function that was flat two years ago may have become seasonal or spiky as the business grew, and the structure resourcing it should be reconsidered against the current shape, not the shape it had when the original decision was made.
Recognise that most businesses have a mix of curve shapes across their functions simultaneously, and the resourcing structure should vary accordingly. There is rarely a single right answer for an entire business. There is a right answer for each function’s actual curve.
Frequently Asked Questions
Is the Workload Curve the same idea as seasonality?
Seasonality is one of the four shapes the curve can take, but the framework covers more than seasonal patterns. Flat, growth, and spiky curves each point toward a different structure, and seasonality is only one of several patterns worth identifying.
How long a period should a business look at to identify its curve shape?
A full year is usually the most reliable period, since it captures seasonal patterns that a shorter window would miss. For newer functions without a year of history, a best estimate based on known drivers, client cycles, product launches, hiring seasons, is a reasonable starting point, refined as real data accumulates.
Can a function’s curve shape change over time?
Yes, and this is common as a business grows or its market shifts. A function that was genuinely flat can become seasonal as the business enters new markets with different cyclical patterns, or a spiky curve can smooth into something closer to flat as a business’s client base matures and diversifies.
What if a function shows a mix of shapes, partly seasonal and partly growing?
This is common in practice, and the honest answer is usually a blended structure, a stable core sized for the underlying trend, with additional flexible capacity layered on top specifically for the seasonal or spiky component. The curve does not need to resolve into a single clean shape to be useful, it needs to be looked at honestly.
Does this framework apply to every business function, or mainly operational ones?
It applies broadly. Sales, marketing, finance, technology, and recruitment functions all have a real workload curve, even when it is less obviously seasonal than something like tax filing. The exercise of plotting it is useful wherever a resourcing decision is being made, not just in functions with obvious calendar driven cycles.
Look at the Curve Before You Choose the Structure
Most resourcing mistakes are not failures of execution. They are failures to look at the actual shape of demand before choosing a structure built for a different shape entirely. The Workload Curve is a simple discipline: draw the shape honestly, then match the structure to what it actually shows, rather than to habit, convention, or whichever option feels most familiar.
Talk to our team about mapping your own workload curve and matching the right structure to what it actually shows.