Budgets

A budget is a detailed financial plan for a future time period, setting out the income a business expects to receive and the expenditure it intends to make. It is a target set in advance, against which actual performance is later compared.

A favourable variance is a difference between budget and actual that is good for profit — for example, costs coming in below budget or revenue coming in above budget. An adverse (unfavourable) variance is one that is bad for profit — costs above budget or revenue below budget. The key distinction is the effect on profit: favourable increases it, adverse reduces it.

Zero-based budgeting is a method in which each budget is prepared from a starting base of zero, so that every item of proposed spending must be justified afresh for the coming period rather than being carried over from the previous budget. Only spending that can be justified is funded.

Revenue variance = actual − budget = 48,000 − 50,000 = $2,000 adverse (earned less than planned). Cost variance = budget − actual = 38,000 − 34,000 =$4,000 favourable (spent less than planned). Total (profit) variance = −2,000 + 4,000 = $2,000 favourable: budgeted profit was$12,000 but actual profit was 48,000 − 34,000 = $14,000, so profit beat budget by$2,000.

The adverse sales-revenue variance of $12,000 means actual sales fell$12,000 short of the budgeted figure, reducing profit. Plausible causes include weaker demand than forecast — perhaps an economic slowdown cutting discretionary spending on clothing, a new competitor opening nearby, an unusually warm season depressing sales of winter stock, or having to discount to clear stock so the average selling price fell below plan. The favourable wages variance of $3,000 means wage costs came in below budget. A likely cause is that, because sales were weak, the retailer cut staff hours or overtime, so fewer wages were paid; alternatively, planned vacancies were left unfilled. Crucially, the two variances are probably linked: the same weak demand that caused the adverse revenue variance also caused the favourable wages variance, because management scaled back staffing in response to lower footfall. This shows that a favourable variance is not always 'good news' — here the wage saving is a symptom of the underlying sales problem, not evidence of efficient management.

First, delegated budgets improve accuracy and efficiency because individual store managers know local conditions best. A manager understands their store's customer profile, seasonal patterns and staffing needs far better than head office, so a budget they help set — for wages, stock and local promotion — is more realistic and resources are used where they add most value, reducing both waste and stock-outs. Second, delegated budgets can raise motivation. Being trusted with control of a real budget gives the store manager a sense of ownership, responsibility and recognition (linking to Herzberg's motivators), which can increase effort and commitment to hitting targets. There are limits — an inexperienced manager may set a poor budget, or may 'pad' it or overspend — so the chain must monitor performance through variance analysis. But used well, delegated budgets combine local knowledge with motivation, which is why large multi-site retailers commonly use them.

Incremental budgeting takes last year's budget and adjusts it by a small increment, while zero-based budgeting (ZBB) starts every budget from zero and forces each cost to be justified afresh. For a large, established manufacturer under rising cost pressure, switching to ZBB has clear attractions. Its biggest strength is cutting waste: incremental budgeting automatically carries forward any inefficiency built into past budgets, and after years of small annual increments a mature manufacturer may have accumulated significant slack. ZBB challenges every line, so unjustifiable spending — obsolete activities, over-generous departmental allocations — can be stripped out, directly easing the cost pressure. It also reallocates resources to the highest-value uses and discourages the 'spend up to the budget' behaviour that incremental systems encourage near year-end.

However, ZBB carries serious drawbacks, especially for a LARGE firm. Building every budget from zero across many departments is extremely time-consuming and expensive; the management hours consumed could themselves be a significant cost that partly offsets the savings. It requires skilled managers, can generate conflict as departments compete to justify funding, and may bias spending toward activities whose benefits are easy to quantify, starving harder-to-justify but strategically vital areas such as R&D, maintenance or staff training — risky for a manufacturer that depends on product quality and equipment reliability. Incremental budgeting, by contrast, is quick, cheap, stable and predictable, which a large organisation with many cost centres values.

On balance, a full permanent switch to ZBB is probably not the best response. The stronger recommendation is a hybrid: keep incremental budgeting for routine, stable costs but apply ZBB PERIODICALLY (for example every two to three years, or to targeted high-spend departments) to flush out accumulated waste without incurring its full cost every year. This captures most of the efficiency gain while limiting the management burden. The judgement is contingent: if the cost pressure is severe and threatens survival, a one-off full ZBB review is justified despite the effort; if the pressure is mild, the disruption of a complete switch would outweigh the benefit. The best answer therefore matches the intensity of the budgeting reform to the severity of the cost problem.

Before recommending action, the causes must be diagnosed, because the two adverse variances have very different origins. The $15,000 adverse revenue variance is driven mainly by the road closure cutting visitor numbers — a largely EXTERNAL, and probably temporary, cause. The$9,000 adverse energy variance is driven by a spike in gas prices — also external and outside the hotel's direct control. Recognising this matters: neither variance is evidence of poor management, so corrective action should target the specific causes rather than punishing staff.

For the revenue shortfall, possible corrective actions include targeted marketing to guests who can still reach the hotel by alternative routes, promotional packages or discounts to stimulate demand during the closure, developing local-market revenue (events, restaurant, spa) that does not depend on through-traffic, and partnering with online travel agents to widen reach. The benefit is recovering some lost bookings; the risk is that discounting cuts the average room rate and erodes the very revenue it is meant to protect, and that heavy spending is wasted if the closure ends soon. So the response should be proportionate to how long the closure will last.

For the energy variance, short-term action is limited because the gas price is uncontrollable, but the hotel can negotiate a fixed-price energy contract to cap future volatility, invest in energy-efficient heating, insulation and smart controls, and cut consumption in unused wings while occupancy is low. These reduce exposure to future price spikes rather than reversing this quarter's cost.

Overall, I recommend the hotel: (1) treat the road-closure revenue loss as largely temporary and respond with proportionate, targeted promotion rather than deep across-the-board discounting; (2) reduce energy consumption immediately in low-occupancy areas and negotiate a fixed-price energy deal to control future variances; and (3) flex its budget for the remainder of the closure so managers are not judged against an unrealistic plan. The recommendation is justified by the fact that both root causes are external and temporary: the priority is protecting cash and margin through the disruption while avoiding permanent, costly overreaction. If, however, the closure turned out to be permanent, a more fundamental strategic review (repositioning the hotel or restructuring its cost base) would be warranted.

Variance analysis compares budgeted figures with actual results and labels each difference favourable or adverse, giving managers a structured way to control the business. Its usefulness is real. It provides an early warning system: an adverse cost variance flags overspending quickly, allowing corrective action before small problems become large ones. It supports 'management by exception', letting managers focus attention on the items that deviate most from plan rather than reviewing everything. It aids accountability and control by tying variances to budget holders, and it feeds the monitoring and review that improve the next budget. For a firm with clear, quantifiable costs and revenues, it is a powerful and low-cost discipline.

However, variance analysis has important limitations. It only tells managers WHAT happened, not WHY — the causes still have to be investigated, and a variance can be badly misread if the cause is not understood (for example, treating a favourable wage variance as good management when it actually reflects lost sales and cut hours). It can be unfair if the budget was unrealistic or if actual output differed greatly from plan, unless the budget is flexed to actual activity. Many variances are caused by UNCONTROLLABLE external factors — commodity prices, exchange rates, a recession — so acting on them, or blaming managers for them, is pointless or even damaging. There is also a risk that a fixation on hitting budget numbers encourages short-termism, such as cutting maintenance or training to protect a cost variance. Finally, the analysis is only as good as the budget and the data behind it: 'garbage in, garbage out'.

On balance, variance analysis is a genuinely useful control tool, but it is a starting point rather than a conclusion. Its value depends on how it is used: it works well when the budget is realistic and preferably flexible, when managers investigate causes and distinguish controllable from uncontrollable factors before reacting, and when it is combined with qualitative judgement rather than used mechanically to reward or punish. Used in that way it strengthens control; used as a rigid scorecard it can mislead and demotivate. The strongest judgement is therefore conditional: variance analysis is useful IF the firm treats each variance as a question to investigate, not an automatic verdict.