A customer asks for another report in Odoo, saying the data is already there. That same week, the production team receives a rush order that needs to jump the queue. Both look like chances to earn more, but each needs people or machines already committed to other work.
Before saying yes, I would look beyond the price of the new job. Is the customer actually ready to buy? What work would this displace? What would we have to spend, and would the money arrive in time to cover it? Basic economics connects these questions.
This article offers a way to think through those decisions for business owners and team leads in contract software development, system integration (SI), Odoo partnerships, and software houses, alongside a manufacturing comparison. We will start with constraints and choices, then look at incentives, demand, supply, marginal cost, and the difference between output, profit, and cash.
I suggest keeping one decision you are facing in mind as you read, so you can apply each idea to the same question. Every example here is hypothetical, not a company result or a real customer case.
Scarce resources force a choice about what to give up
Economics studies how we choose to use scarce resources. Scarcity does not always mean a company lacks money. It may have a hiring budget but be unable to find an expert in a legacy system before delivery. A factory may have workers available but only one specialized machine.
Every choice involves a trade-off. Taking a rush job may delay an internal tool. Making a larger batch may reduce machine setup time but tie up cash in materials and inventory for longer. What we give up may be money, time, quality, or the flexibility to take the next job.
I start by identifying the actual constraint. If the hold-up is design approval, adding programmers may not move the work faster. If a machine is waiting for materials, longer shifts may not increase what can be shipped.
These are microeconomic questions about decisions by buyers, producers, and markets. Macroeconomics looks at the wider picture, including inflation, interest rates, and employment. Those forces matter to a business too, but we need to understand their mechanisms rather than assume a national indicator tells us immediately whether to accept a particular project. Read the introduction in OpenStax 1.2
Opportunity cost is the best alternative we give up
Opportunity cost is the value of the best alternative forgone when we choose something else. An expert may spend a day fixing an existing customer’s problem or designing a system for a new project. If we choose the first task, the second may be the opportunity cost of that decision.
We do not add up the value of every job we could not do: the same hours cannot be spent on all of them. Nor should we count wages twice without a reason. Separate the cash costs from the value of the forgone alternative before comparing options.
A hypothetical software house example
Suppose that next week one specialist has 12 hours available for these two jobs after setting aside time for existing commitments. In this example, either job can use that person’s skills, and each needs all 12 hours. The team can therefore do only one of them that week.
Job A updates a report for an existing customer. It adds THB 30,000 in revenue and THB 6,000 in cash spending caused by the job, leaving THB 24,000 before the company’s existing expenses.
Job B builds an integration prototype. It adds THB 40,000 in revenue and THB 10,000 in cash spending, leaving THB 30,000 on the same basis of comparison.
If we choose A, the opportunity cost is THB 30,000
This comparison assumes equal chances of payment, risk, quality, and effects on customer relationships, as well as unchanged regular wages and existing expenses. If we choose A, the value of B forgone is THB 30,000;B would yield THB 6,000 more The opportunity cost is not B’s full THB 40,000 in sales, because doing B also incurs additional costs.
These THB 24,000 and THB 30,000 figures are not the company’s net profit. They are additional revenue less additional cash spending under the stated assumptions. They help compare this particular choice; they are not a pricing formula for every kind of job.
In practice, A might be urgent because it affects a core system, or B might carry more risk. The calculation shows the price of a choice, but the decision maker still needs to explain the factors outside the numbers.
A hypothetical manufacturing example
Suppose one machine has another eight hours available after the existing schedule. It can produce 10 units of product A or five units of product B per hour. Assume those rates stay constant, there is no extra changeover time, materials and labor are ready, and every unit meets quality standards.
If we spend all eight hours on A, we make 80 units but give up 40 units of B. In this example, the opportunity cost of one additional unit of A is half a unit of B.
Because these are different products, the higher unit count alone cannot tell us to choose A. We still need to compare orders, deadlines, revenue, additional spending, and other conditions. Different mold changeover times or defect rates would require a new calculation using the actual facts.
Factories and software teams can ask similar questions, but their units and conditions differ. Developers are not necessarily interchangeable, and more working hours do not necessarily produce a proportional increase in work that passes testing.
Incentives change behavior within a system
An incentive is a benefit or cost that makes one choice more or less attractive. It may take the form of pay, a deadline, workload, or a chance of future work. This idea helps us ask what people have reason to do under a company’s rules.
Suppose salespeople are paid solely for signed contract value. The team might be encouraged to close a deal before the scope is clear. Or if developers are measured by the number of tickets closed, they might favor small, easy tickets. These are risks to check against actual behavior, not accusations that every employee will act that way.
Manufacturing has a similar problem. If rewards depend on units produced without checking defects, rework, or safety, the drive for volume can shift the burden to the next stage.
Before raising a target, I would ask how much control the worker has over the measure and whether there are quality checks, such as work actually accepted, a reviewed scope, or units that pass inspection. Good rules also require us to watch what happens afterward. One metric cannot describe the whole system.
Look at demand, supply, and price together
Demand describes the relationship between price and the quantity buyers are willing and able to buy over a given period. Someone interested in a system but without a budget or approval authority is not yet a sale ready to happen. Inquiries can be a starting signal, but they are not purchases.
When the price of a good or service changes while other factors stay constant, we are looking at a change in quantity demanded along the existing demand curve. Changes in budgets, needs, or the prices of alternatives may shift the whole curve. Keeping these apart stops us from assuming a sales decline was caused by our price alone.
Supply looks at how much sellers are willing and able to offer at each price. Production capacity is one constraint, but it is not the whole of supply. A factory may have an idle machine yet reject a price below its relevant costs. An SI team may have free people who lack the skills a project requires.
In a basic market model, equilibrium is the price and quantity at which buying and selling plans align under the stated conditions. Equilibrium does not prove that the price is fair or that every business will make a profit.
Contract software work needs particular care: proposals may differ in scope, data migration, quality, and support after delivery. Averaging several quotes does not instantly give us an “equilibrium price.” Manufacturers also need to compare material grades, tolerances, and delivery terms before comparing prices.
Useful questions are: What alternatives is the customer comparing? What budget and readiness to buy do they have? Do the quoted prices cover the same thing? See the definitions of demand, supply, and equilibrium and other factors that shift the curves
For one more job, compare what it adds and costs
Marginal analysis asks how benefits and costs change if we do a little more or less. For work that cannot be divided into small identical units, compare the consequences of the whole project or batch rather than pretend every project is the same unit.
An Odoo report using existing data can still require analysis, access-right testing, delivery, and ongoing support. Its added cost is more than the time spent writing the report. A factory’s special order may add materials, machine setup, quality inspection, and rush shipping.
Average cost gives an overall picture, but it cannot stand in for the added cost of this decision. If a factory has spare capacity, the incremental cost of a special batch may differ greatly from its historical average. If capacity is full, the opportunity cost of displaced work matters too.
It is therefore not enough for a job’s added revenue to exceed its added cash spending. We must also consider quality obligations, risk, and opportunity costs not yet counted, without counting the same cost twice. We need to consider the longer-term effect on the business as well. Existing expenses unchanged by this job still need revenue to cover them overall.
I use the marginal view to answer “Should we take this additional job?” Total costs and a market plan help answer a different question: “Can this business model last?” The questions use related information but cover different scopes. Marginal analysis basics in OpenStax 2.1 and average and marginal costs in 7.3
Money already spent differs from costs we can still avoid
A sunk cost is a cost already incurred that cannot be recovered. A decision about continuing should therefore consider benefits and costs from this point forward, rather than continue only because past spending feels hard to abandon. OpenStax 2.1 discusses sunk costs
Suppose a team has spent time developing an internal module, but another option now meets the need better. The unrecoverable time is in the past. Future migration costs, contract termination penalties, and support obligations under each option still need comparison.
A manufacturer may already have bought a mold. The decision to produce more should depend on orders and future costs. But if the mold can be resold, its resale value remains an available alternative, so its full purchase cost is not sunk.
Fixed cost and sunk cost are different concepts. Rent or a monthly service fee may be fixed for a period, but we need to check when it can be canceled, whether any payment is refundable, and what commitments remain. The sunk-cost principle does not authorize abandoning contracts or obligations to customers.
Short run and long run depend on what can change
Production theory looks at how inputs become goods or services. Manufacturing uses labor, machines, materials, and work methods. Software businesses also use skills, time, tools, infrastructure, and customer information.
In the short run, at least one input cannot be adjusted. In the long run, all inputs can be changed. There is no fixed number of months or years separating the two. Read more in OpenStax 7.2
An SI team may add subcontractors but be unable to find another design reviewer who knows the old system before the deadline. A factory may add shift workers but not another machine in time. A remaining constraint can make additional people add less output than expected.
With a longer time frame, options may include training people, changing the process, buying equipment, or redesigning a system. Write the decision about fixing this week’s work separately from the investment decision for next year.
Productivity, revenue, profit, and cash answer different questions
Productivity compares output with the inputs used, so define the unit and quality first. A factory might measure units passing inspection per machine hour while also tracking defects. A software team might track accepted work, delivery time, and post-launch problems without assuming all tasks are equally difficult.
Lines of code, closed tickets, or recorded hours provide some information but cannot represent all the value a customer receives. For an Odoo Partner, a standard feature instead of custom development might meet the need with less code. The actual requirements, risks, and support burden still need comparison.
Revenue records the value of sales under the accounting rules being used. Profit compares revenue with expenses. Cash tracks money actually received and paid. Work that has generated recognized revenue or profit may still be unpaid, and a deposit received is not all immediate profit.
Economics also considers opportunity costs missing from accounting expenses, such as an owner’s time that could be used elsewhere. Take care not to count the same item twice. OpenStax 7.1 explains accounting versus economic costs and profit
Software projects therefore need delivery and collection schedules side by side. A factory also needs to know when materials must be paid for, how much product can actually be sold, and when the customer will pay. Faster work helps, but it does not automatically increase profit or cash.
Use a one-page decision sheet before taking work or adding capacity
I want these basic ideas to lead to clearer decisions in meetings. Try this table with one real job, and record both the sources of the numbers and who needs to confirm them.
| Question before deciding | Software / SI / Odoo team | Production team |
|---|---|---|
| Who wants to buy, and what terms need confirmation? | Budget, approver, scope, and acceptance criteria | Purchase order, specifications, quantity, and due date |
| Which resource is scarce, and what alternative is displaced? | Specialists, testing time, and existing work pushed aside | Machine hours, materials, and an existing batch delayed |
| Which benefits and costs change because of this choice? | Added revenue, testing, service fees, and support duties | Added revenue, materials, setup, scrap, and shipping |
| What has already been spent, and what can still be avoided? | Past development versus migration costs and commitments | Past mold spending versus resale value and cancellation costs |
| What might the rules encourage people to overemphasize? | Contract value, tickets closed, and the quality of accepted work | Unit count, defects, rework, and safety |
| When does cash move, and what if the forecast is wrong? | Billing milestones, reserves, and scope-review points | Material payments, inventory, customer credit, and a backup plan |
Separate known facts from estimates in the table. Do not treat uncertain benefits as guaranteed revenue. Test what happens if the job takes longer, the customer pays later, or defects increase, and see where your decision changes.
A model helps organize reasons, but it cannot supply missing facts. If the conclusion depends heavily on an assumption, gather better information about it or set a review point instead of adding decimal places to a weak estimate.
The next episode will look more closely at production theory and marginal returns: why adding people or hours may fail to increase output in proportion. Demand, elasticity, pricing, and the macroeconomic picture will get separate episodes so there is room for examples and limits in each.
Frequently asked questions
How does basic economics help software and production businesses?
It helps identify the choice, the constraint, which benefits and costs change with each option, and what opportunity is forgone. It can inform job acceptance, pricing, capacity, and investment, provided the units and conditions match the work. Hours or unit counts alone should not decide.
Does a lot of interest mean buyers are ready to purchase?
Not necessarily. Demand requires both willingness and ability to buy at the price and during the period being considered. Check budget, approval authority, need, and the customer’s alternatives before turning interest into a sales forecast.
Should we take every job whose added revenue exceeds added spending?
First check whether all relevant costs are included, along with opportunity cost, quality, risk, obligations, and cash timing. A job may look worthwhile on short-term cash figures while displacing a better one or causing a missed commitment to an existing customer.
Sources of the ideas
This episode explains scarcity, opportunity cost, incentives, demand, supply, marginal analysis, and costs as questions to ask before accepting work or increasing production. It does not cover all of introductory economics.
For the definitions and basic frameworks, see OpenStax, Principles of Economics 3e, through the links in each section. The business situations, examples of team rules, and decision sheet are my applications using hypothetical cases to prompt a review of real work. They are not experiments proving that every organization will get the same result.
