How to Select the Right Project

Every agribusiness organization, whether a small farming cooperative or a large food processing company, faces the same fundamental challenge: too many potential projects and never enough resources to pursue them all. A new irrigation system, an organic product line, a cold storage facility, a market expansion – all may seem worthwhile. But which one do you actually choose? That’s where project selection comes in. It is the process of evaluating and choosing projects based on their potential benefits and alignment with organizational goals – and having a structured approach to it makes all the difference.

Why project selection matters
The two broad categories of project selection models
Non-numeric project selection models
The sacred cow model
Operating necessity model
Competitive necessity model
Product line extension model
Comparative benefit model
Numeric project selection models
Payback period
Net present value (NPV)
Internal rate of return (IRR)
Profitability index (PI) and benefit-cost ratio (BCR)
Weighted factor scoring model
Criteria for a good selection model
Choosing the right model: numeric vs. non-numeric
A practical example from agribusiness

Why project selection matters

Choosing the wrong project doesn’t just waste money – it consumes time, people, and opportunity. Effective project selection ensures that resources like budget, manpower, and time are directed toward initiatives that offer the highest strategic value, rather than being spread thin across too many low-priority activities. For agribusiness organizations operating in resource-constrained environments, this is especially critical.

A well-chosen project aligns with the organization’s overall vision, maximizes return on investment, manages risk upfront, and avoids resource wastage on projects that offer little strategic value. Poor project selection, on the other hand, leads to missed market opportunities and weakened competitive positioning.

It is also important to keep in mind that models do not make decisions – people do. Selection models are tools that support decision-making; they do not replace managerial judgment.

The two broad categories of project selection models

Project selection models fall into two major categories: non-numeric models and numeric models. Non-numeric models do not use numbers for decision-making, while numeric models incorporate financial information and objective data to evaluate projects. Many organizations use both approaches simultaneously, or combine elements of each, depending on the nature of the project.

Non-numeric project selection models

Non-numeric project selection models use discussions, expert opinions, and subjective evaluation as the primary basis for selecting a project. These models are not based on quantitative techniques, which makes them particularly useful when the benefits of a project are difficult to measure in financial terms – such as environmental sustainability, community impact, or regulatory compliance.

The sacred cow model

This is one of the most common real-world selection approaches, even if it’s rarely labelled officially. The project is suggested by a senior and powerful official in the organization, often with a casual remark like “why don’t you look into this,” followed by an undeveloped idea for a new product, a new market, or a major operational change. Once proposed by an influential figure, the project is typically treated as non-negotiable. It proceeds until either it succeeds or the sponsor personally acknowledges failure. While this model can bring bold ideas to life, it carries the risk of bypassing rigorous evaluation.

Operating necessity model

In this model, the project is required to keep the system running. If a flood damages a grain storage facility, you don’t evaluate the repair project against financial benchmarks – you simply do it because the operation cannot continue without it. The urgency of operational survival justifies the expenditure without detailed analysis. In agribusiness, this might apply to emergency borewell repairs during a drought or replacing a broken cold chain unit during harvest season.

Competitive necessity model

Sometimes a project is not driven by internal breakdown but by external pressure. The competitive necessity model applies when a project is necessary to help the business maintain a competitive advantage over other companies. If competitors have adopted precision farming technologies and your organization hasn’t, you may be compelled to invest – not because the financial case is iron-clad, but because falling behind is not an option. The decision is strategic, not strictly financial.

Product line extension model

In this model, projects are judged on how well they fit with the current product line, fill a gap, strengthen a weak link, or extend the line in a new desirable direction. For example, a company that already sells packaged pulses may evaluate a project to launch organic lentils based on how naturally it fits within the existing portfolio – distribution network, customer base, packaging infrastructure – rather than solely on projected profits.

Comparative benefit model

In this model, senior management evaluates several candidate projects and selects the subset that would provide the most benefit to the company. There is no formula here – the selection committee members weigh in and pick the project they collectively believe will benefit the organization most. It is broad, qualitative, and depends heavily on organizational experience and judgment.

Numeric project selection models

Most firms consider numeric models more useful than non-numeric models because they bring objectivity and measurability to project decisions. These models are especially relevant when comparing competing investment proposals with clear financial outcomes.

Payback period

This is the simplest and most widely understood numeric model. The payback period indicates the number of years required to recover the initial project investment, calculated as: Initial Investment ÷ Annual Cash Inflow. A shorter payback period signals lower risk. However, the payback period does not account for the time value of money or cash flows beyond the payback period, which limits its use for long-term investment decisions.

Net present value (NPV)

Net Present Value measures whether an investment creates or destroys value by comparing the present value of future cash inflows to the initial investment. A positive NPV means the project is expected to add value; a negative NPV suggests it may not be worth pursuing. NPV accounts for the time value of money, making it more reliable for evaluating long-term projects and large capital investments – such as building cold storage, setting up processing plants, or investing in irrigation infrastructure.

Internal rate of return (IRR)

IRR represents the break-even discount rate for a project – the rate at which the NPV equals zero. Companies commonly use IRR to compare potential investments and determine whether a project’s expected return meets or exceeds the company’s required rate of return, also known as the hurdle rate. If a project’s IRR is higher than the hurdle rate, it is generally considered worthwhile. IRR is expressed as a percentage, which makes it easier to compare projects of different sizes.

Profitability index (PI) and benefit-cost ratio (BCR)

The Profitability Index measures the value a project creates for every dollar invested, making it especially useful when companies must choose between multiple projects but have limited capital. A PI greater than 1 (or a BCR greater than 1) indicates the project’s benefits outweigh its costs. This model is particularly relevant in agribusiness projects with public or community benefits – such as sustainable farming schemes or rural infrastructure development – where not all returns are purely financial.

Weighted factor scoring model

This model bridges the gap between purely subjective and purely financial approaches. In a weighted factor scoring model, each criterion selected by management is assigned a numeric weight reflecting its relative importance, and each project receives a score that is the weighted sum of its grades across all criteria. Criteria might include payoff potential, risk level, strategic alignment, safety, and competitive advantage. The project with the highest total weighted score is recommended. This model allows multiple dimensions to be assessed simultaneously and can be adjusted as organizational priorities shift.

Criteria for a good selection model

Not every model is suitable for every situation. A good project selection model should be realistic, capable, flexible, easy to use, cost-effective, and easy to computerize. Beyond the model itself, the selection process should evaluate each project against a consistent set of criteria. Common evaluation criteria include return on investment, payback period, net present value, strategic alignment, risk level, resource requirements, and longevity – each weighted according to what matters most to the organization at that point in time.

Choosing the right model: numeric vs. non-numeric

The choice between numeric and non-numeric models is not always straightforward, and in practice, the two approaches are often used together. Organizations assess projects by evaluating both quantitative and qualitative factors, including technical feasibility, market potential, economic viability, and strategic alignment with organizational goals.

As a practical guide: when a project has clearly defined financial metrics – equipment investment, new facility construction, technology adoption – numeric models like NPV and IRR provide the most reliable basis for comparison. When the benefits are harder to quantify – community development, environmental compliance, brand positioning – non-numeric models offer a more appropriate framework. By considering a range of financial metrics alongside qualitative factors, organizations can make more informed investment decisions that align with their strategic objectives and risk appetite.

It is also worth noting the importance of strategic alignment across both approaches. A good project should not reflect only tactical excellence, but also strategic importance. First and foremost, organizations should choose projects that align with their overall strategy – because the more a project moves the organization in the direction it wants to go, the more meaningful and defensible the selection decision becomes.

A practical example from agribusiness

Consider a farming cooperative evaluating two proposals: investing in drip irrigation to improve water efficiency, or launching a new line of organic packaged products. Using a weighted scoring model, the cooperative can evaluate both against criteria like strategic alignment, environmental impact, financial return, and market demand. The irrigation project may score higher on environmental grounds; the organic line may score higher on profitability potential. The NPV and IRR calculations can then give the cooperative a clearer picture of financial viability for each. Combining both analyses leads to a well-rounded, defensible decision – one that is neither purely gut-driven nor purely number-crunching.

For the process of project evaluation and selection to work effectively, four key functions must be performed: analyzing project data and constraints, interpreting results, selecting appropriate options, and refining the selection. This iterative approach ensures that the final decision is grounded in both evidence and organizational context.

What do you think? When your organization evaluates new projects, do you rely more on financial data or on strategic and qualitative judgment – and do you think that balance serves you well? If you had to choose between two projects with similar NPVs but very different strategic implications, what would ultimately tip your decision?

References

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Table of Contents

Why project selection matters 🔗

The two broad categories of project selection models 🔗

Non-numeric project selection models 🔗

The sacred cow model 🔗

Operating necessity model 🔗

Competitive necessity model 🔗

Product line extension model 🔗

Comparative benefit model 🔗

Numeric project selection models 🔗

Payback period 🔗

Net present value (NPV) 🔗

Internal rate of return (IRR) 🔗

Profitability index (PI) and benefit-cost ratio (BCR) 🔗

Weighted factor scoring model 🔗

Criteria for a good selection model 🔗

Choosing the right model: numeric vs. non-numeric 🔗

A practical example from agribusiness 🔗