The Three Critical Phases of Decision Making in Management

Every manager in the tourism and hospitality sector makes dozens of decisions every day, from setting room rates during peak season to handling a sudden cancellation by a tour group. Behind every effective choice lies a structured thought process. Nobel laureate Herbert A. Simon, one of the most influential thinkers in administrative theory, simplified this process into three clear phases: Intelligence, Design, and Choice. Understanding these phases helps managers move beyond gut feeling and approach problems in a methodical way that consistently produces better outcomes.

Who was Herbert Simon and why does his model matter? 🔗

Herbert Alexander Simon was an American economist and political scientist who spent most of his career at Carnegie Mellon University. He received the Nobel Prize in Economics in 1978 and the Turing Award in 1975, making him one of the rare scholars recognized at the highest levels in both economics and computer science. His central interest was how human beings actually make decisions inside organizations, not how textbooks assume they do.

Simon broke from earlier theories that assumed managers had unlimited time, perfect information, and flawless logic. Instead, he introduced the idea of bounded rationality, which acknowledges that real people work with limited data, time pressure, and cognitive limits. Within these constraints, his three-phase model gives managers a workable map. Simon originally proposed the three phases of intelligence, design, and choice in 1977, and later added a fourth phase, implementation, in 1997. The original three remain the heart of the framework studied in management courses today.

Phase 1: Intelligence activity 🔗

The intelligence phase is where decision-making begins. The word “intelligence” here is used in the military sense of gathering information, not in the sense of being clever. The intelligence phase begins with the identification of organizational goals and objectives related to issues of concern, and the determination of whether those goals are being met. Problems occur because of dissatisfaction with the status quo, which is the gap between what people desire and what is actually occurring.

For a tourism manager, this phase is about scanning the environment, spotting that something is off, and then digging deep enough to truly understand what is going on. A hotel general manager might notice that occupancy rates have dropped 12% compared to the same quarter last year. That observation is only the symptom. The real intelligence work begins when the manager starts asking why.

What happens during the intelligence phase 🔗

This phase involves three core activities. First, the manager identifies the problem or opportunity. Second, raw data is collected from internal sources like booking systems, guest feedback, financial reports, and staff observations, as well as external sources like competitor pricing, online reviews, and tourism board statistics. Third, the data is examined, sorted, and analysed to define the actual problem in precise terms.

An important insight here is that what looks like a problem is often only a symptom. Real-world problems are usually complicated by many interrelated factors, so it is sometimes difficult to distinguish between symptoms and the real problem. Falling occupancy might be caused by a new competitor, an outdated property, poor online reviews, a downturn in the regional tourism market, or even a change in flight connectivity to the city. Skipping the intelligence phase and jumping straight to “let us cut prices” is one of the most common and expensive mistakes in hospitality.

How tourism managers gather intelligence 🔗

Modern tourism businesses use a mix of traditional and digital tools during this phase. Property management systems reveal booking patterns. Channel managers show how online travel agencies are performing. Guest feedback platforms surface recurring complaints. Hotels and restaurants use predictive analytics to forecast demand, dynamic pricing models to adjust rates, and sentiment analysis to gauge guest satisfaction in real time. Beyond technology, conversations with frontline staff and direct observation of guest behaviour remain valuable sources of intelligence that no dashboard can fully replace.

Phase 2: Design activity 🔗

Once the problem has been clearly defined, the design phase begins. This is the creative core of the decision-making process. Here, the manager invents, develops, and analyses possible solutions. According to Simon’s framework, design is about generating alternatives and testing whether each one is feasible to implement.

A common pitfall is to settle on the first idea that comes to mind. The whole point of the design phase is to deliberately produce multiple options, even when the answer seems obvious. If a tour operator is losing market share to online travel platforms, the design phase might produce alternatives such as launching a direct booking website with loyalty discounts, partnering with a major OTA on better terms, building niche product packages that platforms cannot replicate, or restructuring the sales team to focus on corporate clients.

Generating and evaluating alternatives 🔗

The design phase has two halves. The first half is about coming up with options through brainstorming, benchmarking competitors, consulting industry reports, and tapping into the expertise of the team. The second half is about evaluating each option against criteria such as cost, feasibility, time to implement, and alignment with the property’s brand. A lot of creativity and innovation is required to design solutions, and at this stage the solutions are only outlines meant for analysis of their suitability. The manager is not committing to anything yet, only mapping out what is possible.

Tools that support the design phase 🔗

Several structured techniques help tourism managers generate and analyse alternatives during this phase. SWOT analysis examines strengths, weaknesses, opportunities, and threats for each proposed solution. Cost-benefit analysis quantifies financial trade-offs. Scenario planning explores how each option might play out under different market conditions. AI tools can support the design and evaluation of tourism development plans by processing large datasets, generating strategic insights, and facilitating scenario simulations, and when combined with methods such as the Analytic Hierarchy Process, they can help build goal hierarchies and prioritise strategic objectives. The design phase is also where models, simulations, and pilot tests come into play, especially for capital-intensive decisions like opening a new property or launching a new tour product.

Phase 3: Choice activity 🔗

The choice phase is the moment of decision. After the alternatives have been designed and analysed, the manager applies a selection criterion and picks the option that best satisfies it. The criterion can be maximum profit, least cost, minimum waste, least time taken, or highest utility, and the criterion is applied to the various decision alternatives so the one which satisfies the most is selected.

In the tourism industry, the chosen criterion often combines several factors. A resort manager picking between two renovation plans might weight return on investment, guest experience improvement, sustainability impact, and time to completion. A travel agency deciding which destination to push during the next campaign cycle might weight margin, demand forecast, supplier reliability, and brand fit. The choice is rarely about one perfect answer; it is about the option that best satisfies the weighted set of criteria.

Satisficing rather than optimising 🔗

Simon coined another important term that comes alive in this phase: satisficing. Because of bounded rationality, managers rarely have the time or information to find the absolute optimal solution. Instead, they look for an option that is good enough, one that meets the threshold of acceptability across the criteria that matter most. A front office manager dealing with an overbooking situation at 9 pm does not run a multi-month optimisation study. They satisfice by choosing the upgrade-and-apologise option that protects guest goodwill within the constraints of the moment.

When the choice does not work out 🔗

One of the most useful aspects of Simon’s framework is that it is not strictly linear. There is a continuous flow of activity from intelligence to design and from design to choice, but at any phase there may be a return to a previous phase for validation, verification, and refinement. If the chosen alternative fails to deliver, the manager loops back to intelligence to gather more data, refine the problem definition, redesign alternatives, and choose again. This feedback loop is what makes the model practical for the messy, fast-changing reality of tourism operations.

Putting the three phases to work in tourism 🔗

To see how the three phases connect, consider a heritage hotel in Rajasthan whose direct bookings have been declining for two consecutive quarters. In the intelligence phase, the management team pulls booking data, reads recent guest reviews, studies competitor websites, and discovers that the property’s online experience is dated, photography is poor, and the booking engine is not mobile friendly. The real problem is not pricing; it is digital presentation.

In the design phase, the team generates alternatives such as commissioning a complete website redesign, investing in professional photography and video, partnering with influencers to build social proof, or shifting marketing budget toward metasearch advertising. Each alternative is assessed on cost, time, and expected impact on direct bookings.

In the choice phase, the team selects a combination of the website overhaul plus new photography because it satisfies the criteria of long-term brand value, reasonable cost, and measurable impact within six months. If three months in the data shows insufficient progress, the loop back to intelligence begins again.

Why this framework remains relevant 🔗

Even in an era of artificial intelligence and predictive analytics, the three-phase structure holds. A Decision Support System enhances the decision-making process by providing decision-makers with relevant and timely information as well as various modeling and analysis techniques, and is typically designed to support semi-structured or unstructured decision-making tasks where decisions are not routine and require subjective judgment, intuition, and creativity. AI tools speed up data gathering in the intelligence phase, simulate scenarios in the design phase, and recommend options in the choice phase, but the underlying logic of moving from understanding to designing to choosing remains a human responsibility.

For students and aspiring tourism managers, internalising these three phases is more than an academic exercise. It is a practical discipline that prevents reactive decisions, encourages thorough analysis, and builds the habit of revisiting choices when results disappoint. Whether the decision is as small as adjusting a breakfast menu or as large as expanding into a new destination, the same structure applies.

What do you think? Looking back at a recent decision in your own work or studies, can you identify which of the three phases received the least attention, and how might the outcome have changed if that phase had been more thorough? Which phase do you find hardest to slow down for when the pressure to act quickly is high?

References

1. https://www.informit.com/articles/article.aspx?p=2992600&seqNum=2
2. https://www.researchgate.net/figure/Description-of-Simons-model-of-the-process-of-decision-making-retrieved-from_fig1_345604784
3. https://www.cesarritzcolleges.edu/en/news/data-driven-decision-making/
4. https://www.scribd.com/document/348598552/Simon
5. https://www.frontiersin.org/journals/artificial-intelligence/articles/10.3389/frai.2025.1599391/full
6. https://www.scribd.com/doc/53044372/SIMONS-3-STAGE-MODEL
7. https://phonesuite.com/articles/decision-support-system-dss-how-it-can-help-optimize-important-hotel-decision/