Why the best business analysts are the ones who pick the best metaphors

Photo by Leks Quintero on Unsplash

About 6 years ago, I first read the book Images of Organization by Gareth Morgan. Since then, my view about business problems has totally changed, and now I see how much the main lesson of the book impacts my job as a business analyst at Hurb. In the book, the author uses metaphors to explain how organizations work. I’m going to describe how Hurb has made use of some of them and then share with you the metaphors I’ve used myself in two different projects: a tool that supports the decision-making process of buying air tickets for our travelers inspired by traffic signals and a cash flow simulator that helps us conceive our packages inspired by the FIFA 21 game.

First, a little bit about the book…

Images of Organization cover

Gareth Morgan studied hundreds of organizations and explained how most of them worked through eight simple metaphors that can be applied to almost every existing company. He compared organizations to:

• machines;
• organisms;
• brains;
• cultures;
• political systems;
• psychic prisons;
• flux and transformation;
• instruments of domination.

These comparisons are powerful because, as Morgan explains:

A metaphor is a way to create meaning for an element through experience related to another element.

Metaphors help us understand business problems that look too complicated at first. When we see their similarities to simple systems, problems become much simpler. The three metaphors presented in the book that I can associate with Hurb are machines, organisms, and political systems.

Machines

The most popular metaphor presented in the book is the image of a machine. Companies managed like machines have clear specific goals. Machines are planned in detail. There is a very explicit understanding of how goals will be achieved and the role of each part of the machine in achieving those goals. People are treated as parts of the machine. When the machine is not achieving its goal, parts are usually replaced or fixed.

The machine approach to management works well in the same conditions under which a machine would perform well:

• When there is a clear task to be performed;
• When the environment is stable and predictable enough so that what is produced fits what is needed (as everything is planned before and there is no much room for adapting what had been planned);
• When you want to keep delivering the same thing;
• When precision and efficiency are essential;
• When the human parts of the machine need to take orders and behave as planned.

Companies that work through franchising, surgical centers, and accounting offices are great examples of how machine-like management can work well. However, in most industries, this management style might fit specific company challenges. On the other hand, mechanistic organizations have a poor performance:

• When they need to adapt fast to changes (changes require planning the entire machine again);
• When they can’t have an answer to every possible situation (exceptional occasions are often ignored in mechanistic work environments);
• When fast communication is important (it’s hard to conciliate fast communication to rigid standards of communication channels and procedures);
• When proactive behavior is valued (people are encouraged to do only what is strictly defined as their jobs);
• When a systemic view is helpful (each piece/person does its job, and there is no space for looking at the organization as a whole).

As in every other company that I know, the machine metaphor is often used at Hurb (you don’t need to explicitly know the metaphor to use it). Hurb is a national price leader in a very competitive industry, and efficiency plays a key role in our strategy. A very common question in our company is: “who is the responsible CPF?” (CPF is the national ID in Brazil). This question emphasizes the importance of clear responsibilities, which is one of the characteristics of the machine metaphor. Although the machine metaphor has been helpful in our strategy, we implicitly know that we can’t innovate and be flexible enough being machines at all times. That’s why we might act like organisms as well.

Organisms

The organismic perspective has emerged as an alternative to most of the mechanistic problems. As organisms, organizations are open systems related to their environments. They have subsystems (similar to organs, cells, molecules, etc) that interrelate. Organism organizations can also be grouped in species, which helps us understand them through comparable cases.

The main advantages of seeing organizations as organisms are:

• This way, we understand how they relate to external forces;
• Aiming for survival and evolution is something that helps companies to have long term visions instead of simple goals;
• Organisms can be structured in a way that fits their environment;
• It helps managers diagnose problems (diseases) in their companies.

Some of the main disadvantages of this metaphor are:

• The metaphor might be too deterministic (it ignores the fact that companies themselves can shape their environments);
• Companies are not totally organized through a single unity (as organisms are), so interdependence between companies’ subsystems (departments, processes, people…) is exaggerated.

During my MBA, there was a lecture by our former Operations Director. Only by the way she described the company, I got how much of an organism Hurb is! She described how the different departments of the company were closely interrelated. This expectation was totally confirmed after I joined the company. In a single Black Friday planning meeting that I was involved in last year, there were people from about 6 different departments. If you can’t see how your job impacts other areas and our travelers, you risk failing your work.

Although both mechanistic and organismic perspectives are helpful when we want to coordinate the entire organization, they somehow ignore the fact that organizations are formed by people who also have their own interests. Hence, Hurb is no different from all the other companies in this sense. We’re political systems as well.

Political Systems

When we apply the image of political systems to organizations, we explore the different interests, conflicts, and power games that exist. In political systems, it’s important to know the prevalent power structure: autocracy (power centered in a single individual), bureaucracy (power originated from formal rules), technocracy (power originated from technical knowledge), or democracy (power shared among various shareholders and employees). Managers seek common ground between tasks, careers, and personal interests.

The political systems metaphor has helped organizations to understand the role of:

• Personal interests to influence the company decision-making process;
• Power in determining the functioning of the organization;
• Conflict management to guarantee a balance between company goals and personal interests;
• Integrating the company so that every department and employee will pursue the same objectives.

On the other side, the use of this metaphor might present some risks:

• Politicizing too much is dangerous as it’s possible to conciliate all interests of every single individual in the company in addition to the own company interests;
• While trying to understand the interests of each one, we might underestimate the power imbalance that exists in all companies (even in democracies).

We have big ambitions at Hurb, and we believe that we need to retain the best talents with us to realize them. We recognize our people as individuals who also think of themselves. We also believe that individual and collective goals can walk side by side most of the time.

That belief has made our People & Culture department and leadership busy. Two examples of this are the Wozniacki Program and our Business Analytics (BA) Development Trail. Both are career-related programs. Each Wozniacki round starts with a 180° evaluation of behavioral aspects expected from each career level, and then leaders use input from this evaluation to give feedback and promotions to employees.

In Business Analytics, we complement the Wozniacki company program with a development trail that consists of a matrix of career levels and BA-specific skills. It gives us a very clear picture of what is expected from us and what we can achieve in our career once we evolve as BA professionals in the company. Therefore, I kind of know what I’m going to hear before even entering a career follow-up meeting.

Another good example of how Hurb has managed its political system to retain talents is the Hurb Partners Program, explained in the video below.

The main lesson from the book

Of course, all the information provided by Images of Organization regarding each individual metaphor is valuable. From time to time, I end up turning back to the book and reading some pages again to remember something or get a deeper comprehension of a specific topic. However, I believe that the main lesson from the book is about the value of metaphors in business analyses. There is no “one size fits all” metaphor and there is more than just the eight metaphors presented in the book.

So a very important part of the job of a business analyst is to choose the metaphor that best matches the situation being analyzed. We do pick metaphors in our analyses even when we’re not aware of them. It’s totally possible for someone who hasn’t read Images of Organization to develop great metaphors in their analyses. The knowledge shared by Gareth Morgan through his book only makes us conscious of it and empowers us to make our own metaphors and use already known ones, as best as we can. This allowed me to do two different projects: the stop-and-go system for air ticket purchases and the package cash flow simulator.

Air tickets purchasing: stop and go

Selling attractive products such as travel packages might look easy but delivering them at the lowest cost in a very competitive market is a challenging task.

As part of our business model, our operators have some flexibility of dates when choosing a flight for our packages travelers. Travelers choose three preferred dates to travel and our operators usually have some months to send them a flight option that takes these preferences into consideration. This allows us to choose the cheapest air ticket that we can for a traveler, given the customers’ preferences and the destination constraints. However, if we don’t search enough, chances are we won’t find cheap air tickets. Alternatively, if we keep searching for a flight for too long and don’t find air tickets that are significantly cheaper, the process’ inefficiency won’t pay off. So balancing search time and air ticket cost is an everyday challenge for operators.

Then, after researching for an air ticket in our systems, an operator has three options:

1. Moving on and guaranteeing the air ticket that we’ll suggest to our customers;
2. Researching for another travel date for the same customer;
3. Delaying the flight research for that customer.

Any mistake made during the decision on one of these three options leads somehow to inefficiency, so the operator should be accurate on this part of the process. The problem is that sometimes operators depend so much on their own experience or on their colleagues’ experience to decide on it. So I associated this problem with a trivial similar decision we usually have to take in our lives: respecting traffic signals. Traffic signals are simple because they provide us with clear instructions of what to do in each case. In a traffic signal, there are also three options that have meanings that share some characteristics with our air ticket purchasing process:

1. Moving on with your car (green light);
2. Evaluating if you have time to move on with your car before the red sign appears (yellow light);
3. Stopping your car (red light).

Then my job was trying to transform the decision process of buying air tickets into something as similar to a traffic signal as possible. Traffic signals might use criteria related to time and sometimes a button pressed by pedestrians to change its colors.

In our case, one of the main criteria that influences the buying decision is cost. Another one is the process execution time. So I chose to use just the two of them in this project. First of all, I created cost limits for flights given each origin and destination that we use at Hurb. These limits were defined considering statistical methods related to our historic costs for the same origins and destinations. Then, I aligned a procedure with our Operations Department (the one responsible for buying the air tickets) based on the logic of traffic signals. After researching for a flight on a specific date, the operator should check for the green light (lower limit) and red light (upper limit) cost limits for the origin and destination being researched. Then they’d be presented with three options:

Stop and Go framework for purchasing air tickets

1. If the actual flight cost is under the green light, the operator can just move on and guarantee that flight for the customer (and then they are safe deciding not to spend more time researching alternative travel dates).
2. If the flight cost is between the green and red lights, the operator should research for an alternative travel date, among the customer preferences.
3. If the cost is above the red light, the operator should check for alternative dates, close to the ones chosen by the customer and if it’s not enough, they should discuss with their leadership what to do.

Package Cash Flow Simulator and FIFA 21

Before joining Hurb, I couldn’t imagine how complex the decision of creating a new package was. Our Package Department has to deal with variables related to our production capacity, destination constraints, demand, competition, strategic decisions… It might become even overwhelming to decide whether a package should be sold or not, what its price should be etc. Bad decision making related to these package settings could lead us to huge financial or market share losses or an enormous success.

So, in a meeting with our Package Team Lead, Rodrigo Andrade, our CX Director, Romario Melo, and our CEO João Ricardo, they told me that they wanted to anticipate what would happen to a package cash flow before starting to sell it. We concluded that we should develop a simulator to support the decisions related to a package cash flow.

Then I was given the challenge to parameterize all of our cash inflows and outflows so that our Package Team could make better decisions regarding package settings. The first step was to understand what all our cash streams related to packages were. So I kind of tracked the whole process from the acquisition of the customer until their travel, including customer service, and listed all these cash streams in a Miro diagram. Summing different types of cash inflows and outflows, I’d have to consider about 50 different variables in this simulator! Some of them are based on simple business rules but others are dependent on destination characteristics and require gathering historical data to be included in a simulation.

So I compared this complex task of making the package cash flow simulator to another much more familiar simulation: the FIFA 21 game by EA Sports. My goal is absolutely different from EA Sports final goal of entertaining people with FIFA, but our products (FIFA 21 and the package cash flow simulator) share the need of simulating a complex experience. In FIFA 21, users can be soccer players and managers at the same time. A match score in FIFA 21 is influenced by users’ ability, players’ characteristics, and some hazards. FIFA also simulates the soccer experience related to hiring and training players, players’ appearance and behavior, stadiums’ appearance, climate conditions etc.

Then my job was trying to learn as much as I could from a game that has simulated complex experiences for 28 years. My key takeaways from FIFA simulations were:

1. Nowadays, it’s a really complete simulator (they were even criticized for being too realistic in this FIFA 20 review from Wired), but in its first editions, the only things a user could do were: passing the ball, kicking the ball, and running with a player. And still the game was a success. If EA had waited to have all the resources it has nowadays to launch a first version, it would take forever to develop the game.
2. They’ve focused their resources on simulating more accurately what mattered the most for users. A good example of this is their players’ face scan program called Fifa Start Heads: a group of EA professionals visits some soccer clubs facilities to take photos of the players and replicate their appearance in the game. FIFA 21 features over 17,000 players from 5 continents. Imagine if they would try to scan 17,000 faces each time a new edition is launched! So they prioritized the most popular clubs and players in the world in this program and drew a less accurate appearance for the other ones.
3. The soccer experience couldn’t be simulated without any inputs from the user. If too much input was needed to play the game, some FIFA users who just want something closer to the basic “kicking-passing-running” dynamics would find it too complicated. That’s why FIFA 21 offers different game modes: in some, you just choose the two teams that are going to play and go straight to the match; while in others you must even attend press events and manage the team payroll!

Now the question is:

How do these 3 takeaways from FIFA 21 have helped me to simulate Hurb packages’ cash flow?

Illustrative image of our package cash flow simulator

First of all, I definitely wouldn’t have launched a first version of the simulator if I had tried to parameterize 50 different types of cash inflows and outflows in a first attempt. So I picked 11 of them to start with. After I launched this first version, I talked with my main stakeholders — the Package Team — about what was included in the model and what was missing and they pointed out to me what was still missing the most for them, so that these new features have become my priorities in this project.

Secondly, I had to admit that the simulator will never be 100% accurate in estimating costs. I know there are several methods for doing this and some are more sophisticated and harder to implement, while others are simple but much less accurate. So, again I recognized I had to prioritize costs and apply more accurate methods (such as exponential recency weighted average) to more significant costs like flight tickets and easier methods (such as simple average over past years’ results) to less significant costs like customer acquisition.

Finally, I knew this could become an exploratory tool for us, even to reflect about our package business rules. At the same time, some of the 11 variables I selected could only be estimated with some manual input, but not all of them mattered for all use cases so I made the entire bank slip (“boleto” in Portuguese) section optional. If you don’t use it, you won’t have a full-frame of the expected cash flow, but you’ll still get an estimate of some of the main cash inflows and outflows.

Having delivered a first version of this data product, I see how useful the FIFA 21 metaphor was in some parts of the project. Maybe the most obvious metaphor for this challenge would be facing it as a dashboard. Now it is still not totally different from a regular dashboard, but I know I wouldn’t deliver the same thing if I had tried to make it as a dashboard and it probably wouldn’t feel like a simulator. So, we’d miss the whole point about being able to anticipate decisions regarding our packages.

Using metaphors in our analyses

Maybe not all analyses deserve a metaphor. In some cases, you’ll know exactly what to do at the moment you identify the demand for a project. However, complex situations require us to compare them to similar situations we know much better, or similar challenges someone has already solved. As business analysts, we can use these similar situations and challenges to provide better solutions to our own challenges. Images of Organization presents ourselves with 8 widely used organizational metaphors, but we can and should create our own specific metaphors to improve the quality of our work.