Architecture and Infrastructure as foundations of Digital Taxation

Chapter 12. System Architecture and ICT Infrastructure Alternatives

ICT as a Strategic Tool to Leapfrog the Efficiency of Tax Administrations


Managing the IT strategy in a tax institution presents professional challenges that few other work environments can offer.

Its computer solutions have a target audience of thousands of users, and in medium-sized countries they are counted in millions of users.

As if this were not enough, we can mention a whole set of features that make the operation of these systems, real tests of planning, design and implementation.

  • Due dates and deadlines for periodic operations. Taxpayers must file their returns before these dates or there will likely face consequences in the form of late payments and fines. A poor response from computer systems at this time will lead to reactions of disapproval.

  • For a few years now, most countries have embarked on electronic invoicing projects. It is about receiving and issuing documents in real time, and where any delay affects the universe of economic activities that are being developed in the country.

  • Many times people think about the external services systems of the institution, forgetting that the daily tasks of a large organization must also be supported. Human Resources, Collections, Auditing, among many others.

  • From the above points, it is clear that we handle large volumes of information. They describe in detail the economic activity of an entire country. Just as important as the capture of this information is the use we will make of it. Identifying patterns and areas of interest will help define the country’s economic policies.

When reading about these features, we will surely remember talks, articles and technical papers from the last years with recurrent topics about Micro Services, Big Data, Scalability and Cloud Computing.

Are these the solution for the requirements of a Tax Administration?  They are undoubtedly excellent tools that can be used to meet the objectives mentioned, but like any tool, their use is applied to specific problems and a set of measures must be taken to maximize their efficiency and effectiveness.

Each reality implies a set of actions and technologies to be applied that must be selected. You must know and manage their strengths and weaknesses in order to select the best solution for each situation.


The first objective we face in every administration is to improve taxpayer service through digital means. Ten years ago, the challenge was for taxpayers to use digital media, today, the challenge is to have everyone using it.

We are interested in providing as many services as possible, and to the greatest number of taxpayers. Obviously, if our requirements grow, the traffic of information and the need for processing also grows. At the beginning we can accompany this growth with the improvement of our ICT equipment.  More powerful servers using faster and faster Internet connections certainly improve the performance of our systems.

But there will come a time when the improvements will not be significant, and updating our equipment will involve a major expenditure that cannot be justified by the results obtained. Add to that, the question is how we make this improvement. In an ideal scenario we can improve without the need for interruptions in the service provided, but the fact is that these equipment improvements often require suspending operations for the time consumed by the upgrade operation.

How did we come to this problem, what can we do to avoid falling into it?

We must identify and recognize the fundamental role that our systems’ architecture plays. A well designed system allows for expansion and the best use of available resources. It is the invisible component that ensures you will make the best use of the equipment available.

The first section of Chapter 12 aims to present us with architectural models that seek to produce high quality systems, ready to face the passage of time and increased demand from their users.


We have achieved it.  Our system is running correctly, its response times are as expected, the taxpayers are grateful and our management is improving.

But the national political and economic situation leads to modifications in the regulations, to coincide with the due dates for the presentation of Returns, Informative Statements and Payments receipts. Or perhaps the identification of new taxpayers or new criteria in their regard, make their number increase, and for each taxpayer, a new user.

Will we be able to cope with this increase in demand and maintain response levels?

The search for this answer leads us to the concept of scalability of systems, its definition will be presented, as well as its variants.

We addressed this issue because of the extreme case of unexpected increases in demand from users. But remember we mentioned that the tax feature leads to have dates within the period where the maturities of obligations cause sudden increases in the use of the systems. Therefore, a priori we will have to acquire computer equipment powerful enough to respond to the day of greatest demand in the period.  And the rest of the time? Will our equipment be idle? It would be ideal to be able to use it at that time to support other systems.

The chapter presents the concepts of scalability where its objective is not only to grow with demand, but to allow adjustment to demand, even in cases where it means reducing its size.


We have focused on our Taxpayer Service Tax System and reviewed the importance of its Architecture and Design. This allows us to scale it up according to users’ demands and provide good service.

But the Administration provides a variety of services, many for the execution of their officials, remember the areas of Collection, Control, Summary. Even for taxpayers, a variety of services are provided; it is natural that the Electronic Invoicing system is independent from the Tax Management system.

By applying the concepts to their architectures we can make each system efficient.

But we have other situations to deal with:

  • Software packages acquired from third parties, with their own structure and data.

  • Own systems developed long ago with other languages and architectures.

  • Use of information in Data Analysis Systems (BI, Big Data) for management analysis and management results.

All of these systems share unique concepts, for example, Taxpayer Identification, Registration data, tax compliance, tax returns. They may use it with particular approaches for their task, but much of this information is shared.

This is why we seek solutions to achieve that:

  • The systems can share the information that each one has with the other.

  • Avoid duplicating the same data, between several systems. In the sense of avoiding producing inconsistencies where one system has a value for certain information and we find that another system stores something different.

Various solutions are presented that have been applied over time to meet these objectives, such as Enterprise Service Bus (ESB), Service-Oriented Architecture (SOA), the use of this information in BI tools and Big Data, until culminating in an evolution of all these concepts, under the name of Master Data Management.

Data Governance

For years we have been participating in the explosion of the digital or information age. New areas of information where added to what began as a registry of taxpayers and their economic activities.

Gradually, we requested and received from the taxpayers more information about their management. Tax returns, detailed information on transactions made, financial statements, reports of results, and to today we digitalize the issuance of invoices and have a real time map of transactions that are made throughout the country, at all times. The search for information does not stop there, but expands into collaboration between public and private institutions. International treaties widen horizons even further, and we have sources of information from all over the world.

But having more information often does not translate into more knowledge. We need a process to transform all the information we receive or have available into knowledge that will make us better able to perform our tasks.

Something similar happens in institutions. We have immense volumes of information, but that does not automatically mean that its management will improve:

  • Is the quality of information good?

  • Is this information reaching the areas involved in an understandable and easy-to-use format?

  • Are we clear about the potential of the information we have? What can I achieve and what processes could I improve with it?

  • Am I doing it right as an institution? Do I have the ability to analyze my situation and determine weaknesses and strengths of my information management?

As you will see, our questions have led us from less to more, from more punctual analyses to existential doubts that would make the most tempered of philosophers tremble.

Fortunately this analysis has received much attention in recent times, and a maturity model has been developed, which is presented in the book under the name Data Governance.

This model will help us answer these questions and make the best use of the large volumes of information available.

Hardware, Networking and Cloud

Finally, all systems must run on computer equipment that will process the requested instructions, save or retrieve information from a storage site and communicate it to the users’ devices, through data networks responsible for transmitting the message quickly and reliably.

What used to be a clear separation of knowledge areas, such as hardware and software, has more and more in common and the borders are intermingled in hybrid solutions. Modern hardware has more and more software to define the conditions of its execution and the type of processing it must perform.

One of the first revolutions in the use of software in hardware has been the concept of virtualization. A single physical computer is divided into one or more virtual servers, each with a subset of the original physical server’s capabilities and the ability to run independently an operating system and the installed services. Remember we mentioned before situations where there are high demands on resources at special times, and we had to prepare our hardware, with more memory, processor or disk? Implementing these improvements involves physically working on the equipment, opening it and installing the components, often with the need to turn it off completely for as long as the operation takes. Virtualization offers us to become true strategists, and in something similar to a board game, distribute resources according to our needs. Increase or decrease a resource by editing a software configuration, and see its results immediately.

Now that we are starting to divide a physical computer into many virtual ones, are we using the most of their physical capabilities? Running one operating system for each of these instances seems to be an overload. We know that an operating system is responsible for many other routine tasks besides running systems. This is how the concept of containers was born, systems that run independently, sharing a single operating system instance that coordinates them.

Continuing this path of virtualization that we have been walking, we arrive at the following evolution of the concept: The Cloud.

We move away from the physical management of computer resources, to become resource managers and their configuration. The cloud offers us to leave behind the work of installation and maintenance of physical equipment.

All these alternatives are presented in the final part of chapter 12, together with the presentation of recommended architectures for the execution of high performance systems.


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Disclaimer. Readers are informed that the views, thoughts, and opinions expressed in the text belong solely to the author, and not necessarily to the author's employer, organization, committee or other group the author might be associated with, nor to the Executive Secretariat of CIAT. The author is also responsible for the precision and accuracy of data and sources.

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