By Dileep Verma (Research Expert, Associate Editor of Track2Training, New Delhi, India)

For many PhD scholars, choosing statistical software becomes one of the first difficult decisions in quantitative research. A researcher may have collected hundreds of questionnaires or downloaded years of economic and institutional data, but the next question is often less clear: Which software should I use for data analysis?

SmartPLS, IBM SPSS Statistics, and Stata are three widely used options. However, there is no single “best” software for every PhD thesis. The right choice depends on the research questions, type of variables, theoretical model, statistical technique, and nature of the data.

A common mistake among early researchers is to choose software simply because their supervisor, friend, or department uses it. A better approach is to first identify what the study needs to estimate and then select the software that can perform that analysis appropriately.

Start with Your Research Design, Not the Software

Before comparing SmartPLS, SPSS, and Stata, researchers should understand the difference between data type and analytical method.

Primary data are collected directly for a particular study. Surveys, questionnaires, interviews, experiments, and observations are common examples. In quantitative social science research, questionnaires often measure concepts that researchers cannot observe directly, such as social inclusion, institutional trust, job satisfaction, perceived discrimination, human dignity, or consumer attitudes.

Researchers commonly call these concepts latent constructs. Multiple questionnaire items may measure each construct.

Secondary data, in contrast, already exist before the researcher begins the study. Government databases, Census records, National Sample Survey data, company financial statements, administrative records, and international development databases are examples.

But this distinction alone should not determine the software. A primary survey can be analysed using SPSS or Stata, while secondary datasets can sometimes form part of structural equation models. The central question is therefore: What statistical model does your research require?

SmartPLS: Useful for PLS-SEM Research

SmartPLS is particularly useful when a researcher wants to estimate Partial Least Squares Structural Equation Modeling (PLS-SEM).

PLS-SEM allows researchers to examine relationships among multiple constructs while also assessing how well observed indicators measure those constructs. Hair et al. (2022) explain that researchers using PLS-SEM need to evaluate both the measurement model and structural model.

This makes SmartPLS attractive for survey-based research in management, marketing, information systems, psychology, education, and other social sciences.

Suppose a researcher wants to examine whether institutional inclusion improves human dignity and whether human dignity subsequently influences perceived well-being. Each concept may have several questionnaire items. A simple regression using an average score cannot provide the same measurement-model assessment that SEM offers.

SmartPLS allows researchers to assess indicator loadings, internal consistency reliability, convergent validity, discriminant validity, structural path coefficients, indirect effects, and explanatory and predictive measures.

Another practical advantage is its graphical interface. Researchers can construct theoretical models visually and estimate relationships using procedures such as bootstrapping.

However, SmartPLS should not be selected simply because the researcher has Likert-scale data. The decision to use PLS-SEM requires a methodological justification based on the research objectives and model characteristics.

SPSS: Strong for General Statistical Analysis

IBM SPSS Statistics remains one of the most accessible statistical packages for students entering quantitative research.

Its main strength is usability. Researchers can conduct many analyses through menus without extensive programming knowledge. This makes SPSS particularly useful for data cleaning, descriptive statistics, reliability analysis, exploratory factor analysis, correlation, t-tests, ANOVA, and regression analysis.

For example, a PhD scholar conducting a questionnaire survey may initially use SPSS to examine missing observations, identify coding errors, calculate descriptive statistics, and understand the demographic characteristics of respondents.

SPSS is also valuable when the research questions do not require a complex structural model. If a study primarily asks whether groups differ or whether several observed predictors explain an outcome, SPSS may be entirely sufficient.

Therefore, researchers should not treat SPSS as merely an elementary package. The appropriateness of a statistical technique matters more than whether the software appears sophisticated.

Stata: Particularly Strong for Econometrics

Stata has a particularly strong position in economics, development studies, epidemiology, political science, sociology, and public policy research.

It becomes especially useful when researchers work with cross-sectional, panel, longitudinal, or time-series datasets and need econometric estimation.

For example, a researcher studying employment across Indian states over 15 years may need to account for differences between states and changes over time. Panel-data approaches such as fixed-effects or random-effects models may therefore be appropriate.

Stata provides strong support for these models and for methods dealing with issues such as heteroskedasticity, clustered observations, instrumental variables, treatment effects, and other econometric problems.

Another major advantage is reproducibility.

Researchers can save their commands in do-files. Instead of manually repeating every analytical step, they can rerun the same commands when data change or when reviewers request additional robustness tests. This creates a transparent record of how the researcher moved from raw data to final results.

For doctoral research and journal publication, such reproducibility is highly valuable.

SmartPLS vs SPSS vs Stata: How Should a PhD Scholar Decide?

The simplest way to choose is to begin with the methodological requirement.

If the study develops a theoretical model containing latent constructs measured by multiple indicators and the chosen methodology is PLS-SEM, SmartPLS is a natural option.

If the research requires descriptive statistics, group comparisons, conventional regression, exploratory factor analysis, or straightforward survey analysis, SPSS provides an accessible environment.

If the study focuses on econometric questions involving panel data, longitudinal observations, causal inference strategies, or advanced regression models, Stata may be more appropriate.

Importantly, these programs are not mutually exclusive.

A researcher may clean and describe survey data in SPSS and estimate a PLS-SEM model in SmartPLS. Another researcher may initially inspect data in SPSS before conducting econometric analysis in Stata.

The software should follow the methodology rather than determine it.

What Do Journals Actually Expect?

PhD scholars sometimes worry that journals prefer one particular software package. This concern can lead researchers to select fashionable software even when it does not match their research design.

In most cases, reviewers are more concerned with whether researchers selected an appropriate method, tested its assumptions, reported the analysis transparently, and interpreted the findings correctly.

A sophisticated software package cannot rescue a poorly specified research model.

Similarly, using a familiar program does not weaken a study when the analytical technique is appropriate.

Researchers should therefore be able to answer three questions clearly: Why was this statistical method selected? Why is it appropriate for the research questions and data? How were the results assessed for reliability and robustness?

These questions matter much more than the software logo appearing in the methodology section.

Final Advice for PhD Scholars

Choosing statistical software should be a methodological decision, not a popularity contest.

Use SmartPLS when PLS-SEM genuinely fits your theoretical model. Use SPSS when your study requires accessible general statistical analysis. Use Stata when econometric modelling, panel structures, longitudinal analysis, or related methods form the core of the research.

Most importantly, learn the statistical reasoning behind the software.

Knowing where to click can generate an output table. Understanding why a model is appropriate, what its assumptions mean, how to evaluate its results, and what conclusions the evidence permits is what turns statistical output into credible research.

For a PhD scholar, that distinction matters. Software is only a tool. The research question, theoretical framework, data structure, and methodological reasoning should always come first.

References

Baum, C. F. (2006). An Introduction to Modern Econometrics Using Stata. Stata Press.

Field, A. (2018). Discovering Statistics Using IBM SPSS Statistics (5th ed.). SAGE.

Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2022). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) (3rd ed.). SAGE.

Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24.

Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135.

Wooldridge, J. M. (2020). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning.

✍️ By Dileep Verma
Research Expert and Associate Editor of Track2Training, New Delhi, India

We are living in one of the most exciting periods in human history.

Artificial intelligence can write, translate, analyse data and help scientists discover new medicines. Robots are working in factories and hospitals. Machines can learn from huge amounts of information. Private companies are sending people into space. Countries are investing billions in semiconductors, quantum computing, biotechnology, clean energy and advanced defence technologies.

Knowledge has become power.

Technology has become power.

Research has become power.

And in this fast-changing world, India has more than a billion people, millions of young students, engineers, researchers and entrepreneurs. We have enormous human potential.

Yet sometimes, when I open social media or watch our public debates, I ask myself a simple question:

Are we using enough of this potential in the right direction?

We have smartphones in our hands, high-speed internet in our homes and access to almost unlimited knowledge. But too much of our public conversation is still trapped in caste fights, Hindu-Muslim arguments, religious controversies, political abuse and social-media hatred.

This is one of the great contradictions of modern India.

A Modern Phone Does Not Automatically Make a Modern Society

Think about the smartphone in your hand.

It may contain technology developed across several countries. Its processor, operating system, display, camera sensors, software and applications are the result of decades of scientific research.

Through this small device, we can read books from the world’s best universities, learn programming, study mathematics, watch scientific lectures, use artificial intelligence, start a business or communicate with people thousands of kilometres away.

But what are we sometimes doing with this extraordinary technology?

We forward rumours.

We fight over caste.

We abuse people because of religion.

We share edited videos without checking whether they are true.

We insult strangers because they support a different political party.

There is something deeply ironic about using some of the world’s most advanced technology to fight some of society’s oldest battles.

Technology may be modern, but our thinking must also become modern.

Caste and Religion Are Real, But Hatred Is Not a Solution

India cannot simply pretend that caste and religion do not matter.

Caste discrimination is real. Social inequality is real. Religious freedom matters. Minority rights matter. Historical injustice matters.

These issues deserve serious discussion.

But discussing inequality is different from spreading hatred.

Protecting one’s religious freedom is different from insulting another person’s religion.

Being proud of one’s community is different from believing another community is inferior.

India’s diversity is not the problem.

The problem begins when diversity is converted into permanent hostility.

A country of more than a billion people cannot move forward if every community is continuously encouraged to fear or hate another community.

We Also Need to Change the Questions We Ask Politicians

Politicians respond to what voters reward.

If elections are discussed mainly through caste arithmetic, religious identity and community polarization, political parties naturally invest more energy in those issues.

But imagine if voters repeatedly asked different questions:

Where are the jobs?

How good are our government schools?

Why is the air in our city polluted?

How much are we spending on scientific research?

Where are the new universities and laboratories?

Why is public transport poor?

How many new industries have come to our district?

What are we doing in AI, robotics and semiconductor technology?

Why are talented researchers leaving our institutions?

These questions can change political priorities.

Voting is not only a right. It is also one of the ways citizens communicate what they expect from government.

India Is Making Progress, But We Should Aim Higher

It would also be unfair to say that India is doing nothing in technology.

India has built a major IT industry, a respected space programme and important digital public infrastructure. Electronics and mobile-phone manufacturing have expanded significantly. The country is investing in artificial intelligence and semiconductor capabilities.

These achievements should be recognized.

But recognizing progress does not mean that we should stop asking difficult questions.

India’s expenditure on research and development remains relatively low compared with several major technology-driven economies.

That matters.

Countries do not become scientific powers simply because millions of their citizens use smartphones.

They become scientific powers when they create knowledge.

They build laboratories.

They fund researchers.

They produce patents.

They develop technologies.

They manufacture sophisticated products.

They encourage experimentation.

They allow talented people to take risks.

We Must Move From Consumers to Creators

Most of us use global digital platforms every day.

We watch videos.

We upload photographs.

We send messages.

We use AI tools.

There is nothing wrong with using foreign technology. International trade and knowledge exchange are important parts of modern civilization.

But India should also ask:

What are we building for the world?

Can the next major AI platform come from India?

Can Indian companies become global leaders in robotics?

Can we design and manufacture advanced semiconductor chips?

Can our universities become destinations where researchers from other countries want to work?

Can an Indian company create a digital product used by billions of people?

Can India develop affordable technologies that solve problems in healthcare, agriculture, education and clean energy?

These are the conversations young Indians should be having.

Do Not Blame Young Engineers for Going Abroad

We often complain that India’s best engineers and researchers leave for the United States, Europe and other developed economies.

But we should be careful before blaming them.

Imagine a young researcher receiving two opportunities.

One offers a modern laboratory, strong research funding, professional freedom, a good salary and the opportunity to work with leading scientists.

The other offers limited equipment, uncertain funding and fewer research opportunities.

Which one would most people choose?

Instead of asking only:

“Why are our talented people leaving India?”

we should ask:

“How can we build an India where talented people want to stay, return and create?”

Patriotism is valuable, but patriotism cannot replace laboratories, research grants, professional opportunities and good institutions.

Give talented young people an environment in which they can succeed, and many will happily build their future here.

Civic Sense Matters Too

Technology alone cannot make a country developed.

Our everyday behaviour matters.

Do we stop at a red traffic light when no police officer is watching?

Do we throw garbage on the road?

Do we damage public property?

Do we unnecessarily honk?

Do we respect queues?

Do we verify information before forwarding it?

Can we disagree with someone without abusing them?

Can a Hindu respect a Muslim neighbour?

Can a Muslim respect a Hindu neighbour?

Can people from different castes study, work and live together with dignity?

These small behaviours tell us something important about a society.

Civic sense is also a form of national development.

A developed country is not only one with tall buildings, expensive cars and fast internet.

It is also a society where people respect public spaces, laws, institutions and one another.

Our Education System Must Build Citizens, Not Just Job Seekers

We spend years preparing children for examinations.

Marks matter.

Degrees matter.

Employment matters.

But education should do something more.

It should teach a young person how to think.

How to question information.

How to distinguish evidence from rumours.

How to respect another person’s dignity.

How to behave in public spaces.

How to understand the Constitution.

How to use technology responsibly.

How to disagree without hatred.

And how to solve problems.

Interestingly, India’s Constitution itself speaks about developing scientific temper, humanism and the spirit of inquiry and reform under Article 51A(h).

Those words feel especially important today.

Imagine a Different Competition

Imagine if our young people competed as passionately over innovation as people sometimes fight over identity online.

Which Indian university will produce the next major scientific discovery?

Which state will build the best government schools?

Which Indian startup will create a globally successful AI product?

Which city will become India’s cleanest and most liveable?

Which engineering college will produce the next breakthrough in robotics?

Which Indian company will develop affordable medical technology for the world?

Which research team will create better batteries, solar technologies or agricultural systems?

That is the kind of competition India needs.

The Smartphone in Our Hand Represents a Choice

Every morning, millions of Indians pick up a smartphone.

That device gives us a choice.

We can use it to learn.

Or we can use it to hate.

We can read research.

Or forward rumours.

We can learn artificial intelligence.

Or spend hours fighting strangers over religion.

We can build professional networks.

Or create communal divisions.

We can learn from the world.

Or remain trapped in arguments inherited from the past.

The technology does not make that decision.

We do.

What Kind of India Do We Want?

India does not need to abandon religion, caste identities, traditions or cultural diversity to become modern.

Modernity does not mean becoming Western.

It means developing the ability to use reason, evidence, science, education and good institutions to improve human life.

We can preserve our cultures while building laboratories.

We can practise our religions while respecting other religions.

We can recognize caste injustice without creating caste hatred.

We can disagree politically without treating fellow citizens as enemies.

And we can be proud Indians while remaining open to knowledge from the entire world.

The twenty-first century will not wait for us.

AI is advancing.

Robotics is advancing.

Biotechnology is advancing.

Space technology is advancing.

Clean-energy technology is advancing.

Other societies are investing heavily in the industries and knowledge systems that may define the next fifty years.

India has the population, talent and ambition to be part of that future.

But our greatest resource is not our population alone.

It is what we educate, enable and inspire that population to do.

So perhaps the question we should ask ourselves is not:

Which caste are you from?

Not:

Which religion do you follow?

But:

What are you learning?

What are you creating?

What problem are you solving?

And what kind of India are we building together?

Because the future will not be built by hatred.

It will be built by knowledge, character, scientific thinking, cooperation and human effort.

✍️ By Dileep Verma
Research Expert and Associate Editor of Track2Training, New Delhi, India

Look up at the night sky at the right moment and you may see a bright point of light moving rapidly from one horizon to another.

That light is not a star or a planet.

It is one of the most remarkable machines humanity has ever constructed: the International Space Station (ISS).

Orbiting roughly 400 kilometres above Earth, the ISS travels at about 17,500 miles per hour, completing an orbit approximately every 90 minutes. NASA notes that the station circles Earth about 16 times every 24 hours. It has also been continuously occupied since November 2000. NASA

But the ISS is much more than an engineering achievement.

It is a working demonstration of what human beings can accomplish when science, international cooperation, disciplined administration, technological innovation, and long-term planning are brought together.

A Laboratory Above the Earth

The International Space Station is essentially a permanently crewed research laboratory in low Earth orbit.

Its scale is extraordinary. Yet what makes the ISS especially important is not simply its physical size. It is what happens inside it.

Thousands of experiments have been conducted aboard the station. NASA reports research across biology and biotechnology, human health, physical sciences, Earth and space science, technology development, and other areas. Its research database now encompasses more than 4,000 experiments over more than two decades of station science. NASA

In 2025 alone, researchers using the orbital laboratory conducted more than 750 investigations, according to NASA’s annual research highlights. NASA

Scientists are studying questions such as:

How does the human body respond to prolonged microgravity?

How do plants grow in space?

How do cells and tissues behave without normal gravity?

How can materials be developed differently in microgravity?

How can technologies be improved for future journeys to the Moon and Mars?

The ISS therefore functions not simply as a spacecraft, but as a continuously operating scientific institution.

Five Space Agencies, One Extraordinary Project

Perhaps the greatest lesson of the ISS is not technological at all.

It is institutional.

The station is operated through an international partnership involving five major space agencies: NASA of the United States, Roscosmos of Russia, the European Space Agency (ESA), the Japan Aerospace Exploration Agency (JAXA), and the Canadian Space Agency (CSA). NASA

These partners come from countries with different languages, histories, political systems, national interests, and geopolitical relationships.

Yet hundreds of kilometres above Earth, their technologies have been integrated into one functioning system.

NASA explicitly describes the station as interdependent. Different partners manage different hardware and capabilities, and no single partner currently has the capability to operate the entire station independently. NASA

That is a remarkable organizational achievement.

From Cold War Competition to Scientific Cooperation

The ISS also carries historical significance.

For decades, the United States and Soviet Union competed intensely in space as part of the broader Cold War rivalry.

Space exploration demonstrated technological capability and national power.

Yet the ISS emerged in a different era.

Former competitors became partners.

Engineers began integrating technologies.

Astronauts and cosmonauts trained together.

Mission-control centres coordinated operations.

Scientific institutions shared responsibilities.

This does not mean that geopolitical disagreements disappeared. They did not.

The lesson is more practical:

Countries do not need to agree on everything before they can cooperate on something important.

This principle deserves greater attention in the twenty-first century.

Lesson 1: Shared Problems Need Shared Objectives

Climate change does not recognize international borders.

Neither do pandemics, environmental degradation, ocean pollution, cyber threats, or many economic shocks.

These problems cannot be addressed effectively by one country acting entirely alone.

The ISS demonstrates that cooperation becomes possible when institutions define a sufficiently clear common objective.

Instead of beginning with:

“Where do we disagree?”

international cooperation can sometimes begin with:

“What problem must we solve together?”

This shift from ideological confrontation toward problem-solving is one of the strongest lessons of the space station.

Lesson 2: Science Gives Humanity a Common Language

An American engineer and a Japanese engineer may speak different languages.

Their countries may have different political institutions.

But the physical laws governing orbital mechanics do not change with nationality.

Gravity behaves consistently.

Mathematics works consistently.

Engineering tolerances cannot be negotiated politically.

This makes scientific reasoning a powerful framework for international cooperation.

When evidence changes, scientific understanding can change with it.

That principle is particularly important when societies confront complex problems such as climate change, public health, food security, energy transitions, and environmental protection.

Policy choices involve values and trade-offs, but the factual foundations of those choices should be informed by the best available evidence.

Lesson 3: Enormous Problems Become Manageable When Divided Into Modules

The ISS could not simply be built on Earth as one enormous structure and launched into orbit.

Instead, it was assembled progressively from modules and components.

Different countries and organizations could therefore contribute specialized capabilities to a larger system.

This offers a valuable management principle:

Do not try to solve every part of a complex problem simultaneously. Break it into manageable components.

The same principle applies to governments, universities, companies, infrastructure projects, and even individual research projects.

Climate change is enormous.

But renewable energy, public transport, energy efficiency, forest protection, adaptation, climate science, and industrial innovation can become defined areas of action.

Complexity becomes manageable when it is structured.

Lesson 4: Build Redundancy Before a Crisis Occurs

On Earth, a failed system may cause inconvenience.

In space, it can become life-threatening.

That is why spacecraft engineering places enormous importance on reliability, monitoring, backup capabilities, maintenance, and contingency planning.

This mindset has relevance far beyond aerospace engineering.

Hospitals need backup electricity.

Cities need emergency water systems.

Governments need disaster-response capacity.

Companies need data backups.

Countries need resilient food and energy systems.

The central principle is simple:

Resilience should be designed before the emergency, not improvised after it.

Lesson 5: Human Problems Require Human Action

One of the deeper philosophical lessons of the ISS is human agency.

People hold many different religious and philosophical beliefs, and science does not need to settle those personal questions in order to solve practical problems.

But when astronauts need oxygen, engineers must build functioning life-support systems.

When spacecraft must reach orbit, scientists must calculate trajectories.

When equipment fails, technicians must diagnose the problem.

When climate risks increase, societies must decide how to respond.

Whatever our personal beliefs, practical problems require practical action.

Prayer, hope, or belief may have personal meaning for individuals, but they cannot substitute for engineering calculations, medical evidence, environmental measurements, functioning institutions, or public policy.

Climate change will not be addressed by hope alone.

War will not end simply because humanity wishes it away.

Poverty will not disappear without institutions, resources, education, economic opportunities, and policy action.

Human beings must take responsibility for the problems human societies can address.

The ISS Is Still Making History

This is not merely a historical story.

On October 1, 2026, NASA’s SpaceX Crew-13 mission reached the International Space Station.

NASA astronauts Jessica Watkins and Luke Delaney, Canadian Space Agency astronaut Joshua Kutryk, and Roscosmos cosmonaut Sergey Teteryatnikov docked with the station and joined Expedition 75. NASA

The mission is continuing research that includes human health, plant growth, tissue research, and technologies relevant to future exploration. NASA

So, more than a quarter-century after continuous habitation began, the laboratory is still generating scientific knowledge.

A Blueprint for the Twenty-First Century

Humanity faces serious challenges.

🌍 Climate change and global warming
⚔️ Armed conflict and geopolitical rivalry
💧 Water scarcity
🌾 Food insecurity
🦠 Emerging diseases
⚡ Energy transitions
🤖 Rapid technological change
🌊 Environmental degradation

None has a magical solution.

They require research.

They require evidence.

They require institutions.

They require international cooperation.

They require political negotiation.

They require resources.

And, above all, they require human beings willing to organize and act.

The ISS shows that countries with different interests can still build something together when they recognize a shared objective.

When You See the ISS, Look at What Humanity Built

The International Space Station should therefore be understood as more than a spacecraft.

It is a laboratory.

It is an engineering system.

It is an international institution.

It is an experiment in cooperation.

And it is a demonstration of human agency.

When we see that bright object crossing the night sky, we are looking at thousands of scientists, engineers, astronauts, technicians, administrators, organizations, and institutions whose work has been combined into one extraordinary achievement.

The ISS was not created by chance.

It was studied, calculated, financed, negotiated, engineered, tested, launched, assembled, maintained, repaired, and continuously improved by human beings.

That may be its most valuable lesson for the twenty-first century.

When humanity replaces helplessness with inquiry, isolation with cooperation, and wishful thinking with informed action, seemingly impossible problems can become solvable projects.

The ISS does not prove that humanity can solve every problem.

It proves something more useful:

we already possess powerful tools for trying.

Science gives us evidence.

Reason helps us evaluate it.

Technology expands what we can do.

Cooperation expands who can contribute.

And organized human action turns knowledge into results.

That is the lesson orbiting above us every 90 minutes.

Suggested website categories: Science | Technology | International Cooperation | Management | Public Administration

Suggested tags: International Space Station, ISS, NASA, Space Science, Scientific Thinking, International Cooperation, Human Agency, Climate Change, Global Governance, Project Management, Technology, Space Exploration, Public Administration

✍️ By Dileep Verma
Research Expert and Associate Editor of Track2Training, New Delhi, India

When we look at the Great Pyramid of Giza, we usually think about its enormous stones, extraordinary height, mysterious construction methods, and remarkable survival over thousands of years. It is one of the most recognizable monuments ever created by human civilization.

But there is another way to understand the Great Pyramid.

Beyond architecture and engineering, it represents an extraordinary example of planning, administration, logistics, workforce organization, and long-term project management.

Built for the Egyptian pharaoh Khufu during the Fourth Dynasty, around the 26th century BCE, the Great Pyramid originally stood about 146.5 metres high. According to Egypt’s Ministry of Tourism and Antiquities, it remained the world’s tallest building for approximately 3,800 years.

More than four millennia later, the question is not only how ancient Egyptians built such a monument, but also how they organized the enormous human and material system required to complete it.

More Than an Engineering Achievement

The Great Pyramid was constructed primarily from limestone. Higher-quality Tura limestone was used for its original outer casing, while granite was incorporated into important internal spaces.

Transporting these materials required an organized system extending far beyond the construction site.

Stone had to be quarried and prepared. Boats had to transport material. Workers needed food, water, shelter, equipment, and supervision. Tools had to be produced and maintained. Different teams had to perform specialized tasks while remaining connected to the larger construction programme.

In modern terminology, the project required elements of supply-chain management, human-resource management, procurement, logistics, transportation, supervision, and project coordination.

This was achieved without computers, trucks, cranes, spreadsheets, GPS, or modern communication systems.

That makes the administrative achievement behind the pyramid almost as fascinating as the structure itself.

The Diary of Merer: Evidence of Ancient Administration

One of the most interesting discoveries related to Khufu’s pyramid is the Diary of Merer, part of a collection of ancient papyri discovered at Wadi al-Jarf.

Merer was an official associated with a crew involved in transporting limestone. His records describe journeys connected with moving limestone from Tura toward the pyramid construction area during Khufu’s reign.

This is significant because it gives us a rare glimpse into the administrative machinery behind pyramid construction.

Someone had to organize crews.

Someone had to record activities.

Someone had to coordinate transportation.

Someone had to ensure materials reached their destination.

The pyramid was therefore not simply the product of physical labour. It depended on an administrative system capable of coordinating thousands of activities toward a common objective.

Were the Pyramid Builders Slaves?

Popular movies have often portrayed Egyptian pyramids as products of huge groups of enslaved workers being forced to work under brutal conditions.

Archaeological evidence presents a more complicated picture.

Excavations at Giza have uncovered a workers’ settlement associated with pyramid construction. Archaeologists have identified houses, streets, administrative facilities, storage areas, food-production facilities, and evidence of substantial food provisioning.

Egypt’s Ministry of Tourism and Antiquities describes a settlement south of the Sphinx where workers involved in pyramid construction lived, with evidence including administrative buildings and substantial quantities of animal remains.

This does not mean ancient Egyptian labour conditions should be romanticized. Our evidence is incomplete, and ancient labour systems differed greatly from modern employment.

What it does show is that pyramid construction required a far more organized labour system than the simplistic image of uncontrolled masses performing physical work.

Lesson 1: Large Projects Depend on Logistics

A project of this scale could not continue unless materials arrived when required.

Imagine a construction site where hundreds or thousands of people are ready to work, but the required stone does not arrive.

Or the stone arrives but tools are unavailable.

Or workers are present but food supplies fail.

Construction slows or stops.

Modern organizations face the same basic problem.

Large infrastructure projects, manufacturing plants, hospitals, universities, railways, and government programmes depend on interconnected systems.

The lesson from Giza is simple:

Do not manage only the final project. Manage the entire system that makes the project possible.

Lesson 2: People Are Part of the Infrastructure

The archaeological evidence of worker accommodation and food provisioning provides another important management lesson.

A large project cannot depend only on physical resources.

Workers must also be sustained.

In modern management, organizations often discuss technology, artificial intelligence, automation, finance, and infrastructure. Yet the success of almost every organization ultimately depends on people.

Human-resource management should therefore not be treated merely as an administrative department.

Employee health, training, working conditions, motivation, communication, and organizational clarity can directly influence performance.

The pyramid reminds us that human infrastructure matters alongside physical infrastructure.

Lesson 3: Break a Huge Goal into Smaller Tasks

“Build a pyramid” sounds almost impossible.

But “quarry this stone,” “transport this material,” “prepare these tools,” or “complete this section” is manageable.

This is one of the oldest and most powerful principles of project management.

Complex objectives become achievable when they are divided into smaller tasks and assigned to organized teams.

Different groups involved in pyramid construction would have required different responsibilities and skills.

The broader lesson applies equally well today.

Whether writing a PhD thesis, constructing a highway, implementing public policy, developing software, or running a national programme, a large objective must be transformed into specific, measurable, coordinated activities.

Lesson 4: Long-Term Projects Need Institutional Continuity

The exact construction timeline of the Great Pyramid remains uncertain, but Egypt’s antiquities authority gives an estimate of approximately 10 to 20 years.

A project lasting that long requires continuity.

Workers change. Supervisors change. Weather changes. Resources fluctuate. Unexpected problems emerge.

Yet the larger objective has to continue.

This is particularly important for modern public administration.

Many of today’s biggest challenges cannot be solved within a single financial year or political cycle.

Major transport systems, educational reforms, climate adaptation, scientific programmes, urban development, and institutional reforms may require decades.

Long-term development therefore depends not only on leaders but also on institutions capable of preserving knowledge and maintaining direction over time.

Lesson 5: Administration Is a Form of Technology

We normally associate technology with machines.

But technology can also mean systems and methods that allow humans to accomplish tasks more efficiently.

From this perspective, administration itself can be considered an important organizational technology.

Record keeping, division of labour, supervision, resource allocation, transportation planning, standardization, and coordination enabled ancient societies to undertake projects far beyond the capacity of individuals.

Modern organizations possess dramatically more advanced tools, yet they still fail when coordination breaks down.

A sophisticated computer system cannot compensate indefinitely for unclear responsibilities, poor communication, weak planning, or disorganized leadership.

The ancient lesson remains surprisingly relevant:

Technology improves capability, but organization converts capability into results.

What the Great Pyramid Still Teaches Us

The Great Pyramid is the only surviving monument of the traditional Seven Wonders of the Ancient World.

Its physical survival is extraordinary.

But perhaps its intellectual legacy is equally valuable.

It demonstrates what human beings can achieve when knowledge, labour, resources, planning, and administration are brought together around a clearly defined objective.

Great achievements rarely emerge from one person working alone.

They depend on systems.

Vision without planning remains an idea.

Resources without coordination produce waste.

People without defined responsibilities create confusion.

Technology without organization has limited value.

But when vision, people, knowledge, resources, and administration work together, human beings can accomplish things that initially appear impossible.

More than 4,500 years after its construction, millions of people still look at the Great Pyramid and ask:

“How did they do it?”

Perhaps part of the answer lies not only in engineering.

It lies in the extraordinary power of organized human effort.

One vision. Thousands of workers. Millions of individual tasks. One monument that survived thousands of years.

Suggested website categories: History | Management | Public Administration | Leadership | Project Management | Ancient Civilizations

Suggested tags: Great Pyramid of Giza, Ancient Egypt, Khufu, Project Management, Public Administration, Human Resource Management, Supply Chain Management, Leadership, Organizational Management, Ancient Engineering, History

#GreatPyramid #Giza #AncientEgypt #Management #PublicAdministration #ProjectManagement #Leadership #SupplyChain #HumanResources #Governance #History #OrganizationalManagement #LearningFromHistory

By Dileep Verma (Research Expert and Associate Editor of Track2training, New Delhi, India)

Writing your first research paper and targeting Scopus or ESCI (Emerging Sources Citation Index) journals feels like a daunting task when you start your PhD. Many early-career scholars make the mistake of jumping straight into writing without understanding how academic papers are structured and built.

Here is a step-by-step roadmap to guide you from a raw research idea to a polished paper ready for indexing.

1. Foundation: Framing a Publishable Idea

A paper published in Scopus or ESCI must contribute something distinct. It does not need to revolutionize the field, but it must offer a fresh lens, clear data, or a new context.

• Identify a Specific Research Gap: Read 15 to 20 recent papers (published in the last three years) from top journals in your field. Look at their “Future Research Directions” or “Limitations” sections. That is where your paper begins.
• Refine Your Objective: Avoid broad topics. Instead of writing about “Public Policy in India,” focus on a concrete, measured angle like “Perception Analysis of Reservation Policy Implementation among SC Communities in Central India.”
• Choose the Right Paper Type: As a beginner, focus on either an empirical paper (based on primary data like surveys or interviews) or a systematic literature review (SLR) using PRISMA guidelines. Both are welcomed by Scopus/ESCI journals if done rigorously.

2. Standard Structure of a Research Paper (IMRaD)

High-impact journals follow a clear, predictable structure: Introduction, Methodology, Results, and Discussion (IMRaD).

+-------------------------------------------------------------------+
|                            TITLE                                  |
|         Clear, specific, and reflecting main variables            |
+-------------------------------------------------------------------+
                                  |
                                  v
+-------------------------------------------------------------------+
|                           ABSTRACT                                |
|    Context -> Problem -> Method -> Key Finding -> Implication     |
+-------------------------------------------------------------------+
                                  |
                                  v
+-------------------------------------------------------------------+
|                         INTRODUCTION                              |
|   1. Background & Context                                         |
|   2. Practical & Theoretical Problem                              |
|   3. Literature Gap                                               |
|   4. Research Questions / Objectives                              |
+-------------------------------------------------------------------+
                                  |
                                  v
+-------------------------------------------------------------------+
|                      LITERATURE REVIEW                            |
|   Thematic mapping of existing studies & theoretical framework   |
+-------------------------------------------------------------------+
                                  |
                                  v
+-------------------------------------------------------------------+
|                        METHODOLOGY                                |
|   Research design, sample selection, data collection & tools      |
+-------------------------------------------------------------------+
                                  |
                                  v
+-------------------------------------------------------------------+
|                     RESULTS & FINDINGS                            |
|   Direct, clear presentation of data (Tables/Graphs + Narrative)  |
+-------------------------------------------------------------------+
                                  |
                                  v
+-------------------------------------------------------------------+
|                         DISCUSSION                                |
|   Compare your findings with existing literature & theory         |
+-------------------------------------------------------------------+
                                  |
                                  v
+-------------------------------------------------------------------+
|                         CONCLUSION                                |
|   Key takeaway, policy/practical implications, & limitations      |
+-------------------------------------------------------------------+

The Section-by-Section Breakdown

A. Title and Abstract

Write these last. Your title should be direct and informative. The abstract (150–250 words) must summarize five things:

1. Context/Problem
2. Objective
3. Methodology used
4. Key findings
5. Broader implications

B. Introduction

Your introduction sets the hook for reviewers. Keep it clear and logical using a 4-paragraph model:

• Paragraph 1: Context and importance of the topic.
• Paragraph 2: The core problem and what previous studies missed (the gap).
• Paragraph 3: Your study’s specific objective and research questions.
• Paragraph 4: The value and originality of your contribution.

C. Literature Review

Do not just summarize paper by paper (“Author A said X, Author B said Y”). Instead, organize your review thematically. Group existing works around themes, spot contradictions in past research, and show how your study connects to established theories.

D. Methodology

Write this section with enough clarity that another researcher could replicate your study.

• Explain your research design (quantitative, qualitative, or mixed-methods).
• State your population, sample size, sampling technique, and instruments (e.g., Likert-scale surveys or semi-structured interviews).
• Mention ethical considerations and data validation techniques (e.g., Cronbach’s alpha for quantitative reliability or thematic analysis for qualitative data).

E. Results

Present your data plainly. Use tables and figures to summarize large blocks of information. Walk the reader through the key patterns in your data without over-interpreting them yet. Keep your prose objective and direct.

F. Discussion (The Core of Scopus/ESCI Acceptance)

This is where many early papers fail. Do not just repeat your findings. Answer these questions:

• Why did you get these results?
• How do your findings compare with previous studies? Do they agree, contradict, or extend prior research?
• What does this mean for theory and practice (e.g., policy implementation)?

G. Conclusion and Implications

Summarize the main contribution in simple terms. Clearly outline practical/policy implications (how practitioners or policymakers can use this work) and state the limitations of your study candidly.

3. Transitioning from Conference Papers to Journal Articles

Conferences are testing grounds; journals are permanent records.

How to Convert a Conference Paper to a Journal Paper

1. Expand the Literature Review: Move beyond basic context to deep theoretical analysis.
2. Strengthen the Data: Add a larger sample size or deeper qualitative analysis.
3. Expand the Discussion: Elaborate heavily on why the findings matter.
4. Target a New Draft: Scopus journals typically require significant structural and content updates (at least 30–40% new material) compared to conference proceedings.

4. Academic Writing and Style Essentials

To reach Scopus/ESCI quality, your writing must meet clear academic standards:

• Use Active Voice: Instead of writing “The data was analyzed by the researcher,” write “We analyzed the data using SPSS.” It makes your writing direct and clear.
• Keep Sentences Short and Strong: Express one main idea per sentence. Complex ideas do not require long, convoluted sentences.
• Avoid Fluff: Skip empty phrases like “it is widely acknowledged that” or “a pivotal moment.” Get straight to the point.
• Cite Recent, High-Quality Sources: At least 60–70% of your references should come from indexed journals published in the last 5 years.

5. Submitting and Handling Reviews

Finding the right journal is half the battle.

1. Journal Selection: Use tools like Elsevier Journal Finder, Springer Journal Suggester, or Web of Science Master Journal List. Check if the journal is actively listed in Scopus or ESCI.
2. Follow Author Guidelines: Adjust formatting, citation style (APA, IEEE, Harvard), word count, and heading styles strictly according to the target journal’s template.
3. Handling Rejections and Revisions:
   • Desk Reject: Means the paper does not fit the journal scope or lacks basic formatting. Refine and target another journal.
   • Major/Minor Revision: A huge win. Address every single reviewer comment in a point-by-point response table, explaining clearly what changes you made.

Writing high-quality papers is a skill built through practice. Focus on clear logic, explicit methods, and strong evidence, and your work will find its place in reputed indexed journals.