Category: Thought Leadership

What the Bee Gees Taught Me About Building FAVORIOT

Have you ever watched a documentary and found yourself thinking about your own life more than the story on screen?

That happened to me not long ago. I sat down one evening to watch a documentary about the Bee Gees, expecting to enjoy the music and the nostalgia. What I got instead was something I did not expect: a mirror.

The more I watched Barry, Robin, and Maurice Gibb tell their story, the more I kept seeing echoes of something closer to home. The restarts. The rejections. The moments where everything seemed to be working, then suddenly wasn’t. And through all of it, the stubborn refusal to stop.

I could not help thinking, this sounds a lot like FAVORIOT.

From Humble Beginnings

The Bee Gees did not begin as superstars. They started as three brothers performing in small venues in Australia, trying to be heard, trying to matter. There were years nobody paid much attention. There were record labels that said no. There were periods where they had to reinvent themselves completely just to survive.

I grew up listening to their music. Songs like How Deep Is Your Love, Stayin’ Alive, More Than a Woman. These weren’t just pop songs to me. They were part of a certain era, a soundtrack to a generation. But watching the documentary, I realised I had only ever seen the polished version. I had never truly appreciated the full journey that produced those songs.

FAVORIOT started in 2017. We were not backed by venture capital with deep pockets. We did not launch with fanfare or make headlines. We were a small team with a clear conviction: that IoT in Malaysia needed a proper platform, built locally, understood locally, and committed to for the long term. We believed in it even when the market was not ready to believe with us.

The Reinvention No One Talks About

One of the most striking parts of the Bee Gees story is how many times they had to change direction. They began as a pop group in the 1960s, found some success, then faded. By the early 1970s, they were largely forgotten. Then came disco. The Saturday Night Fever soundtrack happened, and suddenly they were the biggest act in the world.

But here is the part people forget: they did not just get lucky. They studied the new sound, they adapted, and they worked harder than ever to master something different from what had made them famous before.

I think about this a lot when it comes to FAVORIOT. We started with one vision of how the market would grow. Reality had other plans. We shifted our focus, refined our offering, and rebuilt parts of our approach more than once. Each time, it felt uncomfortable. Each time, I had to resist the voice that said, maybe the original plan was wrong.

The Bee Gees teach me that reinvention is not a sign of failure. It is a sign that you are paying attention.

The Years Nobody Noticed

There is a gap in the Bee Gees story that most people skip over. Between their early years and the Saturday Night Fever explosion, there were quiet years. Years of uncertainty. Years where they kept working even without certainty that anyone was watching.

Those years were not wasted. They were the foundation for everything that came later.

FAVORIOT has had its own quiet years. Years where we were building, improving, pitching, and persisting, while the noise around us belonged to other companies and other narratives. It would have been easy to interpret that silence as irrelevance.

But I kept coming back to a simple question: are we building something real? If the answer was yes, then the noise would come eventually.

I still believe that.

Three Brothers and a Shared Dream

Something else struck me watching the documentary. The Bee Gees were brothers. That bond, even when it was tested by disagreements and very human tensions, was ultimately what held the group together through decades of change.

At FAVORIOT, we are not related by blood, but there is something similar in how we operate. The founding team carries a shared belief that goes beyond a business model. We genuinely believe that IoT can transform how organisations operate in Malaysia and across the region. That belief has held us together through the difficult periods, the same way the Gibb brothers held each other together through theirs.

Shared conviction, I have learned, is more durable than shared strategy.

One Day, Stayin’ Alive Becomes Thriving

The title of the documentary I watched was simply Brothers Gibb Bee Gees & Andy Gibb Story. There is something poetic in that title when you think about the startup journey. Because building something from nothing, in a market that is still finding itself, does break you a little. Not permanently. But enough to make you question everything more than once.

What kept the Bee Gees going was not certainty. It was love for what they did. Barry Gibb, speaking about his brothers who are no longer here, talks about the music as something bigger than any of them. The work outlasts the struggle.

I think about FAVORIOT in those terms sometimes. Not as a product, not as a revenue line, but as something we are trying to leave behind. A platform that proves a Malaysian IoT company can compete, contribute, and endure.

We have not reached stardom. We are not at Saturday Night Fever yet. But I do not think the Bee Gees knew it was coming either, right up until it arrived.

What I Am Still Learning from Them

The Bee Gees stayed in harmony, even when harmony was hard. They adapted without abandoning their core. They trusted that the work would eventually speak for itself.

These are not music lessons. These are founder lessons.

FAVORIOT’s documentary is still being filmed. The ending is not written. But if the Bee Gees story teaches me anything, it is that longevity is built in the quiet years, not just the spotlight moments.

And somewhere, in an office in Malaysia, a small team is still showing up every day to build something they believe in.

Maybe that is how every great story begins.

If you are working on an IoT project and want to talk to a team that has stayed in the game long enough to understand what staying actually means, reach out to us at FAVORIOT. We would love to be part of your story.

I wrote a deeper technical take on this over at IoT World (http://iotworld.co)

What My PhD Actually Taught Me (And It Was Never Just About the Research)

People assume a PhD is about becoming an expert in a narrow field. You pick a topic, spend four years buried in it, defend your thesis, and walk away with a title in front of your name. That was how I thought about it when I started mine at Universiti Teknologi Malaysia back in 1989.

I was wrong. The research was almost the least important part.

What the PhD actually gave me, I only fully understood decades later, when I found myself building FAVORIOT from scratch. No corporate safety net. No budget approval processes. No team of fifty people to delegate to. Just a problem to solve, a market to convince, and a very steep learning curve. And somewhere in that pressure, I realised that every skill I was relying on, I had built it during those three years of doctoral work.

You Learn to Think, Not Just to Know

The biggest myth about a PhD is that it fills your head with knowledge. It does, but that is not the point. What it really trains is how you think. How to slow down when a problem looks unsolvable. How to question your own assumptions before anyone else does. How to look at a complex situation and break it into parts that can actually be examined.

Running a startup constantly throws you into situations where there is no clear answer. The market changes. A technology assumption turns out to be wrong. A partnership you counted on falls through. Most people freeze or react. The PhD habit of structured thinking means I almost always go back to basics: what do I actually know, what am I assuming, and what do I need to find out?

That thinking discipline has saved me more times than any specific technical knowledge I carry.

Working Alone Without Falling Apart

A PhD is a deeply solitary journey. Your supervisor guides you, but the work is yours. The thinking is yours. The doubt is yours. Nobody is going to sit with you at two in the morning when you cannot make sense of your own data.

Entrepreneurship feels exactly the same way in the early years. You make decisions that nobody else fully understands. You carry uncertainty that you cannot always share with your team because you are supposed to be the steady one. You have to be comfortable with ambiguity without becoming paralysed by it.

The PhD taught me how to keep working when I had no external validation. It taught me that the absence of certainty is not a reason to stop. You form a hypothesis, you test it, you adjust, and you keep going. That is the startup loop. That is also the research loop.

Finding Knowledge Instead of Waiting for It

Before the PhD, I consumed knowledge the way most students do: someone put it in front of me, and I absorbed it. The PhD changed that completely. You quickly discover that nobody is going to hand you what you need. You have to hunt for it. You learn to search literature strategically, to identify which sources actually matter, to read critically instead of passively.

At FAVORIOT, we operate in a field that moves fast. IoT, AIoT, edge computing, platform architecture, developer ecosystems. The landscape shifts every eighteen months. If I waited for someone to teach me what I needed to know, I would always be behind. The PhD habit of self-directed learning means I am always reading, always synthesising, always asking what the current evidence actually says rather than what the conventional wisdom assumes.

Making the Complicated Simple

The viva examination is the moment every doctoral candidate dreads. You stand in front of a panel of experts and defend work that you have spent years on. They will probe every weakness. They will ask you to justify every assumption. And they will not accept jargon as a substitute for understanding.

To survive a viva, you have to be able to explain your work clearly. Not just to people who already know the field, but to people who are testing whether you truly understand it, or whether you are hiding behind technical language.

That skill matters enormously in a startup context. I cannot afford to lose a potential customer, partner, or investor because I explained our platform in terms only an IoT engineer would recognise. I have to be able to take a genuinely complex system and present it in a way that is meaningful to a city mayor, a business owner, or a university faculty head. The PhD forced me to develop that translation ability.

Defending What You Believe Without Being Defensive

There is a particular kind of confidence that the PhD builds. Not arrogance, which is brittle. A well-grounded, evidence-based confidence that allows you to say: I believe this is right, and here is why. And then to genuinely listen to the counterargument rather than dismissing it.

In business, this matters in negotiation, in pitching, in product decisions, and in those moments when someone more powerful than you tells you that your idea will not work. The PhD trains you to distinguish between a challenge that reveals a real weakness and a challenge that is simply pressure. You learn to stand your ground when the evidence supports you, and to revise when it does not.

Evaluating Other People’s Work Without Ego

A less obvious skill the PhD builds is the ability to critically evaluate the work of others. Peer review, literature critique, comparative analysis of methodologies. You develop a framework for assessing quality, identifying gaps, and recognising when something looks impressive but is actually incomplete.

This translates directly into how I evaluate technology vendors, potential partners, and market claims. The IoT industry is full of noise. Announcements that overstate capability. Case studies that obscure the real cost. Research that is funded to reach a particular conclusion. The critical evaluation skills from doctoral training mean I read all of it with appropriate scepticism, and I draw my own conclusions.

The Scroll Was Never the Point

I do not display my PhD certificate in my office. Not because I am not proud of it, but because I stopped thinking of it as the output a long time ago. The output is how I think, how I work, how I handle uncertainty, and how I communicate. Those are the things the doctorate actually produced.

If you are a PhD holder wondering whether the years were worth it beyond the academic world, I would say this: you were trained for exactly the kind of work that startups and leadership roles demand. The certificate opened some doors, yes. But the habits it built have kept me going long after the doors were open.

So the real question is not whether your PhD is relevant to business. The question is whether you have recognised and applied everything it actually gave you.

The Moment I Realised Something Was Broken Why IoT Projects Fail to Scale, and What Nobody Wants to Admit

A few years ago, I walked into a facility that had spent close to a million ringgit on an IoT deployment. Sensors were installed. A dashboard was running. The operations manager proudly pulled up a screen showing hundreds of data points flowing in, live, in real time.

I asked him one question: “What decision did you make yesterday based on this data?”

He paused. He looked at the screen. He called a colleague over. A few minutes passed.

“Let me check the system,” he finally said.

That pause told me everything. The IoT project was not broken in the way most people imagine broken things to be. The sensors worked. The connectivity was stable. The platform was live. But something deeper had failed, and it had failed quietly, in a way that nobody in the room had named yet.

That was the moment I realised the industry had a serious problem. Not a technology problem. A thinking problem.

We Built the Infrastructure. We Forgot the Purpose.

When I look back at two decades of IoT work, across MIMOS, through my time at REDtone IoT, and now building FAVORIOT, the pattern I keep seeing is the same one. Organisations invest in sensors, platforms, and dashboards. They point to these things as proof of digital transformation. And then they wait for the results to come.

The results rarely come. Not because the technology failed, but because nobody asked the hard question before deployment: what decision are we trying to make faster?

The sensor was never the goal. The data was never the goal. The goal was always a better decision, made quicker, based on something real. But somehow, between the vendor pitch and the project sign-off and the go-live celebration, that goal got buried under the excitement of the technology itself.

I have seen this across manufacturing plants, utility companies, logistics operations, and smart city deployments. The pattern is consistent. The language around it is always optimistic. “We now have full visibility.” “We have a live dashboard.” “We are data-driven now.”

But ask the operations team what decision they made differently last Tuesday because of that dashboard, and the room goes quiet.

I Started Calling It Operational Blindness

Recently, I wrote a more technical definition of this condition for IoT World. I called it Operational Blindness. The full definition is this: it is the condition where an organisation invests in IoT infrastructure, collects operational data at scale, yet still cannot make confident, timely decisions because the data never closes the loop to action.

The organisation sees numbers. It does not see clearly.

This is not a criticism of the people involved. The engineers built what they were asked to build. The analysts produced their reports. The executives attended the strategy sessions. Everyone did their job. But the system, as a whole, was never designed to produce decisions. It was designed to produce data. And data without a decision is just noise dressed up in a dashboard.

When I started naming this condition clearly, something interesting happened. People began recognising it in their own organisations. System integrators told me they had seen this in nearly every project they had ever delivered. Operations managers said they had felt it for years but had no language for it. That recognition mattered to me, because you cannot fix what you refuse to name.

Why IoT Projects Stop Scaling

The question I get asked most often is: why do IoT pilots succeed but never scale?

The answer, in my experience, comes back to the same broken loop every time.

A pilot project works because it is small, focused, and closely watched. Someone with authority and curiosity is paying attention. Decisions get made. Results are visible. Everyone celebrates and writes a press release.

Then comes the scale-up. More sensors, more sites, more data, more dashboards. And suddenly the thing that made the pilot work, which was a human being with a clear question and the authority to act on the answer, gets diluted across a larger organisation with competing priorities, legacy processes, and departments that were never part of the original pilot conversation.

The data multiplies. The decision-making does not.

By the time the system is running at scale, there are alerts nobody reads, dashboards nobody opens, and reports that go straight from the inbox to the archive folder. The operations team, who were not involved in designing the IoT system, have learned to work around it rather than with it. They trust their own experience more than a dashboard they did not ask for.

This is not stubbornness. This is rational behaviour when you design a system without designing it around the people who are supposed to use it.

The Three Things That Actually Need to Change

After watching this pattern repeat itself across too many projects, I have settled on three things that genuinely move the needle.

The first is contextualisation. Raw data is not insight. A temperature reading means nothing unless it is translated into operational language. Not “82 degrees Celsius.” But “Motor 4B has been running above its safe operating threshold for 40 minutes and failure is likely within six hours.” Context converts measurement into meaning. Without it, the dashboard is just wallpaper.

The second is integration into workflow. The insight has to reach the right person through the channel they already use, at the moment they can act on it. Not a report that lands at 9am about something that happened at 2am. Not a dashboard on a screen in a control room that the relevant decision-maker never visits. The signal has to travel to where the decision actually gets made.

The third is closing the loop. The system needs to know whether action was taken, what action, and what the outcome was. Without that feedback loop, the organisation cannot learn from its data. It cannot improve. It cannot measure whether the IoT investment is working. The loop has to close: from sensor to decision to outcome and back.

These are not exotic ideas. But they are consistently absent in organisations that are spending heavily on IoT and wondering why the ROI never materialises.

What I Tell Every Organisation That Comes to Me

When organisations approach FAVORIOT, one of the first things I ask is: what decision do you want to make better, and who in your organisation makes that decision today?

If they cannot answer that question, the deployment is not ready. Not because the technology is not ready. The technology is almost always ready. But the organisation is not yet clear on what it is trying to do with what the technology reveals.

That clarity is everything. It is the difference between a sensor deployment that scales and one that stays a pilot forever. It is the difference between a dashboard that changes operations and one that gets opened once a month during the management review.

We built FAVORIOT precisely because we kept seeing this gap in the market. Not a platform gap. A gap between what the data says and what the organisation decides to do about it. That is the gap we are working to close.

The Real Failure Mode

The IoT industry has spent years convincing organisations that more sensors, more data, and more dashboards are the path to operational excellence. They are not. They are the beginning of the path. What lies between that beginning and actual operational excellence is the hard work of turning data into decisions, and decisions into habits, and habits into results.

Most IoT projects fail to scale not because the technology lets them down, but because nobody built a bridge between the technology and the way the organisation actually makes decisions. The bridge is not a software feature. It is an organisational design question. And it is one that the IoT industry has, for too long, left for somebody else to answer.

If you are running an IoT deployment right now and it is not producing the results you expected, I would encourage you to ask one question before you spend another ringgit on more sensors or a better platform. Ask: what decision am I trying to make, and is my current system designed to help me make it?

The answer to that question will tell you more than any dashboard ever will.

I wrote a deeper technical take on this over at IoT World

Why IoT Pilots Don’t Scale And Who’s Really to Blame

Everyone celebrates a successful IoT pilot. Nobody talks about what happens six months later. Here is an honest look at why IoT pilots fail to scale, and what both vendors and organisations need to do differently.

Everyone celebrates a successful IoT pilot. Nobody talks about what happens six months later.

I have been in this industry long enough to see the pattern repeat itself more times than I care to count. The pilot runs well. The demo impresses the right people. The case study gets written. And then, quietly, the project stalls. The vendor stops getting replies. The internal champion gets moved to another role. The budget for the next phase never quite materialises. Eventually, everyone agrees to revisit it next year, and next year never comes.

This is not a rare failure. It is, in many ways, the default outcome for IoT pilots. And I think it is worth being honest about why.

Pilots Are Designed to Win, Not to Grow

When a vendor runs an IoT pilot, the primary goal is to prove the technology works. Can the sensors communicate reliably? Can the data reach the cloud? Can the dashboard tell a compelling story? These are the questions that get asked, and they are the questions that pilots are built to answer.

What almost never gets asked at the pilot stage is this: what will it actually take to run this at ten times the scale, across three different departments, with an operations team that had no involvement in the original project?

That question feels premature when everyone is still excited about the demo. But it is the question that determines whether a pilot ever becomes infrastructure.

I went through this at FAVORIOT in our earlier years. We were focused on showing what the technology could do, and we were good at it. The pilots looked great. The clients were satisfied. And then the scaling conversation would arrive, and suddenly the gaps that were invisible at pilot scale became very visible. We had not asked the hard questions early enough, and neither had our clients.

The Organisation That Was Not Ready

I want to be fair here, because this is not only a vendor problem.

Many organisations that commission IoT pilots are not genuinely ready to scale the outcome, even when the pilot succeeds technically. They have not decided who will own the system once it moves from pilot to operations. They have not resolved the internal politics between the IT department, the operational team, and the business unit that originated the idea. They have not secured a realistic budget for scaling, only for testing.

Scaling IoT is not primarily a technology challenge. It is an organisational one. It requires data governance policies that most organisations have not written. It requires integration with legacy systems that were never designed to communicate with modern IoT platforms. It requires someone inside the organisation who understands the technology well enough to advocate for it internally, troubleshoot it practically, and keep it alive through the natural turbulence of business priorities shifting.

That person, the internal champion who bridges technology and organisational reality, is often absent at the start. And no pilot result, however impressive, can substitute for what that person provides.

Looking back at the IoT deployments I have seen actually scale, that champion is almost always present. They pushed for budget when enthusiasm faded. They translated technical requirements into business language. They trained colleagues who were sceptical or confused. Without that internal force, a successful pilot becomes a beautiful proof-of-concept that everyone agrees was interesting but no one quite knows how to build on.

The Vendor’s Honest Share

I am a vendor. I run an IoT platform company. So I say this knowing it applies to me.

The commercial pressure on IoT vendors is to win the pilot. The incentives are structured around closing deals, not around ensuring clients succeed eighteen months after the handover. Sales teams make promises during the pitch that reflect best-case conditions. The pilot is then designed around those best-case conditions. When the client tries to scale into their actual messy environment, with their legacy systems, their budget constraints, and their internal disagreements, the gap between what was promised and what is possible becomes apparent.

Beyond the sales process, there is a deeper structural problem. Many IoT vendors invest heavily in customer acquisition and very little in customer success. Helping a client scale is slower, more complex, and less commercially visible than winning the next pilot. The skills required are different too. You need to understand the client’s internal culture, their risk tolerance, their pace of decision-making. Most vendor organisations are not built for that kind of long-term partnership.

What Scaling Actually Needs

If you have just completed a successful IoT pilot and you are serious about scaling it, here is where I would start.

Ask the governance questions before the growth questions. Who owns this system? Who has access to the data, and under what conditions? Who is responsible for maintaining it when the original project team moves on? These conversations feel administrative, but they are what determine whether the investment survives contact with the organisation over time.

Make sure the technology was chosen with operations in mind, not just with the demo in mind. A highly customised pilot solution that runs beautifully in a controlled environment can become extremely difficult to hand over to an operations team that was not involved in building it. Standardisation, supportability, and documentation matter far more at scale than they do at proof-of-concept.

Build internal capability alongside vendor engagement. The organisations that scale IoT well treat adoption as a learning process, not just a procurement process. They develop expertise inside the team. They make sure the knowledge does not leave when the vendor’s project engagement ends.

And if you are a vendor reading this, I would gently suggest reexamining what success actually means for your business. If your client’s pilot succeeds but their deployment never scales, did you really deliver value? The answer is uncomfortable, but it is worth sitting with.

The Blame Is Shared, and So Is the Solution

The reason IoT pilots fail to scale is rarely a single failure. It is usually a combination of technology choices made under pressure, organisational readiness that was overstated, vendor promises that outran execution capacity, and a structural mismatch between how pilots are designed and what scaling genuinely demands.

That is both a frustrating and a hopeful conclusion. Frustrating because there is no single villain to point at. Hopeful because it means there are multiple places where both sides can make better decisions.

I have seen IoT deployments that started small and grew into something that genuinely changed how an organisation operates. Those projects did not succeed because the technology was exceptional. They succeeded because both sides were honest about the challenges, patient with the timeline, and committed to the outcome long after the first demo had faded from memory.

So here is the question I want to leave with you: if you have been through an IoT pilot that succeeded technically but never scaled, what was the one thing you wish both sides had discussed more honestly at the very beginning?

If you’re working through this challenge right now, I’d also point you to what we’ve been building at Favoriot — specifically around helping organisations move from pilot to operational deployment without rebuilding from scratch.

Why Seeing Your Brand Once Is Never Enough: The Science Behind the B2B Buying Decision

In B2B technology marketing, posting once and hoping for conversion is one of the most common and costly mistakes. The Rule of 7 is just the starting point. For IoT platforms, AIoT training, and smart city solutions, the real buying journey demands 12 to 20 meaningful touchpoints before serious action begins.

How many times does a potential customer need to encounter your brand before they are ready to act?

Most marketers have heard of the Rule of 7, the long-standing principle that a buyer needs at least seven brand exposures before taking action. The University of Maryland traces this back to early advertising research, and while the number has been cited across decades of marketing literature, the principle itself has never been more relevant than it is today. In fact, for B2B technology companies selling complex solutions such as IoT platforms, AIoT training, smart city systems, or system integrator services, seven may not even be close to enough.

The Rule of 7 Is a Starting Point, Not a Ceiling

The original Rule of 7 was conceived in a world where buyers had far fewer choices and far fewer distractions. Today, a prospective customer is bombarded with hundreds of brand messages daily across social media, email, search, video, and messaging apps. Cutting through that noise requires more than a single touchpoint or even a handful.

A more practical and realistic framework looks like this. For low-cost, low-risk consumer products where the customer already understands the need, three to five exposures may be sufficient. For B2B software, IoT platforms, training programs, and consulting services where trust must be established before any commitment is made, seven to twelve exposures is a more reasonable expectation. For high-value, technical, government, enterprise, or long sales-cycle decisions, the number often climbs beyond fifteen.

The buyer in a B2B context is rarely a single person making a spontaneous decision. There are budget holders, technical evaluators, procurement officers, and end users, each requiring their own reassurance at their own pace.

The Buying Journey Is No Longer a Straight Line

Google’s research into the modern customer journey confirms what many sales teams already suspect: the path from first awareness to final purchase is not linear. Buyers today move fluidly between searching, scrolling, streaming, and comparing. They might encounter a LinkedIn post on a Monday, watch a product demonstration video on a Wednesday, read a case study on a Friday, and then not think about it again for three weeks, until a colleague mentions the same solution.

This fragmented, non-linear journey means that brand presence must be consistent, varied, and sustained. A company that posts once and then goes quiet is invisible in the decision-making process.

The real question to ask is not simply how many times a buyer must see the brand. The more important question is whether they are seeing the right message at the right stage of their journey.

Mapping Exposures to the Buyer’s State of Mind

For a company like Favoriot, which operates in the IoT and AIoT space and targets enterprise clients, government agencies, and system integrators, the exposure journey can be mapped across three distinct stages.

At the awareness stage, five to seven exposures serve to establish name recognition. The buyer begins to register that Favoriot exists and that it is active in the space they care about. They are not yet evaluating, but they are noticing.

At the trust-building stage, eight to twelve exposures shift the conversation from recognition to understanding. The buyer starts to grasp what Favoriot actually does, why it matters, and how it differs from alternatives. This is where thought leadership content, technical deep-dives, and customer stories begin to do their heaviest lifting.

At the purchase confidence stage, twelve to twenty meaningful exposures bring the buyer to a point where they are ready to initiate contact, request pricing, attend a training session, or discuss a potential project. This is not a passive audience anymore. They have been quietly building a case internally, and now they are ready to move.

Repetition with Variation Is the Real Strategy

The mistake many technology companies make is treating content as a one-time announcement rather than an ongoing conversation. They publish a product update, send one email campaign, and then wait for the pipeline to fill. When nothing happens, the conclusion is often that the market is not ready, when the real issue is that the message has not been delivered enough times or in enough forms.

The approach that works is repetition with variation. The core message stays consistent, but the angle changes with each touchpoint. One week it is a problem statement framed around a real challenge facing a city or an enterprise. The next week it is a customer story showing how a specific outcome was achieved. Then comes a webinar invitation, followed by a demonstration video, a data sheet, a LinkedIn article, a referral from a trusted partner, and eventually a direct proposal.

Each of these formats reaches a different segment of the buyer’s brain at a different moment in the journey. The cumulative effect is what transforms a vague sense of familiarity into a genuine willingness to engage.

Building a Brand That Earns the Right to Be Remembered

For any B2B technology company competing in a space where contracts take months and stakeholders number in the double digits, the discipline of sustained, multi-channel presence is not optional. It is the entire game.

The practical target for companies in this space is a minimum of seven meaningful touchpoints, with a realistic planning horizon of twelve to twenty before serious buying conversations begin. That means building a content calendar that spans LinkedIn posts, email sequences, webinar series, case study libraries, video demonstrations, partner referrals, and direct outreach, all carrying the same core message from a different direction.

The goal is to move the buyer from “I think I have seen that name before” all the way to “I think we should set up a meeting with them.”

How many touchpoints has your company planned for this quarter, and are they designed to move buyers forward or simply to fill a content calendar?

This article draws on principles from Favoriot’s market strategy for IoT and AIoT adoption in B2B and enterprise environments. Favoriot provides IoT platforms, AIoT training, and smart city solutions for system integrators, enterprises, and government agencies across Southeast Asia.

Why Blogging When Nobody Was Reading Was the Best Business Decision I Ever Made

The long game of content, before it was called content marketing. How years of blogging to an empty room became the foundation of a business, a reputation, and a life’s work in IoT.

Let me ask you something. If you wrote something today and nobody read it, would you write again tomorrow?

Most people would say no. And I understand why. We live in a world that measures everything in likes, shares, reach and impressions. If the numbers don’t move, the assumption is that nothing is working. That you are wasting your time. That maybe you should stop.

I started blogging around 2009. At that time, IoT was barely a word in people’s vocabulary. Social media was young. And I was writing about telemetry, machine-to-machine communication, and connected devices… to what felt like an empty room. The analytics were humble, to put it kindly. Sometimes a few dozen readers a day. Sometimes less.

But here is what I know now that I didn’t fully appreciate then: that empty room was being recorded.

Planting Seeds Before Anyone Was Hungry

When I wrote in those early years, I wasn’t writing to go viral. I was writing because I had ideas that needed to get out of my head and onto paper. I was processing things I had seen in my career at MIMOS, CELCOM and UTM. I was trying to make sense of where technology was heading, and writing was how I thought through things properly.

There was no content calendar. No SEO strategy. No analytics dashboard I checked obsessively every morning. Just me, a laptop, and the belief that what I was writing about actually mattered, even if the world hadn’t caught up yet.

And then IoT exploded.

Between 2013 and 2015, the conversation around connected devices went from niche to mainstream almost overnight. And suddenly, people were looking for someone who understood the space, someone who had been thinking about it, writing about it, for years. That someone was already there. I had the archive. I had the track record. I had the voice.

That is when I understood what I had been doing all along. I had been building credibility on a platform I owned, quietly, consistently, before there was any social pressure to perform.

The Business That Content Built

When I co-founded FAVORIOT in 2017, I didn’t have to start from zero when it came to reputation. The blog had done years of work. Every article I had written about IoT platforms, smart city infrastructure, the challenges of data connectivity… those were bread crumbs that led people to me long before FAVORIOT existed as a company.

Investors ask you what makes you credible in your space. Customers ask why they should trust you over a larger competitor. Journalists ask why your opinion matters. What I could always point to was the body of work. Not a pitch deck, not a fancy website, but hundreds of posts that showed how I thought, what I believed, and how long I had been in this conversation.

You cannot fake a ten-year archive of consistent ideas.

That is what content does when you treat it seriously over a long period of time. It becomes proof. It becomes your reputation, made searchable and permanent.

When Nobody Is Watching, That Is the Real Test

I want to be honest about something. There were stretches of time when I wondered if I should just stop. The numbers were not rewarding. Nobody was sharing my posts to their thousands of followers. The inbox was quiet.

But I kept asking myself: do I believe what I am writing? Do I think this matters?

The answer was always yes. And that is what kept me going.

Looking back, I think the discipline of writing when nobody was watching was actually what built the quality of my thinking. When you write for an audience that doesn’t exist yet, you can’t rely on trending topics or viral hooks. You have to write something true. You have to be genuinely useful. You have to develop a real point of view, because there’s no performance to hide behind.

That pressure, the pressure of honesty over popularity, sharpened me in ways that no conference or workshop ever could.

The Compound Interest of Ideas

There is a concept in finance called compound interest. Money grows not just from what you put in, but from the returns building on themselves over time. Content works exactly the same way.

A post I wrote in 2011 about sensor networks brought me a speaking invitation in 2014. A talk in 2014 turned into a collaboration in 2016. A collaboration in 2016 led to a client for FAVORIOT in 2019. And so on. The chain of connections is rarely obvious when you are in the middle of it. You only see it clearly when you look backwards.

If I had stopped blogging in 2010 because the numbers were small, none of those downstream opportunities would have existed. The compound interest would never have started accumulating.

This is what people miss when they treat content as a short-term campaign. Content is infrastructure. You build it slowly, you maintain it, and it works for you even when you are sleeping, traveling, or running a startup that demands every hour of your attention.

What I Tell Founders and Professionals Who Ask Me About Content

People often ask me: “Mazlan, should I start a blog? Should I write on LinkedIn? Is it worth it?”

My answer is always the same. Ask yourself not whether anyone will read it today, but whether you believe what you are writing is true and useful. If yes, write it. Then write it again next week. And the week after that.

Stop thinking about content as a marketing activity. Start thinking about it as a thinking habit that happens to be public.

Because the day will come, and I genuinely believe this for anyone with real expertise and something honest to say, the day will come when someone will find that old post you wrote when nobody was looking, and it will open a door you never expected.

I have lived that story more times than I can count. And it all started with a decision to write anyway, even when the room was empty.

So let me leave you with this: what do you know right now, in your field, in your experience, that the world hasn’t fully caught up to yet? Are you writing it down? Are you sharing it?

Because someone out there is about to start searching for exactly what you already know.

Why I Want More Malaysian Students to Brag About Their Projects

Malaysian students build impressive projects but rarely share them publicly. Here is why that needs to change, and what students, lecturers, and institutions can do about it.

Have you ever built something and then kept it to yourself?

I have seen this happen too many times, and it bothers me more than I probably let on. A student spends weeks getting an IoT sensor to talk to a cloud platform, wires everything up, writes the code, stays up late debugging, and then… nothing. They submit the assignment, get their marks, and move on. Nobody outside that classroom ever knows the project existed.

That project deserved better. And honestly, so did the student.

The Culture of Hiding Our Work

I think we have a cultural habit in Malaysia of downplaying what we build. We are taught, from a young age, that showing off is rude. That humility means staying quiet. That if your work is good, people will somehow find out on their own.

But in the world we are living in today, that thinking is holding our students back.

I recently wrote about how some students in Malaysia are still learning IoT using Blynk, ThingSpeak or Favoriot, platforms that have genuinely served the community well over the years. My concern was not with the tools themselves, it was with the possibility that some students might complete their programmes without being exposed to more current, industry-relevant environments. The response to that piece was warm and it opened a much bigger conversation I want to continue here.

Because there is a second problem, and it sits right next to the tools issue. Even when students build something impressive, they rarely tell the world about it.

What “Bragging” Really Means

I want to be careful with my word choice here, because when I say I want Malaysian students to brag, I do not mean arrogance. I mean documentation. I mean visibility. I mean the courage to say, “I built this, and here is how I did it.”

In the global tech community, sharing your work is not showing off. It is how you contribute. It is how you invite feedback, attract collaborators, and build a reputation before you even graduate. Every time a developer writes a blog post about what they learned building a project, every time a student posts a short video demo on LinkedIn or YouTube, every time someone publishes their code on GitHub with a clear README, they are adding value to the community.

They are also building something that a CV alone cannot carry: a visible portfolio of thinking.

I Have Seen What Happens When Students Share

When students do step forward and share their work, remarkable things happen. I have seen students connect with mentors because someone stumbled across their blog. I have seen project ideas get picked up by companies that were looking for exactly that kind of solution. I have seen young engineers get job offers because a hiring manager found their GitHub repository.

And I have seen something perhaps more important: the student’s own confidence change. When you write about your project publicly, you are forced to explain it clearly. You start to understand what you actually built. You start to see what worked and, more importantly, what did not. That reflection is part of the learning that never shows up in an exam.

The Platforms Are Already There

There is no shortage of places where Malaysian students can share their work. LinkedIn is the obvious starting point, and yet I still see so many profiles with nothing more than a degree listing and a generic summary. Imagine if every final year IoT project at a Malaysian university had a proper LinkedIn post, with photos, a short explanation of the problem it solved, and the tech stack used.

GitHub is equally powerful. A well-documented repository says more about an engineer’s capability than almost anything else. Medium or WordPress and personal blogs remain excellent homes for longer technical write-ups. YouTube or TikTok are perfect for demo videos. Even short-form platforms have an audience hungry for genuine student work.

The tools to publish are free. The audiences are there. What is missing is the habit and the encouragement.

What Lecturers and Institutions Can Do

I want to be fair here: this is not entirely on the students. If we want a culture shift, we need to start from inside the institutions.

Imagine if project documentation and public sharing were built into assessment rubrics. Imagine if a student was graded not only on whether the sensor collected data correctly but also on whether they could explain the project clearly to a non-technical audience. Imagine if universities celebrated student projects the way they celebrate sports achievements.

Some institutions are already doing this, and I applaud them. But it needs to be more systematic. Students should graduate not just with technical skills but with the confidence and habit of communicating those skills to the world.

A Personal Challenge

If you are a student reading this, I want you to do one thing this week. Pick a project you are working on or have completed. Write about it somewhere public. It does not have to be perfect. It does not have to be long. Just write honestly about what you were trying to solve, what you used to solve it, and what you learned in the process.

That one post could be the start of something you cannot predict yet.

If you are a lecturer or a programme coordinator, think about how you can make sharing a formal part of the learning journey. Not as a burden, but as a skill that students will use for the rest of their careers.

Malaysia has genuinely talented engineering students. I have met many of them, worked alongside some of them, and been impressed by what they can build when given the space to do it. My concern is that too much of that talent is invisible to the industry because no one taught them that visibility is part of the job.

So tell me, if you could make one change to how Malaysian engineering education celebrates student work, what would it be?

Why Malaysia Must Stop Treating IoT as a Final Year Project Toy

Every year, I meet students who proudly show me their IoT projects, and I can almost predict what will appear on the table before the demonstration even begins. There will be a sensor, a microcontroller, a few wires, a mobile app, and a dashboard showing temperature, humidity, distance, motion, water level, or some other familiar reading. The student will explain how the system works, the lecturer will nod, the evaluator will ask a few questions, and everyone will feel relieved when the demo runs without embarrassment. For a few minutes, the project looks alive, impressive, and full of promise.

Then, after the presentation, something strange happens. The device is switched off. The components are kept in a box. The dashboard is no longer opened. The video may be uploaded somewhere, but after that, the whole thing quietly disappears into the graveyard of final year projects. Nobody continues collecting data. Nobody studies the pattern. Nobody asks whether the system can be deployed in a real site. Nobody asks whether the idea can be improved, commercialised, or connected to an actual industry problem. It simply ends where it started, on the classroom table.

Each time I see this, I ask myself, “Is this what IoT has become in Malaysia? A temporary demo to pass an assessment?”I am not saying this to mock students. Far from it. I respect students who spend sleepless nights trying to make their projects work. I know the pain of troubleshooting something that refuses to behave when people are watching. Anyone who has handled hardware knows that sensors have a strange sense of drama. They work perfectly at midnight, then suddenly become shy during the presentation.

But my concern is bigger than the student project itself. My concern is that Malaysia has treated IoT for too long as something small, experimental, academic, and temporary, when in reality, IoT should already be part of how we manage our cities, farms, buildings, factories, transport systems, utilities, campuses, and public services. IoT is not a toy. It is infrastructure intelligence. Malaysia must start treating it that way.

The Problem Is Not the Students

Let me say this clearly. The problem is not the students. Many of them are creative, hardworking, and eager to learn. They work with limited budgets, limited time, borrowed components, weak WiFi, and sometimes unclear project guidance. They do what they can with what they have, and for that, they deserve encouragement. The issue is not their effort. The issue is the way we have framed IoT in education, industry, and sometimes even government projects.

For many years, IoT has been taught and demonstrated as a sensor to dashboard exercise. Connect the device. Send the data. Show the graph. Done. That is useful as a starting point, but it is a dangerous place to stop. When IoT is presented only as a dashboard project, students naturally assume that the job is complete once data appears on the screen. They do not always ask what happens after the data appears, who will use it, what decision it supports, what action must follow, what happens when the device fails, or whether the system can survive outside the classroom.

Maybe we taught them to build the wrong finish line, I thought to myself. The finish line should not be “the data appears.” The finish line should be “someone makes a better decision because the data appeared.” That is the difference between a demo and a real solution.

A Sensor Is Not a Solution

One of the biggest misunderstandings about IoT is the belief that once a sensor is connected, the problem is solved. This is like saying a thermometer cures fever. A thermometer does not cure anything. It only tells you something is wrong. What matters next is the interpretation, the decision, the treatment, the follow up, and the responsibility of the person who acts on that reading.

IoT works the same way. A temperature sensor in a cold room does not protect vaccines or food by itself. It only provides signals. The real value begins when the system detects abnormal readings, alerts the right person, records the evidence, helps the operator respond quickly, and supports compliance reporting. A water level sensor near a river does not prevent flooding by itself. It becomes useful only when the data is trusted, the alert reaches the correct agency, the response process is clear, and residents receive warnings early enough to act. A vibration sensor on a machine does not prevent downtime by simply producing numbers. It becomes useful when those numbers are analysed, compared against patterns, and linked to maintenance decisions before the machine fails.

That is why I always say the dashboard is not the destination. The dashboard is only the window. The real question is what we do after looking through that window. If we see a problem and nobody acts, then the system has failed quietly. It may still look beautiful on a screen, but it has not changed anything in the real world.

Malaysia Has Too Many Real Problems for IoT to Remain in the Lab

Malaysia does not lack problems that need better visibility. We have floods that still catch people by surprise, buildings wasting energy after office hours, farms that need better monitoring of soil, water, and climate, logistics operators that must prove temperature compliance, factories that want to reduce downtime, public facilities that need better maintenance, and local councils trying to manage waste, traffic, drainage, parking, lighting, and public complaints with limited manpower.

These are not imaginary classroom problems created for a semester project. These are real operational issues that cost money, time, trust, and sometimes safety. Yet many organisations still operate using manual checks, WhatsApp updates, delayed reports, and reactive decisions. Someone must visit the site. Someone must take a photo. Someone must key in data. Someone must send a message. Someone must wait for approval. By the time the information reaches the decision maker, the problem may already have grown bigger.

This is where IoT should become serious. IoT should help Malaysia see earlier, respond faster, and plan better. It should reduce blind spots in operations. It should help people move from guessing to knowing, and from reacting late to acting early. But that will not happen if IoT continues to be treated as a decorative technology for exhibitions, competitions, and one off prototypes.

A smart city is not built from disconnected demos. A smart factory is not built from one sensor reading on a laptop. A smart farm is not built from a project that stops after the student graduates. Real IoT needs continuity, ownership, maintenance, platforms, training, security, and people who care about the outcome, not just the device.

The Final Year Project Mindset Is Too Small

Final year projects are important. They help students learn, test ideas, make mistakes, and gain confidence. I fully support that. But when the final year project mindset becomes the national mindset, we have a problem. The final year project mindset usually asks whether the system can work for the demo, whether the data can appear on a screen, whether the poster looks good, whether the report can be submitted, and whether the panel can be impressed.

A national IoT mindset asks much harder questions. It asks whether the system can solve a real problem, work outside the lab, scale to multiple sites, be maintained for years, protect the data, support daily decisions, reduce cost, reduce risk, improve service delivery, and continue after the project team leaves. These are the questions Malaysia must start asking more seriously.

We cannot keep celebrating prototypes while ignoring adoption. We cannot keep launching pilots that never move into operations. We cannot keep confusing activity with progress. There is a big difference between building something and making it useful. Malaysia has built many IoT things. Now we must make them useful.

Stop Asking Only “Can It Connect?”

One of the most common questions in IoT is, “Can it connect?” Of course, connectivity matters. Without connectivity, the device becomes an island. But connectivity alone is not enough. A connected device that sends meaningless, unreliable, unsecured, or unused data is not a success. It is only a noisy device.

The better questions are more practical. Can it connect reliably? Can it recover when the network fails? Can it send clean and meaningful data? Can it protect that data? Can it trigger the right response? Can it help the user decide faster? Can it reduce manual work? Can it be supported for years, not weeks?

This is where many IoT projects become weak. They focus too much on the first connection and not enough on long term usefulness. I have seen systems where the data appears nicely on the dashboard, but nobody knows what threshold should trigger an alert. I have seen dashboards that look impressive, but no department has agreed who is responsible when something abnormal happens. I have seen projects where the devices were installed, but after a few months, nobody checked whether the data was still accurate.

That is not IoT maturity. That is technology theatre. It looks good from far, but when you stand closer, you realise the system has no operational backbone.

IoT Must Belong to the People Who Own the Problem

Another mistake I often see is when IoT is handed entirely to the technical team. The technical team can connect devices, configure networks, set up platforms, and build dashboards. That part is important. But they cannot define business value alone. Technology people can build the pipe, but the people who face the pain must define what should flow through it and what should happen after that.

If the project is about energy, the energy manager must be involved. If the project is about farming, the farm operator must be involved. If the project is about city services, the relevant local council department must be involved. If the project is about machine maintenance, the maintenance team must be involved. If the project is about cold chain, the operations and compliance teams must be involved.

IoT fails when it becomes a technology project without an operational owner. The people who feel the pain must be part of the design from day one. They know the messy details. They know where problems happen. They know which alerts matter and which alerts will be ignored. They know what kind of information is useful at 8 a.m. on a busy Monday, and what kind of dashboard nobody will ever open after the vendor leaves.

Who owns the pain? That is the question I often ask myself. Because the person who owns the pain should also own the outcome.

Cybersecurity Must Be Built In From the Beginning

When we connect more devices, we also create more openings. This is the side of IoT that many people do not like to talk about during cheerful demos. A connected device can provide visibility, but a poorly secured device can also become a weak door into a larger system. That is why IoT cannot be treated casually, especially when it starts moving into buildings, factories, campuses, farms, utilities, transport systems, and critical services.

Every IoT project should ask security questions from the beginning. Who can access the device? How is the device authenticated? Can the firmware be updated safely? Can the data be altered? Can someone fake a reading? Can unusual device behaviour be detected? What happens when the device is stolen, damaged, or hijacked? How do we separate normal failure from suspicious activity?

AI can help detect abnormal patterns and support faster response, but AI is not a magic shield. A weak IoT architecture with AI added later is still weak. It is like putting a fancy lock on a wooden door that is already cracked. Security must be designed into the system, not sprinkled on top after the project becomes popular.

This is why I often remind people that IoT is no longer just an engineering conversation. It is also a cybersecurity conversation, a governance conversation, and a trust conversation. Once a device is connected to a larger environment, it becomes part of a bigger responsibility.

The AI Conversation Makes IoT More Important

Today, everyone wants to talk about AI. AI is in every conference, proposal, workshop, policy conversation, and almost every company profile. Sometimes it feels as if even the office pantry will soon claim to have an AI powered coffee strategy. I understand the excitement because AI is powerful, but we must remember something very basic.

AI needs data. Not just old data sitting in spreadsheets, but live, real world, operational data. Data from machines, buildings, vehicles, rivers, farms, cold rooms, energy meters, production lines, and public facilities. Where does that data come from? It comes from IoT.

IoT is the bridge between the physical world and digital intelligence. Without IoT, many AI systems are left guessing from outdated, incomplete, or manually entered information. This is why I find it strange when people say IoT is old news and AI is the future. To me, that is like saying the brain is important, but the nerves are no longer needed.

AI may be the brain, but IoT is part of the nervous system that senses what is happening in the real world. If the nerves are weak, the brain receives poor signals. When the signals are poor, the decisions will also be poor. Malaysia cannot build serious AI for real world operations while treating IoT as an afterthought. The two must grow together.

We Need Local Capability, Not Permanent Dependency

There is another issue that we must discuss honestly. Many students and developers in Malaysia still use overseas IoT platforms by default. They use them because tutorials are easy to find, examples are everywhere, and seniors have used them before. I understand this completely. When a student is rushing to complete a project, the easiest path becomes the most attractive path.

But at a national level, we must ask a bigger question. Do we want to remain only users of other people’s platforms, or do we want to build our own capability as well? This is not about rejecting global platforms. There is nothing wrong with learning from global tools. They have their strengths, and they serve many use cases well. But if every university, student, agency, and company only learns using external platforms, then our local ecosystem will remain thin.

We will produce users, not builders. We will produce dependency, not confidence. We will produce projects, not capability. Malaysia needs local platforms, local examples, local documentation, local support, local case studies, and local success stories. We need students who can say they built something using a Malaysian IoT platform like Favoriot, and that project can be extended into a real solution. We need lecturers who can expose students to platforms that understand local industry needs. We need system integrators who can build faster because they are not starting from zero every time. We need government and industry buyers who care about long term ownership, data governance, and local support.

This is how an ecosystem grows. Not through slogans, but through usage, trust, and repeated real deployments.

Pilots Must Stop Dying After the Launch Photo

Malaysia loves pilot projects. We launch pilots with banners, speeches, handshakes, group photos, and sometimes a nice gimmick where someone presses a button on stage. I have nothing against pilots. A pilot is useful when it helps us learn, reduce risk, and prepare for wider adoption. But a pilot becomes wasteful when it ends at the launch photo.

Too many IoT pilots do not answer the most important questions. What did we learn? Did the system solve the original problem? Who used the data? What decision changed? What cost was reduced? What risk was avoided? What process improved? What failed? What should be changed before scaling? Can this model be repeated in another location?

If we cannot answer these questions, then the pilot was not a learning exercise. It was a performance. A good pilot must have a path to adoption. It must be designed with scale in mind, even if the first version is small. It must include training, maintenance, user feedback, support, and measurable outcomes.

Small pilots are fine. Small thinking is not.

Universities Must Raise the Standard

Universities have a major role to play because they are not just producing graduates. They are shaping how the next generation understands technology. If IoT is taught only as a technical connection exercise, students will graduate thinking that connectivity is the main achievement. But if IoT is taught as a complete system, students will begin to think like solution builders.

They will understand sensors, communication, platforms, data quality, cybersecurity, analytics, user needs, operations, and business value. They will learn that the real world is not as friendly as the lab. In the lab, the WiFi usually works. In the field, the signal disappears when you need it most. In the lab, the power supply is stable. In the field, someone may unplug the adapter because they need the socket. In the lab, the sensor is clean. In the field, it faces heat, rain, dust, insects, vibration, curious hands, and sometimes people who have no idea why the device is there.

This is why students need exposure to real problems. Let them work with local councils, farms, factories, hospitals, logistics companies, buildings, and campuses. Let them talk to actual users. Let them understand frustration, constraints, budgets, maintenance, and accountability. A student who has seen real operational pain will build differently. That student will not simply ask whether a value can appear on a dashboard. That student will ask whether the data can help someone act before the problem becomes worse.

That is the kind of graduate Malaysia needs.

Government and Industry Must Demand Outcomes

The responsibility is not only on universities. Government agencies, local councils, GLCs, enterprises, and private companies must also change how they buy and evaluate IoT. Do not buy IoT because it sounds modern. Do not install sensors because other cities have sensors. Do not ask for dashboards because dashboards look impressive in meeting rooms. Ask for outcomes.

Before starting an IoT project, the buyer should ask what decision the system supports, who will respond to alerts, how success will be measured, how the system will be maintained, how the data will be protected, and how the project will continue after year one. They should also ask what happens when the vendor is no longer standing beside the dashboard during a demo. That is where the truth normally appears.

This is where procurement must become smarter. If the tender only asks for devices and dashboards, the result will be devices and dashboards. If the tender asks for operational outcomes, response workflows, security design, data ownership, maintenance, training, and measurable impact, then vendors will have to design more serious solutions.

Malaysia must stop buying gadgets and start buying operational intelligence.

IoT Is a Long Term Commitment

Many people underestimate what happens after installation. The project is not finished when the devices are installed. In many ways, that is when the real work begins. Devices need monitoring. Sensors need calibration. Users need training. Alerts need tuning. Dashboards need improvement. Data needs review. Network issues need troubleshooting. Reports need refinement. Processes need updating. Budgets need planning.

IoT is not a one day event. It is a living system. This is why the final year project mindset is dangerous when applied to real deployments. In a student project, the goal is often to complete and submit. In a real deployment, the goal is to operate, improve, and sustain.

The system must still work after the excitement fades. It must still provide value when nobody is clapping. It must still help the user on an ordinary Tuesday morning when something goes wrong and people need answers fast. That is the true test of IoT. Not the demo. The ordinary day.

From Prototype Pride to Operational Discipline

We should still be proud of prototypes, but we should not stop there. A prototype is a question. A real deployment is an answer. A prototype asks whether an idea can work. A real deployment answers by showing how it improves operations.

Malaysia has enough prototypes. What we need now is discipline. We need discipline in defining problems, designing systems, securing devices, managing data, training users, measuring outcomes, scaling what works, and stopping what does not. This is not glamorous work. It may not look as nice as a launch ceremony, but this is where real progress happens.

Behind every useful IoT system, there are people doing boring but necessary things. They check data quality, fix device issues, improve alerts, train staff, review reports, update workflows, and make sure the system continues to serve the people who depend on it. That is how IoT becomes part of daily operations. Not through magic. Through discipline.

The Malaysia I Want to See

I want to see Malaysian students building IoT projects that do not disappear after final presentations. I want to see lecturers guiding students toward real world problems, not repeated versions of the same safe ideas. I want to see universities using local platforms and building stronger links with industry. I want to see local councils using IoT to manage floods, waste, parking, lighting, and public facilities more intelligently.

I want to see factories using IoT to reduce downtime and improve maintenance. I want to see farms using IoT to improve productivity and reduce waste. I want to see buildings using IoT to cut energy costs and support sustainability goals. I want to see local system integrators building reusable solutions instead of starting from scratch for every customer. I want to see Malaysia take IoT seriously as a foundation for AI, smart cities, and national competitiveness.

Most of all, I want us to stop underestimating our own ability. We have the talent. We have the problems. We have the technology. We have local platforms. We have universities. We have industries that need better data. What we need now is the courage to connect all of these pieces into something bigger.

IoT Was Never Meant to Stay on the Classroom Table

The blinking LED was never the final achievement. It was only the first sign that something could be connected. The real achievement comes when that connection creates awareness, that awareness leads to action, and that action improves lives, services, businesses, and national capability.

Malaysia must stop treating IoT as a final year project toy because the world has already moved on. IoT is now part of infrastructure, cybersecurity, AI, sustainability, smart cities, industrial growth, and operational decision making. If we continue treating it as a small student experiment, we will produce many demos but too few outcomes. That would be a waste, not just of components or project budgets, but of potential.

Maybe the problem is not that Malaysia lacks IoT projects, I thought to myself. Maybe the problem is that too many of them are never allowed to grow up.

So let us allow them to grow. Let us move IoT from the classroom table to the operations room, from assignment marks to measurable outcomes, from dashboards to decisions, from prototypes to platforms, and from toys to infrastructure. Malaysia does not need more blinking LEDs to prove that we can connect things. Malaysia needs connected systems that help us think, act, and build better.

What do you think? Are we ready to treat IoT as serious national capability, or are we still too comfortable celebrating prototypes that never leave the lab? I would love to hear your thoughts in the comments.

Life on Stage: The Journey of a Speaker Who Never Asked to Become One

Mazlan Abbas  ·  Founder Reflections  ·  2025

Life on Stage: The Journey of a Speaker Who Never Asked to Become One

From a single university talk to hundreds of stages across four continents

If someone asks me, “Mazlan, how many times have you given a presentation?” I’ll just smile. Not out of arrogance. But because I honestly can’t remember. What I do remember is that it didn’t start because I wanted to be a speaker. It started because I had something worth sharing, and people began to listen.

This isn’t a post about achievements. It isn’t a resume list. This is a story about what happened between all those numbers. What I felt standing in front of a room. What I carried back to the hotel. What changed in me, one presentation at a time.

Every time I stepped onto a stage, I asked myself the same question: am I here to teach, or am I here to learn?

The answer was always both.

The expert in anything was once a beginner who refused to stop showing up.
Helen Hayes
2013 – 2015  ·  Seeds Planted

In the early days, I was talking about something most people hadn’t fully grasped yet. IoT. Internet of Things. Back then, when people heard “IoT” their faces went blank. I remember giving a talk at UTHM with barely any questions at the end… but I knew the seeds had to be planted early. Someone needed to walk away thinking, “Huh, that’s actually interesting.”

When I delivered the keynote at the International Conference on Soft Computing in Data Science 2015 at Pullman Putrajaya, I could feel the shift. People were beginning to take it seriously. “Internet of Things and Big Data: The Perfect Marriage” was the title I chose myself. Not for the glamour, but because I genuinely believed these two things were made for each other.

2016 – 2017  ·  The Stage Gets Bigger

These years were relentless. Singapore. Sydney. Jakarta. Kuwait. I was standing in front of people from different countries, talking about smart cities, IoT ecosystems, how technology could reshape the way we live. At the Smart Cities Expo World Forum in Sydney 2016, my message was about citizen engagement. Not just infrastructure. Not just data. People.

That’s what everyone always misses. Technology can be brilliant. But if citizens don’t engage, a smart city is just a smart facade.

Kuwait, Singapore, Sydney, Jakarta… not to collect passport stamps. But to bring back perspectives that no office or lab could ever give you.

2017 was also the year I realized something important: I was no longer just an academic or an industry guy. I had become a bridge. Universities invited me. Industries listened. Government agencies started calling. And with that position came a responsibility I didn’t take lightly.

2018 – 2019  ·  Local to Global

There is one moment I will never forget. Keynote at the Smart Cities Global Technologies and Investment Summit in Algiers, Algeria, June 2018. A single Malaysian standing before an audience from North Africa, talking about the IoT innovation ecosystem. There was a flutter of nerves. But far more than that, there was exhilaration.

Because what I brought to that room wasn’t just theory. It came from the real, lived experience of building Favoriot. From every failure and every struggle that no one in the audience could see behind the clean, polished slides.

2019 was even more intense. IIUM. UTeM. UCSI. Polytechnics. Borneo. Istanbul. Sarawak. Topics widened too, from IoT for the Construction Industry, to IR 4.0 for MINDEF. I had stopped talking about IoT in a narrow box. I was talking about transformation. About the future. About how human beings need to adapt or be left behind.

We cannot solve our problems with the same thinking we used when we created them.
Albert Einstein
2020 – 2021  ·  The World Changes, So Does the Stage

COVID arrived. Everything moved online. Webinars became everyone’s new language. And I, someone who had grown used to feeling the live energy of a room, had to adapt. Talking to a camera. Q&A via chat box. A different kind of connection, but the same message.

What I valued most during that period was that people still wanted to listen. MaGIC, UTHM, UiTM, USIM, ADTEC, Politeknik Mersing, UKM… the 2021 webinar list was endless. That told me something: curiosity about technology doesn’t stop, even when the world is falling apart.

I gave a talk on “Jobs That Don’t Exist Yet.” Halfway through, it hit me: several of the things I do today didn’t exist ten years ago either.

The talk at MMU on “The Entrepreneurship Journey of Pre and Post Covid-19” was when I felt closest to my audience. Not because the slides were great. But because the story was real. Favoriot faced the same tsunami. We survived, but we carry the scars.

2022 – 2023  ·  Deeper and More Specific

By 2022, the nature of invitations had shifted. People no longer called to hear a general talk about IoT. They wanted specifics. ESG. Manufacturing. Financial services. TVET. Smart cities. The energy sector.

That is a sign of maturity, both in the industry and in myself. Penang, Smart Factory Conference, October 2023: ESG in Manufacturing. That same month, ICSIMA at Tamu Hotel: Smart Measurement with IoT. Then WCIT 2023: 10 Ways IoT Can Drive ESG Compliance.

Some weeks had two or three events. The body was exhausted. But the mind couldn’t stop.

And then there was the keynote I gave with the most heart: ICoICT 2023, August that year. “Humanizing IoT: Placing People at the Centre of Technology.” That wasn’t just a title. That was my philosophy. After years of talking about devices, sensors, and connectivity, I needed to remind the room, and myself, that at the end of every data pipeline there is a human being. A mother who wants to know her child is safe. An elderly man who wants to live with dignity at home. A farmer who needs to know tomorrow’s weather.

2024 – 2025  ·  Rethinking Everything

The DSA 2024 talk on secured IoT communications marked my entry into the cybersecurity conversation in a more serious way. Smart applications demand secure communications. That is not optional. It is a requirement.

UTAR Talk, November 2024, “The Ultimate Things about IoT.” The audience was energetic students, full of questions. The best one: “Sir, in ten years, will IoT still be relevant?” I smiled. In ten years, IoT will be like electricity. You won’t see it, but you’ll need it everywhere.

And most recently, WCSC 2025. “From Smart to Regenerative: Rethinking Urban Transformation through IoT.” This represents a major shift in my thinking. Smart cities are no longer enough. We need cities that can heal themselves, adapt on their own, regenerate. Not just connected, but alive in a deeper sense.

Through all of it, I saw one common thread: I was never really talking about technology. I was talking about the people who use it, and the people who get left behind when they don’t.

At the National Address Conference, July 2025 at WTCKL, I carried a message about Technology and Data Sovereignty. This wasn’t purely a technical talk. It was about the future of a nation. Whoever holds the data holds the power. Malaysia must understand this.

200+Presentations
12+Countries
12Years on Stage
The purpose of life is not to be happy. It is to be useful, to be honorable, to be compassionate, to have it make some difference that you have lived and lived well.
Ralph Waldo Emerson

From 2013 to 2025. Hundreds of times standing on a stage. From UTHM to Algeria. From a small webinar to an international keynote. From speaking in front of 20 students to thousands of delegates.

What do I bring back every single time? Not the applause. Not my name in a programme book. Not a selfie with the organizer.

What I bring back are the questions people ask after the session. Simple questions, but deep ones. Questions that remind me why I started doing all of this in the first place.

This journey isn’t over. The next stage is already waiting. And I still have a great deal left to say.

Because technology keeps moving. And people need to move with it.

The Day a Small Malaysian Company Stood Shoulder to Shoulder with Microsoft, PwC and Mastercard

FAVORIOT has been named one of the Top 50 Thought Leading Companies on Innovation 2026 by Thinkers360, alongside Microsoft, PwC, Mastercard, and Tata Consultancy Services. As the only Malaysian company on this global list, here is what that recognition truly means.

When was the last time you sat quietly and let something truly sink in?

I had one of those moments recently. I was scrolling through the Thinkers360 announcement for their 2026 Top 50 Thought Leading Companies on Innovation, half-expecting to scan through the usual suspects and close the tab. Then I saw it. FAVORIOT. Right there in the list. Alphabetically sandwiched between the giants of the global technology and consulting world.

I had to read it twice.

Thinkers360 is not a popularity contest. It is not the kind of list you get onto by having a big marketing budget or by gaming social media algorithms. That is precisely what makes it different from most rankings out there. Their leaderboard is powered by a patented algorithm that evaluates companies based on authentic, personally authored thought leadership content, which includes articles, books, keynotes, media interviews, podcasts, whitepapers, and speaking engagements. You cannot buy your way in. You cannot inflate your score with fake followers or reshared third-party content. What counts is what your people genuinely know and are willing to share with the world.

So when FAVORIOT appeared alongside Microsoft, PwC, Mastercard, Tata Consultancy Services, HCLTech, and ServiceNow, I did not feel triumphant in the way you might after winning a business pitch. I felt something quieter and deeper than that. I felt grateful, and I felt a kind of responsibility.

Let me put this into context, because context matters enormously here.

FAVORIOT is a Malaysian company. We are not a billion-dollar multinational. We did not emerge from Silicon Valley or London or Singapore’s Orchard Road. We were built in Kuala Lumpur, by a team that believes deeply in the power of IoT to transform how cities are managed, how industries are monitored, and how businesses make decisions with real-time data. We have been doing this since 2017, quietly and consistently, publishing our thoughts, sharing our frameworks, speaking at conferences, writing when others are sleeping, and building a body of knowledge that goes far beyond what our company size might suggest.

And I think that is exactly the point.

Thought leadership has never been about size. It has always been about substance. It has always been about the courage to have a perspective, to write it down, to share it publicly, and to do so consistently even when the audience is small and the applause is quiet.

I remember the early days of FAVORIOT, when I would publish an article about IoT adoption in developing markets and wonder if anyone was reading. I remember speaking at regional conferences where I was one of the few voices pushing the narrative that Southeast Asia did not have to be a technology consumer, we could be a technology contributor. I believed that deeply, and I kept writing, kept speaking, kept building.

What Thinkers360 has done with this ranking is validate something I have always believed: that genuine expertise, consistently shared, eventually finds its audience. Their methodology deliberately looks beyond social media reach and evaluates the full body of work a company produces. The articles your team writes. The keynotes your leaders deliver. The books, the whitepapers, the podcasts, the depth of contribution to the global conversation. That is a hard score to fake, and I am proud that FAVORIOT earned it the hard way.

Being the only Malaysian company on this list carries a weight I do not take lightly. This is not just a FAVORIOT achievement. It is a moment for the Malaysian technology ecosystem to recognise that we belong in the global conversation, not as observers, but as contributors. Our ideas about IoT, smart cities, and enterprise connectivity are not local curiosities. They are relevant globally, and this recognition confirms it.

Standing in the same list as PwC, a firm with over 360,000 employees across 151 countries, or Microsoft, which shapes the technology infrastructure of virtually every organisation on earth, is not something I will pretend feels ordinary. It is extraordinary. But it also tells me something important: the criteria that matter, depth of thought, consistency of publishing, willingness to educate and elevate an industry, those criteria do not require a headcount of thousands. They require commitment.

I often tell my team that we are not just building an IoT platform. We are building a body of thought. We are documenting what works, sharing what does not, and contributing to a global understanding of how connected technologies can solve real problems for real people in real cities. Every article published, every keynote delivered, every insight shared on LinkedIn or our blog is a brick in that structure.

Today, Thinkers360 has told us that structure is visible. That it stands tall enough to be counted among the world’s most influential companies in innovation.

What comes next matters more than the recognition itself. We will continue writing. We will continue speaking. We will continue challenging assumptions about what IoT can do and who gets to lead that conversation. And we will continue carrying the Malaysian flag into rooms where, honestly, not many have taken it before.

If you are building something in this part of the world, something real, something you believe in, and you are doing the quiet, consistent work of sharing your knowledge with the world, I want you to know this: it accumulates. It compounds. And one day, it gets seen.

Are you investing in thought leadership the same way you invest in your product? Because in the end, the companies that shape industries are the ones that shape the conversation first.

Explore the full Thinkers360 50 Thought Leading Companies on Innovation 2026 list. If your organization is building something worth sharing, the global conversation is still wide open, and the world is still listening.