Stop Selling “Smart City.” Start Selling the Thing That Actually Works.

A colleague in Bangkok sent me something last month that made me stop scrolling.

He’d been reviewing procurement data across a handful of ASEAN municipalities, trying to understand why so many “smart city” line items in city budgets kept getting quietly renamed, restructured, or dropped altogether after year two. Not cancelled outright. Just… rebranded into something else. A flood monitoring project. A cold chain upgrade. A dengue alert system.

Same money. Same sensors, half the time. Different name on the invoice.

Why does that happen?

The label became the liability

Here’s the uncomfortable finding buried in that data: in the very countries where “smart city” programs have run the longest, the term itself has started to carry baggage. Mention it in a council meeting now and you get polite nods and quiet skepticism. People have seen the glossy master plans. They’ve seen the dashboards nobody looks at after the ribbon-cutting. “Smart city” has become shorthand for over-promised and under-delivered, and everyone in the room knows it, even if nobody says it out loud.

I’ve sat in enough of those rooms myself, going back to my REDtone IoT and FAVORIOT days, to recognize the exact moment a pitch loses the audience. It’s not when the tech is weak. It’s the second you say “smart city” as the category, instead of naming the actual problem you’re solving.

Compare these two openings.

“We’re deploying a smart city platform for your municipality.”

Versus:

“We’re building a system that tells you a flood is coming to Nakhon Si Thammarat 36 hours before it hits, instead of after.”

One is a category. The other is a promise you can be held to.

Nakhon Si Thammarat isn’t hypothetical

I keep coming back to Nakhon Si Thammarat because it’s not a thought experiment. That province has taken real, repeated flood losses, year after year, the kind that show up in disaster relief budgets and insurance claims long before anyone writes a case study about them. Nobody there needs convincing that flood early warning has value. The ROI narrative writes itself: fewer evacuations done blind, fewer bridges washed out with no warning, fewer farmers finding out their fields are underwater from a neighbor’s phone call instead of a sensor.

That same budget line could have been labeled “smart city resilience initiative.” Would it have moved as fast through approval? I doubt it.

Vertical, not category

This is the part I think a lot of us in the industry got backwards for years. We built the category first, dengue and flood and cold chain as features, sub-modules living inside something bigger called Smart City. It felt efficient. One platform, many use cases, one procurement conversation.

But procurement doesn’t buy platforms. Health ministries buy outbreak prevention. Disaster management agencies buy lead time. Cold chain operators buy spoilage reduction they can put a ringgit figure next to. Nobody in those rooms has a budget line called “digital transformation.” They have a budget line called “vaccine wastage,” and that number is already too high, and somebody upstairs is asking why.

Cold chain monitoring, dengue and health surveillance, flood and disaster response, environmental monitoring, these are not features of a smart city. They are the smart city, minus a label that’s stopped helping and started hurting.

The money still often sits inside a smart city budget allocation. That part hasn’t changed. What’s changed is what you say out loud in the pitch meeting.

What I tell founders now

When a founder asks me how to position an IoT solution for government or municipal buyers these days, I tell them the same thing every time: find the named domain. Not the umbrella term. The named domain.

Don’t say you do smart agriculture. Say you cut fertilizer waste for palm oil smallholders by a measurable percentage. Don’t say you enable smart healthcare. Say you cut the time between a dengue cluster forming and a health officer knowing about it, from weeks to days.

Is this just marketing, a coat of paint on the same technology? Partly, yes. But it’s also something more honest than marketing. It’s an admission that “smart city” was always too big a promise for any single vendor, any single deployment, any single budget cycle to keep. The category asked cities to imagine a transformed future. The vertical asks them to solve a problem they already have a number attached to.

I’ve watched too many pilots die waiting for the transformed future to arrive. I’d rather help ship the flood warning that works.

The question worth sitting with

If you’re building or selling IoT into government right now, ask yourself honestly: could a mayor explain what you do in one sentence, using a number, without saying the words “smart city” at all?

If the answer is no, you don’t have a weak product. You have a pitch still hiding inside a category that’s already lost the room’s trust.

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

Malaysia’s IoT Market Has The Infrastructure. So Why Is Adoption Still Crawling?

Every few months a new market research report lands in my inbox with a headline number for Malaysia’s IoT market. Billions of dollars. Double-digit CAGR. Smart city spend projected to grow at 27% a year through 2034. On paper, we look like a country sprinting toward a connected future.

I have been in this industry long enough, from MIMOS to REDtone IoT to building FAVORIOT from scratch, to know the difference between a market projection and a market. The projection is what analysts model when they extrapolate 5G rollout numbers and government budget announcements. The market is what actually gets deployed, paid for, and kept running past the pilot phase. In Malaysia right now, there is a real gap between the two, and I think it is worth naming exactly where that gap comes from.

The Infrastructure Story Is Genuinely Good

Let’s give credit where it belongs first, because the connectivity layer has moved fast. 4G coverage sits above 96% of populated areas. 5G adoption crossed 52% by the end of 2024, and coverage reached over 82% of populated areas by 2025. Malaysia has more than 7,000 5G sites deployed and pulled in over RM86 billion in data center investment in 2024 alone, making the country Southeast Asia’s leading data center hub.

That is not a small achievement. A country cannot build an IoT economy without pipes to carry the data, and Malaysia’s pipes are, by regional standards, excellent. If you had told me in my MIMOS days that we would have this level of physical infrastructure by 2026, I would have been thrilled.

But infrastructure was never the constraint. Demand was.

The Roadmap We Wrote, And The Reality We Got

Go back to the National IoT Strategic Roadmap, the document MIMOS helped shape more than a decade ago. It forecast IoT applications and services reaching RM34 billion by 2025, up from RM7.5 billion in 2020. Device production was projected to hit RM4.3 billion in the same window.

Nobody in this industry seriously believes we hit those numbers. I do not say that to be cynical about the roadmap. I say it because the gap between what we projected and what materialized is the single most instructive data point in this entire market. It tells us the bottleneck was never technological capability. It was adoption discipline, and adoption discipline is a much harder problem to solve with a budget allocation.

Seven Reasons Growth Keeps Stalling

I want to walk through the actual mechanics of why, because “slow adoption” is too vague to act on. Here is what I see happening on the ground, backed by what the data confirms.

SMEs are still building the foundation IoT depends on. Malaysia’s economy runs on small and medium enterprises, and a recent survey found only about 35% of surveyed SMEs had implemented basic digital systems beyond simple accounting software. You cannot sell predictive maintenance sensors to a factory floor that has not digitized its production logs yet. IoT vendors keep pitching step five to companies that are still working through step one, and the pitch lands as noise rather than opportunity.

The payback math does not match buyer expectations. Deploying an IoT platform requires real upfront investment in hardware, software, and integration with legacy systems, and for SMEs this cost is a genuine barrier to entry even when the long-term ROI is positive. Malaysian buyers, especially in manufacturing and plantation sectors, want a return inside 12 to 18 months. Most honest business cases for connected infrastructure deliver in 24 to 36. That gap kills deals at the finance desk long before the technical evaluation even starts.

We have a talent bottleneck on both sides of the table. Adoption requires skills in IoT, data analytics, cybersecurity, and cloud computing, and Malaysia faces a real shortage of professionals who can manage these deployments end to end. This hits twice. Customers cannot maintain what they buy, and system integrators cannot scale delivery teams fast enough to take on more projects. I see this constraint directly in how far my own SI partners can stretch their capacity.

We have become excellent at pilots and mediocre at scale. I have written about this before, going back years: many organizations in Malaysia are still exploring what IoT can do rather than actually implementing it at scale. Government and GLC procurement cycles routinely stretch 12 to 24 months, and by the time a tender closes, the internal champion who pushed for the pilot has often moved to a different role. The institutional memory that would carry a pilot into a fleet-wide rollout simply evaporates.

5G hype outran 5G reality, and it dented confidence broadly. This one deserves more attention than it gets. 5G speeds actually fell 46% as user numbers scaled during 2024 and 2025, with real-world performance landing at roughly half of what marketing promised. Enterprise deployments involving sensors and remote machinery hit ceiling effects faster than expected. The irony is that most industrial IoT use cases never needed 5G in the first place. NB-IoT, LoRaWAN, and plain 4G cover the majority of real deployments. But 5G dominated the boardroom conversation for two years, and when it underdelivered, some of that disappointment bled into skepticism about connected technology in general.

Security fear has outpaced security literacy. IoT devices expand the attack surface for cybercriminals, and data privacy regulations around data ownership add another layer of complexity. Malaysia’s breach history has not helped confidence here. 2023 recorded the highest number of data breaches on record, with fifteen ransomware cases reported per week. For risk-averse government agencies and GLCs, “where does my data actually sit” has become a conversation-ending question, and few local vendors carry the certifications to answer it with authority.

Policy attention has moved on to AI, and IoT lost its dedicated spotlight. Look at where Budget 2026 puts its weight. RM53 million for the Malaysia Digital Acceleration Grant targeting blockchain, AI, and quantum computing. RM18.1 million for the National AI Office. RM2 billion earmarked for a Sovereign AI Cloud. IoT is barely named as a standalone priority anymore. Compare that to Budget 2025’s allocation of just RM15.1 million for smart city development under the Housing and Local Government Ministry, a rounding error next to the AI figures. Without a dedicated policy push, and without a compliance mandate the way India’s FASTag requirement forced RFID adoption almost overnight, Malaysian IoT adoption stays voluntary. Voluntary adoption is slow adoption by definition.

The Pattern Underneath The Pattern

Put these seven factors together and a single story emerges. Malaysia does not have a technology problem. It has a demand-side maturity problem sitting on top of a fragmented supply side. The billions poured into 5G, fiber, and data centers were supply-push investments, and they worked. The AI Nation agenda is also supply-push. What never got properly addressed is demand-pull: regulatory mandates that force adoption where voluntary uptake has failed, financing instruments that convert IoT capex into manageable opex, and system integrator capacity that can deliver at the scale procurement teams keep promising.

Where This Actually Gets Interesting

Here is the part I think most people in the industry are missing, and it is the reason I am not pessimistic about where this goes next.

AI cannot function in the physical world without sensor data. Every company now scrambling to bolt AI onto their operations is going to discover, within the next year or two, that they have nothing meaningful to feed their models. You cannot build a predictive maintenance AI without machine telemetry. You cannot build a smart agriculture AI without soil and climate sensors. You cannot build a smart building AI without occupancy and energy data. The instrumentation layer that IoT was supposed to build over the last decade is exactly the layer AI needs and mostly does not have.

Malaysia spent ten years underinvesting in that instrumentation layer relative to its own roadmap. That is the bad news. The good news is that the correction is coming, driven not by an IoT mandate but by AI ambition that will hit a wall without sensor data behind it. Companies that quietly kept building connected infrastructure through this slow period, the ones who treated IoT as the unglamorous plumbing rather than the headline act, are positioned to become the data supply chain for Malaysia’s AI Nation agenda.

That is not a consolation prize. That is the actual opportunity. The market did not fail. It just took longer to arrive at the reason it needed to exist.

Malaysia’s IoT-specific market figures vary considerably across research houses, and several published reports use templated methodology that should be treated with caution. The directional pattern across every credible source, however, is consistent: infrastructure has outpaced adoption, SMEs remain the binding constraint, and enterprise pilots are not converting to scale at the rate the roadmap assumed.

Why My Best Ideas Arrive Before Sunrise: How Early Morning Writing Became My Greatest Investment

“Why do I keep waking up before sunrise just to write?”

It is a question I have asked myself many times over the years. Nobody expects an article from me every morning. There is no publisher waiting impatiently for another manuscript, no customer demanding a fresh blog post before breakfast, and no deadline forcing me to switch on my laptop while the rest of the house is still asleep. Yet almost every morning, without needing an alarm to remind me, I find myself making a cup of coffee, settling into the same chair, and opening a blank document. Somewhere along the way, this routine stopped feeling like work. It became something I genuinely looked forward to. I realised that I was no longer writing because I needed to. I was writing because I could no longer imagine starting my day any other way.

Many people begin their mornings by checking emails, scrolling through social media, or immediately responding to messages that arrived overnight. I used to do that too. Before long, I noticed that I was allowing other people’s priorities to dictate how my day unfolded. Instead of beginning with clear thoughts, my mind was already crowded with requests, problems, and distractions before I had even given myself a chance to think. Writing changed that completely. It became my opportunity to spend the first hour of every day listening to my own thoughts before listening to everyone else’s.

What started as a simple habit gradually became one of the most valuable investments I have ever made in myself.

The Early Morning Gives Me Something the Rest of the Day Cannot

There is something remarkably different about the world before sunrise. The silence feels almost tangible. The constant stream of emails has not yet begun. WhatsApp groups remain quiet. News headlines have not started competing for attention, and the endless interruptions that define a normal working day simply do not exist. During those precious moments, the world seems to slow down just enough to allow the mind to breathe.

I have often wondered why my clearest ideas almost always appear during these early hours. I do not think it is because I suddenly become more intelligent at six o’clock in the morning. Instead, it is because my mind is still uncluttered. It has not yet been overwhelmed by meetings, urgent phone calls, customer requests, financial decisions, or the countless small issues that naturally arise when running a business. The ideas that emerge during this quiet period feel more genuine because they are not competing with dozens of other voices demanding attention.

Some mornings I begin with only a vague thought or a simple question. By the time I finish writing, that small idea has often grown into something much larger. What seemed uncertain at the beginning suddenly becomes surprisingly clear. I have learned not to wait for perfect inspiration before writing because, more often than not, inspiration appears only after I begin.

Writing Is How I Discover What I Really Think

People often imagine that writing is simply recording thoughts that already exist. My experience has been completely different. I have found that writing is not the final step in thinking. It is the thinking process itself.

Many times I start an article believing I already understand a subject. As I begin putting words onto the page, I quickly realise that some parts of my reasoning are incomplete, while others are built on assumptions that I have never questioned. Writing forces those weaknesses into the open. It refuses to allow vague ideas to hide behind complicated language or technical jargon. If I cannot explain something clearly enough for another person to understand, it usually means I have not fully understood it myself.

This is one of the reasons why writing has become such an important discipline in my life. Every article becomes a conversation with myself. As I write, I constantly challenge my own conclusions. Does this really make sense? Have I overlooked another perspective? Would a customer see this differently? Am I explaining the problem or merely describing the symptoms? Those quiet questions rarely appear during busy meetings because there is never enough time to pause and reflect.

The blank page has become one of my most honest critics. It never accepts weak arguments. It never rewards unclear thinking. Every paragraph demands that I organise my thoughts before moving to the next one. Over time, I have realised that writing has sharpened my ability to analyse problems far beyond the articles themselves. It has influenced how I approach business decisions, technology strategy, and even personal challenges.

Every Morning Is a Personal Strategy Session

As the founder of a technology company, I spend much of my day making decisions. Some decisions are relatively small, while others shape the direction of the company for years to come. Questions about product development, partnerships, customer needs, market positioning, hiring, pricing, and long-term strategy constantly compete for attention. It is very easy to become trapped in responding to whatever feels most urgent rather than focusing on what is genuinely important.

Morning writing has become my way of avoiding that trap.

Before opening my inbox or joining my first meeting, I spend time reflecting on questions that rarely receive enough attention during the working day. Rather than asking what needs to be completed today, I ask what deserves to exist five years from now. Instead of focusing only on immediate customer requests, I think about the larger problems that customers may not even realise they have yet.

Questions such as these often become the starting point of my writing:

  • Are we solving the right problem, or are we simply improving an outdated solution?
  • What assumptions have we accepted without questioning?
  • What have our customers been trying to tell us through their behaviour rather than their words?
  • Where is the industry heading, and are we preparing early enough?
  • Which activities create real value, and which merely keep us busy?

Many of these reflections eventually find their way into our business strategy. Some become new product features. Others shape our marketing message. Occasionally, an article written during a quiet morning evolves into an entirely new business concept. Looking back, I realise that ideas such as Operational Blindness did not suddenly appear during a brainstorming workshop. They emerged gradually through months of writing, reflecting, and connecting observations that initially seemed unrelated.

Writing Has Refined My Vision as a Leader

Leadership is often associated with speaking confidently, making difficult decisions, or inspiring people to follow a vision. While those qualities certainly matter, I have come to believe that effective leadership begins much earlier. It begins with developing the discipline to think clearly before expecting others to believe your ideas.

Writing has helped me refine not only my communication but also my vision. Every article forces me to revisit what I believe, why I believe it, and whether those beliefs still make sense in today’s environment. As industries change and technology continues to evolve, leaders cannot afford to cling to outdated assumptions simply because they once worked. Writing provides me with a structured way to revisit those assumptions regularly.

When I look back at articles I wrote several years ago, I sometimes smile because I can clearly see how much my thinking has changed. Earlier in Favoriot’s journey, I often described the company as an IoT platform provider. Today, I increasingly describe Favoriot as an Operational Visibility Platform because my understanding of the customer’s real problem has matured. We were never simply helping organisations connect devices. We were helping them see their operations more clearly so they could make better decisions.

Without years of writing, I might never have noticed that shift in perspective. The articles became milestones marking the evolution of my thinking.

My Articles Have Become My Personal Knowledge Library

One benefit of writing consistently that I never expected is the knowledge archive it has created. Whenever I prepare for a keynote speech, customer presentation, university lecture, workshop, or panel discussion, I rarely begin with a blank page. Instead, I revisit articles I have written over the years. Those articles remind me not only of what I once believed but also why I believed it at that particular point in time.

They serve as more than a collection of published ideas. They document my personal growth as an entrepreneur, engineer, educator, and technology leader. Sometimes I discover ideas that remain just as relevant today as when I first wrote them. Other times, I find conclusions that I would now challenge because experience has taught me something different.

I value both equally.

The articles that stood the test of time reinforce my convictions. The articles that no longer reflect my current thinking remind me that growth requires the humility to change our minds. Without that written record, many valuable lessons would simply fade into memory, leaving little evidence of how far my thinking has evolved.

Writing Allows Me to See Connections Others May Miss

One of the greatest gifts that writing has given me is the ability to recognise patterns across seemingly unrelated subjects. I may begin writing about manufacturing and unexpectedly discover lessons that apply equally well to healthcare, agriculture, education, or smart cities. A discussion about artificial intelligence often leads naturally into conversations about organisational culture, leadership, or decision-making. Those connections rarely appear during ordinary conversations because we are usually too focused on solving immediate problems.

Writing encourages a slower, deeper form of thinking. It creates enough distance from day-to-day activities to reveal patterns that would otherwise remain hidden. Many of the frameworks I now use, including Connect, See, Act and Operational Blindness, were not invented during formal planning sessions. They emerged because writing repeatedly forced me to look at familiar problems from different perspectives until a larger pattern finally became obvious.

The Best Meeting of Every Day

Looking at my calendar, it may seem that the most important parts of my day are the meetings with customers, partners, investors, universities, or government agencies. Those conversations certainly matter, but they are not the meeting that shapes me the most.

The most valuable meeting happens before any of those begin. It is the quiet hour I spend alone with a keyboard, an empty page, and a mind that is still free from the demands of the day.

That hour reminds me that writing is far more than producing articles for other people to read. It is where I clarify my vision, refine my strategies, challenge my assumptions, capture lessons that would otherwise disappear, and record the gradual evolution of my thinking. Every article becomes another chapter in a journey that is still unfolding.

Tomorrow morning, while much of the world is still asleep, I know exactly where I will be. Not because another blog post needs to be published, but because I have learned that the clearest ideas, the strongest strategies, and the most meaningful insights often arrive long before the first meeting of the day ever begins.

Nine Years, 141 Countries: What the Favoriot Numbers Are Really Telling Us

(Article based on July 9, 2026 Favoriot Statistics)

What does it take for a platform built in a small office in Malaysia to end up with a user in Suriname, another in the Cook Islands, and one in Greenland?

The honest answer is: nobody plans for that. You plan for the first ten users. The rest is what happens when you keep showing up, year after year, and the internet does the rest.

I went back into the Favoriot user registry recently, not the pitch deck version of our story, the raw one. 10,984 registered accounts. 141 countries. Records stretching from a single Tuesday morning in March 2017 to a signup that came in at 12:50am today. It felt like the right moment to read the numbers as a story rather than a spreadsheet.

Day one was quieter than you’d think

The very first entry in the system is dated March 31, 2017, 9:36am, a demo account, ours, set up to make sure the platform actually worked before anyone else touched it. Seventeen days later, the first real user outside our own team registered. By the end of that year, Favoriot had 136 users. Nearly all of them Malaysian. Nearly all of them people we could have named from memory.

2018 wasn’t much louder: 191 new signups, still a story confined mostly to home ground. If you’d shown me that number in 2018 and asked whether this platform would one day count users on every inhabited continent, I’m not sure I would have bet on it.

Then 2019 happened

Something shifted. New signups jumped from 191 to 2,097, an eleven-fold increase in a single year, still the single biggest year of growth Favoriot has ever recorded. But the more telling number isn’t the user count. It’s the countries. Favoriot went from being registered in 6 countries to being registered in 92 countries, 86 new countries added in twelve months. That’s not a marketing campaign. That’s a platform quietly crossing borders because IoT builders were finding it, using it, and telling the next person.

That single year did more to internationalize Favoriot than the two years before it combined.

The year the world stayed home, and found us anyway

2020 tells its own story. Total new signups dropped from the 2019 peak, as you’d expect in a year when everything slowed down. But look at the mix: 38.3% of that year’s new users came from outside Malaysia, the highest international share in Favoriot’s history, before or since. When the world went indoors, remote monitoring, sensors, and connected devices stopped being a “nice to have” conversation and became the conversation. People searching for IoT platforms that year found their way to us in Brazil, in Ecuador, in Nigeria, in places we had never run a single ad.

The long, steady climb

What followed wasn’t another explosion, it was something harder to pull off: consistency. 1,825 new users in 2021. 1,411 in 2022. 1,246 in 2023. 1,105 in 2024. 1,006 in 2025. And 706 already this year, with months still to go. Nine straight years without a single one falling to zero. That’s not a viral moment. That’s a platform that keeps earning its next user the same way it earned its first, by working.

Home, and how far from home

Malaysia remains the anchor. Roughly 8 in 10 users with a known country still call Malaysia home, and that’s exactly as it should be for a platform that grew up here. But sitting alongside that anchor is a footprint that now reaches 141 countries and every populated continent:

Asia beyond our own borders accounts for over 1,200 users, led by India (365), Indonesia (244), the Philippines (141), Thailand (72), Pakistan (51), China (40), Singapore (34), Vietnam (30), and Bangladesh (29). Europe has quietly built up 260 users across 35 countries, Portugal, Germany, France, the UK, Russia, and Poland among them. The Americas contribute close to 300 users spanning 26 countries, from the United States (59) and Canada (29) down through Brazil (47), Mexico (39), Ecuador (27), and Argentina (17). Africa’s 180 users span 29 countries, Egypt, Tunisia, Kenya, Nigeria, Morocco, Algeria, and Sudan among them. And even Oceania, the smallest slice, has 33 users across 7 countries, Australia and New Zealand among them.

That’s not a company with an “international strategy” slide. That’s a platform that IoT builders in 141 countries decided, on their own, was worth signing up for.

Why this matters more than the total

It would be easy to just say “almost 11,000 users” and move on. But the number that actually matters is the 141, because it means the problem Favoriot set out to solve in Malaysia was never a Malaysian problem. It was an IoT problem, everywhere devices needed to talk to each other and someone needed to make sense of the data. Kuala Lumpur just happened to be where we started solving it first.

Nine years ago, day one looked like a single demo account and a hope that it would work. Today it looks like 10,984 people across 141 countries who decided to build something on top of what we started. If that’s not proof that a good idea built in Malaysia can travel, I’m not sure what would be.

The next chapter is still being written, one registration at a time.

Dr. Mazlan Abbas, Founder, Favoriot


Source: Favoriot platform user registry, March 2017 to July 2026 (10,984 registered accounts, 141 countries represented).

Nine Years, 141 Countries: What the Favoriot Numbers Are Really Telling Us
Nine Years, 141 Countries: What the Favoriot Numbers Are Really Telling Us

Why I Almost Let Malaysia’s Market Size Kill Favoriot’s Biggest Dream

The Number I Kept to Myself

For years I carried a number I never said out loud in meetings. Thirty four million. That is the size of Malaysia. It is the size of the market that raised Favoriot, fed our first customers, and forgave our first mistakes.

It was also, quietly, the size of the ceiling above my own ambition.

You knew this a long time ago. Why does it hurt to admit it only now, at fifty something, with a PhD and a company that people already respect?

Because admitting it means admitting that comfort had a cost. And I do not think anyone enjoys discovering that the very thing that kept them safe is now the thing quietly holding them back.

Through My Own Eyes

I did not start Favoriot as a young man with nothing to lose. I started it at fifty six, after MIMOS, after Celcom, after a PhD I earned while still trying to prove something to myself. I had already failed in public before Favoriot even existed. Raqib, a smartwatch, did not survive. Favorsense did not survive. Dscover did not survive.

Each failure took something from me. Confidence, mostly, and a little bit of the certainty that I knew what I was doing. But each one also handed me a single sentence I could not have written any other way: customers do not want more sensors, they want to stop feeling blind about what is already happening inside their own operations.

That sentence, operational blindness, is the only thing from those years I would not trade back.

Through the Eyes of the Team Who Stayed

I think often about the people who joined Favoriot when it was still unproven. Engineers who chose a small Malaysian platform company over safer jobs at bigger names. They did not sign up to serve one country forever. They signed up because they believed the problem we were solving was bigger than the market we were solving it in.

I imagine what it must feel like from their side, building something at 2am that works beautifully, then watching it get used mostly by customers a short drive away. Talented people do not stay motivated by small ceilings. They stay motivated by the size of the problem, not the size of the postcode.

If I have learned one thing about leadership in this company, it is that I owe them a bigger horizon than the one I have been offering.

Through the Eyes of Someone We Have Not Met Yet

Somewhere right now, in Nairobi or Riyadh or Ho Chi Minh City, there is a founder running a hardware company. Good sensors, good gateways, good relationships with customers. And somewhere in the last few months, a customer asked them a question that made them go quiet for a second: where is the dashboard, where is the alert, can we host this locally, can we put our own name on it.

I know that silence. I have lived inside it.

That founder does not know Favoriot exists yet. They do not know that eight years of our own local failures produced exactly the missing piece they need. That gap, between what they already built and what they still need, is not a sales opportunity to me. It feels more like an obligation. We found the answer to a question they are quietly struggling with, and we have been too comfortable to bring it to them.

The Lessons I Am Carrying Into This Next Chapter

Build the platform before you chase the market, not the other way round. We needed years of local mistakes before the Operational Data Platform was strong enough to stand next to anyone, anywhere.

Credibility travels further than a brand name does. Nobody overseas knew Favoriot five years ago. Some of them already know me, through papers, through talks, through the slow accumulation of trust that has nothing to do with advertising.

The partners worth having were never going to come from a cold email. They come from warm introductions and founder to founder honesty, the same honesty I wish someone had extended to me back when Favoriot was unproven and unknown.

And the hardest lesson, the one I am still learning: waiting for the home market to feel finished is not patience, it is fear wearing a more respectable name.

What I Am Choosing Now

So this is the choice in front of us. Stay where it is comfortable and let a good company quietly become a small one. Or reach for the founders, the engineers, the cities and the farms outside our borders who are living the exact problem we already know how to solve.

I am choosing the second one, not because I am certain it will work, but because the alternative, staying safe inside thirty four million people, has stopped feeling like enough of a reason to keep going.

Malaysia gave Favoriot everything it needed except the size of the dream. The world is next, and I would rather fail reaching for it than succeed quietly inside a ceiling I helped build myself.

What ceiling have you built for yourself without noticing, and what would it take for you to finally name it?

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

Mastering IoT & AIoT with FAVORIOT – eBook [Download]

Mastering IoT & AIoT with FAVORIOT — Free eBook by Dr. Mazlan Abbas
Dr. Mazlan Abbas · FAVORIOT
A Field Guide for IoT & AIoT Builders

From First Sensor
to Systems That Matter.

In Mastering IoT & AIoT with Favoriot, Dr. Mazlan Abbas walks you through a ten-act journey — the same one every IoT builder lives through — from that first spark of curiosity to deployments that actually change how decisions get made.

🔥 Free download — pay what you want, starting at $0

Get Your Free Copy Now

PDF · Instant access — no experience required. Written for builders, not just engineers.

Mastering IoT & AIoT with Favoriot — book cover
The Problem

Most IoT projects never make it past the demo.

Not because the technology fails — because the thinking behind it does. This book was written to close that gap.

01

Cool demos, no outcomes

Dashboards get built, sensors get connected — and nothing downstream ever changes. Data is collected, but never acted upon.

02

The wrong starting point

Teams start with the technology instead of the decision it’s meant to inform, and the project drifts before it ever ships.

03

No practical path forward

Most resources are either too academic or too vendor-specific. What’s missing is a field-tested method to go from idea to working system.

Inside the Book

A ten-act journey, shaped by real deployments.

Told through relatable, real-world scenarios — smart vehicles, environmental monitoring, cold-chain tracking, and smart city systems — this book mirrors the actual path every IoT builder walks, following the Build-Readiness Ladder:

Cloud→ Dashboard→ Intelligence→ Decisions→ AIoT
The Starting Point

Why most IoT projects fail

Before you build anything, you’ll learn to recognize the common failure patterns that quietly derail IoT projects long before launch.

The Shift

From “cool demos” to measurable outcomes

A reframing of what success actually looks like — moving away from proof-of-concept theatre and toward systems that deliver decisions.

The Method

Idea to working system in four weeks

A practical, repeatable method focused on the part that matters most: turning raw data into decisions people can act on.

The Proof

Real scenarios across real industries

Smart vehicles, environmental monitoring, cold-chain tracking, and smart city systems show how IoT and AIoT come together in practice.

The Mindset

Why technology alone is never enough

The book’s central challenge: connecting the dots between sensors, data, people, and decisions — because dashboards don’t create value, actions do.

Who This Book Speaks To

Written for every role in the ecosystem.

Whether you’re just starting out or already delivering IoT for clients, the method holds.

St

Students

Building your first IoT project and want a real method, not just theory.

Lc

Lecturers

Shaping the next generation of IoT talent with field-tested material.

SI

System Integrators

Delivering solutions to clients and needing a sharper delivery framework.

Bz

Business Leaders

Seeking clarity on where IoT and AIoT actually create business value.

“If you’ve ever wondered what to build next — this book will show you where to begin, and how to go all the way.”

— Dr. Mazlan Abbas, Author
About the Author
Dr. Mazlan Abbas

Dr. Mazlan Abbas

Dr. Mazlan Abbas is the co-founder and CEO of FAVORIOT, a cloud-based IoT platform company with a partner network spanning Malaysia, Canada, Indonesia, the Philippines, and India. He previously served as CEO of REDtone IoT and Senior Director at MIMOS Berhad, with earlier experience at CELCOM Axiata.

He is Deputy Chairman of the Malaysia IoT Association (MIoTA) and a widely recognized voice in IoT and smart cities — a field guide written from inside the deployments, not from the sidelines.

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Questions

Before you download

Is the book really free?

Yes. It’s offered on a pay-what-you-want basis starting at $0 through Payhip — you can download it at no cost.

What format is the book in?

You’ll receive a PDF file you can read on any device, immediately after downloading.

Do I need a technical background?

No. The book is written in a clear, story-driven style for students, lecturers, system integrators, and business leaders alike — not just engineers.

What will I actually be able to do after reading it?

You’ll understand why most IoT projects stall, and you’ll have a practical method for moving from idea to a working system in four weeks — with a focus on decisions, not just dashboards.

Mazlan Abbas Newsletter – January 2025 Issue

Dr. Mazlan Abbas | January 2025 — Monthly Digest
mazlanabbas.com — Monthly Digest — Issue #01

January 2025


Startup confessions. AI without the hype. The stories that don’t make it onto the slide deck.

A note from Mazlan

January 2025 was the month I stopped pretending. Stopped pretending Medium still worked. Stopped pretending that building an IoT platform in Malaysia was going to be straightforward. The articles this month were honest in a way I hadn’t let myself be before. I hope you find something useful in them.

10+ Articles published
4 Themes explored
9,375 FAVORIOT users milestone
AI & Technology
30 Jan 2025 AI Tools

ChatGPT, CoPilot, Gemini, Grok, Perplexity, Claude & DeepSeek: Which One Should You Choose?

Seven AI tools. One practical breakdown. This guide cuts through the hype to give you an honest picture of what each tool is actually good at — from ChatGPT’s coding depth to Perplexity’s real-time research, to Claude’s contextual intelligence. Includes a note on which tools work in Malay, and which remain largely unknown locally despite being genuinely excellent.

Read the breakdown
27 Jan 2025 Research & Education

15+ Must-Have AI Tools for Master’s and PhD Students

From Consensus to SciSpace, from Elicit to Research Rabbit, this is the AI toolkit every graduate student should know about. Organised by purpose: finding papers, answering research questions, mapping literature, reading faster, writing sharper. If you’re supervising students or studying yourself, this list is worth sharing.

See the full list
· · ·
31 Jan 2025 AI Strategy

How AI Democratization by Alibaba Is Changing the World — And Why It Matters to You

DeepSeek changed the conversation. Alibaba doubled down. The question of who controls the global AI stack is no longer purely a Silicon Valley debate. This piece looks at what open, accessible AI means for businesses and developers in Southeast Asia — and why this moment may be more significant than most people realise.

Read the analysis
31 Jan 2025 AI Strategy

Who Will Lead the AI Race? Alibaba, DeepSeek, or OpenAI?

Three players. Very different philosophies. This piece asks which model of AI development will actually win: proprietary and monetised, or open and accessible. The answer has real implications for anyone building in this space, especially those of us working outside the US.

Read the piece

“By 2024, our persistence began to pay off. FAVORIOT was no longer an unknown name in the IoT landscape. Out of 9,375 users, 80% came from our own country. We did it.”

Dr. Mazlan Abbas AIoT Evangelist  |  Startup Founder  |  Thought Leader

Read the blog at mazlanabbas.com  ·  IoT insights at iotworld.co

© 2025 Dr. Mazlan Abbas  ·  Kuala Lumpur, Malaysia

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