Cleve Gibbon

One of the fascinating aspects of language is the myriad ways to convey the same message. Different audiences require tailored messaging that resonates specifically with them. Today, the tech industry emphasizes that execution with AI is the future. However, let’s step back and consider a simple formula:

• Value = Idea x Execution

Where:

• Value is your desired output.
• Idea is what will lead to that desired output.
• Execution is how you bring your idea to life.

From this formula, here are a few key takeaways:

1. A good idea multiplied by good execution drives significant value.
2. Poor execution combined with a bad idea generates low value.
3. Bad execution can hinder good ideas, leading to deferred value.
4. A bad idea can stress good execution, delivering marginal value through brute force.

It’s straightforward to identify when you’re at either end of the spectrum—either both good or both bad. The challenge is determining where you fall between these extremes, especially when neither the idea nor the execution is outright poor but rather not good enough.

What If We Can Improve Execution with AI?

Consider Instagram: thirteen people executed a brilliant idea exceptionally well, creating a $1 billion company. Now, there’s speculation about when the first 1-person billion-dollar company will emerge. With executable technology or AI, this could become a reality. AI might even lead to the creation of zero-person companies, where AI autonomously incorporates itself. Therefore, the critical task then becomes finding a good idea and leveraging AI for execution to deliver value.

This leap doesn’t seem far-fetched. So, where are you investing your time? Are you focusing on generating good ideas or getting better at executing with AI?

As the calendar flipped to 2024, I found myself wanting more. After a transformative decade at WPP. A period marked by growth, learning, and remarkable achievements. I decided it was time for a change. This decision wasn’t made lightly. It was the culmination of introspection and a desire for new challenges. Thus, I bid farewell to WPP and took a well-deserved sabbatical to recharge and refocus. I’m now at Omnicom with a focus on technology, workloads and AI.

WPP

My journey with WPP started with a bang in Apr 2014. Our company, Cognifide, was acquired by WPP under the Wunderman OpCo. Wunderman was undergoing massive digital transformation. Cognifide’s role within WPP was to build owned experience platforms for its clients. Many clients. Ford, Investec, ColPal, EY, HSBC, Dell, Herman Miller, Coutts, Barclays, Unilever, Shell, etc. We delivered hundreds of digital platforms during my time at WPP. Then Wunderman became Wunderman Thompson after it merged with JWT, and now it’s VML. I left WPP after a couple of years of leading technology back into The Coca-Cola Company.

So what changed?

Me. After graduating from Oxford University in 2023 with a Master’s in AI for Business, the world looked very different. Something unlocked in me. Like many others, I believe that AI is mission-critical to businesses and people. But it was more than using AI, which is just technology. I’m curious about the operationalization of AI across the organization and equally its widespread adoption. What are the better business outcomes that an intelligent enterprise can deliver at scale, with speed, and sustainably? There’s so much going on. Understanding workloads, standardization of approaches, automating where appropriate, leveraging AI, and tying everything back to results has my full attention.

Omnicom

So, I joined Omnicom in 2023. They have a clear mission, with key partners like Microsoft, and have invested in an AI-driven future. Now I’m part of a technology team helping to accelerate Omnicom towards that future reality.

What’s next?

Focus and execute. Listen and learn. Collaborate and communicate. And above all else, keep moving forward into 2024.

I’m a big fan of Peter Diamandis’s 6D framework used to describe the exponential growth and impact of emerging technologies.  It depicts how technology moves from ’emerging’ to ’emerged’.

The rate of technological change starts with digital and moves deceptively slowly under the radar until its true disruptive impact becomes clear to the few. Once established, the technology dramatically accelerates along an exponential growth path getting cheaper (demonetized), smaller (dematerialized), and accessible (democratized) to the masses. Think iPhones, 5G, the Internet, and now AI.

Singularity University

Back in May 2017, I spent a week at NASA with 30 other business and technology leaders, many of which oversee $1 billion revenue companies.  Peter Diamandis ran a series of future-forward technology lectures as part of his Singularity University program to share the collective current state, provoke discussions with divergent audiences, to change our collective thinking.  He succeeded. 

Now AI was high up on the agenda.  We had luminaries such as Ray Kurzweil sharing his predictions on the future of human-machine integration. 

6D Framework for AI

Now let’s position AI within that 6D framework.  It’s literally been 6 years since I attended Singularity University and our 2017 AI predictions are bang on target.

AI used to be costly, but now it’s more affordable. Smaller versions of huge language models focus on specific problems, and we’re seeing these models targeting web and mobile devices. And of course, everyone has access to AI now.

Every day, we humans are adapting to AI. Governments and corporates alike are navigating the challenges of ethical, responsible, and unbiased solutions as part of creating an acceptable AI code of conduct. Nobody wants an existential crisis.

And finally, talent. Augmented humans, or people comfortable with AI, have an advantage. The workforce is changing fast, especially for non-augmented individuals. Companies are proactively replacing future roles with AI solutions, both led and managed by experienced, AI-adept individuals. Nobody knows what the future talent mix will be, but it will be different.

Wrapping up, that 6D framework shows us that AI is no longer a technology of the future; it’s here now. So, what will you do with it?

I recently listened to a McKinsey podcast that features Miklos talking about the “economy ecosystem“.  It put into words something that has been bugging me for a while now about articulating the true role technology plays within organizations of the future.  Let me unpack that with a little help from Miklós.

I’ve been in the agency technology business for over two decades now.  There has been a lot of change.  Today, as a chief technology officer I spend a lot of time in group therapy with Fortune 500 senior executives in the customer experience space.  The problem is simple to state, harder to solve.  

The Problem

Traditionally businesses tend to compete within sectors.  Health companies care for patients.  Finance companies manage wealth.  Entertainment businesses entertain. You get the picture.  And with over 80 different sectors, the swimlanes were clear and comforting for organizations to win market share and grow revenue.  

However, technology is breaking down these industry vaults making it easier for companies to move between swimlanes to offer consumers multi-sector services.  Amazon started with books and now has many service lines from finance, to films, to food, to computing just to name a few.  I love the way Miklós likened the multi-sector service approach to the rise of supermarkets; now commonplace and widely adopted. Time poor consumers love one stop marketplaces and prefer that over moving between multiple isolated shopping experiences. Can you remember the last time you shopped in several locations to get meats, medicines, fruit and veg, deli goods, alcohol, stationnery, and hardware in a single day? I used to do that growing up, however now I’m part of a loyalty program for a supermarket chain that owns a part me. I chose to major in the supermarket and minor is specialised brands for luxury items.

The Challenge 

The same thing is happening digitally for the ownership of the consumer on a larger scale.  Technology is the dam buster, breaking down the sector silos that both producers and consumers are no longer imprisoned by.  So the race is on to own (a piece of) the consumer and there is everything to play for.  

Organizations can go deep (within a sector) and broad (across sectors).  How deep or broad is an imprortant business decision?  We know how hard it is to create engaging customer journeys within a sector you already excel at with business experience and expertise. However, tomorrow’s winner are getting out of their sector comfort zones to compete broadly across entire, multi-industry customer journey economy ecosystem.

The Approach

This is not easy.  So if vertical customer journey design processes are complicated, horizontal multi-dimensional interconnected ones are highly complex.  Literally, orders of magnitude are harder.  Although not an intractable problem, good strategy is key here.  

So think big, start small to build your economy ecosystem.   Take on board Amazon’s leadership principles, be humble, and be intentional about your capabilities to win.  We have to move past passive know your customer (KYC) discussions to actively owning them by putting theory into practice. Do this with a healthy dose of valuing progress over perfection.  

Have you ever heard someone say, “it’s not just about the tech“?  Yes, you have.  In fact, it’s more like, how many times?  Now think back to the context in which technology was presented in that way.  This isn’t a magic trick, but I already know. Technology was put down to better position something else. To sell something.  Raise something up an agenda. To make a point.  To change a mind. It doesn’t have to be this way.

Technology “versus” mindset is a common tactic to advocate for something that isn’t technology.

I’m a technologist.  And technologists know that technology enables something.  It’s seldom a versus situation.  More a “plus” mindset.   So technologists tend to roll their eyes when we hear technology pitted against something.  Frankly, it’s a dated, naive (verging on silly), and uncompetitive way to position technology in the world today. However, things are changing.

What’s changed?

Technology enables so many things that we rely upon everyday to get stuff done.  Ordering groceries.  Buying clothes.  Texting.  Playing music.  Watching movies.  Gaming.  Video chatting.  Table stakes!  And when COVID hit in 2020 our reliance on technology reached all time highs. Onwards and upwards. 

The value of technology is no longer in question.  Technology kept the human race connected through a pandemic.  

What needs to change?  

Whether you’re a technologist or not, think of technology with a plus not a versus mindset.  Technology enables something. It strives to adds more, not takeaway. Yes, we have to adapt. And no, it’s not gong to be easy. But in which mindset do sit?

Versus: It’s not just about the technology, we have to consider the people and processes to deliver better customer experience.

Or

Plus: Technology makes our people and processes smarter to deliver better customer experiences. 

I urge you to favour plus over versus.

Summary

When you hear the versus narrative for technology, please call it out.  I do.  Change the story.  Be inclusive. Make technology a tool for good whether you’re a technologist or not. Why? Because collectively we have a bigger challenge now demystifying technology. The world sees its true value.   Closing that gap requires technologists and non-technologists alike to adopt a plus mindset to help technology make a better world for us all. 

What is the best way to forecast technology cost declines? And why is that important?

Well if you can accurately predict cost, you can better plot growth. Moreover, if that cost is technology – a massive engine for exponential growth – we can make smaller and smarter investments, earlier and more often, to maximise future returns.

Forecasting technology cost declines is important. Wright’s Law and Moore’s Law have guided our technology industry here. So meet the minds behind them. Who are they and what did they say?

Theodore Wright

In 1936, whilst studying airplane manufacturing, Theodore Wright (on the left) discovered that:

For every doubling of airplane production the labor requirement was reduced by 10-15%

He stood on that observation for Wright’s Law, that states:

For every cumulative doubling of units produced, costs will fall by a constant percentage

Now units can be anything. Cars, pizzas, batteries, phones, transistors. Anything! Now hold that thought and let’s step over to Moore’s Law.

Gordon Moore

In 1965, whilst working at Fairchild Semiconductor, Gordon Moore came straight out and said:

Every two years, doubling transistor density would consequently result in halving of computation costs

And so the great race to cram as many components onto circuits began. And it has served the technology industry well, particularly Intel, for many years. Not any more?

What changed?

Transistor production declined. Costs plateaued. Consumer demand is changing. So research units started to question Moore’s Law. One of those units was ARK, a leading hedge fund. ARK found that a priced based on Wright’s Law is 40% more accurate than one based on Moore’s Law. Take a look at their data:

So, what are you looking at? We’re going back and re-applying both laws to semiconductor production. We see that Wright’s Law (above the line) is more accurate most of the time than Moore’s Law (below the line). But why?

Comparing the Laws

Moore’s Law is cost as a function time. Wright’s Law is cost as a function of units produced. Put another way, Wright’s Law forecasts technology costs declines based on tangible outputs. Not time. So, the more things you produce, the more you understand, the lower yours costs. And it’s proving to be a better way to forecast technology cost declines.

Closing out

We are all looking for exponential growth. 10% growth is good, but 10x growth great. Knowing where and how to apply technology to execute disruptive ideas is critical. However, demonetisation (make cheaper), dematerialisation (make smaller), and democratisation (make accessible) of technology requires that we get a firm handle on our costs, and where the future declines lay. In doing so, you are not predicting the future, you are helping to shape it.