Why I Use the Term "Exponential Strategy"

In 2023, I chose the term "Exponential Strategy" to describe the focus of my work. It is not an established term and it still requires some explanation. I did not pick it just because it sounds distinctive; there is a real concept behind it, and I would like to explain it here.

My background is in software products. I studied computer science and then worked for the global software products business at Hewlett-Packard. HP was founded in a Palo Alto garage in 1939, one of the companies credited with laying the foundation for what later became known as Silicon Valley. By the time I left, HP had grown into a company generating nearly $120 billion in annual revenue, with its software business making up only a small slice of that, in the $3 to $4 billion range.

In effect, the software products were very much the outlier inside a hardware giant. And because HP's fortunes as a whole depended on its hardware units, even working in software meant staying aware of what was happening in those global hardware markets. This gave me a close view of the IT industry's mindset, on both the software and hardware sides.

When I left HP and started as an independent consultant in 2010, some of my work was with industrial high-tech companies embedding strong software capabilities into their products. I also attended and spoke at industrial events over the years, and saw a similar pattern across high-tech industries like automotive, industrial equipment, or mechanical engineering: I was struck by how differently these companies operated, not only compared to the software products world, but also compared to the IT hardware business I had been exposed to at HP.

While software vendors were used to shipping updates every few weeks, product cycles in these industries were typically measured in years. Development processes were managed very differently. And the approach to strategy was different as well: In the world of software or IT hardware, vendors are expected to have a clear vision and strategy and to articulate it, not only to industry analysts, but to customers as well.

By contrast, in several of these European high-tech companies, product and company strategy was something a small circle of top executives worked out behind closed doors, not something discussed openly or frequently, inside the company or outside it.

I wondered what actually caused these differences. My first thought was that it might simply come down to the particular characteristics of software: fast development cycles, fast product evolution, especially for SaaS products, and the fact that even existing customers get frequent updates for products they already operate.

But that hypothesis does not hold up well. There are hardware businesses that develop products and approach strategy in ways I recognize from the software world. Vendors of IT hardware are one example. Tesla, with its electric vehicles, is another.

So I arrived at a different explanation. The real dividing line is the speed of evolution in the underlying technology. Software can evolve quickly in part because it builds on top of an exponential technology: IT hardware itself has been on an exponential improvement curve for decades, with the compute power delivered per dollar (or Euro) roughly doubling every two years.

Here is a concrete example of what this means: In 2016, NVIDIA hand-delivered one of the first units of its DGX-1 to a small research lab called OpenAI: a $129,000 "supercomputer in a box" that NVIDIA described as delivering the throughput of 250 ordinary servers, the kind of capacity that would otherwise have filled a machine room. OpenAI used it for research that eventually contributed to what became ChatGPT. In 2026, just a decade later, a Mac Studio, priced like a well-equipped gaming PC rather than a data-center server, can run large language models with tens of billions of parameters entirely on its own, sitting on an ordinary desk. That is what a decade of doubling does: it takes what once filled a room, then a box, and makes it fit onto a desk.

Industries built on more slowly evolving technologies, like internal combustion engines or traditional industrial equipment, simply are not set up for that kind of speed. Their markets and their planning horizons move on a different timescale, even though many of their products have quietly included software for decades.

For a long time that software stayed in the background. It did not define the product, and it was not what created most of the customer value, so these products were never conceived with a "software-first" mindset: Product development started from the mechanical parts and added software afterwards, rather than designing a product's architecture and features based on what software makes possible.

However, as software becomes a bigger part of high-tech products, and drives an ever-larger share of customer value, it starts to change the industry around it. And this observation can be generalized: Once an exponential technology like software or AI becomes central to a product's value, it sets the pace for the entire industry.

And it does something else, too: it opens the playing field to a different set of competitors than the industry is used to. These new competitors include technology companies with no prior footprint in the sector, established industrial players pivoting in from adjacent markets, and new startups unconstrained by legacy products or processes.

Electric cars are a good example for that. The battery is a defining element of an electric car, and battery technology has been on a clear improvement curve for decades, both regarding the performance a dollar (or Euro) can buy, and in energy density (smaller form factor, less weight). This is a steeper curve than internal combustion engines have ever been on.

Electric cars are also easier to control with software, which makes the software-defined approach easier to implement. And software itself improves even faster than batteries. With electric cars being built on top of two exponential technologies, they are now evolving at a pace that established car manufacturers are finding hard to match. That dynamic is driven mostly by entrants from outside the traditional automotive industry: Tesla first, and now a wide range of new Chinese car manufacturers.

The good news is that approaches for Exponential Strategy do exist, developed mostly out of Silicon Valley's software and IT industries over the past decades.

Recognizing this gap, between what leaders in exponential markets actually need and what most leadership and strategy training still teaches, is exactly why I built The Exponential Strategy Playbook: an executive program designed specifically for the reality of exponential technology markets.

I would be curious what it looks like for you: Has your industry always been driven by exponential change, or is it something that's arriving now?