Forget Cool Tech. Only Strategy Can Unlock Customer & Business Value.
Separating hype from fundamentals
Thanks to everyone who responded to my recent posts.
The ideas you’ve shared will continue to have a big impact on the editorial direction going forward, so please keep them coming!
In this edition
Newsletter Exclusive: What Deep Expertise in a “Flattening” Tech looks like
Strategy, Not Technology, Is the Key to Winning with GenAI
Differentiating AI is Like Selling Bottled Water
Everyone fresh & ready to go?
What Deep Tech Expertise looks like: Larry, Sergey, & Google AdWords
Understanding “Flattening” Technologies
Roger L. Martin’s concept of “flattening” strategies lays out three ways technology and strategy can mix in one of my favorite mental models:
Martin suggests three ways “flattening” technologies work with strategy, ranging in degree from lesser to greater strategy influence, and earlier to later in the tech lifecycle:
When you’ve invented a groundbreaking technology, you can ride that wave, as TikTok has with algorithmic-based social media
When you’ve built up deep expertise in a “flattening” technology as OpenAI has recently done with ChatGPT
When you’re able to combine deep customer insights with technology in new and differentiated ways as Apple has done for years
In my latest long-form article, I go into how Apple has effectively used proven technologies with customer insights.
As a newsletter exclusive, we’ll take a look at an example of the second approach to blending tech and strategy.
What Deep Expertise in a “Flattening” Technology looks like
Larry Page and Sergei Brin took advantage of their deep technical expertise in emergent search algorithms and Web technology.
The rising availability of internet access allowed them to use the Web as their main “Where to Play” channel. By solving the problem of giving customers fundamentally better and more relevant Internet search, they created a new channel connecting companies with their customers.
AdWords “flattens” print
For the first time, Google’s AdWords product offered businesses the opportunity to micro-target people’s interests by creating the revolutionary business of “selling” words.
Google benefitted from increasing Web access to build and sustain what may be one of the greatest money-printing machines in the history of business. In so doing, they completely “flattened” the classified ad business that had been the cash cow of every print newspaper for years and removed the friction and lack of transparency connecting businesses with the right customers in a totally new way.
How well did it work for them? Google reported $220,000 in annual revenue in 1999. Four years later, in 2003, their revenue approached $1 billion.
Were Larry and Sergei following a deliberate strategy?
No. They had no idea where their AdWords product would ultimately end up, as they were in the “exploration” phase of pushing the boundaries on emerging technologies.
When you may not need an intentional strategy
In retrospect, it’s clear that Google’s AdWords represents one of those rare, transformative revolutions that took advantage of a flattening technology to build a once-in-a-lifetime business value creation opportunity.
As long as you’re either creating that revolutionary piece of tech, or taking advantage of your deep expertise to clearly provide massive value for a target set of customers, you too, can go ahead without an intentional strategy.
But because the unique set of macro and tech forces aren’t likely to be recreated anytime soon, Larry’s and Sergei’s success won’t be easily repeated.
Unless you have the same depth of expertise with the latest emerging technologies, you’re probably better off designing an intentional, client-centric strategy.
Read more in my latest piece on tech vs. strategy here on my blog
Strategy, Not Technology, Is the Key to Winning with GenAI
Milan Miric, assistant professor at USC’s Marshall School writes a great piece in HBR on strategy as a key differentiator for AI-based businesses.
He brings up three key trends based on the “arms race” of AI technology:
Firms will succeed on their business models, not proprietary technology.
Mainstream products will become more homogenous.
Companies will see high turnover rates with workers who create or manage AI products.
As Miric notes:
“As AI products are increasingly built on a standardized set of tools, this puts a premium on strategy over proprietary technology. Companies who use these tools will need to think about how they’ll create value beyond the technical features they offer and what they will do to stand out from the pack.”
Read the full piece on HBR here (free, but registration may be necessary)
AI is Like Water
In a similar vein to Miric’s perspective above, Morgan Beller over at NFX notes that we’ve come to an inflection point where tech is no longer the differentiator in AI applications.
For Beller, data and models are no longer key differentiators:
“It is basically impossible to differentiate yourself now when it comes to data and model. Sure, there will be some sources of unstructured data that may give you an edge for a little while. But ultimately, data isn’t enough on its own. As for models, most will be interchangeable.”
For Beller, AI companies can only play across 3 key differentiators:
User Experience
Distribution
Perceived brand value of your company
Beller goes on to draw some pretty insightful parallels with Perrier and bottled water marketing.
For me, it also makes the case that Strategy = Marketing.
Read the full piece on the NFX blog here for additional insights & takeaways.
Regardless of the leading tech trends, developing a client-centric strategy practice across your organization will always remain more crucial than ever.
Mike
