Category Archives: Innovation

Necessary, but not sufficient

When asked “who created Apple?”, it’s tempting to say Steve Jobs did it.  The truth is that, although he may have been necessarily, he was not sufficient.

Similarly Bill Gates, who (as Malcolm Gladwell tells us in Outliers) experienced a unique confluence of circumstances that led to the founding of Microsoft.  Gates deserves tremendous credit, but alone he was not sufficient.

The brain likes to simplify, and history sometimes prefers to leave out the details for the benefit of a better story. Continue reading

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Guest post: Mindset GPS: Navigating New Realities

Great leaders make the right call at the right time to deliver outstanding results. They avoid relying on outdated mindsets and practices in a complex and changing environment. Leaders today must be willing to help others to think strategically, question past practices, and explore new alternatives.

Relying on old habits, acquiescing to group think, and depending on obsolete assumptions limits individual careers and reduces organizational viability.  A painful example: in the 1990s, mortgage bankers granted 95% mortgages based on the wrong assumption that home prices never fall more than 5%. They paid a high price for their narrow thinking. Additionally, they ignored expert warnings about a real estate bubble. One bank executive stated that he knew it would blow up, but as long as the music was playing, he had to keep dancing. Instead of searching for a new melody, he went along for the ride.

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What is machine learning, and why you should care (in 500 words)

It’s critical that you understand machine learning, even if just a little bit. Why? Machine learning is at the heart of the most common artificial intelligence systems today. It’s an important new technology that’s moved beyond hype to the brink of an exponential explosion, at the core of a 320% growth in AI-based startups last year. And, in combination with decision intelligence, Machine Learning has the potential to solve some of the most important problems faced by humanity today.

So here’s what you need to know.

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What causes the technology hype cycle (and what to do about it)?

The Internet of Things…Machine Learning…Self-Driving Cars…Artificial Intelligence…Big Data…Smart Cities…Decision Intelligence…my friends talk to me about their excitement about a whole lot of trends.  But which ones are real, and which will fizzle?

Before founding Quantellia, I spent six years as a technology analyst, where I was privileged to have an inside look at how tech trends boom and bust.  I learned a few important lessons.

It’s funny: the Hype Cycle is well-understood: those curves from Gartner, Geoffrey Moore, and others that show how technology follows a hype/disillusionment/acceptance curve. Continue reading

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Guest post: Can technology help fix us?

No matter whether you pull for Donald or Bernie or are an “occupier” or a “tea partier” or anywhere in between, you have to admit that we have a problem. The system is broken, due to gerrymandering, big money, or any other possible reason that you can name. We have issues, such as “income inequality,” or “climate change” that are of major concern to one of our major parties while the other is somewhat unconcerned to the extent that some within the party don’t think that the problems exists; we have one party claiming credit for what it sees as tremendous success of its health care bill while the other party constantly tries to repeal or dismantle it.

Gone are the days of the bipartisanship that brought us the Civil Rights and Voting Rights bills (even in the face of southern segregationists) and Environmental legislation. We have a booming economy in terms of Wall Street and corporate profits and a stagnant one in terms of worker salaries and buying power. Continue reading

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The antifragility of the open source bazaar

When I was helping to develop the MVS/XA mainframe operating system at IBM in the 1980s, we had a disciplined process for software development. We knew that a bug fixed in requirements was a hundred times cheaper than if we repaired it after it was out in the field. So we were careful and diligent, writing thorough specifications documents, then carefully crafted design docs, and only then could code begin.

All good software engineers know this is the way to go.   Or at least that’s what we’d always thought.

But it turns out we were wrong.  And not in a small way.  Continue reading

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The Decision Intelligence Ecosystem

It’s been an incredible last few weeks in the Decision Intelligence world, as we’re seeing an ecosystem emerging with new vendors, articles in IEEE, the New York Times, at HBR, and much more. I’ve taken a first shot, in the graphic below, of mapping the ecosystem. It’s not at all complete, so please send me entries for new nodes. I’ll also be tweaking the graphic going forward to make it easier to navigate. Enjoy! Continue reading

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Baby steps

It’s not easy selling into an emerging market, no matter how important it is.  We won two projects in the last week or so.  In both cases, the customer hadn’t heard  of decision intelligence before talking with us.  In one, they were looking for data analysis to guide a marketing investment; in the other, the question was to determine the effectiveness of various college course offerings. Continue reading

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