Operational Excellence is the New Customer Intimacy

By Geoffrey Moore, Jul 24, 2018

Michael Treacy and Fred Wiersema argue that market leaders achieve competitive advantage by excelling in one of three value creation disciplines: product leadership, customer intimacy, or operational excellence. This blog discusses how digital transformation is rocking this institution and allowing operational excellence to trump customer intimacy.

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There are two serious crises looming over our workforce at present. The one getting all the attention is the threat of artificial intelligence to eliminate vast numbers of jobs. The one lurking in the corners is a pervasive lack of engagement among workers from all sectors of the economy. What people are neglecting to note is that the two are related.

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In this context, BI is a highly evolved form of decision support software whereas OI is an emerging next-generation form of digital automation. And that is a very big difference indeed.

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Is this your year to invest in big data?

By Geoffrey Moore, Apr 05, 2018

Everybody is talking about it. Mine your data for insights. Use your digital exhaust to feed machine learning programs to develop algorithms that will transform your productivity. Amazon does it. Google does it. Microsoft does it. All three offer cloud services to help you get started. Shouldn’t you be doing it too?

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Records vs. Signals: The Landscape of Digital

By Geoffrey Moore, Mar 13, 2018

Everyone gets that data is the new oil in the digital economy, but not everyone gets that there is a critical difference between data as records­­—data in databases—and data as signals—data from log files, sensors, social media posts, and the like. Let me explain.

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Data-driven decision-making: who doesn’t think it is a good idea? But it typically has a rough go in the real world of enterprise management, in part because the data itself often proves unreliable. For much of my business life IT has been tasked with building systems that could represent a single source of the truth. Unfortunately, that quest proved to be right up there with the holy grail and the fountain of youth—at best, aspirational, at worst, delusional. Today we have an opportunity to make a great leap forward, however, because for the first time in history we have broad access to high-volume data from a variety of sources that, when matched against each other, dramatically increase the probability of something like truth, and do so in a time window that is actionable. Part 3 of the blog series.

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Data-driven decision-making: who doesn’t think it is a good idea? But it typically has a rough go in the real world of enterprise management, in part because the data itself often proves unreliable. For much of my business life IT has been tasked with building systems that could represent a single source of the truth. Unfortunately, that quest proved to be right up there with the holy grail and the fountain of youth—at best, aspirational, at worst, delusional. Today we have an opportunity to make a great leap forward, however, because for the first time in history we have broad access to high-volume data from a variety of sources that, when matched against each other, dramatically increase the probability of something like truth, and do so in a time window that is actionable. Part 2 of the blog series.

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Data-driven decision-making: who doesn’t think it is a good idea? But it typically has a rough go in the real world of enterprise management, in part because the data itself often proves unreliable. For much of my business life IT has been tasked with building systems that could represent a single source of the truth. Unfortunately, that quest proved to be right up there with the holy grail and the fountain of youth—at best, aspirational, at worst, delusional. Today we have an opportunity to make a great leap forward, however, because for the first time in history we have broad access to high-volume data from a variety of sources that, when matched against each other, dramatically increase the probability of something like truth, and do so in a time window that is actionable. Not everyone, of course, has access to all the sources, so to kick things off let me present a framework of the possible, within which each organization can determine what its actual will be. Part 1 of the blog series.

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Disintegrating Castles & Category Kings

By Geoffrey Moore, Oct 03, 2017

The most prevalent impact of digitalization on the structure of markets has been to reduce the barriers to entry for a whole raft of established categories—as it has, for example in media, retail, consumer packaged goods, fast food, and transportation. A flood of small but numerous new entrants, individually nothing more than minor nuisances, become collectively a real presence. This shows up in market-share pie charts where the catch-all category Other is growing faster than the market as a whole. The result in each case is category fragmentation, and the big loser in each case is the currently reigning category king.

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Digital Systems Maturity Model

By Geoffrey Moore, Aug 17, 2017

Every so often a phrase emerges from the Word Cloud to achieve capital importance, the sort of thing that authors and pundits can dine out on years to come (well, we do have to eat too, you know). At present that phrase is digital transformation.

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