Ariel Silverstone

[An] effective way to detect what [customer data] has leaked, and through which possible partner, is to pre-poison the data, sowing into it information that can provide a reference point in the case of a leak.

Laura LaBerge

Many organizations have spent decades understanding how to make trade-offs in their businesses, where the profit pools are, and the structure of their value chains. Digital changes all that. First, on an overarching level, digital currently destroys more economic value for incumbents than it creates. There are two main drivers. The first one is that digital creates transparency that allows a much higher percentage of … [ Read more ]

Bill Schaninger

We make decisions every day about who we hire, how we deploy them, what teams we put them in, what we have them working on. Then we sit in judgment of their performances. Every one of those decisions can be made better with data. Not all those decisions are equally important, so you don’t have to bring it to bear in all of them, but … [ Read more ]

Ajay Agrawal

When looking at artificial intelligence from the perspective of economics, we ask the same, single question that we ask with any technology: What does it reduce the cost of? Economists are good at taking the fun and wizardry out of technology and leaving us with this dry but illuminating question. The answer reveals why AI is so important relative to many other exciting technologies. AI … [ Read more ]

Howard Yu

In the midst of predictive analytics and machine learning, with big data sweeping across sectors and industries, the importance of small data cannot be overstated. Big data and machine learning concern themselves with correlation, not causation. Computers excel at precision, rigor, and consistency, but they are not designed to integrate social interactions across domains, or traverse data online and offline, or come up with a … [ Read more ]

Michael Chui, James Manyika, and Mehdi Miremadi

It can be difficult to discern how a mathematical model trained by deep learning arrives at a particular prediction, recommendation, or decision. A black box, even one that does what it’s supposed to, may have limited utility, especially where the predictions or decisions impact society and hold ramifications that can affect individual well-being. In such cases, users sometimes need to know the “whys” behind the … [ Read more ]

Carl F. Mela, Christine Moorman

Companies should do two things to harness the power of analytics in their marketing functions. First, rather than create data and then decide what to do with it, firms should decide what to do first, and then which data they need to do it. This means better integrating marketing and IT, and developing systems around the information needs of the senior management team instead of … [ Read more ]

Shelly Palmer

We’ve found that few enterprises fully recognize the value of data, data governance, and data hygiene. Data is cash, and it should be treated like cash. You need a data P&L.

There are really three kinds of data. First-party data is your own company’s asset, which you are directly responsible for collecting. It may be from cookies, email subscriptions, orders, or sales receipts. Or it may … [ Read more ]

Helen Mayhew, Tamim Saleh, Simon Williams

Just because information may be incomplete, based on conjecture, or notably biased does not mean that it should be treated as “garbage.” Soft information does have value. Sometimes, it may even be essential, especially when people try to “connect the dots” between more exact inputs or make a best guess for the emerging future.

To optimize available information in an intelligent, nuanced way, companies should strive … [ Read more ]

Kentaro Toyama

I think there’s an illusion that big data simplifies decision making. The danger is that as we have more and more big data, we’ll increasingly be able to justify anything as a truth simply because there appear to be a lot of data points behind it. […] Because we now have more numbers than ever, we need even keener subjective judgment about what those numbers … [ Read more ]

Kentaro Toyama

The idea that technology amplifies whatever forces already exist is as true for business as it is for anything else.

Kentaro Toyama

Powerful technologies will work in exactly the direction we point them in. Almost paradoxically, as more technology becomes available, human judgment and wisdom matter more.

Hermann Simon

As [Peter Drucker] saw it, the winners of the IT revolution are not the hardware or software developers of today, but rather the companies which have access to knowledge and content.

Paul Saffo

It takes 30 years for a new idea to seep into the culture. Technology does not drive change. It is our collective response to the options and opportunities presented by technology that drives change.

Tucker Bailey, James M. Kaplan, Chris Rezek

When companies think about cybersecurity […] most ask, “How can we protect ourselves and comply with standards or regulations?” instead of “How do we make confident, intelligent investments given the risks we face?” Many also treat cybersecurity primarily as a technology function rather than integrating it into business operations. As a result, they get the wrong answer about how to construct a cybersecurity program.

Hana Ben-Shabat

Digital technologies have caught fire because they address three core human needs: the need for connection with other humans, the need for self-expression, and the need for exploration. Wrapped up in the seductive ribbon of convenience, there has never been a better formula for consumer engagement. Understanding the human side of the digital revolution will be a key success factor for businesses trying to compete … [ Read more ]

Peter Bell

Analytics is to management as a light bulb is to darkness: it is illuminating and helpful in revealing both future opportunities and pitfalls. Descriptive analytics seeks to understand past data and is widely used. Predictive analytics seeks to understand the future. This is a challenge for many firms, since it brings in risk (the future is uncertain) and the need to manage risk. Prescriptive … [ Read more ]

Michael Dertouzos

The late Michael Dertouzos observed in his last book, The Unfinished Revolution, that all too often, humans are at the service of computers, rather than the much more desirable opposite. To take full advantage of new technologies, to really enable the widest range of possibilities opened up by innovation, we must make sure that technologies aren’t designed in isolation from their eventual users; technology ought … [ Read more ]

Joe Gorup

Do not buy, install or set expectations based on the features of a given technology. One should focus on the business processes first, then apply the software to specifically meet or enhance these processes. Technology can almost do anything. The question is not what it could do; the question is what it should do.

Peter Drucker

[Economics and technology] are the wrong places to begin. The fundamental changes are social, and they are the greatest changes imaginable.