Phil Simon is a keynote speaker and recognized technology expert. He is the award-winning author of eight management books, most recently Analytics: The Agile Way. His ninth will be Slack For Dummies (April, 2020, Wiley) He consults organizations on matters related to strategy, data, analytics, and technology. His contributions have appeared in The Harvard Business Review, CNN, Wired, The New York Times, and many other sites. He teaches information systems and analytics at Arizona State University's W. P. Carey School of Business.
Data matters more than ever. Progressive organizations such as Netflix, the University of Texas System and others are using contemporary data visualization tools to find the signal in the noise that is big data. Dataphobes won't be able to hide for much longer. These facts were very much on my mind as
There's been no shortage of eye-opening mergers and acquisitions activity in the news lately. Tumblr might have been the trojan horse of the more recent and expensive M&A activity; OcculusVR, Nest and Whatsapp have made many Wall Street "experts" ask the bubble question. With all this activity, one has to wonder if
We live in an era in which it's not terribly difficult for companies to ape many of their competitors' products and services, especially digital ones. For relatively small amounts of money (compared to years past), an organization can more or less mimic another's raison d'être and even specific functionality. As for design,
We have entered the era of big data, but many questions remain unanswered. For instance, who owns all of this information, anyway? If you take a photo and post it on Facebook or Twitter, does it still belong to you? If you create a presentation with Google Docs, does Google
"Most” organizations are embracing big data. For instance, a 2013 Gartner survey found that 64 percent of enterprises were deploying or planning big data projects, up from 58% the year before. Those numbers simply don't fit with what I’m seeing, and I suspect that I'm hardly alone. (By way of
With respect to data, there seem to be a few types of companies: Those that do fairly little with the value of their data. I've consulted for quite a few. Those that maximize the value of their data, often controversially. Facebook and Google are squarely in this group. Those that maximize the
While we live in an era of big data, it's folly to claim that all data is accurate. Just because you read something on the internet doesn't make it true. In this post, I'll look at two organizations that are working to increase data accuracy and transparency. I'll spare you
For as long as I can remember, I have known about the importance of literacy. Without being able to read and write, you can only go so far in life. Imagine not being able to read warnings on prescription medicine. You are able to recognize a stop sign, but how
It's hard to imagine a hotter job now than the data scientist. Supply trails demand and, as a result, there's no shortage of myths around them. But is there any real difference between traditional statisticians and what we now call data scientists? I asked my friend Melinda Thielbar, a research statistician developer at JMP (a
How does one select the "right" or "best" way to visually represent data? Of course, the short answer is it depends. (In fact, that theoretical manner might not even exist.) Beyond that, it's an interesting question and, as I argue in The Visual Organization, a harder one to answer these days
