Posts Tagged ‘social media’
In my post from this past summer Through a PRISM, Darkly, I blogged about how ours is a world still struggling to come to terms with having more aspects of our everyday lives, both personal and professional, captured as data.
We rarely consider the data privacy implications of our brave new data world, which prompted me to ask why we are so concerned about the government accessing data that in many instances we voluntarily gave to companies like Google, which provides free services (not counting the money we do pay for our mobile phone plans and to our Internet service providers) that are not really free because we pay for them with our privacy.
“Google has sucked millions of people into its web by delivering a feature-packed email service that comes only at the price of our privacy,” David Braue recently blogged.
“We must face the unavoidable reality that we have sold our souls for free email. Think about it: We bleat and scream to the hills about the government’s invasions of our privacy, then turn around and mail our personal information using a service specifically designed to harvest that information.”
“Google has positioned Gmail as a gateway drug to a world where everything runs according to Google. Google wants to manage our photos, our social media, our email, our word-processing documents, our everyday tasks, even our general documents.”
“This is the brave new world of the Internet,” Braue argued, “where privacy is an historical footnote and we are tricked or simply bribed to give it up. By and large, we are quite happy to do so. We may not love the need to deliver our personal lives on a platter in exchange for a spam-free, easily-accessible and substantially awesome email experience — but we do so with a smile, over and over again.”
To Braue’s point, no one is forcing us to use Gmail. Many, myself included, use it for the convenience of managing multiple email accounts across multiple mobile devices.
And Google is certainly not our only enemy combatant in what I have previously dubbed the Data Cold War. However, when we trade convenience for privacy, we have to admit the inconvenient truth that Pogo taught us long ago: “We have met the enemy and he is us.”
We don’t give away those slips of paper in our wallets without realizing that’s a form of currency. And we don’t give away the digital currency that is our credit card numbers (e.g., via Twitter, you could use a single tweet to post seven of your credit card numbers, with one space after each 16-digit number, and hashtag it with #MyCreditCardNumbers — but I will assume you would not).
However, we do give away countless bytes of our personal data in exchange for Internet/mobile-based services that we consider to be free because, unlike the companies providing those services, we do not count personally identifiable information as a form of currency.
The reality is our privacy is currency — and we are giving it away.
Richard Ordowich, commenting on my Hail to the Chiefs post, remarked how “most organizations need to improve their data literacy. Many problems stem from inadequate data definitions, multiple interpretations and understanding about the meanings of data. Skills in semantics, taxonomy and ontology as well as information management are required. These are skills that typically reside in librarians but not CDOs. Perhaps hiring librarians would be better than hiring a CDO.”
I responded that maybe not even librarians can save us by citing The Library of Babel, a short story by Argentine author and librarian Jorge Luis Borges, which is about, as James Gleick explained in his book The Information: A History, A Theory, A Flood, “the mythical library that contains all books, in all languages, books of apology and prophecy, the gospel and the commentary upon that gospel and the commentary upon the commentary upon the gospel, the minutely detailed history of the future, the interpolations of all books in all other books, the faithful catalogue of the library and the innumerable false catalogues. This library (which others call the universe) enshrines all the information. Yet no knowledge can be discovered there, precisely because all knowledge is there, shelved side by side with all falsehood. In the mirrored galleries, on the countless shelves, can be found everything and nothing. There can be no more perfect case of information glut.”
More than a century before the rise of cloud computing and the mobile devices connected to it, the imagination of Charles Babbage foresaw another library of Babel, one where “the air itself is one vast library, on whose pages are forever written all that man has ever said or woman whispered.” In a world where word of mouth has become word of data, sometimes causing panic about who may be listening, Babbage’s vision of a permanent record of every human utterance seems eerily prescient.
Of the cloud, Gleick wrote about how “all that information—all that information capacity—looms over us, not quite visible, not quite tangible, but awfully real; amorphous, spectral; hovering nearby, yet not situated in any one place. Heaven must once have felt this way to the faithful. People talk about shifting their lives to the cloud—their informational lives, at least. You may store photographs in the cloud; Google is putting all the world’s books into the cloud; e-mail passes to and from the cloud and never really leaves the cloud. All traditional ideas of privacy, based on doors and locks, physical remoteness and invisibility, are upended in the cloud.”
“The information produced and consumed by humankind used to vanish,” Gleick concluded, “that was the norm, the default. The sights, the sounds, the songs, the spoken word just melted away. Marks on stone, parchment, and paper were the special case. It did not occur to Sophocles’ audiences that it would be sad for his plays to be lost; they enjoyed the show. Now expectations have inverted. Everything may be recorded and preserved, at least potentially: every musical performance; every crime in a shop, elevator, or city street; every volcano or tsunami on the remotest shore; every card played or piece moved in an online game; every rugby scrum and cricket match. Having a camera at hand is normal, not exceptional; something like 500 billion images were captured in 2010. YouTube was streaming more than a billion videos a day. Most of this is haphazard and unorganized.”
The Library of Babel is no longer fiction. Big Data is the Library of Babel.
In the era of big data, we’re confronted by the question Brenda Somich recently blogged: How do you handle information overload? “Does today’s super-connected and informative online environment allow us to work to our potential?” Somich asked. “Is all this information really making us smarter?”
I have blogged about how much of the unstructured data that everyone is going gaga over is gigabytes of gossip and yottabytes of yada yada digitized. While most of our verbalized thoughts were always born this way, with word of mouth becoming word of data, big data is making little data monsters of us all.
In a way, we have become addicted to data. In her post, Somich discussed how we have become so obsessed with checking emails, news feeds, blog posts, and social media status updates, that even after hours of using information have gone by, we are still searching for our next data fix. Our smartphones have become our constant companions, ever-present enablers reminiscent of the nickname that the once most popular smartphone went by — CrackBerry.
In his book Hamlet’s BlackBerry: Building a Good Life in the Digital Age, William Powers explained that “in the sixteenth century, when information was physically piling up everywhere, it was the ability to erase some of it that afforded a sense of empowerment and control.”
“In contrast, the digital information that weighs on us today exists in a nonphysical medium, and this is part of the problem. We know it’s out there, and we have words to represent and quantify it. An exabyte, for instance, is a million million megabytes. But that doesn’t mean much to me. Where is all that data, exactly? It’s everywhere and nowhere at the same time. We’re physical creatures who perceive and know the world through our bodies, yet we now spend much of our time in a universe of disembodied information. It doesn’t live here with us, we just peer at it through a two-dimensional screen. At a very deep level of the consciousness, this is arduous and draining.”
Without question, big data is forcing us to revisit information overload. But sometimes it’s useful to remember that the phrase is over forty years old now — and it originally expressed the concern, not about the increasing amount of information, but about our increasing access to information.
Just because we now have unprecedented access to an unimpeded expansion of information doesn’t mean we need to access it right now. Just because disembodied information is everywhere doesn’t mean that our bodies need to consume it.
One thing we must do, therefore, to avoid such snafus as the haunting hyper-connected hyperbole of the infinite inbox, is acknowledge the infinitesimal value of most of the information we consume.
When you are feeling overwhelmed by the amount of information you have access to, stop for a moment and consider how underwhelming most of it is. I think part of the reason we keep looking for more information is because we’re so unsatisfied with the information we’ve found.
Although information overload is a real concern and definitely does frequently occur, far more often I think it is information underwhelm that is dragging us down.
How much of the content of those emails, news feeds, blog posts, and social media status updates you read yesterday, or even earlier today, do you actually remember? If you’re like me, probably not much, which is why we need to mind the gap between our acquisition and application of information.
As Anton Chekhov once said, “knowledge is of no value unless you put it into practice.” By extension, consuming information is of no value unless you put it to use. And an overwhelming amount of the information now available to us is so underwhelming that it’s useless to consume.
“If you analyzed the flow of digital data in 1980,” Stephen Baker wrote in his 2011 book Final Jeopardy: Man vs. Machine and the Quest to Know Everything, “only a smidgen of the world’s information had found its way into computers.”
“Back then, the big mainframes and the new microcomputers housed business records, tax returns, real estate transactions, and mountains of scientific data. But much of the world’s information existed in the form of words—conversations at the coffee shop, phone calls, books, messages scrawled on Post-its, term papers, the play-by-play of the Super Bowl, the seven o’clock news. Far more than numbers, words spelled out when humans were thinking, what they knew, what they wanted, whom they loved. And most of those words, and the data they contained, vanished quickly. They faded in fallible human memories, they piled up in dumpsters and moldered in damp basements. Most of these words never reached computers, much less networks.”
However, during the era of big data, things have significantly changed. “In the last decade,” Baker continued, “as billions of people have migrated their work, mail, reading, phone calls, and webs of friendships to digital networks, a giant new species of data has arisen: unstructured data.”
“It’s the growing heap of sounds and images that we produce, along with trillions of words. Chaotic by nature, it doesn’t fit neatly into an Excel spreadsheet. Yet it describes the minute-by-minute goings-on of much of the planet. This gold mine is doubling in size every year. Of all the data stored in the world’s computers and coursing through its networks, the vast majority is unstructured.”
One of Melinda Thielbar’s three questions of data science is: “Are these results actionable?” As Baker explained, unstructured data describes the minute-by-minute goings-on of much of the planet, so the results of analyzing unstructured data must be actionable, right?
Although sentiment analysis of unstructured social media data is often lauded as a great example, late last year Augie Ray wrote a great blog post asking How Powerful Is Social Media Sentiment Really?
My contrarian’s view of unstructured data is that it is, in large part, gigabytes of gossip and yottabytes of yada yada digitized, rumors and hearsay amplified by the illusion-of-truth effect and succumbing to the perception-is-reality effect until the noise amplifies so much that its static solidifies into a signal.
As Roberta Wohlstetter originally defined the terms, signal is the indication of an underlying truth behind a statistical or predictive problem, and noise is the sound produced by competing signals.
The competing signals from unstructured data are competing with other signals in a digital world of seemingly infinite channels broadcasting a cacophony that makes one nostalgic for a luddite’s dream of a world before word of mouth became word of data, and before private thoughts contained within the neural networks of our minds became public thoughts shared within social networks, such as Twitter, Facebook, and LinkedIn.
“While it may seem heretical to say,” Ray explained, “I believe there is ample evidence social media sentiment does not matter equally in every industry to every company in every situation. Social media sentiment has been elevated to God-like status when really it is more of a minor deity. In most situations, what others are saying does not trump our own personal experiences. In addition, while public sentiment may be a factor in our purchase decisions, we weigh it against many other important factors such as price, convenience, perception of quality, etc.”
Social media is not the only source of unstructured data, nor am I suggesting there’s no business value in this category of big data. However, sometimes a contrarian’s view is necessary to temper unchecked enthusiasm, and a lot of big data is not only unstructured, but enthusiasm for it is often unchecked.
The nineteen century belonged to the engineers. Western society had been invigorated and changed beyond recognition by the industrial revolution through its early years and by its close the railroads were synonymous with the building of wealth.
The nineteen century was the era that saw the building of modern business with the foundation being established for many of the great companies that we know today. The management thinkers who defined the discipline cluster around the first part of the twentieth century and it should be no surprise that they were heavily influenced by the engineers.
Business was built around the idea of engineered processes with defined inputs and outputs. I’ve written before about the shift from process-driven to information-driven business. In this post, though, I am really focusing on another consequence of the engineering approach to the running of businesses, the expectation of achieving planned outcomes.
There is a lot to be said for achieving a plan. Investors dream of certainty in their returns. Complex businesses like to be able to align production schedules. Staff like knowing that they have a long-term job.
When you’re building a bridge or a railroad, there is certainty in the desired outcome. Success is measured in terms of a completed project against time and budget.
When your business has a goal of providing products or services into a market, the definition of success is much harder to nail down. You want your product or service to be profitable, but you are usually flexible on its exact definition. However, internal structures tend not to have this flexibility built in. Large businesses operate by ensuring each part of the organisation delivers their component of a new project as specified by the overall design.
This sounds fine until you look at these components in more detail. Many are fiendishly complex. In particular the IT can often involve many existing and new systems which have to be interfaced in ways that were never intended when they were originally created. Staff trained to achieve a single outcome in the market keep on testing customers until they gain (or even bludgeon) acceptance for the product or service design.
Because of the scale of these projects, failure is not an option. The business engineering philosophy that I’ve described will push the launch through regardless of the obstacles. However, there is a growing trend in business to try and use “big data” to run experiments and confirm that the design of a new product or service is correct before this effort is undertaken.
There is also another trend in business. Agile. Agile methods are characterised by an evolutionary approach to achieving system outcomes.
Individually these trends make sense. Taken together they may actually be starting to indicate a deeper change. In a future world we may treat business as an experiment in its own right. We know what the outcome is that we expect, but we will push our teams to embrace issues and look for systemic obstacles to guide us in new, and potentially more profitable, directions.
When customers don’t react positively to our initial designs, rather than adjust the design to their aesthetic, business should ask whether the product is appropriate at all and consider making a radical shift even at the last minute.
When IT finds that a system change is harder than they expected, they can legitimately ask whether there is a compromise that will deliver a different answer that might be equally acceptable, or sometimes even more useful.
One of the major differences between scientists and engineers is that the former look for the unexpected in their experiments and try to focus on the underlying knowledge they can get from things not going as planned. Perhaps twenty-first century business needs less people thinking like engineers trying to railroad new products and services into the market and more who are willing to don the lab coat of a scientist who is willing to allow the complexity of modern business to flourish and support their innovation.
The social profile component has been enhanced to store data in a structured fashion to link to information management capabilities.
You can now tag your experience and the experience of others and look at the skills within our community.
Thanks to (Xiping) Kevin – who did a fantastic job in extening our social networking capability!
It’s been a lucrative five years for consultants in information management with new work being as easy to win as saying the word “compliance”. Executives are more than willing to sign-up new consulting engagements based the need to meet their compliance and regulatory requirements. The trouble is, this type of information management engagement breeds a defensive rather than a confident enterprise.
A defensive organization believes that data needs to be locked-down, that risks need to be taken out and the analysis resulting from any dataset should be predictable. Of course, any regular reader of this blog would know that we view data contained in large enterprises as complex and displaying all of the attributes of chaos mathematics which means any attempt to remove surprises from data is a fruitless endeavor.
A confident organization, on the other hand, recognizes that data is complex and chaotic but seeks to gain benefit from that complexity. Rather than be afraid of randomness, they use the techniques of MIKE2.0 to identify the risks and then focus on monitoring and measuring. In general, I observe a strong correlation between the confident enterprise and the adoption of Web 2.0 techniques and principles. The confident organization believes that there is more value in collaboration and is willing to sponsor individual innovation.
A good example of why this is so important can be seen in social networking sites such as Facebook. With the rapid growth in their use by a new generation of consumers, service providers ranging from telecommunication and financial services right through to government, need to come to grips with both the technology and the cultural drivers behind them. Consumers are becoming more confident in sharing quite detailed information about themselves in a way that they expect others to pick-up. Increasingly it will make no sense for providers to ask individuals to provide data about their relationships, locale or other details when those are already available in the public web.
In fact, one of the reasons why Facebook is so powerful is its ability to interface into custom applications. Imagine the impact if you wanted to sell these consumers a new financial or telecommunications product and you made it possible to apply online from within Facebook! More importantly, you can give the individual a sense of control by allowing them to privately share critical information with you and then maintain it in a form with which they are comfortable – perhaps for a multitude of providers.
Obviously there are challenges in this type of initiative, but good use of data measurement, reconciliation and parsing approaches allow it to be done. The question is whether your enterprise has even considered whether it’s worth doing? You can bet it won’t be long before your competitors do!
TODAY: Mon, April 24, 2017April2017