Linked Data Marketplaces. A study on Groupon.com. The 100 Most Social Big Data Companies. Big Data Trends. Leveraging Big Data To Transform Your Business Model. The North American video game market was in a massive recession in 1985. Revenues that had peaked at $3.2 billion in 1983, fell to $100 million by 1985 (a drop of almost 97 percent). The crash almost destroyed the then-fledgling industry and led to the bankruptcy of several companies, including Atari. Many business analysts doubted the long-term viability of the video game console industry[1]. There were several reasons for the crash. The hardware manufacturers had lost exclusive control of their platforms’ supply of games, and consequently lost the ability to ensure that the toy stores were never over-stocked with products.
But the main culprit was the saturation of the market with low-quality games. The video-game industry was revitalized in 1987 with the success of the Nintendo Entertainment System (NES). Transforming Your Business Model With Big Data From Product To Platform Enabling An Ecosystem The platform provider will then need to focus on ensuring that the platform is: Summary. Big Data Business Model Maturity Chart. Customers ask me: How far can big data take us from a business perspective? What could the ultimate end point look like? How do I compare to others with respect to my organization’s adoption of big data as a business enabler? How far can I push big data (“Virile Data”?)
To power – even transform – my value creation processes? To help address these types of questions, I’ve created the below “Big Data Business Model Maturity” chart. Organizations can use this chart to get an idea as to where they sit with respect to exploiting big data and advanced analytics to power their value creation processes and business models. Big Data Business Model Maturity Chart Organizations are moving at different paces with respect to how they are adopting big data and advanced analytics to create competitive advantage. A select few are looking well beyond just improving their existing business processes with big data analytics.
Figure 1: Big Data Business Model Maturity Chart 1. 2. 3. 4. 5. Why Data Will Never Replace Thinking - Justin Fox. By Justin Fox | 12:00 PM October 4, 2012 Big data, it has been said, is making science obsolete. No longer do we need theories of genetics or linguistics or sociology, Wired editor Chris Anderson wrote in a manifesto four years ago: “With enough data, the numbers speak for themselves.”
Last year, at the Techonomy conference outside Tucson, I heard Vivek Ranadivé — founder and CEO of financial-data software provider TIBCO, subject of a Malcolm Gladwell article on how to win at girls’ basketball, and part owner of the Golden State Warriors — say pretty much the same thing: I believe that math is trumping science. What I mean by that is you don’t really have to know why, you just have to know that if a and b happen, c will happen.
Anderson and Ranadivé are reacting to something real. But that does that really mean there are no hypotheses involved? As best I can tell, there are three hypotheses inherent in this replace-the-Fed-with-algorithms-plan. More >> Researchers Say Much to Be Learned from Chicago's Open Data. View Full Caption Robert Kozloff/University of Chicago HYDE PARK — Chicago is a vain metropolis, publishing every minute detail about the movement of its buses and every little skirmish in its neighborhoods. A team of researchers at the University of Chicago is taking that flood of data and using it to understand and improve the city. “Right now we have more data than we’re able to make use of — that’s one of our motivations,” said Charlie Catlett, director of the new Urban Center for Computation and Data at the University of Chicago.
Over the past two years the city has unleashed a torrent of data about bus schedules, neighborhood crimes, 311 calls and other information. Residents have put it to use, but Catlett wants his team of computational experts to get a crack at it. “Most of what is happening with public data now is interesting, but it’s people building apps to visualize the data,” said Catlett, a computer scientist at the university and Argonne National Laboratory. The 4 Phases Of Big Data. EMC Shows the Power of Big Data Analytics CIO.
CIO — This week I attended EMC's analyst briefing, but before things started I had dinner with Jim Bampos, EMC's vice president of quality. Bampos is arguably the technology industry's leading expert in the area of customer care, with one patent in hand and two more in process. I'd also just finished a review of the use of data analytics in the U.S. election and in that exercise had been fascinated by the fact that Mitt Romney didn't use analytics properly and President Barack Obama did. Romney had better tools but outsourced the effort, while Obama created the capability internally, and the result is now history. What fascinated me was that the candidate who was a former CEO and widely believed to be the more capable manager clearly didn't know how to successfully use analytics—and likely mirrored many executives who use the buzzword but don't really understand what it means.
News: Presidential Election a Victory for Statistical Modeling Why Most IT Executives Hate Valid Data. Managing the Information Tsunami to Accelerate Product Design & Development. Managing the Information Tsunami to Accelerate Product Design & Development Posted on Mon, Oct 22, 2012 40 percent. Just four out of every ten manufacturers claim they have the decision-making capabilities necessary to innovate. The preponderance of information available to product development teams is growing – in volume and in complexity - at an incredible rate. From internal knowledge to external authoritative content, companies across industries are struggling to fully leverage the wealth of available know-how in order to make better, faster, smarter product decisions. Decisions that materially impact the top and bottom line. Last week, Supply & Demand Chain Executive and IHS hosted a complimentary webcast exploring the roadblocks companies face managing the rising tide of data.
Check on the infographic below for a quick snapshot of the challenges organizations encounter in managing the data deluge and turning critical business information into actionable innovation intelligence. 5 ways big data is transforming everyday life — Data | GigaOM. Big Data Analytics and Social Business: An E-Book. From Big Data to Big Decisions: Three Ways Analytics Can Improve the Retail Experience. Despite our best efforts to collect and analyze data, good business decisions will always include elements of judgment, intuition or just plain luck. Many day-to-day decisions are made with little or no thought, because the option selected just seems “right.” Gut-feel decisions might be examples of what Malcolm Gladwell called “thin-slicing” in his provocative 2005 bestseller Blink. However, the best decision can sometimes be counter-intuitive.
For example, the financial services firm Assurant Solutions wanted to improve its “save” rate on customers calling in to cancel their protection insurance. The industry’s conventional wisdom, which resulted in 15-16% retention rates, was to focus on reducing wait time to boost customer satisfaction. But data analysis found a solution that tripled the retention rate: matching customer service reps with customers based on rapport and affinity. The question is not about tools or even data. Bigger Data Doesn’t Mean Better Decisions. Big Data, Analytics and the Path From Insights to Value.
How the smartest organizations are embedding analytics to transform information into insight and then action. Findings and recommendations from the first annual New Intelligent Enterprise Global Executive study. Image courtesy of Best Buy. In every industry, in every part of the world, senior leaders wonder whether they are getting full value from the massive amounts of information they already have within their organizations. New technologies are collecting more data than ever before, yet many organizations are still looking for better ways to obtain value from their data and compete in the marketplace.
Their questions about how best to achieve value persist. Are competitors obtaining sharper, more timely insights? Full Report This article presents the highlights of our Special Report Analytics: The New Path to Value. Among our key findings: Top-performing organizations use analytics five times more than lower performers. 10 Insights: A First Look at The New Intelligent Enterprise Survey. How do you win with data? SMR surveyed global executives about turning the data deluge and analytics into competitive advantage. Here’s an early snapshot of how managers are answering the most important question organizations face. Image courtesy of Flickr user gonzales2010 Last May, at the MIT Sloan CIO Symposium main-stage discussion on “Emerging Stronger from the Downturn,” one panelist listened with a growing private smile as his fellow speakers described example after example of how technology-driven information and analytics applications were transforming their companies.
The stories were of data and analysis being used to understand customers, parse trends, distribute decision making, manage risk; they foretold of organizations being reinvented and management practice being rethought. They told of change, basically. He’s right. However, the focus on exactly what’s changing can be misplaced. IBM CEO Study: Openness by Social Media Is Key Enabler to Organizational Success. According to the IBM CEO study conducted amongst 1,700 CEOs from 64 countries and 18 sectors, Open CEOs' identify openness enabled and supported by social media and technologies, as a major influence on their organization and its success. These organizations perform better because they are utilizing the collective intelligence, are more agile, able to act quickly to gain higher profitability and growth.
The research shows that currently only 16 percent of CEOs are using social networks to be more directly involved and connected with their employees, customers and partners. In the next three to five years this figure will increase to 57 percent. Social media are currently the least used means to interact with stakeholders. Within five years they become the number two “engagement” method, closely behind face-to-face interactions as number one. Forbes reports the following key findings: Trust Market-driven organization By Gianluigi Cuccureddu About the author: Gianluigi Cuccureddu. Balancing Intuition with Analysis. Interview – Roger Martin of “The Design of Business” I had the opportunity to interview Roger Martin, the author of “The Design of Business” about the challenges companies face when they fail to balance analytical thinking with intuitive thinking.
We also discuss a variety of other innovation topics including: barriers to innovation, education, and risk taking. Roger Martin has served as Dean of the Rotman School of Management since 1998. He is an advisor on strategy to the CEO’s of several major global corporations. He writes extensively on design and is a regular columnist for BusinessWeek.com’s Innovation and Design Channel. He is also a regular contributor to Washington Post’s On Leadership blog and to Financial Times’ Judgment Call column. He has published several books, including: “The Design of Business” and “The Opposable Mind”. Here is the text from the interview: 1. 2. 3. Two main reasons. 4. 5. 6. That is a lame argument. 7.
They need to nurture their originality. 8. The Promise for Big Data in Open Innovation. The Pitfalls of Prediction. Prognostication is a multi-billion dollar industry. We have weathermen, Wall Street Analysts, political pundits and futurologists. They all claim some expertise. These people exist because there is strong demand for their services. Businesses need to create budgets. People have to decide what to wear. Politicians are expected to anticipate issues that will matter to society. Without predictions, there can be no plans. Messy Data The problem starts when smart people in nice suits and lab jackets proclaim that “the data says…” In truth, the data never says anything. Data is, after all, messy. Moreover,as I explained in an earlier post, the mathematics we have long used to form statistical models has been found wanting.
Data is anything but objective. What You See is All There Is Nobel laureate Daniel Kahneman explains another reason why our predictions often fail in this article. Another point Kahneman brings up is that we tend to give more weight to the first information that we see. What a Data-Rich Smart City Experience Could Really Be Like - Technology. Welcome to the "meta-city. " It's a networked urban world of smart infrastructure and ubiquitous data that could soon become the typical city experience. Just by looking around, you'll be able to see where that bus across the street is going, when the train you need is leaving, how to buy a ticket, when the weather's going to turn nasty, what's located on the fourth floor of that pretty building in front of you, and exactly where you can charge your phone – likely the screen-of-choice for displaying all this information in the smart (and, it turns out, incredibly helpful) city of the future.
The meta-city is visualized in this video as a "hybrid digital physical environment" where information about one's surroundings can be superimposed in real-time to create a data-rich view of the functions and actors within a city. Explosive innovation and adoption of computing, mobile devices, and rich sources of data are changing the cities in which we live, work, and play. Image credit: frog.
Ten tech-enabled business trends to watch - McKinsey Quarterly - High Tech - Strategy & Analysis. Two-and-a-half years ago, we described eight technology-enabled business trends that were profoundly reshaping strategy across a wide swath of industries. We showed how the combined effects of emerging Internet technologies, increased computing power, and fast, pervasive digital communications were spawning new ways to manage talent and assets as well as new thinking about organizational structures.
Since then, the technology landscape has continued to evolve rapidly. Facebook, in just over two short years, has quintupled in size to a network that touches more than 500 million users. More than 4 billion people around the world now use cell phones, and for 450 million of those people the Web is a fully mobile experience. The rapidly shifting technology environment raises serious questions for executives about how to help their companies capitalize on the transformation under way. Across the board, the stakes are high. 1. Facebook has marshaled its community for product development. 2. Richard Branson on Decision-Making For Entrepreneurs. Editor's Note: Entrepreneur Richard Branson regularly shares his business experience and advice with readers. What follows is the latest edited round of insightful responses. Ask him a question and your query might be the inspiration for a future column. Q: What were your most important managerial decisions -- the ones that changed your business?
-- Volodymyr Kravchuk, Kiev, Ukraine A: Most good chief executives or entrepreneurs only make three or four key decisions every year. Looking back over my career, which now spans more than four decades, there were many occasions when I got it right and a few when I did not. 1. This was the case when we launched our airlines Virgin Atlantic and Virgin Blue (recently rebranded Virgin Australia), in 1984 and 2000, respectively.
Virgin Atlantic went from strength to strength, and now carries over 5 million passengers per year. 2. Related: Richard Branson on Embracing Change I rarely paid attention (which also drew criticism from some analysts). 3. The Right to Be Forgotten. Big Data’s Impact in the World.