Is DNA Really Personally Identifiable Information (PII)? No. Maybe? Yes!

February 5, 2013

Biometric data is at the limits of what current personal data privacy laws consider worthy of protection. This type of identifier covers fingerprints, voiceprints, and facial images. While the risk factors are not nearly as threatening to consumers as more traditional PII, they do exist. Until recently, the dangers of biometric identification using DNA were more theoretical than real. That has suddenly changed. An article in The New York Times last month put a spotlight on research that proved the feasibility of identifying a person—getting a specific name and address—all from a DNA sequence posted online.

It’s not that regulators have overlooked biometric identifiers. Under HIPAA’s safe harbor rules, for example, the Department of Health and Human Services has a list of 18 e-PHIs that would need to be removed from public medical data for it to be effectively considered de-identified. Along with IP addresses, URLs, email addresses, HHS mentions biometric data, with voiceprints and fingerprints given as the only examples.

I’ve already written about how the Federal Trade Commission, another key US agency involved in data privacy regulation, has issued new guidelines to companies collecting facial images. Driving the FTC’s suggestions—mostly directed at retailers—are the recent improvements in image recognition technology and the availability of massive amounts of tagged photos on social media sites. Image matching software is now good enough so that a face captured by a store’s mall kiosk can eventually reveal ethnicity, mood, and with good likelihood, an actual name behind the face.

The risk of linking a name to a set of fingerprints is less serious for the general public— unless you have a criminal record. However, after the Graduate Management Admission Council  (GMAC) began using fingerprints to establish the identity of students taking their “GMATs” for admission to US business schools, the testing company realized there could be privacy issues.

GMAC ultimately decided to use palm scans, which are based on digitizing vein patterns. Since public databases of hand veins don’t exist, the possibility of identification is eliminated.

I would have put DNA into the same category as palm scans: there’s advanced matching technology—available even at the consumer level—but without a public database, there isn’t much of a privacy issue, and therefore DNA is not really a PII.

However, this is not true anymore, and that was the starting point for the researchers mentioned in the Times article. There are actually two public genealogy databases for tracking down one’s ancestry, Ysearch and SMGF, with a combined 135,000 records of DNA data and covering about 39,000 unique last names.

These genealogy databases simply accept a key—actually a pattern on the Y-chromosome—and then return a surname (along with a confidence level). The idea behind these services is to help subscribers find their ancestors and learn more about family backgrounds.

The researchers then examined whether they could narrow down their search. They assumed that they had the state of residency of the subject along with a birthdate—both of these, by the way, are not considered PII under current HIPAA rules. With these three data points and public US Census data, they were able to prove that successful DNA matches would lead to just 12 people on average. That’s a stunning end result from starting with just a DNA pattern.

How good is the DNA “keyword” match at finding a last name? The researchers projected a success rate of 12% for males—since it’s based on the Y chromosome—with a 5% false positive. This is not nearly as accurate as the facial scans, but still a cause for concern. They concluded that the risk of this DNA-based last name search will grow in the future, and there are other scientists and experts who are calling for more public discussion.

I decided to check the privacy policy of one of the DNA testing services. Here’s the good news. They’ll only release your DNA data to third parties with your consent; they treat genetic data as personal data (like name and address), and they say that the genetic data is stored on “secure servers”.

However, thinking purely in term of bytes, folders, and access rights, I’m wondering how truly secure those DNA files are, and whether there are already hackers looking to get that data using the same techniques and exploits they use to snatch credit card numbers and other personally identifiable information.


Big data and the future of health care

January 21, 2013

Big Data and the Future of Healthcare


Analytics-Driven Companies See Competitive Advantage: IBM-MIT Study

January 2, 2013

In recent years, there have been a lot of anecdotal accounts of analytics making a positive impact on business growth — and now a new study of 4,500 executives provides some data points to back this up.

Source: MIT-IBM 2011 Analytics Study

The global survey of executives, managers and analysts, released by MIT Sloan Management Review and the IBM Institute for Business Value, finds the information ‘haves’ — companies with in-depth experience with analytics technologies and methodologies — increasingly saw competitive advantage, and were more than twice as likely to have outperformed their analytically challenged peers over the past year. (Full report available from MIT SMR or IBM.)

Overall. adoption of analytic capabilities has been rapidly proliferating as of late. Fifty-eight percent of organizations now apply analytics to create a competitive advantage within their markets or industries, up from 37% just one year ago, the study confirms.

Eight out of ten “Transformed” companies — those with strong, industry-leading analytics capabilities — report demonstrable competitive advantage, up 23% from the MIT-IBM survey a year ago. For “Experienced” companies — those with moderate to heavy analytics usage — there was a 66% spike in reported competitive advantage. Among the less-advanced portion of the respondents, the percentage of those with favorable competitive positions slipped over the past year.

However, there is still much, much work to be done. The study found that the majority of organizations are using analytics to manage financial and operational activities, but are less likely to rely on analytics-based insights for decisions in other key areas.  Tellingly, only about half of the advanced analytics companies rely on data and analytics outside finance, to make decisions involving customers, business strategy and human resources. Fewer than 25% of the less-developed companies are using analytics in this way.

The information ‘haves’ tend to be further along in their abilities to analyze data (78%); capture and aggregate data (77%); foster a culture open to new ideas (77%); build analytics into their core business strategies and operations (72%); embed predictive analytics into process (66%); and make insights available to those who need them (65%). This last point is significant, as it suggests that two out of three of the advanced analytics companies have figured out ways to “democratize” their business intelligence and analytics to decision makers at all levels.

The report also provides guidelines on building a more analytics-capable operation, starting with an assessment of  current analytic capabilities; focusing on improving competencies via information foundation, analysis skills and tools, and creating a culture that acts on analytics; and  having an overall information agenda to make analytics part of the day-to-day enterprise.  As the survey finds, 44% of respondents say their organizations aren’t receptive to becoming a more analytical culture. Only 24% say they don’t have access to the right technology to make it happen.


IBM IOD 2012 – How Analytics is Transforming the C-Suite.

December 12, 2012

Fred Balboni, Global Leader, Business Analytics and Optimization, speaking to the need of infusing analytics throughout the organization and how IT and LOB executives are changing partnership models to bring this to reality. In the panel discussion, JP Morgan Chase shared how they are using analytics to mine information from the “new” customer who is banking via mobile channels and Thompson Reuters described the role that analytics plays in their customer centricity by creating upsell and cross-sell opportunities externally and greatly reducing the cost of ownership internally.


Shifts in Retail Demand New Analytics

October 15, 2012

Our benchmark research into retail analytics says that only 34 percent of retail companies are satisfied with the process they currently use to create analytics. That’s a 10 percent lower satisfaction score than we found for all industries combined. The dissatisfaction is being driven by underperforming technology that cannot keep up with the dramatic changes that are occurring in the retail industry. Retail analytics lag those in the broader business world, with 71 percent still using spreadsheets as their primary analysis tool. This is significantly higher than other industries and shows the immaturity in the field of retail analytics.

While in the past retailers did not need to be on the cutting edge of analytics, dramatic changes occurring in retail are driving a new analytics imperative:

Manufacturers are forming direct relationships with consumers through communities and e-commerce. These relationships can extend into the store and influence buyers at the point of purchase.  This “pull-through” strategy increases the power and brand equity of the supplier while decreasing the position strength of the retailer. This dynamic is evidenced by JC Penney, which positions itself as a storefront for an entire portfolio of supplier brands. Whereas before the retailer owned the relationship with the consumer, the relationship is now shared between the retailer and its suppliers.

What this means for retail analytics: Our benchmark research shows retail has lagged behind other businesses with respect to analytics. Given the new co-opitition environment with suppliers, retailers must use analytics to compete. Their decreasing brand equity means that they need analytics not just for brand strategy and planning, but also in tactical areas such as merchandising and promotional management. At the same time, retailers are working with ever-increasing amounts of data that is often shared throughout the supply chain to build business cases and to enrich customer experience, and that data is ripe for analysis in service to business goals.

E-commerce is driving a convergence of offline and online retail consumer behavior, forcing change to a historically inert retail analytics culture. As we’ve all heard by now, online retailers such as Amazon threaten the business models of showroom retailers. Some old-line companies are dealing with the change by taking an “if you can’t beat ’em, join ’em” approach. Traditional brick-and-mortar company Walgreens, for instance, acquired Drugstore.com and put kiosks in its stores to let customers order out-of-stock items immediately at the same price. However, online retailers, instead of looking to move into a brick-and-mortar environment, are driving their business model back into the data center and forward onto mobile devices. Amazon, for instance, offers Amazon Web Services and Kindle tablet.

What this means for retail analytics: There has historically been a wall between the .com area of a company and the rest of the organization. Companies did mystery shopping to do price checks in physical trade areas and bots to do the same thing over the Internet. Now companies such as Sears are investing heavily to gain full digital transparency into the supply chain so that they can change pricing on the fly – that is, it may choose to undercut a competitor on a specific SKU, then when its system finds a lack of inventory among competitors for the item, it can automatically increase its price and its margin. Eventually the entire industry, including midtier retailers, will have to focus on how analytics can improve their business.

Retailers are moving the focus of their strategy away from customer acquisition and toward customer retention. We see this change of focus both on the brick-and-mortar side, where loyalty card programs are becoming ubiquitous, and online via key technology enablers such as Google, whose I/O 2012 conference focused on the shift from online customer acquisition to online customer retention.

What this means for retail analytics: As data proliferates, businesses gain the ability to look more closely at how individuals contribute to a company’s revenue and profit. Traditional RFM and attribution approaches are becoming more precise as we move away from aggregate models and begin to look at particular consumer behavior. Analytics can help pinpoint changes in behavior that matter, and more importantly, indicate what organizations can do to retain desired customers or expand share-of-wallet. In addition, software to improve the customer experience within the context of a site visit is becoming more important. This sort of analytics, which might be called a type of online ethnography, is a powerful tool for improving the customer experience and increasing the stickiness of a retailer’s site.

In sum, our research on retail analytics shows that outdated technological and analytical approaches still dominate the retail industry. At the same time, changes in the industry are forcing companies to rethink their strategies, and many companies are addressing these challenges by leveraging analytics to attract and retain the most valued customers. For large firms, the stakes are extremely high, and the decisions around how to implement this strategy can determine not just profitability but potentially their future existence. Retail organizations need to consider investments into new approaches for getting access to analytics. For example, analytics provided via cloud computing and software as a service are becoming more pervasive help ensure they meet the capabilities and needs of business roles. Such approaches are a step function above the excel based environments that many retailers are living in today.

thanks to http://tonycosentino.ventanaresearch.com/2012/10/12/shifts-in-retail-demand-new-analytics/

 


Mastering Big Data

October 3, 2012

Date: Thursday, November 1, 2012
Time: 14:00 – 15:00 GMT

Big data analytics has already turned entire industries on their heads. To date, many big data analytics are associated with “machine generated” data like trade information, location data, etc. However, 80% of organizational data lives on file servers, NAS devices and email systems in the form of spreadsheets, presentations, audio files, video files, blueprints and designs—human generated content.

Learn how big data analytics helps organizations better leverage, manage, and protect their human generated content:

  • Identify areas of high risk
  • Optimize workflows
  • Connect disparate teams and data sets
  • Discover new patterns, flag potential abuse
  • Enhance data access control, ownership, classification, entitlements and authorization processes

Please see link below to the webinar

http://www.varonis.com/partner/uk/promo/1?utm_source=VAR-C24-UK


Live @ IBM Smarter Commerce Global Summit Madrid: IBM’s Mike Rhodin On Insight-Driven Computing

September 20, 2012

IBM vice president Mike Rhodin hit the stage this morning at the IBM Smarter Commerce Global Summit, with presenter emcee Jon Briggs introducing Mike as “the man who eats analytics for breakfast, lunch, and dinner.’

IBM senior vice president Mike Rhodin explains to the gathered audience in Madrid how the Smarter Commerce initiative was a logical and inevitable offshoot of IBM’s smarter planet campaign, one driven by the need for more insight- and action-driven analytics.

Rhodin’s talk was entitled “Transform Your Business Around the Customer,” again with the central theme of the Summit that if more businesses wanted to keep theirs, they would increasingly have to pivot their business around customer needs.

Thanks to Turbotodd

Rhodin indicated that he wanted to take a step backward from yesterday’s more outcome-driven discussion, and instead talk about “some of the foundational ideas that led us to Smarter Commerce.”

He explained that four years ago, IBM started a conversation about having a “smarter planet,” one increasingly instrumented, interconnected, and intelligent, and that since that time, “analytics emerged as a centerpiece across our entire portfolio.”

Rhodin joked that the financial crisis’ onslaught wasn’t the best time to launch a new marketing campaign, but then explained smarter planet wasn’t that, that it was a signal call heralding a new age of computing. That it was, in fact, the beginning of a movement that was going to happen “no matter what else happened in the world.”

The change this movement would bring was startling. We saw the social media embraced in both the social, political, and, increasingly business realms, and we saw that the physical world was about to become digitized…to some degree, because of the crisis.

Ergo, the world, and organizations, needed to better understand systemic risk in advance of its rearing its ugly head. Hence, the need to instrument the world around us.

“Information was flowing around the planet at a breakneck speed,” Rhodin articulated, “and so there was another form of input to make business decisions that became apparent.”

“We also instrumented the virtual world,” he went on, “whereby understanding the sentiment of your employees, your partners, and other constituents was critical.”

Yet all this new data was overwhelming many. “It was growing at such a speed that people couldn’t read or process it with traditional means, and so that’s where analytics started to play a key role, and served as a foundation for Smarter Commerce.”

“This began what we’re classifying as the next generation of computing,” Rhodin went on to explain. “We went through the age of ‘tabulating’ — we’re now entering the age of “information-based” computing.”

In this age, business outcomes are increasingly insight-driven, solutions are more intelligent, and technology is designed to be more and more cognitive.

“It’s not about understanding what happens, but rather, what you do about it, what actions you take,” Rhodin concluded.

With this explosion of data from a hyper-connected society of empowered consumers, we “must extract insight from our most important assets – employees and customers – through smarter analytics,” and the challenge, then, is to address the need for “volume, velocity, and veracity” to help find the right data amidst all those needles amidst all those haystacks.

And it’s a big series of haystacks and needles. The data generated between the dawn of civilization and 2003 is now created every two days! Rhodin explained.

He went on: “These next gen systems are creating opportunities in IT we haven’t seen in 50 years. But now, with all this information and analytics, and the march of globalization, we can start to automate areas of business we could never automate before. We can start to automate and make more intelligent the front-office areas of our business. Chief Financial Officers, CMOs, head of sales, HR…we can turn HR from a reactive to proactive process.”

“We’ve identified a new pattern of automation across industries, one whereby we can instrument, interconnect, and analyze more and more data about the world, and in the process unlock more and more valuable insight,” he explained. “We are infusing intelligent into the fabric of organizational processes. This shift is as profound as the last evolution was to transaction processing and back office automation.”

The shift being, of course, a continual transition whereby today’s analytics evolves into tomorrow’s cognitive computing capability, where Watson-style technologies utilizing natural language processing and hypothesis-generating and adaptation and learning systems virtually reinvent the IT future.

“We can remake parts of industries that have been untouched by IT in the past,” Rhodin concluded.


Taking Sports Analytics to the Next Level

July 31, 2012

Major League Soccer literally made a heart-pounding announcement last Thursday when it unveiled plans to use the new adidas micoach Elite System on Wednesday when the MLS All-Stars take on Chelsea.

Billed as the world’s first “smart game,” the micoach system will be placed in players’ uniforms, tracking movement, force, heart rates and more in real-time. Data will be sent to an iPad or other device that will help coaches and training staff monitor athletes, providing the first real internal view of what an athlete’s body goes through during actual high level competition. All MLS teams will be using it for training during the 2013 season.

“It will be interesting, I think as time goes by we’ll see more and more applications,” says MLS executive Nelson Rodriguez. “I think the analysis will get sharper and deeper, but it’s certainly a very exciting opportunity. It’s been fascinating. The data will gain in importance once a dataset is established, so the longer you use the system and the more data you acquire, the deeper your analysis can be.”

In development for over two years by adidas, with some of the top teams in the world on board, including Real Madrid, AC Milan and Bayern Munich, micoach actually uses a lot of commercially available technology, like a gyroscope, accelerometer and GPS tracking (which anyone with an iPhone also has in their pocket) in a round tic tac box sized cell that is worn in a compression shirt in a pocket between their shoulder blades. There’s also a small tracker placed in their shoe to measure force of a kick and distance travelled. The tech reportedly sends 200 data records per player per second to a central computer, which are then simplified and synthesized and sent to coaches.

The potential ramifications and uses are far-reaching. For soccer alone, it could measure the force of a kick scoring, or even potentially, if a player is forced down or is flopping.

Great video below that showcases the technology


Analytics Priority #1

July 9, 2012

Studies, Surveys, and CEO’s all point to the same thing. Analytics and Data Insights are “The Top Priority” for companies.

http://blogs.sap.com/analytics/2012/01/25/bi-and-mobility-top-the-2012-priorities-for-cios/

http://thesologuide.com/2725/website-analytics-is-the-top-priority-for-marketers-in-2012/

http://practicalanalytics.wordpress.com/2011/11/02/ibm-cio-study-bi-and-analytics-are-1-priority-for-2012/

Why then do so many firms struggle to glean maximum intelligence, if any, from their data? Why are they struggling to fill the exponentially growing number of open head counts they appear to be prioritizing.

Here’s why: An individual employee actually has a “Priority #0”, which takes precedence over Priority #1. While Analytics sole purpose is predicting and improving business performance in the future, somehow employees are recognized, rewarded, and evaluated on something other than Analytics. Your product owner is responsible for making sure the product ships, not so much on how it “will do”. The engineers and designers don’t understand why proper data infrastructure is needed to make current design decisions… because its not. Its for future design decisions. However without that infrastructure in place upon launch, there is simply no way of tracking a product’s success or failure post-launch.

How does this get resolved? While there’s no silver bullet, the solution must start from the top. It’s not enough for executives to preach data driven decisions from a soap box, or for internal recruiters to post, post, and repost analytic positions which they can’t seem to fill. They must make sure that proper incentives are in place and that perverse political disincentives are eliminated (like needing a particular number to be the answer aside from the actual number). In fact, I often get asked “Scott – What do you when you have tomake up the numbers”? 

Woah.

While Data Insights is what the CEO’s are calling for, CFOs, CIOs and other internal staffers know its also a bit of a whistle blower, or political “Debbie Downerhttp://slashdot.org/topic/bi/big-data-top-priority-executives-mckinsey-survey/. What would you do if there were actual data on your products performance beyond marketing hype and conjecture? Your departments contribution, your online presence, customer loyalty, call center efficiency, etc… all up for mathematical analysis. Would you pass muster?

But on the upside, maybe that multi-million dollar advertising budget can be reallocated toward a far more profitable end. Analytics can help you make these crucial decisions.

http://sokotech.com/2012/07/06/analytics-priority-1/


Digital Analytics: Key Trends on the Horizon for 2012

April 25, 2012

The business of measuring digital activity has come a long way since its early development. It is now technologically advanced enough to provide a vivid picture of what is going on at and around a site as well as what is going on with visitors. The motivational force behind the advancement of digital analytics has been because of the growth of online business and stakeholders looking for more reliable metrics and precise feedback they can use to maximize profit. As a result, 2012 will be an eventful year for the digital analytics industry as it continues to catch up with the growing online ecosystem, which holds a variety of businesses. Below are three key trends to look out for in 2012.

1. Real Time Analytics:

More and more marketers have asked for real time data to react more quickly to what is going on with their web strategy. In 2011, Google launched a beta version of real time analytics and Facebook as well in 2012, which clearly shows they both already are seeing the need for real time tracking and not predictive analysis anymore. Real time analytics will be extremely important going forward for brands that are working on time sensitive campaigns or want to see data on who is on their site currently and how fast certain information is spreading. This is why real time analytics will play an increasingly important role in 2012 and service providers will continue to develop solutions to make it more practical for users.

2. Big Data Analytics:

In 2012, the hot new thing is data, data, and data! Decision makers cannot get enough of it and lately companies are digitizing more information than ever. Fueling this data explosion are over 30 billion pieces of content shared on Facebook per month, 20 billion Internet searches per month, and five billion mobile phones. Big Data is the platform used for transforming all of this data into actionable items for business decision making and companies that are able to put this technology to work are likely to find considerable revenue generating that will differentiate them from competition and drive success into the next decade.

3. Multi-channel Integration:

Onsite and offsite are becoming more entangled in business as customers research, compare, and make purchase decisions on different site channels and at different times. Measuring return only based on the last click gives an incomplete picture and potentially misses key insights about how customers are reached. For 2012, we are already seeing integration of onsite metrics with offsite metrics and Google Analytics recently released Multi-channel Funnels as a feature to let users look at interactions across different digital media and show how these channels work together to create sales. Consequently, the best business strategies going forward will be those that can take advantage of this interplay between different site channels, which will allow for better understanding and targeting of customers and potential users.

Thanks http://dobmarketing.wordpress.com/2012/04/25/digital-analytics-key-trends-on-the-horizon-for-2012-2/

 


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