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Posts from the ‘Business Intelligence’ Category

2
Jun

Apple’s HealthKit vs. Google Fit – Wellness Platforms powered by big data and analytics


mobile-applicationsGame on….I think we just witnessed a next generation leap in Healthcare Wellness (powered by Data and Predictive Analytics).  Apple jumped into the health information business on June 2 2014, launching both a new health app (Health) and a cloud-based health information platform with IOS 8 (HealthKit). This was followed by Apple Watch, (Watch launch in September 10, 2014), an intelligent health and fitness companion.

Google followed with Google Fit on June 25. Fit is a set of APIs that will allow developers to sync data across wearables and devices. Google Fit is the equivalent of Apple’s HealthKit.  Google didn’t announce an equivalent of Apple Health app.  It is expecting its ecosystem of Android partners to innovate with apps. Google also might be taking a different approach with Fit aligned with Android Wear SDK which extends the Android platform to a new generation of wearable devices.

The connected health and wearable devices market has a multitude of participants, including specialized consumer electronics companies, such as Fitbit, Garmin, Jawbone, and Misfit, and traditional health and fitness companies, such as adidas, Nike and Under Armour. In addition, many large, broad-based consumer electronics companies either compete in fitness market or adjacent markets, including LG, Microsoft, and Samsung. Read more »

13
May

Cloud-based Healthcare Analytics and Decision Support Solutions


CostTransparencyThe old playbook no longer works. Everyone acknowledges that U.S healthcare is broken.

Technology (preventative apps like Apple Health and HealthKit; EHR, claims and reimbursement analytics; Physician Practice management etc.)  will reinvent healthcare as we know it.  I expect the  healthcare transformation to start incrementally and develop slowly in sophistication.  Though the early changes will appear clumsy and underwhelming, by 2030 they will seem obvious, inevitable and well beyond the changes we might envision today.

Why change? Consider this:

  • Honeywell, a Fortune 100 technology and manufacturing company, needed to manage the ever-escalating cost of insuring its 130,000 employees and their dependents. Honeywell has reported that health care costs were growing approximately 8-10% per year.
  • Self-insured employers like Wal-Mart want to make health care cost and quality information available to their 1.2 Million employees.  Useful information that can be used by employees to select physicians based on how their rank, or how much they cost, resulting in savings for both the employee and the employer. Decision support enabler.

Read more »

12
May

Consumerism, Health Exchanges, and Payor Big Data – A Primer


EmployerRequirementsHealthcare Benefits are the 2nd costliest line item for companies in the U.S. So, companies are taking aggressive steps to reduce this spend. Consider this:

  • IBM is moving to a private health exchange…Extend Health private exchange will be handling plan options for 110,000 IBM retirees
  • Walgreens is moving employees to a Corporate Health Exchange. Of the 180,000 Walgreen employees eligible for healthcare insurance, 120,000 opted for coverage for themselves and 40,000 family members. Another 60,000 employees, many of them working part-time, were not eligible for health insurance.
  • Trader Joe’s  — decided to send some employees to the new public exchanges. Trader Joe’s has left coverage for three-quarters of its work force untouched but is giving part-time workers a contribution of $500 to buy policies. Because of the employees’ low incomes, the company says it believes many will be eligible for federal subsidies to help them afford coverage.

For the past year I have done strategy and implementation work in the employee Healthcare benefits and Private Exchange area.  I wanted to share my insights into the massive structural changes taking place in health insurance. The move to patient-centered, consumer-driven, and value-based models is real.

This posting has been updated and posted on disruptivedigital.wordpress.com

 

10
Mar

Fan Engagement and Wearables: Disney MyMagic+


MagicBandA satisfying experience is the driver of any business’s revenue growth. Disney Theme Parks is no exception. Disney is executing a guest (and fan) personalization strategy leveraging wearables (and analytics) to track, measure and improve the overall park experience. The goal is increase sales, return visits, word of mouth recommendations, loyalty and brand engagement across channels, activities, and time.

Wearables are the next big thing.  The new crop of gadgets — mostly worn on the wrist or as eyewear — will become a “fifth screen,” after TVs, PCs, smartphones, and tablets.

Wearables are already being used to monitoring vital signs, wellness and health. Devices like Fitbit, UP, Fuelband, Gear2 track activity, sleep quality, steps taken during the day. Consumers of all sorts — fitness buffs, dieters, and the elderly — have come to rely on them to capture and aggregate biometric data.

What most people don’t understand is how powerful wearables (coupled with  analytics) can be in designing new user experiences.  Businesses thrive when they engage customers by creating a longitudinal predictive view of each customer’s behavior. To understand the wearables use cases and potential we did a deep dive into a real-world application at Disney Theme Parks.

Wearable Computing at Disney: MyMagic+

Read more »

4
Mar

Big Data Performance Anxiety and Data Grids


In Memory Data Grid (IMGD) is a data structure that is being increasingly The Gridcited as a solution to the problem of scaling big data applications. Unlike in-memory applications, IMGDs distribute only the data across RAM over multiple servers.  With memory prices continuing to fall and the volume of data for an application continuing to rise, solutions based on memory are looking more attractive to manage the performance bottlenecks of applications using Big Data. Should IMGD be on your radar screen for a Big Data application?

In order to understand this and other questions on IMGDs, Carpe Datum Rx spoke to Miko Matsumura, VP of Marketing and Developer Relations at Hazelcast, who has seen recent adoption of this technology in banks, telcos and technology companies. Here is an extract from our discussion.

Why is it so important to distribute data in a data grid? Why should it be In-memory?

Read more »

24
Feb

Security Analytics – Big Data Use Case


Another day, another data breach.  Just received another “We’re sorry you got hacked”…letter.  

This is the fifth letter I have received in the past 3 months:  Forbes.com, Target, Neiman Marcus, credit card company and a previous employer.  What is going on?

Why aren’t firms investing in beefing up their predictive ability to spot the cyber-security intrusion threats? What’s taking them so long to identify?  Why is the attack signature – sophisticated, self-concealing  malware – so difficult to spot?   Do firms need to invest in NSA PRISM type threat monitoring capabilities?

The three impediments to discovering and following up on attacks are:

  • Volume, velocity and variety – Not collecting appropriate security data
  • Immaturity and not identifying relevent event context (event correlation)
  • lack of system awareness and vulnerability awareness

Obviously… where there is pain…there is opportunity for entrepreneurs see below – data from IBM).  There is a growing focus on big data use case for security analytics after all the breaches we are seeing.  General Electric announced it had completed a deal to buy Wurldtech, a Vancouver-based cyber-security firm that protects big industrial sites like refineries and power plants from cyber attacks.

securityanalytics3

 

Here are three recent examples that I was personally affected by – Forbes,  Target, Neiman Marcus.  

Read more »

23
Dec

2014 Year in PreReview for Big Data Analytics


In the movie “Minority Report,” set in 2054,Time Travel Tom Cruise plays the captain of the “PreCrime” police force, which uses “precognitive” abilities of mutants to stop crime before it happens. Silicon Valley futurists have sometimes used this reference in the context of the art of the possible with Big Data. We have another 40 years to go to see how analytics can accurately forecast future events based on human behavior. Meanwhile, imagining the future with some level of accuracy is within our reach today.

Value creation in the data economy made headlines in 2014. While Big Data continued to be the buzzword of the year in 2014, solutions that created economic impact were center stage.  Trending terms such as “predictive analytics” and “advanced analytics” approached the levels of “Big Data” on Google Trends during the year. “ROI,” which was vaguely referenced in the last two years, became the most commonly used term with Big Data in 2014. Here is a cross-section of 2014 events.

Apple announces TopsyTV

This is their next-generation TV appliance that integrates social media engagement with the TV watching experience. Earlier in 2013, Apple acquired Topsy Labs, a reseller for Twitter content for $200M. This was followed by a series of less publicized acquisitions of social media data companies. Apple is characteristically tight-lipped about its plans for monetizing this product with advertising, but speculation is rife that Apple is poised to get a piece of the $600 billion that is spent on advertising today.

Read more »

23
Oct

Market Sizing – Business Analytics and Big Data


future-of“Google, Facebook are really big data companies, not software companies. They collect data, process it and sell it back with value added extensions. They don’t have better algorithms. They simply have more data.”   —  Anonymous

——————–

The convergence of cloud, social, mobile and connected computing has sparked a data revolution. More than 90 percent of the world’s data has been generated over the last two years . And with a projected 50 billion connected “things” by 2020 , the volume of data available is expected to grow exponentially. This proliferation of data has created a vast ocean of potential insights for companies, allowing them to know their customers in a whole new way.

Data is valuable. Data is plentiful. Data is complex. Data is in flux. Data is fast moving. Capturing and managing data (Cloud, On-Premise, Hybrid IT) is challenging. It’s a paradox of the information age. The glut of information that bombards us daily too frequently obscures true insight.

Help people uncover, see, understand and visualize data presents a broad and momentous market opportunity….call this user-driven discovery. Take for instance, Facebook (like Amazon.com) builds a custom Web page every time you visit. It pores over all the actions your friends have taken—their postings, photos, likes, the songs they listen to, the products they like—and determines in milliseconds which items you might wish to see, and in what order. Is this the future for every firm…..

The opportunity is simply getting bigger by the day. Every customer interaction is generating a growing trail of data (“data exhaust”). Every machine that services the customer is generating data. Every conversation, transaction, engagement, touchpoint location, offer, response  is a potential digital bread-crumb of opportunity.

Now let’s flip the context.   A typical mobile user check their phone interface 150 times a day for updates.  A Gen Y  or Millenial user obviously much more than a Gen X user.  The consumption patterns for information are changing continuously.  Facebook style real-time updates which were revolutionary 5 years ago seem outdated in the mobile world. We live in an “attention deficit economy” where attention is the new basis for competition. The firms that create the evolving experience using data which can grab/hold your attention will attract marketing and ad $$.

As a result, the buzz and hype around data…small data, big data, machine data, social data, mobile data, wearables data….is relentless. As a result there are a lot of new initiatives and companies.  I have been asked repeatedly by a lot of entrepreneurs and strategy teams about analytics market size and opportunity size.  Product and services firms are also interested in opportunity sizing as they create new offerings in the data rich world.

WorldofDataChanging

I thought i would share a mashup of industry and market sizing data i have collected so far.

  • How big is the overall market for Analytics, Big Data?
  • How big is the market for Digital Customer Interaction or Engagement?
  • How big is the market for Mobile and Social Intelligence?
  • How big is the market for Wearables?
  • What is growing fast, faster and fastest?

All good questions as services firms think about digital strategy, analytics and future state.  You always want to be in the “hot” area… selling is easier, valuations are richer, revenue growth percentages exponential.

Read more »

12
Aug

Quantified Self, Ubiquitous Self Tracking = Wearable Analytics


google_glassesThe future is here. It’s just not evenly distributed yet.”   – William Gibson

Self-tracking,  Seamless Engagement and Personal Efficiency improvement’s new frontier is Personalized Big Data and Digital Health. This is really becoming a viable idea around wearable and sensor computing and the basis for new data platform wars.

The new platforms for digital life or data driven life — that collect, aggregate and disseminate — will  cover a wide range of new User Experience  (UX) use cases and end-points… medical devices, sensor-enable wristwear, headset/glasses, tech-sensitive clothing.  All of them are going to collect a lot of data, low latency analytics, and enable  data visualization. Several new firms are entering the activity tracker market LG (Life Band Touch), Sony (the Core), Garmin (Vivofit), Glassup, Pebble, JayBird Reign etc.

Data collection is just one piece of the solution. The foundation for personalized big data is Descriptive and Predictive Analytics.  Ok…What do i next? what is the suggestion? in the form of predictive search (automated deduction or augmented reality).

How do i discover useful patterns, analyze, visualize, share, query and mobilize the collected data?  A wide range of start-ups – Cue, reQall, Donna, Tempo AI, MindMeld, Evernote, Osito, and Dark Sky – and big companies like Apple, Google, Microsoft, LG and Samsung are working on predictive apps — aimed at enabling new robo-assistants that act as personal valets, anticipating what you need before you ask for it.

DataLeverage

Read more »

9
Aug

Goldman Sachs – Big Data is a Disruptive Theme


Innovation Matrix

The following eight secular disruptive themes are what Goldman Sachs believe have the potential to reshape their categories and command greater investor attention in the coming years.

The Eight Themes:

  • E-cigarettes – The potential to transform the tobacco industry
  • Cancer Immunotherapy – The future of cancer treatment?
  • LED Lighting – A large, early-stage and multi-decade opportunity
  • Alternative Capital – Rise of a new asset class means growing risk for reinsurers
  • Natural Gas Engines – Attractive economics drive strong, long-term penetration
  • Software Defined Networking (SDN) – Re-inventing networking for the cloud era
  • 3D Printing – Disruption materializing
  • Big Data – Solutions trying to keep up with explosive data growth and complexity  (Industrial Big Data and Personalized Big Data)

These eight themes – through product or business innovation – Goldman claims are poised to transform addressable markets or open up entirely new ones, offering growth insulated from the broader macro environment and creating value for their stakeholders.

Goldman focuses on the impact of creative destruction – a term made famous by the Austrian economist Joseph Schumpeter, which emphasized the fact that innovation constantly drives breeding of new leaders and replacement of the old.

Read more »

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