Product Development

NEW FACEBOOK PAGE

New Facebook Page – will focus on #entrepreneurship, #predictive analytics, #new ventures, #healthcare

More to follow. Check out http://tinyurl.com/m8t5z4g
Paul B. Silverman writes about entrepreneurship, healthcare, and strategy management and serves as Advisor, Speaker, Educator, and Managing Partner of the Gemini Business Group, LLC, a new venture development firm, and Adjunct Professor in the R.H. Smith School of Business at the University of Maryland.

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Music Streaming and Analytics-How Spotify is Impacting the Music Business

Excellent New Yorker article about Spotify and how music sector business models are changing- very clear here that the online music market business models are morphing quickly- check out http://tinyurl.com/lw88lkc

The article reinforces my view that analytics, not content, packaging, or other features will be the primary success driver in most of today’s markets, including the music sector. I am looking at analytics-centric healthcare, financial, and business management ventures and clear to me these ventures will reshape current sectors and create new large scale opportunities just as Spotify is doing in online music

To fully understand the possibilities here, consider the following 3 points noted in the article:

  • Note migration from early stage “collaborative filtering” analytics-using what you did before to define what you want in the future – first generation analytics here which provided a competitive edge.
  • Spotify bought Echo Nest-an analytics company and created “Truffle Pig” – result is an artificial music intelligence platform that helps Spotify dissect in detail the music elements (they now look at 50 parameters for all music products) and further tighten ability to meet users’ needs
  • Most significant, Spotify’s analytics are what I call second generation, seeking to use other external personal/ environmental data to improve their ability to meet users’ needs/improve user satisfaction (and of course not switch to iTunes or Pandora). To get a glimpse into what is meant here, check out the following from the article:

Now that the Echo Nest is part of Spotify, its team has access to the enormous amount of data generated by Spotify users which show how they consume music. Spotify knows what time of day users listen to certain songs, and in many cases their location, so programmers can infer what they are probably doing—studying, exercising, driving to work. Brian Whitman, an Echo Nest co-founder, told me that programmers also hope to learn more about listeners by factoring in data such as “what the weather is like, what your relationship status is now on Facebook.”

When I look at how analytics is shaping all market sectors, we see explosive growth of what I call second generation analytics- this will spawn many exciting new ventures, and some of these will be in new market sectors that don’t even exist today. Exciting times lie ahead here
Paul B. Silverman writes about entrepreneurship, healthcare, and strategy management and serves as Advisor, Speaker, Educator, and Managing Partner of the Gemini Business Group, LLC, a new venture development firm, and Adjunct Professor in the R.H. Smith School of Business at the University of Maryland.

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Comments on Business Models at “For Entrepreneurs”

Excellent summary by David Skok on new business models we now see in the entrepreneurial arena. If you are interested in understanding the variety of business models we now see in the market this is a good place to start. I contributed comments on Data Intensity Models or “DIM” which I am looking at for new ventures- very exciting area using analytics. Check out David Skok’s site and my comments at  http://www.forentrepreneurs.com/business-models/    Copy of my comments below:

David
Excellent summary on business models – good work. Glad to
contribute here. I am focusing on a related models in the new venture arena looking at how companies create value based on their customer and ‘community of interest’ data. The Data Intensity Model (“DIM”) goes beyond lead generation models to increase revenue and looks at the value created by understanding customer needs using analytics. Mint.com is the widely quoted example here but other directions are emerging. Sounds far out but the DIM model may shape how you manage your wardrobe- check out http://paulbsilverman.com/2012… Obvious opportunities in finance arena similar to Mint.com but major opportunity I foresee is in healthcare arena. Check out my post/exchange about new business models on Accenture blog http://paulbsilverman.com/2013…. The excellent contribution you are making to educate entrepreneurs is I am sure appreciated by all.

Paul B. Silverman

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Failure Is Often A Key Driver for Success: Check out “Failing Forward — 3 Tips for Failing Your Way to Success”

Most entrepreneurs are familiar with the story of Thomas Edison’s invention of the light bulb. To outsiders, looks like a waste of time and effort- we see about 10,000 failures and one success. Thomas Edison saw it differently in his widely quoted views on success and failure: “I have not failed 10,000 times. I have not failed once. I have succeeded in proving that those 10,000 ways will not work. When I have eliminated the ways that will not work, I will find the way that will work.”

I agree with Thomas Edison and always define failures as “Learning Experiences” — this works for me.

I recommend checking out “Failing Forward — 3 Tips for Failing Your Way to Success” – an excellent perspective on success and failure from Marshall Graham, Managing Partner at Indian River Advisor, LLC. Excellent insights here for all entrepreneurs.

 

Paul B. Silverman writes about entrepreneurship, healthcare, and strategy management and serves as Advisor, Speaker, Educator, and Managing Partner of the Gemini Business Group, LLC, a consultancy firm, and Adjunct Professor in the R.H. Smith School of Business at the University of Maryland.

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WSJ – Comments on Alibaba “Singles Day” Results

On November 10th, the WSJ reviewed Alibaba results and the Gross Merchandising Volume or “GMV” metric used to measure performance of e-marketplace companies such as AliBaba and others. I find GMV and related platform business model metrics not well understood. These will be increasingly important as growth of “customer to customer” platform networks accelerate in healthcare and other sectors. Below is a full copy of my comments. Link to the WSJ article and edited comments at http://tinyurl.com/n369mha

Eeading about Alibaba’s business model, I recall the “eyeball model” driving the e-commerce explosion in the 1990’s. The premise- attract large numbers of users/customers to your site, generate value by product and service sales and, most important, generate scale to drive advertising revenue and “exponential” future earnings. Some did it well such as eBay, but the model spawned hundreds of new ventures and most failed. Why? Management, undercapitalized, poor execution strategy- these are the usual reasons most ventures fail. But there was also a fatal flaw here- the eyeball model at the time could not create a universally successful business in all sectors without careful positioning and deep pockets, not the outcome many investors expected. “Build it and they will come”- they didn’t.

Fast forward to today. Alibaba reported very impressive results on “Singles Day”, I.e., 111114, reporting 35 billion yuan ( about $5.75 billion) in the 24 hour Singles Day period. GMV or Gross Merchandise Value is their key business model metric- high GMV translates to higher revenue and presumably long term earnings growth. Following a $25 billion IPO two months ago, there is great pressure to show high GMV.

Several comments here. No question Alibaba is an outstanding success by any measure. One question is long term sustainability. Having merchants offer steep discounts ( 50 % in some cases) to create high single day sales volume looks like a “loss leader” strategy- at least one analyst also questioned whether this is sustainable long term. Remember Groupon and LivingSocial issues. Secondly, note GMV shows total value of transactions sold through Alibaba’s marketplace platform and is not a well defined standard. GMV may include shipping charges, items that will be returned, and other components for the “customer to customer” sales via Alibaba’s platform. GMV is excellent for comparing marketplace companies, but each player may use different assumptions to calculate. Finally, recognize GMV is one of several platform model metrics such as Gross Transaction Volumes or GTV which is well suited for platforms using commission-based pricing strategies. Bottom line here- Alibaba’s success will spur other “GMV” centric new ventures as did the “eyeball” model- lets understand the definitions here and standardize, ensure the proper financial accounting and reporting practices are in place, and ensure the e-marketplace sector achieves the global market growth we all foresee.

Paul B. Silverman writes about entrepreneurship, healthcare, and strategy management. He serves as Managing Partner of the Gemini Business Group, LLC, a consultancy firm, and Adjunct Professor in the R.H. Smith School of Business at the University of Maryland.

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Data Marketing 101: New Directions. Infographics +Predictive Analytics

Excellent article by Shannon Byrne on how startups can use Infographics – good insights here. Check out http://thenextweb.com/dd/2014/08/18/data-marketing-101-startups-can-put-data-work/

Coupling Infographics with predictive analytics pushes the boundary here and I shared some thoughts – here is copy of my posted comments

Shannon. Excellent post. Thanks for sharing. Infographics is an exciting area and I see predictive analytics pushing the boundary further and opening new possibilities. For example as you say need to ‘mine data that’s helpful to your audience’ and you suggest several questions to address.
But suppose we mine data and use PA tools to identify drivers that are not known – predicting the ‘unknown-unknowns’ and showing these in Infographics provides exciting and powerful capabilities. For example, suppose you are showing attributes of your customers and show typical data, e.g., sales by region, sector, customer size and so on. But suppose you can also identify and show that the highest sales are driven by sales staff with certain backgrounds who sell to certain sectors. Or you identify and show how sales rank based on variations in the sales process; I.e., response to RFP, sales call center query, direct sales call, and so on.
Key point here- the relationships I suggested here and the questions to ask will be defined by the PA model not the Infographic data modeler- that is the real power of predictive analytics ‘technology and a concept still not fully understood by many.

In the healthcare sector for example, we use PA tools to optimize clinical treatments based on data going well beyond a patient’s condition and symptoms. Mining data using PA defines ‘ inferences’ and the rules between business metrics. Fast forward here and we can envision many exciting Infographic applications that will push the boundary enabling us to improve clarity and communications of complex and insightful business metrics

Paul B. Silverman is an Adjunct Professor in the R.H. Smith School of Business at the University of Maryland, former CEO of public and private companies, Managing Partner Gemini Business Group, LLC. He can be reached at paul@paulbsilverman.com or blog at http://paulbsilverman.com/blog/, or twitter at @globalbizmentor.

 

 

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HBR Taps Data Scientist as the Sexiest Job of the Century

HBR Taps Data Scientist as the Sexiest Job of the Century

Here is an interesting post from the Spitfire Business Intelligence blog about a recent HBR article

“The award is the business world’s equivalent of People Magazine’s annual Sexiest Man Alive designation.But who could ever have imagined that the nod would go to the data scientist, a role pioneered by the world’s Web behemoths and now being sought after by mainstream companies seeking to gain actionable business insight from sifting through large volumes of data?”

http://spotfire.tibco.com/blog/?p=14455

 

Click on the above link to read the complete post and you may also want to access the HBR article which I think most will find interesting. These are the same messages I and many others are making about analytics and its ability to dramatically reshape and improve current business processes, create more efficient operations, and drive significant new product development and other high potential revenue opportunities.

The role of creative, powerful analytics is also reshaping our traditional perspectives on industry analysis and strategy development which are being integrated into traditional business management programs. And new career and business opportunities are emerging from all sectors in many diverse organizations, and I foresee these accelerating. We should keep in  mind analytics are still in early stage of development and deployment, and today’s management is only beginning to understand how these techniques add real value and competitive edge.You can be sure exciting and challenging times lie ahead in the analytics arena.

 

Paul B. Silverman

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THE ‘SUGGESTIVE’ VS. ‘PREDICTIVE’ ANALYTICS ISSUE

I posted comments on the HealthCIO.com site in response to article suggesting ‘suggestive’ rather than ‘predictive’ analytics (“PA”) provides real, demonstrable benefits and that, rather than PA,  should be today’s primary focus. My point is with the proper vision and commitments here, PA tools offer powerful, exciting new tools to improve health care, both from patient care and financial perspective, reducing claims fraud and improving processes.And these same tools are spawning exciting new ‘analytics-centric’ ventures which I see as a high potential new venture sector and is one of my focus areas.

You can visit the HealthCIO.com site to see the original article “A Suggestion About Predictive Analytics” at http://tinyurl.com/7nw6twd and also see a reply to my comments. Copy of my comments follows:

Paul says:

‘SUGGESTIVE’ AND ‘PREDICTIVE’ ANALYTICS WILL BOTH HELP IMPROVE HEALTH CARE
Thanks for sharing your insights. As a former CEO of a predictive analytics company, and currently leading a new ‘analytics-centric’ leading edge, personal health and wellness company, among other activities, I am pleased to also contribute my perspectives here.
I like your idea of contrasting Suggestive vs. Predictive Analytics- there is obvious proven benefit in using analytics to improve quality at the point of patient care.
With regard to predictive analytics, I am pleased to offer comments:
–Predictive analytics is often muddled in with other statistical tools as you say, it is often difficult to appreciate and understand just how powerful these tools are and what is their specific contribution
–Rather than saying there are two flavors of PA, “easy and hard”, I suggest a better approach is to say there are two PA target opportunity areas in health care (and also in other sectors):
— Using PA to analyze the “known unknowns” – all of the patient treatment enhancements you described fall into this category- addressing known issues and processes, using analytics to improve processes, quality of care, and doing this more efficiently and at lower cost.
—Using PA to analyze the “unknown unknowns” – this is the real and power of predictive analytics and I believe really offers high upside for all health care players, and patients as well
–Look at the magnitude of today’s health care issues. As one example, increasing complexity of medication regimens used by patients, coupled with a fragmented health care system involving multiple prescribers, has made the occurrence of serious drug-drug interactions more likely today than ever before. For example, one study suggests Preventable Adverse Drug Events injure 1.5 million people a year, costs the U.S. healthcare system $3.5 billion and resulting in an estimated 44,000 to 98,000 deaths every year. Some studies show even higher numbers.
–Our aging population exacerbates the above issues. Studies show 41 percent of seniors take
5 or more prescription medications, and more than half has 2 or more prescribing physicians. And 24 percent- about 1 out of 4 – seniors having 3 or more chronic conditions have not shared information with their health care providers during the last 12 months. No wonder medication errors among seniors on Medicare are estimated at almost $900 million.

–We can use the real power of PA to better understand the “unknown-unknown” drivers here that are impacting our health care system, and create powerful new tools, improved processes and do this more efficiently while improving patient care.

–The “unknown-unknown” data I would like to see addresses questions such as why do we have adverse drug events; what are the rules we should be looking at and changing to reduce these events save lives, and reduce health costs; what are the underlying drivers and patterns for adverse drug events- do these vary by geography, treatment modalities, user demographics, specific types of medical facilities, maybe how and where medical practitioners are trained. “Unknown-unknowns” may, for example, identify certain treatment modalities and drug regimens used by select groups of medical professionals which drive adverse drug events. Predictive analytics, an inductive rather than deductive process, offers a powerful tool to help us identify these and many other critical underlying health care drivers.

I agree there are many PA projects that today may seem academic, but I do see great possibilities to improve our health care system, using powerful new predictive analytics computing tools and platforms coupled with more traditional analytics (both suggestive and deductive ‘rule based’ analytics), to dramatically improve the quality of our health care system. These new analytics and tools will address clinical issues such as the growing problem of adverse drug events, as well as addressing Medicare and other health care claims fraud and errors.

We are making progress, but I still believe we can be doing much more to achieve significant improvement in our nation’s health care system and very clear to me predictive analytics and other tools, with the proper vision and commitments, will play a substantive role.

Paul Silverman, Managing Partner, Gemini Business Group, CEO  Sante Corporation, Adjunct Professor, R.H. Smith School of Business in the University of Maryland.

 

v. is what we need to focus on to improve health care

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HOW BOOK MARKETING/PROMOTION DRIVES CLIENT BUSINESS AND SELLS PRINT BOOKS

BOOK SIGNING AND MEET THE AUTHOR AND  EVENT AT  EXPO EAST CONFERENCE  ATLANTIC CITY : HOW BOOK  MARKETING/PROMOTION DRIVES CLIENT BUSINESS AND SELLS PRINT BOOKS

I was invited to do a book signing and “Meet the Author” event June 5th at the Expo East promotions expo in Atlantic City, NJ. for my first book in the   “Worm on a Chopstick” series,   Understanding Today’s Entrepreneurial Age: Directions, Strategies, Management Perspectives, and discuss my second book planned for release in late 2012.

One of the largest promotions/marketing conferences, the trade-only event attracts major corporate buyers, sales reps, promotion/marketing companies, ad agencies, and others.  Today we see explosive growth of  e-books which is driving market demand, and also see the demise of traditional ‘brick and mortar’ bookstores.

However, before we writeoff the traditional print book market, it is clear to me based on discussions at this event and elsewhere, that print books are supporting many creative marketing and promotion initiatives to create new markets, promote major lines of business, and sell books in large quantities. While we may typically think about print books sold in bookstores, airport kiosks, via Amazon or other mail order channels, the following are some of the marketing and promotion channels I have discussed now being used to support business and sell books:

  • Major bank develops a “Small Business Corporate Library’ to offer selected clients to strengthen their relationship with small business customers and reinforce their brand
  • Pharmaceutical firms integrate nutritional health and wellness programs with one or more selected books
  • Insurance companies use selected ‘branded’ planning/lifestyle texts to create new educational programs for their clients
  • Emergency services (local police and fire) ‘private label’ educational publications for children to provide safety education
  • State governors add ‘tip-in’ pages in a customized version of a business/entrepreneurship or other book to support economic development and attract businesses to the region (“tip-in” pages are custom pages inserted upfront into print books)

All of the above are driven by a basic need – companies want to attract, educate and strengthen relationships with customers. Traditionally, you may have received an imprinted calendar, pen or notepad from your favorite bank, and probably still will, but the above are some of the many new creative and exciting marketing/promotion activities we see emerging now. Given today’s intense global competition, I expect these initiatives to accelerate and others to emerge also linking social media, print books, and e books- we are seeing major new, exciting market opportunities developing here.

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New Predictive Analytics Application:Managing Your Wardrobe

I see the new ‘data intensity’ business model getting traction in new sectors and creative applications are emerging. Check out Stylitics, a new analytics platform to help manage your wardrobe.

http://mashable.com/2012/02/03/stylitics/

Note the reference to linking branding, couponing and so on. Most importantly, note the clear reference to Mint.com which I and many others view as a “flagship” data intensity business model.

Working with Sante Corporation, a new healthcare/analytics venture, it is clear to me providers can add high value to consumers through next generation analytics, carefully crafted to deliver insights to consumers and provide significant public benefit. The key points here – information aggregation and retrieval are yesterday’s business and commoditizing. Real opportunity now is going deeper, developing “data intensity” models, identifying the “unknown unknowns” providing real value, using powerful, creative predictive analytics to create sustainable value, and developing high value partnerships using electronic couponing, machine readable packaging and other new tools to deliver real value to consumers and create exponential shareholder value growth.

Given Mint.com’s successful business strategy, we can expect to see the data intensity business model trend accelerating. Very exciting developments are coming in this high potential market space.

Paul B. Silverman

Author: Worm on a Chopstick : Understanding Today’s Entrepreneurial Age: Directions, Strategies, Management Perspectives http://paulbsilverman.com/books/

Chief Executive Officer
Sante Corporation
Creating Next Generation Personalized, Simple Solutions to Improve Personal Health Management

Email:      paul@paulbsilverman.com
Linked in:  Paul Silverman
Twitter:     globalbizmentor

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