Business models

Forbes-Roundup Analytics,Big Data,BI, IOT

IOTExcellent article in Forbes on big data, analytics, and business intelligence. You can see my comments (top comments section)  and the Forbes article at http://www.forbes.com/sites/louiscolumbus/2015/05/25/roundup-of-analytics-big-data-business-intelligence-forecasts-and-market-estimates-2015/

One of the best roundup articles showing forecasts and outlook in these explosive growth markets. All businesses and providers must recognize the challenges that must be met and how all must adapt to secure real value from these trends.

Summary:

Summary of my recommendations in posted comments here – view big data/analytics/IOT as ‘technology enablers’, enabling you to improve and streamline business processes. The winning strategy- get past what I call the ‘gee-whiz’ factor, recognize IOT, analytics, and other technologies are a “means to the end,” driving new business processes to reduce costs, increase revenue, and improve strategic position.

Forbes article is highly recommended reading for all interested in big data, analytics, and IOT.

 

Paul B. Silverman is Managing Partner of The Gemini Business Group, LLC, a new venture development firm dedicated to helping global entrepreneurs succeed (www.geminibusinessgroup.com) . He is the former CEO of a predictive analytics company and writes and speaks about entrepreneurship, healthcare, analytics, and strategy management and is the author of “8 Building Blocks To Launch, Manage, And Grow A Successful Business.” See more at Paul B. Silverman Blog.

 

 

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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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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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