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How will the 'economics of machine learning' impact your business model?

“You can’t stop the incessant march of economics” – Bill Schmarzo

Okay, so it’s probably not cool to quote oneself, but hey, this is my blog and I get to do what I want.  And for anyone who follows me knows, I love to “riff” on the game-changing power of economics.  The “economics of big data” – where the cost to store, manage and analyze data is 20x to 100x cheaper than traditional analytics – started this big data and data science craze.  But ultimately it is the economics of value, or to be specific, “value in use” where the economics really become a game changer.

I recent article titled “The Simple Economics of Machine Intelligence” from the Harvard Business Review highlights very well the role that economics (maybe even more than data science) is going to play in separating the winners from the losers in digital transformation.  To quote the article:

  • Machine intelligence is, in its essence, a prediction technology, so the economic shift will center on a drop in the cost of prediction.
  • When the cost of any input falls so precipitously, there are two other well-established economic implications. First, we will start using prediction to perform tasks where we previously didn’t. Second, the value of other things that complement prediction will rise.
  • Using the language of economics, judgment is a complement to prediction and therefore when the cost of prediction falls demand for judgment rises.

So how will the “economics of machine learning” – or the “economics of advanced analytics” – impact your business model?  We developed the Big Data Business Model Maturity Index as a framework help organizations understand where and how they can leverage data and analytics to power their business models (see Figure 1).

Figure 1:  Big Data Business Model Maturity Index

The Maturity Index provides a roadmap to guide customers in integration data and analytics into their business models.  See “Big Data Business Model Maturity Index Guide” for a “How To” guide on leveraging data and analytics to advance along the Maturity Index.

Advanced Analytics Continuum
Recent conversations with Walker Stemple of Intel’s @intelAI organization got me thinking about where and how organizations can leverage “advanced analytics” to power their business models.  Now “advanced analytics” is a broad definition, but I have included the following analytics in that definition: Regression, Clustering, Neural Networks, Machine Learning, Deep Learning, Artificial Intelligence and Cognitive Computing.  And while these “classifications” seem to change on a regular basis (sometimes due to us getting smarter; sometimes due to non-value-add marketing hype), it is critical that tomorrow’s business leaders understand where and how to apply these advanced analytics to power their business models.

My conversation with Walker helped me to understand how organizations can leverage the clusters of advanced analytics to advance along the Maturity Index (see Figure 2).

Figure 2:  Advanced Analytics Continuum

The Advanced Analytics Continuum covers the following classifications:

  • Descriptive Analytics is not really advanced analytics, but it is foundational in helping organizations understand “What happened?” to their business. This is traditionally the domain of Business Intelligence.  Business Intelligence is primarily focused on “Comparative Analytics” such as Current Period versus Previous Period reporting, Period-to-date cumulative calculations and projecting trend plots.  The primary analytic tools in Descriptive Analytics are reports, dashboards and alerts.
  • Predictive Analytics is focused on uncovering insights about what happened in order to create foresight, or predictions, about what is likely to happen. Predictive Analytics seek to quantify cause-and-effect – and measure the analytic model’s goodness-of-fit – in order to drive those predictions.  Predictive analytic algorithms include Statistics, Clustering, Classification, and Regression Analysis.  This is also where you will see the use of ANOVA, Covariance and Confusion Tables to measure the goodness of model fit.
  • Prescriptive Analytics is focused on building analytic models that can prescribe or recommend what actions consumers and employees should take in order to optimize key business or operational processes. Advanced analytic algorithms of choice in the area of Prescriptive Analytics include Collaborative Filtering, Neural Networks, Deep Learning, and Machine Learning.
  • Cognitive Analytics is focused on creating an environment (system or application) that can self-monitor, self-diagnose, self-fix and ultimately self-learn. These environments are constantly measuring the effectiveness of decisions and updating/refining the analytic models based upon the outcomes of decisions.  Think about an autonomous vehicle that is moving through a new environment and has to learn quickly about the nuances of that environment (e.g., traffic patterns, potholes, road maintenance, temperature variations, wind gusts, precipitation). Advanced analytics tools of choice in the area of Cognitive Analytics include Reinforcement Learning, Artificial Intelligence, and Cognitive Computing.

We can bring this all together by showing how the Advanced Analytics Continuum can help organizations advance along the Big Data Business Model Maturity Index as seen in Figure 3.

Figure 3:  Advanced Analytics Power Business Model Maturity Index

While not perfect (and likely will never be perfect) the merging of the Advanced Analytics Continuum with the Big Data Business Model Maturity Index helps organizations to understand not only in what advanced analytics to invest, but understand how those analytics can help advance the organization along the maturity index.

Advanced Analytics in Action
Let’s walk through an example of how we might apply the Advance Analytics Continuum to create an intelligent organization.  For our example, I am using publicly available data from the City of San Jose Open Data Portal (https://data.sanjoseca.gov/home) that shows where and when fatal traffic accidents have occurred in the San Jose Area.  The City of San Jose Open Data Portal is part of the city’s Open Data Community Architecture (ODCA) initiative led by the City of San Jose Data Architect, Arti Tangri and CIO, Rob Lloyd.  The ODCA project provides a highly adaptable reference architecture that encourages local community analytics by providing an adoptable design that (1) exposes data for use, (2) arranges analytics and skills for informed decisions, (3) builds a platform that enables automation and prediction, and (4) aims the data for shared data lakes for government/academia/private sector use.  In these structures, the ODCA lays the foundation for economic monetization of the City of San Jose’s data.

Descriptive Analytics:  Reporting Fatal Accidents
Let’s start the advanced analytics transformation process by creating descriptive analytics about what has happened.  For example, let’s say we have a map showing fatal accidents over a select period of time (see Figure X).

Figure 4:  Reporting of Fatal Traffic Accidents

While Business Intelligence is a great starting point, we must embrace advanced analytics to become more actionable.

Predictive Analytics:  Predicting Where Accidents Are Likely To Happen
We can apply Predictive Analytics (e.g., Statistics, Clustering, Classification, Regression Analysis) to “quantify cause-and-effect” in order to predict when and where a fatal traffic accident is likely to occur (see Figure 5).

Figure 5: Predicted Fatal Traffic Accidents

In order to create this prediction, we need to brainstorm with the key stakeholders the variables and metrics that might help us make a better prediction of fatal traffic accidents.  In particular, we want to brainstorm the following question:

What data might you want in order to predict when and where a fatal traffic accident might occur in the South Bay?

The brainstorming exercise will produce a wide variety of data sources that the data science team might want to consider as they build the predictive analytics (see Table 1).

Traffic Patterns Weather Conditions Local Events
Time of Year Day of Week Time of Day
Holidays Population Growth Economic Activity Growth
Building Permits Road Maintenance New Driver Permits
Tourism Large Truck Traffic Electric Vehicles
Changes in Retail Sales Building Renovations Pedestrian Traffic
Bike Traffic Motorcycle Traffic Sunrise Location

Table 1:  Potential Data Sources for Predicting Fatal Traffic Accidents

Prescriptive Analytics:  Recommending Where and When to Locate Police
Next we want to leverage prescriptive analytics in order to augment human decision-making and optimize key business and operational processes.  In our reduce crime application, Prescriptive Analytics can create recommendations about when and where to locate police (see Figure 6).

Figure 6: Recommended Police and Emergency Equipment Locations

It is important that the application captures the actual decisions made about where and when the police and emergency equipment are located in order to measure the effectiveness of the recommendations.  This feedback on the decisions and the associated outcomes is critical in creating Cognitive Analytics.

Creating a Self-learning, Intelligent Accident Response App
Finally, we want to leverage Cognitive Analytics to create an intelligent or learning application to reduce fatal traffic accidents.  We want the application to continuously learn from new environments and potentially new data, more granular data sources (see Figure 7).

Figure 7:  Cognitive Analytics to Continuously Learn and Refine Analytic Outcomes

The model should tell the data scientist which variables are the most predictive (variable predictability or the relative importance of a particular variable to the analytic model’s results) so that proper effort can be placed in ensuring that the data is complete, accurate, timely and governed.

Summary: The Economics of Advanced Analytics
The process of determining or quantifying the economic value of an organization’s data based upon Adam Smith’s “value in use” concept (“Wealth of Nations”, 1776) is greatly augmented via advanced analytics; where “value in use” is defined as the use of an asset to create new economic or financial value (see the University of San Francisco research paper “Applying Economic Concepts To Big Data To Determine The Financial Value Of The Organization’s Data And Analytics Research Paper” for more details on how to determine the economic value of your organization’s data).  Advanced Analytics drive the “value in use” aspects of economics by creating new digital assets (data, analytics and intelligent applications) that power an organization’s business models and fuel an organization’s digital transformation.

Tomorrow’s business leaders cannot be content to leave the understanding of advanced analytics to just their data science or business analyst teams. Tomorrow’s business leaders must be at the forefront of understanding the capabilities of advanced analytics so they can determine where and how to apply advanced analytics to power today’s as well as tomorrow’s business model battles.

In the end, it’s not having the advanced analytics capabilities that will determine the winners from the losers, but it’s where and how organizations exploit advanced analytics to re-invent their business models.

The post Leveraging Advanced Analytics to Power Digital Transformation appeared first on InFocus Blog | Dell EMC Services.

Internet of @ThingsExpo, taking place October 31 - November 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA, is co-located with 21st Cloud Expo and will feature technical sessions from a rock star conference faculty and the leading industry players in the world.

Download Show Prospectus ▸ Here

The Internet of Things (IoT) is the most profound change in personal and enterprise IT since the creation of the Worldwide Web more than 20 years ago.

All major researchers estimate there will be tens of billions devices - computers, smartphones, tablets, and sensors - connected to the Internet by 2020. This number will continue to grow at a rapid pace for the next several decades.

With major technology companies and startups seriously embracing IoT strategies, now is the perfect time to attend @ThingsExpo in Silicon Valley. Learn what is going on, contribute to the discussions, and ensure that your enterprise is as "IoT-Ready" as it can be!

With major technology companies and startups seriously embracing Cloud strategies, now is the perfect time to attend 21st Cloud Expo, October 31 - November 2, 2017, at the Santa Clara Convention Center, CA, and June 12-14, 2018, at the Javits Center in New York City, NY, and learn what is going on, contribute to the discussions, and ensure that your enterprise is on the right path to Digital Transformation.

Track 1. Enterprise Cloud | Cloud-Native
Track 2.
Big Data | Analytics
Track 3. Internet of Things | IIoT | Smart Cities

Track 4. DevOps | Digital Transformation (DX)

Track 5. APIs | Cloud Security | Mobility

Track 6.
AI | ML | DL | Cognitive
Track 7.
Containers | Microservices | Serverless
Track 8. FinTech | InsurTech | Token Economy

Cloud Expo | @ThingsExpo 2017 Silicon Valley
(October 31 - November 2, 2017, Santa Clara Convention Center, CA)

Cloud Expo | @ThingsExpo 2018 New York 
(June 12-14, 2018, Javits Center, Manhattan)

Download Show Prospectus ▸ Here

Every Global 2000 enterprise in the world is now integrating cloud computing in some form into its IT development and operations. Midsize and small businesses are also migrating to the cloud in increasing numbers.  

Companies are each developing their unique mix of cloud technologies and services, forming multi-cloud and hybrid cloud architectures and deployments across all major industries. Cloud-driven thinking has become the norm in financial services, manufacturing, telco, healthcare, transportation, energy, media, entertainment, retail and other consumer industries, and the public sector.

Cloud Expo is the single show where technology buyers and vendors can meet to experience and discus cloud computing and all that it entails. Sponsors of Cloud Expo will benefit from unmatched branding, profile building and lead generation opportunities through:

  • Featured on-site presentation and ongoing on-demand webcast exposure to a captive audience of industry decision-makers.
  • Showcase exhibition during our new extended dedicated expo hours
  • Breakout Session Priority scheduling for Sponsors that have been guaranteed a 35-minute technical session
  • Online advertising in SYS-CON's i-Technology Publications
  • Capitalize on our Comprehensive Marketing efforts leading up to the show with print mailings, e-newsletters and extensive online media coverage.
  • Unprecedented PR Coverage: Editorial Coverage on Cloud Computing Journal.
  • Tweetup to over 75,000 plus followers
  • Press releases sent on major wire services to over 500 industry analysts.

For more information on sponsorship, exhibit, and keynote opportunities, contact Carmen Gonzalez by email at events (at) sys-con.com, or by phone 201 802-3021.

The World's Largest "Cloud Digital Transformation" Event

@CloudExpo | @ThingsExpo 2017 Silicon Valley
(Oct. 31 - Nov. 2, 2017, Santa Clara Convention Center, CA)

@CloudExpo | @ThingsExpo 2018 New York 
(June 12-14, 2018, Javits Center, Manhattan)

Full Conference Registration Gold Pass and Exhibit Hall ▸ Here

Register For @CloudExpo ▸ Here via EventBrite

Register For @ThingsExpo ▸ Here via EventBrite

Register For @DevOpsSummit ▸ Here via EventBrite

Sponsorship Opportunities

Sponsors of Cloud Expo | @ThingsExpo will benefit from unmatched branding, profile building and lead generation opportunities through:

  • Featured on-site presentation and ongoing on-demand webcast exposure to a captive audience of industry decision-makers
  • Showcase exhibition during our new extended dedicated expo hours
  • Breakout Session Priority scheduling for Sponsors that have been guaranteed a 35 minute technical session
  • Online targeted advertising in SYS-CON's i-Technology Publications
  • Capitalize on our Comprehensive Marketing efforts leading up to the show with print mailings, e-newsletters and extensive online media coverage
  • Unprecedented Marketing Coverage: Editorial Coverage on ITweetup to over 100,000 plus followers, press releases sent on major wire services to over 500 industry analysts

For more information on sponsorship, exhibit, and keynote opportunities, contact Carmen Gonzalez (@GonzalezCarmen) today by email at events (at) sys-con.com, or by phone 201 802-3021.

Secrets of Sponsors and Exhibitors ▸ Here
Secrets of Cloud Expo Speakers ▸ Here

All major researchers estimate there will be tens of billions devices - computers, smartphones, tablets, and sensors - connected to the Internet by 2020. This number will continue to grow at a rapid pace for the next several decades.

With major technology companies and startups seriously embracing Cloud strategies, now is the perfect time to attend @CloudExpo@ThingsExpo, October 31 - November 2, 2017, at the Santa Clara Convention Center, CA, and June 12-4, 2018, at the Javits Center in New York City, NY, and learn what is going on, contribute to the discussions, and ensure that your enterprise is on the right path to Digital Transformation.

Delegates to Cloud Expo | @ThingsExpo will be able to attend 8 simultaneous, information-packed education tracks.

There are over 120 breakout sessions in all, with Keynotes, General Sessions, and Power Panels adding to three days of incredibly rich presentations and content.

Join Cloud Expo | @ThingsExpo conference chair Roger Strukhoff (@IoT2040), October 31 - November 2, 2017, Santa Clara Convention Center, CA, and June 12-14, 2018, at the Javits Center in New York City, NY, for three days of intense Enterprise Cloud and 'Digital Transformation' discussion and focus, including Big Data's indispensable role in IoT, Smart Grids and (IIoT) Industrial Internet of Things, Wearables and Consumer IoT, as well as (new) Digital Transformation in Vertical Markets.

Financial Technology - or FinTech - Is Now Part of the @CloudExpo Program!

Accordingly, attendees at the upcoming 21st Cloud Expo | @ThingsExpo October 31 - November 2, 2017, Santa Clara Convention Center, CA, and June 12-14, 2018, at the Javits Center in New York City, NY, will find fresh new content in a new track called FinTech, which will incorporate machine learning, artificial intelligence, deep learning, and blockchain into one track.

Financial enterprises in New York City, London, Singapore, and other world financial capitals are embracing a new generation of smart, automated FinTech that eliminates many cumbersome, slow, and expensive intermediate processes from their businesses.

FinTech brings efficiency as well as the ability to deliver new services and a much improved customer experience throughout the global financial services industry. FinTech is a natural fit with cloud computing, as new services are quickly developed, deployed, and scaled on public, private, and hybrid clouds.

More than US$20 billion in venture capital is being invested in FinTech this year. @CloudExpo is pleased to bring you the latest FinTech developments as an integral part of our program, starting at the 21st International Cloud Expo October 31 - November 2, 2017 in Silicon Valley, and June 12-14, 2018, in New York City.

@CloudExpo is accepting submissions for this new track, so please visit www.CloudComputingExpo.com for the latest information.

Speaking Opportunities

The upcoming 21st International @CloudExpo@ThingsExpo, October 31 - November 2, 2017, Santa Clara Convention Center, CA, and June 12-14, 2018, at the Javits Center in New York City, NY announces that its Call For Papers for speaking opportunities is open.

Submit your speaking proposal today! ▸ Here

About SYS-CON Media & Events
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Cloud Expo®, Big Data Expo® and @ThingsExpo® are registered trademarks of Cloud Expo, Inc., a SYS-CON Events company.

More Stories By William Schmarzo

Bill Schmarzo, author of “Big Data: Understanding How Data Powers Big Business”, is responsible for setting the strategy and defining the Big Data service line offerings and capabilities for the EMC Global Services organization. As part of Bill’s CTO charter, he is responsible for working with organizations to help them identify where and how to start their big data journeys. He’s written several white papers, avid blogger and is a frequent speaker on the use of Big Data and advanced analytics to power organization’s key business initiatives. He also teaches the “Big Data MBA” at the University of San Francisco School of Management.

Bill has nearly three decades of experience in data warehousing, BI and analytics. Bill authored EMC’s Vision Workshop methodology that links an organization’s strategic business initiatives with their supporting data and analytic requirements, and co-authored with Ralph Kimball a series of articles on analytic applications. Bill has served on The Data Warehouse Institute’s faculty as the head of the analytic applications curriculum.

Previously, Bill was the Vice President of Advertiser Analytics at Yahoo and the Vice President of Analytic Applications at Business Objects.

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