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Five Innovative Social, Mobile, Cloud, and Big Data Apps From the US 2012 Election Campaigns

Greg Chase

With the US 2012 election campaign finally, thankfully, winding down, I wanted to share some interesting stories about the technology being used by the campaigns and super PACs to more effectively direct their field staff and target voters.  From the various news stories I’ve heard over the past few weeks on NPR, and read in articles, it seems that both the presidential campaigns and the big budget super PACs have been making heavy use of social media, mobile device applications, cloud platforms, and big data.

This blog isn’t meant to take a position in the campaign. I can’t even argue that one campaign has made more effective use of new technology than another. Whereas in 2008, the Obama campaign clearly made more effective use of social media than his opponent, it seems that both campaigns in 2012 have aggressively embraced emerging technologies.

Here are five descriptions of applications that I was able to find. I will add to this list as I run across more.  Please feel free to add any links to interesting stories that you know about as well in the comments. Also, the application of this technology is strictly an American perspective. I suspect many of my European colleagues will have an entirely different view of the acceptability, and even legality, of some of these applications. Please share your perspectives on this issue as well.

Use of cloud computing to link sprawling, temporary field offices with a single system.

This article points out that both campaigns are making use of cloud computing to link together their many field offices to state and national offices. Another excellent point is that the campaigns are temporary, so purchasing extensive IT infrastructure makes no sense when these campaigns can just rent system capacity as needed.

Finally, one point I didn’t see in the article is that in the case of Romney, he had only a matter of weeks to set up field offices after wrapping up the Republican nomination whereas the Obama campaign had the luxury of planning his next election over four years. There is no way that Romney could roll out an effective organization without making liberal use of cloud computing to speed up the process.

The article specifically points out an application called Campaign Cloud by electionmall in association with Microsoft. In this application, campaigns can manage their staffs and fundraising activities.

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Features of the Campaign Cloud by electionmall [SOURCE]

Cloud storage for campaign intelligence tracking

This article by Kai Ryssdal from NPR’s Marketplace describes the job of a campaign tracker – people working for super PACs and opponents’ campaigns that follow a candidate to every event, document everything a candidate says, and try to capture video and audio of inconsistencies and gaffes. This information is then uploaded into a searchable database in the cloud along with a whole ton of other public information.  Back at the Super PAC, the staff spend hundreds of hours searching facts and video putting together a political history, trying to find contradictions or other bits that eventually end up in political advertising.

Big data profiles of voters for better targeting and motivation

Then there is this article that describes how there are at least seven companies that are combining multiple public and private data sources to create voter profiles including age, gender, voter registration, how often you actually voted, and your political donation history. This information currently profiles 180 million voters in the United States – 80% of registered voters. The key is applying the right psychological and social behavioral science criteria to this data. This article from The Slate, heavily slanted towards Obama, describes the difference between merely constructing a model of how you think voters look like, as opposed to considering actual behaviors.

Some of this information comes from search engines. Google apparently does not share political beliefs as it considers this to be sensitive personal information. However, this article does claim that Yahoo and Microsoft sell access to registration information for political targeting.

This data isn’t just for targeting ads. This transcript from an NPR  news article describes how this data is allowing campaign workers to target individual voters instead of merely grossly targeting precincts.  What’s even more interesting is how they’re motivating people to go vote. They send out postcards showing your previous voting history and those of your neighbors. No, this isn’t how you voted, just whether you actually cast a ballot or not. This results in a sort of self-inflicted peer pressure. Many people don’t want their neighbors to see that they are disaffected and not taking part in their patriotic duty to vote. If this seems invasive, records of who voted in an election have been displayed for years, and it was common practice for precinct watchers to pay attention as to whether their party members had come out to cast their ballot.

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A slide taken from an online slideshow by a political targeting firm. [SOURCE]

Social media to influence voting

Certainly both campaigns and super PACs are making massive use of social media to get their message out, and to solicit donations. But what about using social media to both motivate people to actually cast their vote, and maybe even to influence how they vote. This article describes a research study that shows exactly how a social media site like Facebook can be used exactly to that effect. I don’t know whether this was actually deployed by any campaign, but don’t be surprised to see it in the next election cycle.

Startup company Votizen has taken these concepts to create as service that matches online social media profiles with registered voters.  You can sign in with your Twitter or Facebook account and see your friends party registration, where they are registered to vote, and how often they actually cast their ballot. You can then enter your favorite candidate, whether for President of the  United States, or the local school board, and find out which of your friends you need to motivate to vote for your candidate and cast their ballot.

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View candidate profile and friends you can influence to vote for a candidate through social media in Votizen. [SOURCE]

Based on the information they’ve gleaned from social media networks and registered voter lists, Votizen is able to project a real time voter sentiment page of tweets.

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Tweets and real time statistics of registered voters sentiment in the US by Votizen. [SOURCE]

Mobile devices tied to real time big data and cloud applications for canvasser efficiency and voter data collection

Lastly, this article and broadcast from Aarti Shahani from NPR’s All Things Considered describes the most impressive application I’ve heard about in this election cycle – The Door Knocking App, Electioneer from startup company Organizer. This application provides real time status updates to campaign coordinators of the voters being targeted by canvassers.  You can see the progress of their canvassers and also get real time information of the voter’s sentiment.

http://tctechcrunch2011.files.wordpress.com/2012/09/canvass-results.png

Coordinators view of canvassing status. Check marks are targeted voters that were visited. [SOURCE]

There’s a corresponding mobile device application that canvassers use to know which voters they are assigned to talk with, and to be able to update sentiment in real time via a multiple choice poll.

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View of poll input screen for individual voters in canvassing mobile application.  [SOURCE]

One quote from the NPR article suggests that this kind of real time sentiment gathering could even replace traditional polling since you’ll have actual data about how each voter is feeling rather than having to make statistical guesses.

I was able to find this demo of the application on YouTube from the Disrupt conference:

Video demonstration of Electioneer cloud application and mobile device from Disrupt Conference. [SOURCE]

Innovating ideas for your company

None of the applications described above are for sale from SAP. If, however, one of these stories sparks a creative idea in your head, I encourage you to check out the SAP NetWeaver Cloud Developer Center. Here you can get a free developer license, and see what combining cloud computing with social, mobile, and big data functionality can do to create a competitive advantage for your company.

What are your thoughts?

This post originally appeared on the SAP Community Network.

The implications of collaboration in the networked economy will continue to shape every aspect of the world we live in today and the changing world we will live in tomorrow. Get involved in the conversations on The Future of Business and read, watch and learn about the networked economy.

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Greg Chase

About Greg Chase

Greg Chase previously was the Senior Director of Product Marketing for SAP HANA in the Cloud. He was responsible for driving awareness, messaging, and initial customer experience for SAP customers, partners, ISVs and start ups looking to get started using SAP HANA on demand, and elastically via the cloud.

Innovation Without Boundaries: Why The Cloud Matters

Michael Haws

Is it possible to innovate without boundaries?

Of course – if you are using the cloud. An actual cloud doesn’t have any boundaries. It’s fluid. But more important, it can provide the much-needed precipitation that brings nature to life. So it is with cloud technology – but it’s your ideas that can grow and transform your business.USA --- Clouds, Heaven --- Image by © Ocean/Corbis

Running your business in the cloud is no longer just a consideration during a typical use-case exercise. Business executives are now faced with making decisions on solutions that go beyond previous limitations with cloud computing. Selecting the latest tools to address a business process gap is now less about features and more about functionality.

It doesn’t matter whether your organization is experienced with cloud solutions or new to the concept. Cloud technology is quickly becoming a core part of addressing the needs of a growing business.

5 considerations when planning your journey to the cloud

How can your organization define its successful path to the cloud? Here are five things you should consider when investigating whether a move to the cloud is right for you.

1. Understanding the cloud is great, but putting it into action is another thing.

For most CIOs, putting a cloud strategy on paper is new territory. Cloud computing is taking on new realms: Pure managed services to software-as-a-service (SaaS). Just as legacy computing had different flavors, so does cloud technology.

2. There is more than one way to innovate in the cloud.

Alignment with an open cloud reference architecture can help your CIO deliver on the promises of the cloud while using a stair-step approach to cloud adoption – from on-premise to hybrid to full cloud computing. Some companies find their own path by constantly reevaluating their needs and shifting their focus when necessary – making the move from running a data center to delivering real value to stakeholders, for example.

3. The cloud can help accelerate processes and lower cost.

By recognizing unprecedented growth, your organization can embark on a path to significant transformation that powers greater agility and competitiveness. Choose a solution set that best meets your needs, and implement and support it moving forward. By leveraging the cloud to support the chosen solution, ongoing maintenance, training, and system issues becomes the cloud provider’s responsibility. And for you, this offers the freedom to focus on the core business.

4. You can lock down your infrastructure and ensure more efficient processes.

Do you use a traditional reporting engine against a large relational database to generate a sequential batched report to close your books at quarter’s end? If so, you’re not alone. Sure, a new solution with new technology may be an obvious improvement. But how valuable to your board will you become when you reduce the financial closing process by 1–3 days? That’s the beauty of the cloud: You can accelerate the deployment of your chosen solution and realize ROI quickly – even before the next full reporting period.

5. The cloud opens the door to new opportunity in a secure environment.

For many companies, moving to the cloud may seem impossible due to the time and effort needed to train workers and hire resources with the right skill sets. Plus, if you are a startup in a rural location, it may not be as easy to attract the right talent as it is for your Silicon Valley counterparts. The cloud allows your business to secure your infrastructure as well as recruit and onboard those hard-to-find resources by applying a managed services contract to run your cloud model

The cloud means many things to different people. What’s your path?

With SAP HANA Enterprise Cloud service, you can navigate the best path to building, running, and operating your own cloud when running critical business processes. Find out how SAP HANA Enterprise Cloud can deliver the speed and resources necessary to quickly validate and realize solid ROI.

Check out the video below or visit us at www.sap.com/services-support/svc/in-memory-computing/hana-consulting/enterprise-cloud-services/index.html.

Connect with us on Twitter: @SAPServices

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Michael Haws

About Michael Haws

Michael Haws is the Vice President of HANA Enterprise Cloud at SAP. His specialties include Enterprise Resource Planning Software & Services, Onshore, Nearshore, Offshore--Application, Infrastructure and Business Process Outsourcing.

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Consumers And Providers: Two Halves Of The Hybrid Cloud Equation

Marty McCormick

Long gone are the days of CIOs and IT managers freely spending money to move their 02 Jun 2012 --- Young creatives having lunch and conversation. --- Image by © Hero/Corbisexisting systems to the cloud without any real business justification just to be part of the latest hype. As cloud deployments are becoming more prevalent, IT leaders are now tasked with proving the tangible benefits of adopting a cloud strategy from an operational, efficiency, and cost perspective. At the same time, they must balance their end users’ increasing demand for access to more data from an ever-expanding list of public cloud sources.

Lately, public cloud systems have become part of IT landscapes both in the form of multi-tenant systems, such as software-as-a-service (SaaS) offerings and data consumption applications such as Twitter. Along with the integration of applications and data outside of the corporate domain, new architectures have been spawned, requiring real-time and seamless integration points.  As shown in the figure below, these hybrid clouds – loosely defined as the integration of data from systems in both public and private clouds in a unified fashion – are the foundation of this new IT architecture.

hybridCloudImage

Not only has the hybrid cloud changed a company’s approach to deploying new software, but it has also changed the way software is developed and sold from a provider’s perspective.

The provider perspective: Unifying development and operations

Thanks to the hybrid cloud approach, system administrators and developers are sitting side by side in an agile development model known as Development and Operations (DevOps). By increasing collaboration, communication, innovation, and problem resolution, development teams can closely collaborate with system administrators and provide a continuous feedback loop of both sides of the agile methodology.

For example, operations teams can provide feedback on reported software bugs, software support issues, and new feature requests to development teams in real time. Likewise, development teams develop and test new applications with support and maintainability as a key pillar in design.
After seeing the advantages realized by cloud providers that have embraced this approach long ago, other companies that have traditionally separated these two areas are now adopting the DevOps model.

The consumer perspective: Moving to the cloud on its own terms

From the standpoint of the corporate consumer, hybrid cloud deployments bring a number of advantages to an IT organization. Specifically, the hybrid approach allows companies to move some application functionality to the cloud at their own pace.
Many applications naturally lend themselves to public cloud domains given their application and data requirements. For most companies, HR, indirect procurement, travel, and CRM systems are the first to be deployed in a public cloud. This approach eliminates the requirement for building and operating these applications in house while allowing IT areas to take advantage of new features and technologies much faster.

However, there is one challenge consumers need to overcome: The lack of capabilities needed to extend these applications and meet business requirements when the standard offering is often insufficient. Unfortunately, this tempts organizations to create extensive custom applications that replicate information across a variety of systems to meet end user requirements. This development work can offset the cost benefits of the initial cloud application, especially when you consider the upgrades and support required to maintain the application.

What this all means to everyone involved in the hybrid cloud

Given these two perspectives, on-premise software providers are transforming themselves so they can meet the ever-evolving demands of today’s information consumer. In particular, they are preparing for these unique challenges facing customers and creating a smooth journey to a hybrid cloud.

Take SAP, for example. By adopting a DevOps model to break down a huge internal barrier and allowing tighter collaboration, the company has delivered a simpler approach to hybrid cloud deployments through the SAP HANA Cloud Platform for extending applications and SAP HANA Enterprise Cloud for hosting solutions.

Find out how these two innovations can help you implement a robust and secure hybrid cloud solution:
SAP HANA Cloud Platform
SAP HANA Enterprise Cloud

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Marty McCormick

About Marty McCormick

Marty McCormick is the Lead Technical Architect, Managed Cloud Delivery, at SAP. He is experienced in a wide range of SAP solutions, including SAP Netweaver SAP Portal, SAP CRM, SAP SRM, SAP MDM, SAP BI, and SAP ERP.

Running Future Cities on Blockchain

Dan Wellers , Raimund Gross and Ulrich Scholl

Building on the Blockchain Framework

Some experts say these seemingly far-future speculations about the possibilities of combining technologies using blockchain are actually both inevitable and imminent:


Democratizing design and manufacturing by enabling individuals and small businesses to buy, sell, share, and digitally remix products affordably while protecting intellectual property rights.
Decentralizing warehousing and logistics by combining autonomous vehicles, 3D printers, and smart contracts to optimize delivery of products and materials, and even to create them on site as needed.
Distributing commerce by mixing virtual reality, 3D scanning and printing, self-driving vehicles, and artificial intelligence into immersive, personalized, on-demand shopping experiences that still protect buyers’ personal and proprietary data.

The City of the Future

Imagine that every agency, building, office, residence, and piece of infrastructure has an entry on a blockchain used as a city’s digital ledger. This “digital twin” could transform the delivery of city services.

For example:

  • Property owners could easily monetize assets by renting rooms, selling solar power back to the grid, and more.
  • Utilities could use customer data and AIs to make energy-saving recommendations, and smart contracts to automatically adjust power usage for greater efficiency.
  • Embedded sensors could sense problems (like a water main break) and alert an AI to send a technician with the right parts, tools, and training.
  • Autonomous vehicles could route themselves to open parking spaces or charging stations, and pay for services safely and automatically.
  • Cities could improve traffic monitoring and routing, saving commuters’ time and fuel while increasing productivity.

Every interaction would be transparent and verifiable, providing more data to analyze for future improvements.


Welcome to the Next Industrial Revolution

When exponential technologies intersect and combine, transformation happens on a massive scale. It’s time to start thinking through outcomes in a disciplined, proactive way to prepare for a future we’re only just beginning to imagine.

Download the executive brief Running Future Cities on Blockchain.


Read the full article Pulling Cities Into The Future With Blockchain

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Dan Wellers

About Dan Wellers

Dan Wellers is founder and leader of Digital Futures at SAP, a strategic insights and thought leadership discipline that explores how digital technologies drive exponential change in business and society.

Raimund Gross

About Raimund Gross

Raimund Gross is a solution architect and futurist at SAP Innovation Center Network, where he evaluates emerging technologies and trends to address the challenges of businesses arising from digitization. He is currently evaluating the impact of blockchain for SAP and our enterprise customers.

Ulrich Scholl

About Ulrich Scholl

Ulrich Scholl is Vice President of Industry Cloud and Custom Development at SAP. In this role, Ulrich discovers and implements best practices to help further the understanding and adoption of the SAP portfolio of industry cloud innovations.

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Are AI And Machine Learning Killing Analytics As We Know It?

Joerg Koesters

According to IDC, artificial intelligence (AI) is expected to become pervasive across customer journeys, supply networks, merchandizing, and marketing and commerce because it provides better insights to optimize retail execution. For example, in the next two years:

  • 40% of digital transformation initiatives will be supported by cognitive computing and AI capabilities to provide critical, on-time insights for new operating and monetization models.
  • 30% of major retailers will adopt a retail omnichannel commerce platform that integrates a data analytics layer that centrally orchestrates omnichannel capabilities.

One thing is clear: new analytic technologies are expected to radically change analytics – and retail – as we know them.

AI and machine learning defined in the context of retail

AI is defined broadly as the ability of computers to mimic human thinking and logic. Machine learning is a subset of AI that focuses on how computers can learn from data without being programmed through the use of algorithms that adapt to change; in other words, they can “learn” continuously in response to new data. We’re seeing these breakthroughs now because of massive improvements in hardware (for example, GPUs and multicore processing) that can handle Big Data volumes and run deep learning algorithms needed to analyze and learn from the data.

Ivano Ortis, vice president at IDC, recently shared with me how he believes, “Artificial intelligence will take analytics to the next level and will be the foundation for retail innovation, as reported by one out of every two retailers globally. AI enables scale, automation, and unprecedented precision and will drive customer experience innovation when applied to both hyper micro customer segmentation and contextual interaction.”

Given the capabilities of AI and machine learning, it’s easy to see how they can be powerful tools for retailers. Now computers can read and listen to data, understand and learn from it, and instantly and accurately recommend the next best action without having to be explicitly programmed. This is a boon for retailers seeking to accurately predict demand, anticipate customer behavior, and optimize and personalize customer experiences.

For example, it can be used to automate:

  • Personalized product recommendations based on data about each customer’s unique interests and buying propensity
  • The selection of additional upsell and cross-sell options that drive greater customer value
  • Chat bots that can drive intelligent and meaningful engagement with customers
  • Recommendations on additional services and offerings based on past and current buying data and customer data
  • Planogram analyses, which support in-store merchandizing by telling people what’s missing, comparing sales to shelf space, and accelerating shelf replenishment by automating reorders
  • Pricing engines used to make tailored, situational pricing decisions

Particularly in the United States, retailers are already able to collect large volumes of transaction-based and behavioral data from their customers. And as data volumes grow and processing power improves, machine learning becomes increasingly applicable in a wider range of retail areas to further optimize business processes and drive more impactful personalized and contextual consumer experiences and products.

The transformation of retail has already begun

The impacts of AI and machine learning are already being felt. For example:

  • Retailers are predicting demand with machine learning in combination with IoT technologies to optimize store businesses and relieve workforces
  • Advertisements are being personalized based on in-store camera detections and taking over semi-manual clienteling tasks of store employees
  • Retailers can monitor wait times in checkout lines to understand store traffic and merchandising effectiveness at the individual store level – and then tailor assortments and store layouts to maximize basket size, satisfaction, and sell through
  • Systems can now recognize and predict customer behavior and improve employee productivity by turning scheduled tasks into on-demand activities
  • Camera systems can detect the “fresh” status of perishable products before onsite employees can
  • Brick-and-mortar stores are automating operational tasks, such as setting shelf pricing, determining product assortments and mixes, and optimizing trade promotions
  • In-store apps can tell how long a customer has been in a certain aisle and deliver targeted offers and recommendations (via his or her mobile device) based on data about data about personal consumption histories and preferences

A recent McKinsey study provided examples that quantify the potential value of these technologies in transforming how retailers operate and compete. For example:

  • U.S. retailer supply chain operations that have adopted data and analytics have seen up to a 19% increase in operating margin over the last five years. Using data and analytics to improve merchandising, including pricing, assortment, and placement optimization, is leading to an additional 16% in operating margin improvement.
  • Personalizing advertising is one of the strongest use cases for machine learning today. Additional retail use cases with high potential include optimizing pricing, routing, and scheduling based on real-time data in travel and logistics, as well as optimizing merchandising strategies.

Exploiting the full value of data

Thin margins (especially in the grocery sector) and pressure from industry-leading early adopters such as Amazon and Walmart have created strong incentives to put customer data to work to improve everything from cross-selling additional products to reducing costs throughout the entire value chain. But McKinsey has assessed that the U.S. retail sector has realized only 30-40% of the potential margin improvements and productivity growth its analysts envisioned in 2011 – and a large share of the value of this growth has gone to consumers through lower prices. So thus far, only a fraction of the potential value from AI and machine learning has been realized.

According to Forbes, U.S. retailers have the potential to see a 60%+ increase in net margin and 0.5–1.0% annual productivity growth. But there are major barriers to realizing this value, including lack of analytical talent and siloed data within companies.

This is where machine learning and analytics kick in. AI and machine learning can help scale the repetitive analytics tasks required to drive leverage of the available data. When deployed on a companywide, real-time analytics platform, they can become the single source of truth that all enterprise functions rely on to make better decisions.

How will this change analytics?

So how will AI and machine learning change retail analytics? We expect that AI and machine learning will not kill analytics as we know it, but rather give it a new and even more impactful role in driving the future of retail. For example, we anticipate that:

  • Retailers will include machine learning algorithms as an additional factor in analyzing and  monitoring business outcomes in relation to machine learning algorithms
  • They will use AI and machine learning to sharpen analytic algorithms, detect more early warning signals, anticipate trends, and have accurate answers before competitors do
  • Analytics will happen in real time and act as the glue between all areas of the business
  • Analytics will increasingly focus on analyzing manufacturing machine behavior, not just business and consumer behavior

Ivano Ortis at IDC authored a recent report, “Why Retail Analytics are a Foundation for Retail Profits,” in which he provides further insights on this topic. He notes how retail leaders will use new kinds of analytics to drive greater profitability, further differentiate the customer experience, and compete more effectively, “In conclusion, commerce and technology will converge, enabling retailers to achieve short-term ROI objectives while discovering untapped demand. But implementing analytics will require coordination across key management roles and business processes up and down each retail organization. Early adopters are realizing demonstrably significant value from their initiatives – double-digit improvements in margins, same-store and e-commerce revenue, inventory positions and sell-through, and core marketing metrics. A huge opportunity awaits.”

So how do you see your retail business adopting advanced analytics like AI and machine learning? I encourage you to read IDC’s report in detail, as it provides valuable insights to help you invest in – and apply – new kinds of analytics that will be essential to profitable growth.

For more information, download IDC’s “Why Retail Analytics are a Foundation for Retail Profits.

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Joerg Koesters

About Joerg Koesters

Joerg Koesters is the Head of Retail Marketing and Communication at SAP. He is a Technology Marketing executive with 20 years of experience in Marketing, Sales and Consulting, Joerg has deep knowledge in retail and consumer products having worked both in the industry and in the technology sector.