Top 50 #BigData Twitter Influencers

Jen Cohen Crompton

#BigData – Twitter Influencers

We are aimed at becoming an authority on business innovation and want to help you identify the top influencers so you can follow the latest trends, news and opinions of these influencers in the field of Big Data. We’ll be publishing more lists on cloud computing, analytics and enterprise mobility in the coming weeks. In the meantime, here is the list of Top 50 Big Data Influencers on Twitter.

Note: Big Data Twitter influencers were determined based on tweeted topics, influence as measured by Klout, number of followers, and number of tweets. Below are the “top” influencers at this time based on the combination of factors.

@bigdata – Ben Lorica
Big Data, Analytics, Cloud Computing resources from Ben Lorica, Chief Data Scientist @OReillyMedia – San Francisco, CA ·
Klout – 49

@BigDataAnalysis – John Akred
Big Data R&D Lead at Accenture Technology Labs, Musician, Engineer, Technologist, Analog Audio and Vacuum Tube lover, Provocateur. These thoughts are my own. – Chicago / San Jose ·
Klout – 44

@imbigdata – Manish Bhatt
News and Updates about BigData, NoSQL, Hadoop, BI and other Big Data related technologies from BigData enthusiast Manish Bhatt
Klout – 24

@ibmbigdata – IBM Big Data
Talking about the challenges and approaches to handling Big Data. Primarily managed by @TheSocialPitt – ·
Klout – 37

@bobgourley – Bob Gourley
A CTO. Also find me @CTOvision and @CTOlist. National Security, Cyber Security, Enterprise IT and tech fun are key topics of interest.
Washington, DC ·
Klout – 50

@klintron – Klint Finley
I write for SiliconAngle. I also run Technoccult and build strange soundscapes.
Portland, OR ·
Klout – 45

@KristenNicole2 – Kristen Nicole
News editor at SiliconANGLE, writer at Appolicious, recovering social media addict –
Klout – 40

@dhinchcliffe – Dion Hinchcliffe
Business strategist, enterprise architect, keynote speaker, book author, blogger, & consultant on social business and next-gen enterprises. – Washington, D.C. ·
Klout – 52

@dmkimball05 – Dan Kimball
CMO at Kontagent, helping companies interpret patterns in social & mobile data to optimize their customer economics – San Francisco, CA ·
Klout – 18

@HadoopNews – John Ching
Latest news about Hadoop, NoSQL & BigData from John Ching, Big Data Guru, Consultant, and Evangelist for BI, Machine Learning, and Predictive Analytics
Klout – 44

@medriscoll – Michael E. Driscoll
CEO @Metamarkets. I ♥ Big Data, analytics, and visualization. – San Francisco, CA ·
Klout – 48

@peteskomoroch – Pete Skomoroch
My mission is to create intelligent systems that help people make better decisions. Principal Data Scientist @LinkedIn. Machine Learning, Hadoop, Big Data.
Silicon Valley ·
Klout – 56

@hmason – Hilary Mason
chief scientist @bitly. Machine learning; I ♥ data and cheeseburgers.
Klout – 56

@TimGasper – Tim Gasper
@Infochimps product manager, @Keepstream co-founder, techie, app addict, music writer/lover, #BigData, #Cloud – Austin, TX ·
Klout – 43

@flowingdata – Nathan Yau
Data, visualization, and statistics. Author of ‘Visualize This.’ Background in eating. – California ·
Klout – 58

@bradfordcross – Bradford Cross
design and data @prismatic – San Francisco ·
Klout – 44

@CityAge – City Age
We amplify good ideas through unique dialogues and their associated campaigns. We’re now organizing The Data Effect, amid other projects. – Vancouver, BC ·
Klout – 32

@BigDataExpo – Big Data Expo
Join 30,000+ Delegates in 2012 at World’s Largest #Cloud Events! New York [June 11-14] Silicon Valley [Nov 5-8] Register & Save! ▸ – New York/Silicon Valley ·
Klout – 34

@acmurthy – Arun C Murthy
Founder & Architect, Hortonworks. VP, Apache Hadoop, Apache Software Foundation i.e. Chair, Hadoop PMC. Moving Hadoop forward since day one, since 2006. – online ·
Klout – 43

@infoarbitrage – Roger Ehrenberg
Big Data VC at IA Ventures. Data junkie. Quant dude. Baseball coach. – ÜT: 40.76136,-73.980129 ·
Klout – 56

@jeffreyfkelly – Jeff Kelly
I am an Industry Analyst covering Big Data and Business Analytics at The Wikibon Project and SiliconANGLE – Boston ·
Klout – 45

@timoreilly – Tim O’Reilly
Founder and CEO, O’Reilly Media. Watching the alpha geeks, sharing their stories, helping the future unfold. – Sebastopol, CA ·
Klout – 69

@digiphile – Alex Howard
Gov 2.0 @Radar Correspondent, @OReillyMedia: Intrigued by technological change, taken with ideas, cooking, the outdoors, books, dogs and media – Washington, DC ·
Klout – 74

@band – William L. Anderson
Sociotechnical systems developer, open access advocate, and editor at CODATA Data Science Journal – austin texas
Klout – N/A

@HenryR – Henry Robinson
Engineer @ Cloudera, Zookeeper committer / PMC member, professional dilettante – San Francisco, CA ·
Klout – 43

@furrier – John Furrier
Silicon Valley entrepreneur Founder SiliconANGLE Network. Inventing New Things, Blogging, Tweeting Social Media – Palo Alto, California ·
Klout – 49

@mikeolson – Mike Olson
Cloudera CEO – Berkeley, California ·
Klout – 48

@davenielsen – Dave Nielsen
Co-founder of CloudCamp & Silicon Valley Cloud Center – Mountain View, Ca ·
Klout – 44

@znmeb – M. Edward Borasky
Media Inactivist, Thought Follower, Sit-Down Comic, Former Boy Genius, Real-Time Data Journalism Researcher, Open Source Appliance Maker And Mathematician – Portland, OR ·
Klout – N/A

@rizzn – Mark ‘Rizzn’ Hopkins
I’m the editor in chief for SiliconANGLE and the purveyor of fine content at ·
Klout – N/A

@edd – Edd Dumbill
Telling the story of our future, where technology is headed, and what we need to know now. O’Reilly Strata and OSCON program chair. Incurably curious – California ·
Klout – 57

@kellan – Kellan E
Technological solutions for social problems. CTO, Etsy. (if you follow me, consider introducing yourself with @kellan message) #47 – Brooklyn, NY ·
Klout – 58

@mikeloukides – Mike Loukides
VP Content Strategy, O’Reilly Media, pianist, ham radio op usually in Connecticut
Klout – 54

@laurelatoreilly – Laurel Ruma
Director of Talent (speaker and author relations) at O’Reilly Media. Homebrewer, foodie, farmer in the city – Cambridge, MA ·
Klout – 45

@neilraden – Neil Raden
VP/Principal Analyst,Constellation Research;Analytics, BigData, DecisionManagement. Author/Writer,Blogger,Speaker.Husband/(Grand)Father
Santa Fe, NM ·
Klout – 53

@greenplum – Greenplum
Greenplum, a division of EMC is driving the future of big data analytics.
San Mateo, California ·
Klout – 48

@squarecog – Dmitriy Ryaboy
Analytics Tech Lead at Twitter. Apache Pig committer.
San Francisco
Klout – 48

@BigData_paulz – Paul Zikopoulos
Director of Technical Professionals for IBM’s Information Management, BigData, and Competitive Database divisions. Published 15 books and over 350 articles.
Klout – 38

@moorejh – Jason H. Moore
Third century professor, Director of the Institute for Quantitative Biomedical Sciences at Dartmouth College, Editor-in-Chief of BioData Mining – Lebanon, NH, USA ·
Klout – 47

@GilPress – Gil Press
I launched the #BigData conversation; Writing, research, marketing services; &
Klout – 41

@ToddeNet – Todd E. Johnson PhD
Educational Access and Academic Sustainability • STEM •Data Informed Decisions (DID) • Always Dreaming and Learning(ADL)….Tweets here are my own!!
Olympia, WA ·
Klout – 27

@digimindci – Orlaith Finnegan
Provider of Competitive Intelligence & Market Intelligence Software. Online Reputation, Real-time Web Monitoring and Analysis, Social Media Monitoring.
Boston, Paris, Singapore ·
Klout – 36

@SmartDataCo – Smart Data Collective
Expert writers on analytics, BI and big data brought to you by the folks at Social Media ·
Klout – 42

@al3xandru – Alex Popescu
NOSQL Dreamer, Software architect, Founder/CTO, Web aficionado, Speaker, iPhone: 44.441881,26.139629 ·
Klout – 49

@marksmithvr – Mark Smith
CEO & Chief Research Officer at Ventana Research – & follow

@ventanaresearch – San Ramon, CA ·
Klout – 51

@BernardMarr – Bernard Marr
Leading global authority and best-selling author on delivering, managing and measuring enterprise performance – London
Klout – 50

@johnlmyers44 – John L Myers
Senior Analyst for EMA Business Intelligence and Data Warehousing practice specializing in telecom analytics and business process management – Boulder, Colorado ·
Klout – 54

@leenarao – Leena Rao
Tech Writer (tech Crunch), dog-lover, foodie, quirky – Chicago
Klout – 68

@HKotadia – Harish Kotadia Ph.D
Big Data, Predictive Analytics, Social CRM and CRM. Work for Infosys (NASDAQ: INFY). Views and opinion expressed are my own. – Dallas, Texas, USA ·
Klout – 42

@chuckhollis – Chuck Hollis
technologist, marketeer, blogger and musician working for EMC.
Holliston, MA ·
Klout – 49

Disclosure: I am being compensated by SAP to produce a series of posts on the innovation topics covered on this site. The opinions reflected here are my own.


About Jen Cohen Crompton

Jen Cohen Crompton is a SAP Blogging Correspondent reporting on big data, cloud computing, enterprise mobility, analytics, sports and tech, and anything else innovation-related. When she's not blogging, she can be caught marketing, using social media and/or presenting at conferences around the world. Disclosure: Jen is being compensated by SAP to produce a series of articles on the innovation topics covered on this site. The opinions reflected here are her own.

The Future Of Wholesale Distribution: Using Data To Drive Action

Werner Baumbach

Recently I was asked if I thought that wholesale distribution would be any different 30 years from now. To me, the answer is so obvious that I took me a few seconds to respond.

Instead of polishing the crystal ball, let’s look back 30 years and think about how much our world has changed since 1986.

Back in the second half of the 1980’s, most of my music collection was still on tape, and the Internet was still not available to most of us. When I had to write a paper (yes, I was still in high school back then), I would go to the library and hope to find a book or two on my subject.

My PC had a hard drive that most modern cameras would fill with fewer than 5 shots. Drones were science fiction, globalization was not part of my vocabulary, and shopping internationally meant bringing something home from vacation.

I think we will all agree that the world has changed dramatically since then, and so has the way we do business. Technology has gone through through revolutionary cycles, and most of it is now based on vast amounts of data.

A 2015 study revealed that 90% of all data created has been released in the last two years. With the emergence of all kinds of intelligent tools and gadgets, it is not surprising that the same study predicts continuous data volume growth rates north of 40%.

Looking at some social media posts, I will admit that much of that data has limited value. But on a less judgmental level, for the first time in history, the problem is not that we have too little data. The challenge now is to comprehend the vast amount of information available, create insight, and act based on that knowledge.

The wholesale industry has traditionally had a very detailed picture of its customers, especially on the sales side. Our industry benefits from maintaining close relationships with customers. In our new global and virtual world, these relationships are becoming more complex – a risk for future success, but more importantly, a vast opportunity.

Customers do have a simple choice: to take their business elsewhere. But we need to understand how to best meet our customers’ needs, and to be truly successful, we must find the best approach for individuals or for groups of customers with similar interests.

Already we are seeing wholesale companies use sentiment analysis to optimize their assortments. Items that receive bad feedback can be eliminated to avoid unhappy customers. In the next step, predictive modelling can be used to increase efficiency for new product introductions and monitor success. Customer segmentation will need to significantly evolve to factor in additional aspects and insight and deliver personalized offers and value. And we will need to find ways to stay consistently engaged with our customers across all channels.

The key to success is being able to compile all information across different sources—both virtual and direct—and create an instant picture that can be used to best service the customer in the moment. Just because a customer was looking for a printer a week ago, for example, doesn’t necessarily mean they are still interested in that purchase today.

Going back to the initial question: I am convinced that in 2046, the world—and the wholesale distribution industry—will look significantly different than it does today. And while my crystal ball is a bit murky on how much automation, robotics, drones, and virtual reality the future will include, it is fairly clear on one point: Everything will be based on data and the ability to use it to drive informed action and activities.

For more insight on digital transformation in wholesale, see Winning The Gold Medal In Wholesale Distribution.


About Werner Baumbach

Werner Baumbach is a solution manager for the SAP Global Wholesale Distribution Industry Business Unit at SAP. Werner has over 20 years of experience in different roles in software and consumer industries. He has a passion for innovative and future technologies and solutions in Wholesale and Retail.

Integrating Data Labs And Factories To Operationalize Advanced Analytics

Carsten Bange

Although explorative business intelligence requires different processes and approaches compared to traditional BI, it still has to be integrated with existing IT and BI structures to ensure analytics solutions are operationalized. Data labs design new analytics solutions and factories operationalize these solutions, and while they differ in terms of goals and methods, they can also share resources and approaches to foster integration.

Challenges for advanced and predictive analytics projects

According to the BARC Survey “Advanced & Predictive Analytics,” the most common problems that obstruct advanced analytics projects are:

  • a lack of resources in business and IT;
  • difficulty quantifying the business value of advanced analytics; and
  • poor understanding of a data-driven business culture.
factors inhibit your Advanced & Predictive Analytics

Figure 1: Which factors inhibit your Advanced & Predictive Analytics projects? (n=89) Source: BARC Survey “Advanced & Predictive Analytics” (n=200)

All of these factors create challenges when applying advanced analytics and putting analytics solutions into practice by turning them into reliable products and services. To understand why this is a challenge, we will look at how advanced analytics projects are conducted and how data labs and factories operate.

Conducting analytics projects

The “analytical cycle” (Figure 2) is a standard procedure for managing advanced analytics projects. It can be broken down into the following steps:

  • A problem definition provides clearly documented goals and serves as reference for the entire project.
  • Data understanding, data selection, and data preparation create a solid database for the task at hand.
  • Modeling & model validation aim to identify a suitable modeling approach. This may require various iterations with regard to data preparation.
  • Results evaluation is important for quality management. All prior steps are reviewed and checked to determine whether the project meets the business objectives, then a decision about utilization of the results is made. The choices are no utilization (i.e., cancellation or start over), onetime utilization, or operationalization.
  • Operationalization means deploying the model and integrating it into relevant IT systems to improve decisions, products, or services.
  • In the continuous model evaluation, the impact of advanced analytics solutions is measured. Model adaptations are carried out in response to changing conditions. Since this also implies checking the business assumptions and data sources, the cycle starts from the beginning.

Data labs and factories

Traditional BI tasks have been standardized and streamlined for many years in many organizations. A defined output of reports, dashboards, or data for analysis is provided to users in a defined quality and a defined output format for the least possible cost. This approach resembles a factory. Factories focus on high quality and often on high volume throughput, which is achieved by standardization, automation, and stable processes. Traditional BI systems correspond to systems of record that are best run in a factory approach that, organizationally, is often part of the IT department or organized in a cross-departmental BI competency center (BICCs).

The new demand for exploring data with advanced and predictive analytics does not usually suit this approach. Therefore, data labs are created that, like a laboratory in a research and development organization, provide for agile experimentation and discovery. Trial and error, as a typical approach to finding innovative solutions, is key. Explorative BI with advanced and predictive analytics in data labs or analytics labs corresponds to systems of innovation. The labs use agile methods for developing prototypes. Analytical solutions are often quickly discarded when they are used for discovery purposes, do not show promising results, or only provide a benchmark for further solutions. This often makes the value-add or return-on-investment hard to quantify, especially if it has to be defined upfront. Funding for these initiatives comes from innovation budgets.

While often operating in isolation, the factory and the lab approaches must work together when it comes to integrating analytics solutions into operational systems in a stable and sustainable way. The analytical cycle shows which tasks are assigned to which approach (see Figure 2).

Labs focus on the stages of problem definition, data understanding and preparation, modeling, and results evaluation, which may feed back to problem definition. Usually this cycle is repeated until a viable solution is found.

But the goal of advanced analytics initiatives is to operationalize analytical discoveries. Model deployment and integration in productive IT environments are tasks for factories. Here, the factory approach for implementing and running a solution with a focus on data governance, reliability, maintenance, scalability, and reusability is important.

The handover from evaluating the results of a prototype in a lab to the factory for operationalization is the key aspect to consider when setting up advanced analytics initiatives. Whether this is working or not will make or break any analytics strategy.

different tasks for labs and factories
Figure 2: The analytical cycle, with different tasks for labs and factories

Common needs and resources

Despite their differing focus, labs and factories have commonalities. Labs require data engineers, often found in BICCs or in IT departments. They are important in the data understanding, data selection, and data preparation phases, which are the most time-consuming steps in analytics projects. On the other hand, do IT departments need data scientists for processes such as continuously checking model quality, model retraining, model adaptations, and support for users? Data scientists can also be useful when checking data quality. “Data artists” that are familiar with the visual representation of results are part of many BI teams but are also necessary for data labs that need to communicate complicated results to lines of business. Sometimes BI managers become BI and analytics managers, overlooking both processes and ensuring that labs and factories are integrated. Technology-wise, labs and factories are integrated when models or model results generated by explorative BI are displayed in BI systems or used in operational systems when processes are automated.


Labs and factories focus on different tasks in the analytical cycle, but both share a common goal – to turn insights from data into products and services. To do this, good communication between labs and factories is crucial, and this can be enhanced by sharing human resources between labs and factories.

Learn more: read other blogs in the “Enabling the Data-Driven Enterprise” series or review the BARC Survey “Advanced & Predictive Analytics.”

This blog was co-authored by Dr. Sebastian Derwisch, data scientist at the Business Application Research Center (BARC). Sebastian holds a PhD in economics and has extensive experience advising companies in the areas of use-case identification for data analytics, tool selection for advanced analytics, and the organization of data science teams.


Carsten Bange

About Carsten Bange

Dr. Carsten Bange is founder and managing director of the Business Application Research Center (BARC), an IT market analysis and consulting group he founded in 1999 and later merged with Le CXP and PAC to form CXP Group, the largest European IT analyst group. Carsten holds a PhD in management information systems, is a frequent speaker at IT conferences and seminars and has served as an analyst and management consultant on business intelligence, data management and digitalization strategy, organization, architecture and technology selection for over 20 years. He can be reached at

From E-Business to V-Business

Josh Waddell, Pascal Lessard, Lori Mitchell-Keller, and Fawn Fitter

Some moments are so instantly, indelibly etched into pop culture that they shape the way we think for years to come. For virtual reality (VR), that moment may have been the scene in the 1999 blockbuster The Matrix when the Keanu Reeves character Neo learns that his entire life has been a computer-generated simulation so fully realized that he could have lived it out never knowing that he was actually an inert body in an isolation tank. Ever since, that has set the benchmark for VR: as a digital experience that seems completely, convincingly real.

Today, no one is going to be unaware, Matrix-like, that they’re wearing an Oculus Rift or a Google Cardboard headset, but the virtual worlds already available to us are catching up to what we’ve imagined they could be at a startling rate. It’s been hard to miss all the Pokémon Go players bumping into one another on the street as they chased animated characters rendered in augmented reality (AR), which overlays and even blends digital artifacts seamlessly with the actual environment around us.

Believe the Hype

For all the justifiable hype about the exploding consumer market for VR and, to a lesser extent, AR, there’s surprisingly little discussion of their latent business value—and that’s a blind spot that companies and CIOs can’t afford to have. It hasn’t been that long since consumer demand for the iPhone and iPad forced companies, grumbling all the way, into finding business cases for them.

sap_Q316_digital_double_feature1_images1If digitally enhanced reality generates even half as much consumer enthusiasm as smartphones and tablets, you can expect to see a new wave of consumerization of IT as employees who have embraced VR and AR at home insist on bringing it to the workplace. This wave of consumerization could have an even greater impact than the last one. Rather than risk being blindsided for a second time, organizations would be well advised to take a proactive approach and be ready with potential business uses for VR and AR technologies by the time they invade the enterprise.

They don’t have much time to get started.

The two technologies are already making inroads in fields as diverse as medicine, warehouse operations, and retail. And make no mistake: the possibilities are breathtaking. VR can bring human eyes to locations that are difficult, dangerous, or physically impossible for the human body, while AR can deliver vast amounts of contextual information and guidance at the precise time and place they’re needed.

As consumer adoption and acceptance drives down costs, enterprise use cases for VR and AR will blossom. In fact, these technologies could potentially revolutionize the way companies communicate, manage employees, and digitize and automate operations. Yet revolution is rarely bloodless. The impact will probably alter many aspects of the workplace that we currently take for granted, and we need to think through the implications of those changes.

sap_Q316_digital_double_feature1_images2Digital Realities, Defined

VR and AR are related, but they’re not so much siblings as cousins. VR is immersive. It creates a fully realized digital environment that users experience through goggles or screens (and sometimes additional equipment that provides physical feedback) that make them feel like they’re surrounded by and interacting entirely within this created world.

AR, by contrast, is additive. It displays text or images in glasses, on a window or windshield, or inside a mirror, but the user is still aware of and interacting with reality. There is also an emerging hybrid called “mixed reality,” which is essentially AR with VR-quality digital elements, that superimposes holographic images on reality so convincingly that trying to touch them is the only way to be sure they aren’t actually there.

Although VR is a hot topic, especially in the consumer gaming world, AR has far more enterprise use cases, and several enterprise apps are already in production. In fact, industry analyst Digi-Capital forecasts that while VR companies will generate US$30 billion in revenue by 2020, AR companies will generate $120 billion, or four times as much.

Both numbers are enormous, especially given how new the VR/AR market is. As recently as 2014, it barely existed, and almost nothing available was appropriate for enterprise users. What’s more, the market is evolving so quickly that standards and industry leaders have yet to emerge. There’s no guarantee that early market entrants like Facebook’s Oculus Rift, Samsung’s Gear VR, and HTC’s Vive will continue to exist, never mind set enduring benchmarks.

Nonetheless, it’s already clear that these technologies will have a major impact on both internal and customer-facing business. They will make customer service more accurate, personalized, and relevant. They will reduce human risk and enhance public safety. They will streamline operations and smash physical boundaries. And that’s just the beginning.

Cleveland Clinic: Healing from the Next Room

Medicine is already testing the limits of learning with VR and AR.

sap_q316_digital_double_feature1_imageseightThe most potentially disruptive operational use of VR and AR could be in education and training. With VR, students can be immersed in any environment, from medieval architecture to molecular biology, in classroom groups or on demand, to better understand what they’re studying. And no industry is pursuing this with more enthusiasm than medicine. Even though Google Glass hasn’t been widely adopted elsewhere, for example, it’s been a big success story in the medical world.

Pamela Davis, MD, senior vice president for medical affairs at Case Western Reserve University in Cleveland, Ohio, is one of the leading proponents of medical education using VR and AR. She’s the dean of the university’s medical school, which is working with Cleveland Clinic to develop the Microsoft HoloLens “mixed reality” device for medical education and training, turning MRIs and other conventional 2D medical images into 3D images that can be projected at the site of a procedure for training and guidance during surgery. “As you push a catheter into the heart or place a deep brain stimulation electrode, you can see where you want to be and guide your actions by watching the hologram,” Davis explains.

The HoloLens can also be programmed as a “lead” device that transmits those images and live video to other “learner” devices, allowing the person wearing the lead device to provide oversight and input. This will enable a single doctor to demonstrate a delicate procedure up-close to multiple students at once, or do patient examinations remotely in an emergency or epidemic.

Davis herself was convinced of the technology’s broader potential during a demonstration in which she put on a learner HoloLens and rewired a light switch, something decidedly outside her expertise, under the guidance of an engineer wearing a lead HoloLens in the next room. In the near future, she predicts, it will help people perform surgery and other sensitive, detailed tasks not just from the next room, but from the next state or country.

Customer Experience: From E-Commerce to V-Commerce

Consumers are already getting used to sap_Q316_digital_double_feature1_images3thinking of VR and AR in the context of entertainment. Companies interested in the technologies should be thinking about how they might engage consumers as part of the buying experience.

Because the technologies deliver more information and a better shopping experience with less effort, e-commerce is going to give rise to v-commerce, where people research, interact with, and share products in VR and AR before they order them online or go to a store to make a purchase.

Online eyewear retailers already allow people to “try on” glasses virtually and share the images with friends to get their feedback, but that’s rudimentary compared to what’s emerging.

Mirrors as Personal Shoppers

Clothing stores from high-end boutiques to low-end fashion chains are experimenting with AR mirrors that take the shopper’s measurements and recommend outfits, showing what items look like without requiring the customer to undress.

Instant Designer Shows

Luxury design house Dior uses Oculus Rift VR goggles to let its well-heeled customers experience a runway show without flying to Paris.

Custom Shopping Malls

British designer Allison Crank has created an experimental VR shopping mall. As people walk through it, they encounter virtual people (and the occasional zoo animal) and shop in stores stocked only with items that users are most likely to buy, based on past purchase information and demographic data.

A New Perspective

IKEA’s AR application lets shoppers envisage a piece of furniture in the room they plan to use it in. They can look at products from the point of view of a specific height—useful for especially tall or short customers looking for comfortable furniture or for parents trying to design rooms that are safe for a toddler or a young child.

Painless Do-it-Yourself Instructions

Instead of forcing customers to puzzle over a diagram or watch an online video, companies will be able to offer customers detailed VR or AR demonstrations that show how to assemble and disassemble products for use, cleaning, and storage.

sap_Q316_digital_double_feature1_images4Operations and Management: Revealing the Details

The customer-facing benefits of VR and AR are inarguably flashy, but it’s in internal business use that these technologies promise to shine brightest: boosting efficiency and productivity, eliminating previously unavoidable risks, and literally giving employers and managers new ways to look at information and operations. The following examples aren’t blue-sky cases; experts say they’re promising, realistic, and just around the corner.

Real-Time Guidance

A combination of AR glasses and audio essentially creates a user-specific, contextually relevant guidance system that confirms that wearers are in the right place, looking at the right thing, and taking the right action. This technology could benefit almost any employee who is not working at a desk: walking field service reps through repair procedures, guiding miners to the best escape route in an emergency, or optimizing home health aides’ driving routes and giving them up-to-date instructions and health data when they arrive at each patient’s home.

Linking to the Hidden

AR technology will be able to display any type of information the wearer needs to know. Linked to facial identification software, it could help police officers identify suspects or missing persons in real time. Used to visualize thermal gradients, chemical signatures, radioactivity, and other things that are invisible to the naked eye, it could help researchers refine their experiments or let insurance claims assessors spot arson. Similarly, VR will allow users to create and manipulate detailed three-dimensional models of everything from molecules to large machinery so that they can examine, explore, and change them.

Reducing the Human Risk

VR will allow users to perform high-risk jobs while reducing their need to be in harm’s way. The users will be able to operate equipment remotely while seeing exactly what they would if they were there, a use case that is ideal for industries like mining, firefighting, search and rescue, and toxic site cleanup. While VR won’t necessarily eliminate the need for humans to perform these high-risk jobs, it will improve their safety, and it will allow companies to pursue new opportunities in situations that remain too dangerous for humans.

Reducing the Commercial Risk

sap_Q316_digital_double_feature1_images5VR can also reduce an entirely different type of operational risk: that of introducing new products and services. Manufacturers can let designers or even customers “test” a product, gather their feedback, and tweak the design accordingly before the product ever goes into production. Indeed, auto manufacturer Ford has already created a VR Immersion Lab for its engineers, which, among other things, helped them redesign the interior of the 2015 Ford Mustang to make the dashboard and windshield wipers more user-friendly, according to Fortune. In addition to improving customer experience, this application of VR is likely to accelerate product development and shorten time to market.

Similarly, retailers can use VR to create and test branch or franchise location designs on the fly to optimize traffic flow, product display, the accessibility of products, and even decor. Instead of building models or concept stores, a designer will be able to create the store design with VR, do a virtual walkthrough with executives, and adjust it in real time until it achieves the desired effect.

Seeing in Tongues

At some point, we will see an AR app that can translate written language in near-real time, which will dramatically streamline global business communications. Mobile apps already exist to do this in certain languages, so it’s just a matter of time before we can slip on glasses that let us read menus, signs, agendas, and documents in our native tongue.

Decide with the Eye

More dramatically, AR project management software will be able to deliver real-time data at a literal glance. On a construction site, for example, simply scanning the area could trigger data about real-time costs, supply inventories, planned versus actual spending, employee and equipment scheduling, and more. By linking to construction workers’ own AR glasses that provide information about what to know and do at any given location and time, managers could also evaluate and adjust workloads.

Squeeze Distance

Farther in the future, VR and AR will create true telepresence, enhancing collaboration and potentially replacing in-person meetings. Users could transmit AR holograms of themselves to someone else’s office, allowing them to be seen as if they were in the room. We could have VR workspaces with high-fidelity avatars that transmit characteristic facial expressions and gestures. Companies could show off a virtual product in a virtual room with virtual coworkers, on demand.

Reduce Carbon Footprint

If nothing else, true telepresence could practically eliminate business travel costs. More critically, though, in an era of rising temperatures and shrinking resources, the ability to create and view virtual people and objects rather than manufacturing and transporting physical artifacts also conserves materials and reduces the use of fossil fuel.

Employees: Under Observation

The strength of digitally enhanced reality—and AR in particular—is its ability to determine a user’s context and deliver relevant information accordingly. This makes it valuable for monitoring and managing employee behavior and performance. Employees could, for example, use the location and time data recorded by AR glasses to prove that they were (or weren’t) in a particular place at a particular time. The same glasses could provide them with heads-up guided navigation, alert employers that they’re due for a legally mandated break, verify that they completed an assigned task, and confirm hours worked without requiring them to fill out a timesheet.

However, even as these capabilities improve data governance and help manage productivity, they also raise critical issues of privacy and autonomy (see The Norms of Virtual Behavior). If you’re an employee using VR or AR technology, and if your company is leveraging it to monitor your performance, who owns that information? Who’s allowed to use it, and for what purposes? These are still open legal questions for these technologies.

Another unsettled—and unsettling—question is how far employers can use these technologies to direct employees’ work. While employers have the right to tell employees how to do their jobs, autonomy is a key component of workplace satisfaction. The extent to which employees are required to let a pair of AR glasses govern their actions could have a direct impact on hiring and retention.

Finally, these technologies could be one more step toward greater automation. A warehouse-picking AR application that guides pickers to the appropriate product faster makes them more productive and saves them from having to memorize hundreds or even thousands of SKUs. But the same technology that can guide a person will also be able to guide a semiautonomous robot.

The Norms of Virtual Behavior

VR and AR could disrupt our social norms and take identity hacking to a new level.

The future of AR and VR isn’t without its hazards. We’ve all witnessed how distracting and even dangerous smartphones can be, but at least people have to pull a phone out of a pocket before getting lost in the screen. What happens when the distraction is sitting on their faces?

This technology is going to affect how we interact, both in the workplace and out of it. The annoyance verging on rage that met the first people wearing Google Glass devices in public proves that we’re going to need to evolve new social norms. We’ll need to signal how engaged we are with what’s right in front of us when we’re wearing AR glasses, what we’re doing with the glasses while we interact, or whether we’re paying attention at all.

More sinister possibilities will present themselves down the line. How do you protect sensitive data from being accessed by unauthorized or “shadow” VR/AR devices? How do you prove you’re the one operating your avatar in a virtual meeting? How do you know that the person across from you is who they say they are and not a competitor or industrial spy who’s stolen a trusted avatar? How do you keep someone from hacking your VR or AR equipment to send you faulty data, flood your field of vision with disturbing images, or even direct you into physical danger?

As the technology gets more sophisticated, VR and AR vendors will have to start addressing these issues.

Technical Challenges

To realize the full business value of VR and AR, companies will need to tackle certain technical challenges. To be precise, they’ll have to wait for the vendors to take them on, because the market is still so new that standards and practices are far from mature.

sap_Q316_digital_double_feature1_images6For one thing, successful implementation requires devices (smartphones, tablets, and glasses, for now) that are capable of delivering, augmenting, and overlaying information in a meaningful way. Only in the last year or so has the available hardware progressed beyond problems like overheating with demand, too-small screens, low-resolution cameras, insufficient memory, and underpowered batteries. While hardware is improving, so many vendors have emerged that companies have a hard time choosing among their many options.
The proliferation of devices has also increased software complexity. For enterprise VR and AR to take off, vendors need to create software that can run on the maximum number of devices with minimal modifications. Otherwise, companies are limited to software based on what it’s capable of doing on their hardware of choice, rather than software that meets their company’s needs.

The lack of standards only adds to the confusion. Porting data to VR or AR systems is different from mobilizing front-end or even back-end systems, because it requires users to enter, display, and interact with data in new ways. For devices like AR glasses that don’t use a keyboard or touch screen, vendors must determine how to enter data (voice recognition? eye tracking? image recognition?), how to display it legibly in any given environment, and whether to develop their own user interface tools or work with a third party.

Finally, delivering convincing digital enhancements to reality demands such vast amounts of data that many networks simply can’t accommodate it. Much as videoconferencing didn’t truly take off until high-speed broadband became widely available, VR and AR adoption will lag until a zero-latency infrastructure exists to
support them.

sap_Q316_digital_double_feature1_images7Coming Soon to a Face Near You

For all that VR and AR solutions have improved dramatically in a short time, they’re still primarily supplemental to existing systems, and not just because the software is still evolving. Wearables still have such limited processing power, memory, and battery life that they can handle only a small amount of information. That said, hardware is catching up quickly (see The Supporting Cast).

The Supporting Cast

VR and AR would still be science fiction if it weren’t for these supporting technologies.

The latest developments in VR and AR technologies wouldn’t be possible without other breakthroughs that bring things once considered science fiction squarely into the realm of science fact:

  • Advanced semiconductor designs pack more processing power into less space.
  • Microdisplays fit more information onto smaller screens.
  • New power storage technologies extend battery life while shrinking battery size.
  • Development tools for low-latency, high-resolution image rendering and improved 3D-graphics displays make digital artifacts more realistic and detailed.
  • Omnidirectional cameras that can record in 360 degrees simultaneously create fully immersive environments.
  • Plummeting prices for accelerometers lower the cost of VR devices.

Companies in the emerging VR/AR industry are encouraging the makers of smartglasses and safety glasses to work together to create ergonomic smartglasses that deliver information in a nondistracting way and that are also comfortable to wear for an eight-hour shift.

The argument in favor of VR and AR for business is so powerful that once vendors solve the obvious hardware problems, experts predict that existing enterprise mobile apps will quickly start to include VR or AR components, while new apps will emerge to satisfy as yet unmet needs.

In other words, it’s time to start thinking about how your company might put these technologies to use—and how to do so in a way that minimizes concerns about data privacy, corporate security, and employee comfort. Because digitally enhanced reality is coming tomorrow, so business needs to start planning for it today. D!

Read more thought provoking articles in the latest issue of the Digitalist Magazine, Executive Quarterly.



Make No Mistake – Social Media is Massively Affecting The Sales Process (And Here's Why)

Malcolm Hamilton

These days, if your business strategy isn’t aligned with your social media plan, you are needlessly making both your sales and marketing teams work overtime. This can end up costing your company HUGE amounts of money. One extensive study shows that 60% to 80% of today’s B2B technology and vendor selection processes are conducted in the digital world, which often are invisible to your company and your sales teams. This is why it is critical that your company brand and value proposition are highly visible to these invisible buyers across as many social media platforms as possible.

Studies show that B2B companies that have effective sales and marketing alignment are:

  • Outgrowing their peer group competitors by 5.4%
  • 38% better at closing proposals
  • Lowering their churn rates by 36%

The trouble is that it can be hard to get sales and marketing on the same page because the nature of their work is so different. It’s no one’s fault, but sales needs to rely on marketing to do more outbound lead generation, advertising, and outreach, and marketing needs sales to quickly follow up on marketing-generated leads, hand back stalled leads for nurture tailored to each buyer’s journey, and close deals. There has rarely been much love between sales and marketing departments, because each one often thinks the other one is either slacking off or simply not adding value.

The fact is digital & social marketing is at the heart of sales, the lines between sales and marketing have been steadily blurring, and social media and digital marketing are at the heart of this intersection. Social sales means that marketing has to drive awareness in order to help develop a company’s brand and the brand’s value proposition, a process that relies extra heavily on the marketing department. Let’s take a closer look at how marketing can offer sales a lot of help in today’s world of social media.

How marketing can help sales win more deals

Salespeople need to lean on the marketing team for a variety of things in order to make sure that they are using social media in the best ways. For example, marketing can:

  • Help sales teams come up with social updates that foster engagement with new clients and actually work
  • Generate tailored and compelling content that will move customer prospects that are frozen in the sales pipeline
  • Lend a hand with creating content that their prospects will value and respond to
  • Figure out a way to make the company really stand out from the crowd on social media
  • Listen to the ideas that sales team members have and put them to work
  • Help sales team members position themselves as thought leaders in their target industry sectors
  • Help keep all social media messaging on-brand across platforms
  • Use analytics to track performance across platforms – salespeople love to see results

So how does marketing help accomplish these goals? Here are two tools that can help sales and marketing teams stay on top of their social media game.

  • GaggleAmp enables companies to aggregate social media updates and quickly and easily send notifications out to team members that they can share on various social media platforms with just a couple of clicks. The app can even keep track of how many shares a post is getting and then let you compare certain posts with others to see which is performing better. It’s a pretty cool way to keep sales and social media interested in the same game.
  • helps sales and social media intermingle by leveraging the power of your teams to send out consistent, effective posts. It breaks down the interactions that are happening on different networks and with different posts and helps you understand which ones your audience is engaging with most so you can refine your marketing strategy.

How sales can help marketing do an even better job

Sales can also help marketing move its goals along when it comes to success on social media. Salespeople can:

  • Communicate in a clear manner so marketing understands what they need
  • Openly share numbers and forecasts so marketing has a better grasp of how you are succeeding and where you’re falling short
  • Offer tips for keeping messaging more on-point
  • Provide regular feedback into how lead generation and follow-up are going
  • Hand stalled leads back to marketing for further nurture
  • Hang back and let them work their magic
  • Provide direction to marketing on the current buying drivers for prospects and target businesses

How social media marketing and sales can work together

There are some definite steps that these two teams can take to make sure they are working together in the most effective way. Here are a few tips for helping the teams stay on the same page:

  • Regular meetings: It sounds simple enough, but actually getting sales and marketing teams together to talk regularly can work wonders for both. It’s incredibly important for keeping your social media game on point and helps to resolve any miscommunication or issues that might be happening on either side. Research shows that businesses that are sales and marketing aligned grow five percent to 10% faster than their peer group.
  • Content process: Sales reps engage with prospects all of the time, but to be effective they need to know what will get prospects excited. Teams can stay in the loop by making sure there is a process in place to create content for social media by gathering info at weekly brainstorming sessions, using shared docs to collect ideas, and coordinating an editorial calendar so everyone knows what content you are putting out there and when.
  • Get schedules in sync: Social media is a great way to put new offers and content out there, but the sales team needs to stay up-to-date with promotions so they can respond to leads in the right way. Keep promotions on a shared calendar, and keep sales teams looped in on whatever offers your company is putting out there. It’s also helpful for sales staff to have talking points on the offer and its value to the customer.
  • Listen: At the end of the day, teams just need to listen to each other to get better at their jobs. It’s a great way to learn about what customers really want and need and to get ideas for future social media content creation.

The bottom line is that social media is a huge part of how sales teams are drumming up high-quality leads today, so it’s more important than ever for marketing and sales teams to stay aligned.

The caveat

I believe I have one of the best marketing jobs in the world as a global channel marketing manager for the world’s leading business software company, SAP. I get to travel around the globe delivering leading-edge knowledge transfer workshops to our business partners, where we share these trends and guidance on how to initiate the necessary change management to capitalize on the incredible power of digital and social media marketing

And I am witnessing a very definite trend. Those partners that are aligning and applying these digital and social marketing best practices after attending the workshops are experiencing significant uplift in net new business. There is a BUT. Measurable impact and ROI are not always felt overnight, so leadership has to exercise patience. Build a 12-month strategic plan that captures objectives for your digital and social media go to market and measure, measure, measure.

Stop confining social media to marketing. To boost returns, it must be embedded into how companies do business. In a Live Business, Social Gets Its MBA.


Malcolm Hamilton

About Malcolm Hamilton

Malcolm Hamilton is Director of Global Strategic Initiatives for Global Indirect Channel Marketing (GIC) team at SAP. He has a proven track record of building and executing leading edge Channel Marketing & Sales & enablement programs. During a career that spans close to two decades, Malcolm is widely regarded as an IT industry thought leader and innovator with international experience in working with channel partners.