Tag Archives: social big data for human insight

Facebook and Oculus: A step forward for Social Big Data

Oculus Rift and Social Big Data
Oculus Rift photo courtesy of Sergey Galyonkin.

Yesterday, Facebook announced that it was purchasing Oculus VR, makers of the Rift 3D virtual reality headset, for two billion dollars. If you’re not a hard core gamer locked into the happenings of the International CES show, you many not have seen this technology before.

Oculus has created a development kit, originally funded on Kickstarter, for an immersive 3D headset. This headset won multipleBest of Show” awards at CES and was widely seen as one of the top technologies in Las Vegas this year.

But cool technology alone doesn’t automatically lead to a multi-billion dollar price tag. Even in Silicon Valley, there usually is a reason for throwing billions of dollars at someone. In this case, Facebook is seeking to maximize the value of a technology that telecom and unified communications professionals have read much about in past years, Virtual Reality.

In our world, we have seen a variety of virtual reality technologies come and go with limited market success ranging from Second Life to Avaya web.alive to Musion 3D telepresence to Suitable Technologies’ Beam Robot. Although all of these technologies looked promising at one point and have the potential to make some waves, none have justified the price tag that Mark Zuckerberg has placed on virtual reality. What are we all missing? Where is Facebook going to do that is different from the rest of the collaboration and communications market?

The Zuck has already blogged about this on Facebook, but he sees the Oculus Rift as a potentially new interaction platform to come after the mobile phone dies out. Facebook was late to the mobile revolution and wants to get in front of the next key interaction platform.

In his post, Zuckerberg lays out the next generation vision that Facebook has for virtual reality as an extension of Facebook:

“After games, we’re going to make Oculus a platform for many other experiences. Imagine enjoying a court side seat at a game, studying in a classroom of students and teachers all over the world or consulting with a doctor face-to-face — just by putting on goggles in your home.”

And imagine going through Facebook to gain access to these experiences. In theory, you could also bring your friends along to the courtside experience and Facebook could offer the same view to thousands of people at once. Students and Millennials are already used to working together by keeping social media windows open that keep access to their friends on their phone, tablet, or laptop. With Oculus, they could have their own immersive space for studying or hanging out.

(Interestingly, Plantronics developers have an interesting demo that they are starting to show where their headset was able to control a Google Maps view simply by moving your head from side to side. This is undoubtedly a first step in building the type of experience that Facebook would like to emulate over time.)

But one of the most interesting aspects of this vision isn’t how futuristic this seems, but how this vision actually reflects the past few years of unified communications. A couple of years ago, the Big Thing in unified communications was the potential to merge social networks with unified communications to create a converged collaboration environment. We already had virtual reality solutions. We already had immersive video, which has only gotten better year over year. And, of course, we already had the most advanced voice solutions in the world. The only thing left was to add a social aspect.

As social companies such as Jive Software and Yammeremerged as front runners, the common thought was that these would merge with UC vendors such as Cisco, Avaya, and Microsoft. But, despite Microsoft’s acquisition of Yammer, this hasn’t really happened as of yet. The biggest challenge has been that these social software vendors only see themselves as a portal for specific types of interaction, rather than a single point of interaction for all communications types. And in the vast majority of enterprise environments, social communities and call control are still completely separate in nature. Only now, with the advent of improved user experiences such as Unify’s Ansible product does it look like social media is finally being integrated into the typical business end user’s workflow.

Even in the consumer world, calling and social media are typically separate as well. Consumers rarely look for “unified communications” as a standalone capability from their phone company; they simply have a mobile phone that provides most of the benefits of unified communications: text, video, chat, presence, and social. And even then, the voice and video aspects are typically separated from the social networks they use, such as Facebook, Twitter, LinkedIn, Pinterest, Snapchat, and Instagram. Although Facebook and Google+ have started to make inroads into real-time communication, it would be hard to argue that either of these services are replacing Skype or Snapchat any time soon. So, not only does the enterprise world not accept this merger, but the consumer world still isn’t sure how to connect social networks with immersive speech or video communications.

Of the existing vendors in enterprise communications, only Microsoft seems to currently have the pieces needed to compete with Facebook’s vision. Between the XBox Kinect, Skype, Yammer, and Lync, Microsoft has the pieces to pursue a similar vision where social experiences can lead to immersive video and interaction. However, Microsoft hasn’t built a Virtual Reality department for a simple reason: lack of business demand. And despite the criticism that Microsoft has received on business execution, nobody has ever accused Microsoft for not chasing big markets: their investments into mobile and cloud technologies show real commitments to Windows Phone, Office365, Azure, and other technologies.

So, did Mark Zuckerberg just throw away 2 billion dollars? Given that Facebook is near an all-time high with a market cap over 150 billion dollars, this is a drop in the bucket for them. But two things tell me that this investment could potentially pay off.

First, the newest Oculus Rift experience really is head and shoulders above any virtual reality helmet or goggles that have previously been on the market, both in terms of comfort and immersiveness. I’ve worn my share of 5 pound helmets where one could only focus on a single area that would leave me crosseyed and dizzy when entering the real world. In comparison, the current Oculus development set is less than half a pound and provides a stereoscopic view to support normal vision. This provides a level of physical comfort that has been missing in virtual reality. But this admittedly only means that Oculus meets the minimal standards of being usable without creating pain for its user.

Second, and more importantly, technology has finally started to catch up to the demands of virtual reality, although it is still early. The combination of increased bandwidth and improved networking, immense back-end cloud resources to create better video environments, and the emerging concept of “wearable” mobile technologies such as Fitbit and Google Glass are leading to an environment where end users are starting to look at virtual reality as a potential option. The real key here is ultimately the adoption of wearables, as this determines whether end users will actually use a technology like this without thinking of this as a bizarre experience.

A relevant parallel may end up being the tablet computer industry. Back in 2000, Bill Gates demoed a tablet PC at COMDEX (Remember that name?) and announced that it was the future of computing. It ends up that he was right, but it took another 10 years of slogging through the UMPC (Ultra Mobile Personal Computer) and PDA (Personal Digital Assistant) market before the iPad finally made the tablet usable. The key wasn’t the size of the tablet or the processing power, but creating a user interface that replaced the stylus and awkward handwriting detection software of the time with a simple touch-and-swipe interface that is now standard.

For Oculus to succeed, Facebook is going to have to learn from the challenges of the unified communications market and the concerns of the consumer technology market. It won’t be enough just to have an interesting technology or to achieve integration between Facebook, Oculus, and real-time events. And it won’t be enough to build the massive infrastructure needed to provide a 3D viewing experience to a home audience. With this investment, Facebook is going to need to play a primary role in advocating and educating consumers on how to use headsets and augment their existing world with a virtual world. So far, that has been a tough sell. Then again, 10 years ago, the idea that a “social network” would be a 150 billion dollar company was a tough sell as well.

The frustrating angle for DataHive Consulting is the realization that the eventual integration of Facebook and Oculus is probably another 3-5 years down the road, meaning that we are unlikely to have any true projects for Oculus-based data before 2020. But while we wait for the tools of the future to gain widespread acceptance, it’s good to know that somebody is actually working on building it. In the mean time, we’ll have to maintain our focus on the social media, video analytics, and telecom big data problems that permeate the enterprise.

Do HR Organizations Really Need Big Data?

Big Data Funnel
Big Data photo courtesy of hrringleader.

Over the past couple of years, the hottest trend in enterprise technology has been the evolution of HR applications from basic benefits, payroll, and workforce management to a variety of applications covering a much wider set of needs – from finding potential employees and predicting the need for specific skills to optimizing employee capabilities to the appropriate offboarding and succession of core talent. To get a strategic advantage, HR departments are being asked to use “Big Data” to “Moneyball” and quantify their approaches. But is this really the right way to go?

To determine this, consider what Big Data really is. Big Data is a set of technologies designed to store, process, and analyze data that does NOT fit into traditional spreadsheets, databases, and other basic structured data sources. Depending on whether you need your data to be faster, bigger, or more varied, you may be looking for specialized high velocity messaging solutions, cloud-based and multi-tenant storage, high performance analytic engines, Social Network Analytics, sentiment and natural language processing, or video analytics. This is the world of Big Data. A practical definition of Big Data would be 5+ terabytes of data, including some aspect of machine data, interactions, video, or high velocity streaming data.

In this context, is HR looking for solutions that can hold hundreds of terabytes of data and provide real-time analysis? Or are you really looking for some analytic insight for existing data? Chances are that you need a little bit of both depending on the maturity of your current HR data, the maturity of your current analytic capabilities, and your appetite for new and emerging technologies. But you should start with basic analytics and traditional data discovery tools before talking about Big Data.

For your current HR data, you have probably invested in some level of HRIS system to keep track of your employees and define your cost or profit centers. In addition, you have some level of workforce management to track hours worked and to seek what level of resources you have in-house to carry out key projects. This data, in and of itself, is already a wealth of data that is often underutilized to provide greater insight for your organization. As a basic example, consider that all of your employees have usernames and passwords for one or more applications, including email, ERP, CRM, document management, marketing asset management, and many other potential use cases. What happens when you start tracking your application usage on an employee-specific or department-specific basis? You may find out that you need to build a new office, or at least invest in new application licenses and network bandwidth, even before employees fully realize for themselves the extent to which their own work may be hampered or degraded.

Organizations that have invested more deeply into HR, training, market research, and succession management may have even more data regarding the skills of their employees, the ability to benchmark internal talent against readily available talent, and the relative volatility of performance for each position. The value of this data can quickly be increased by integrating tactical decisions and communications with higher-level KPIs to seek how the best employees work or if there are fundamental gaps that internal employees have relative to the market. This approach can also detect potentially troubling aspects in the organization, such as if employees start losing key skills or performance as they continue to work in an organization, or if they fail to learn skills at the same rate as the general market. This may indicate a need for cultural or development changes within the company.

It is important to realize, though, that these approaches are NOT Big Data, but a combination of data integration and analytics capabilities that likely exist already in mid-sized to large enterprise organizations. To get insight like this, start working both with IT and line of business executives to build out the potential value of these approaches and take advantage of the business intelligence initiatives that your company has built out for financial and operational insight. In fact, by being the visionary who understands how to bring human resource insights to a higher level, you may get the HR “Big Data” result you are looking for with just a bit of internal resource allocation. And given the choice of Big Results or Big Buzzwords, good HR professionals should choose results every time.

Defining Social Big Data for Human Insight

Social Big Data for Human Insight
Internet map 1024 by The Opte Project is licensed under CC BY 2.5.

DataHive Consulting is focused on the concept of Social Big Data for Human Insight. But what does that actually mean? For us, there are three key components to this phrase: Social, Big Data, Human Insight.

“Social” is about the engagements and transactions that we use to interact with each other. Social media and social networking are the most obvious examples, but we are interested in the entire span of interactions. Email is a social interaction. Telephony call detail records and text messages are also social interactions. Even our interactions with locations and content can potentially be social if two or more people are interacting with the same location. In short, we are focused on personal and shared interactions.

The most important aspect of “social” is in getting good data. In this case, good data is determined by the quality of interaction. Social data will not be useful if employees, customers, and partners are not interacting with each other and getting value. So, from this perspective, the lessons of effective social collaboration are vitally important for maximizing the value of Social Big Data. Garbage in, garbage out is just as true for relationships as it is for data. Because of this, we care about setting up social engagements properly to create business value and to support ongoing social insight through Social Big Data for Human Insight.

“Big Data” is a bit of a marketing play, to be perfectly honest. We do care about the 3 Vs of Variety, Velocity, and Volume, and we work with video, sentiment analysis, predictive analytics, and data mining. But we also deal with the traditional data management and business intelligence tools that can analyze social data. Often, the key to unlocking the value of social data is as simple as connecting the correct data to the correct applications. In cases like this, DataHive will recommend a basic data integration and connection process rather than a Big Data implementation. The goal is to use the correct business intelligence and analytic tools and not to simply add Big Data tools for its own sake.

At the same time, there are specific challenges to Social Big Data as well. Companies trying to gain value from the full Twitter firehose need to have semantic strategies, sentiment tracking capabilities, focused goals, and a strong knowledge of which Twitter fields are more likely or less likely to provide value to those goals. Video analysis may require packet inspection, natural language processing, metadata creation and analysis, video surveillance, and user participation tools to translate gigabytes of video sharing into actual insight. These social data sources are much more complicated than the relational databases and structured data marts that DBAs initially grew up with. When we conduct data-driven work, it is in light of Social Big Data for Human Insight.

“Human Insight” is the most important part of this model. DataHive is not concerned with data analysis for its own sake. In fact, one of our biggest criticisms of the “Big Data” mentality is concept that the supposed “data scientist” would look at data without hypotheses and look for findings. (We know that not all data scientists take this approach by any means, but we believe in an empirical and scientific approach for analyzing data.) In our world, businesses and organizations have specific goals that they are trying to achieve and Social Big Data needs to help them to improve processes, provide guidance, and foment disruptive innovation.

Although social media is typically in the hands of marketing or customer service, DataHive believes that there are Human Insights that go across the entire organization: human resources, sales, research, operations, IT. The insight may be a simple as picking up website complaints which lead to the realization that the corporate WAN is being impaired at a key node. From an HR recruiting and morale perspective, the sentiment for your organization may be much stronger or weaker online than your internal metrics may track. And the pure insight and educational value of key thought leaders online can provide value to every level of the organization if the correct information is used.

But beyond the sentiment of the social media itself is another level of insight held through metadata, social connections, and context provided through sales, talent, and other key business capabilities. Data has a topology and a specific meaning, especially as we try to collaborate together. Social efforts can be pointless if we are not talking to the right people or if we lack a critical mass of users. There is also a bigger world of human insight associated with global challenges, but we are starting with business challenges. Today, businesses, tomorrow, the world!

As we look at human insight, we want to show you how to gain value from all three of these areas both in isolation and in combination. We use our decades of experience in using social media, our use of metadata and relational data, our social science backgrounds in understanding the sentiment and psychology of social data, and our business backgrounds to provide you with greater insight into using social data.

If you have questions on what social data is or how to take optimal advantage of your social data, we would love to discuss your social strategy and social data use cases. Please contact us at connect@datahiveconsulting.com to schedule a free consultation.

What HootSuite Should Do with uberVU’s Analytics

HootSuite acquires uberVU
HootSuite acquires uberVU image courtesy of HootSuite.

Today, HootSuite acquired uberVU, a social analytics solution. DataHive has already written about the importance of HootSuite in supporting B2B social media and we’re a fan of many of Hootsuite’s data aggregation, tracking, and scheduling capabilities. But uberVU will provide HootSuite with opportunities to improve social HR, sales, marketing, innovation, and core social analytics. Continue reading