Tag Archives: social big data

The future of HR Big Data

As HR applications continue to evolve, HR needs to consider the new data sources and types that are coming towards them. It is no longer sufficient to simply track basic employee information. With the evolution of HR, companies now have wide ranging options including video interviews, dynamic and social learning and development solutions, social monitoring for talent identification and internal collaboration, external survey benchmarks (including but not limited to salary, skills, performance, behavior, and personality), application logs, and predictive models for understanding cultural fit and preparedness for new jobs.

This complexity provides the need for HR Big Data. To deal with the variety and velocity of social data, video, documents, and transactional logs, HR departments need to work with other departments that may have already needed to work with these new data sources. Social monitoring is typically associated with marketing, video is often seen as a corporate communications or public relations tool, document management is seeing a new renaissance with the development of social and cloud-based software solutions, and transactional and network logs are core IT tools. Continue reading

What Big Data can learn from the NBA

94Fifty smart sensor basketball photo courtesy 94Fifty.

On Thursday, February 13, Grantland’s Zach Lowe wrote an article on the latest technological development in professional basketball: measuring biometric information in game settings. Four D-League (the NBA’s developmental league) teams will start using one ounce sensors fitted on player jerseys to start measuring metrics such as heart rate speed, and position. These sensors are currently available from one of three companies: STAT Sport, Zephyr, and Catapult. These sensors are not new to professional basketball, as nearly two-dozen NBA teams already use these devices. However, NBA teams currently only use these sensors in practice settings, rather than in game-time situations.

There are a couple of interesting Social Big Data lessons that professional basketball could potentially learn from this experiment that every Big Data expert should be interested in finding out.

First, consider one of the quotes from the Grantland article:

“As the research-and-development arm of the NBA, the NBA D-League is the perfect place to unveil innovative performance analytic devices in-game,” said NBA D-League president Dan Reed.

This concept of an R&D product where you collect more data in an experimental setting is one that many technology companies could start to use. For instance, does your core cash cow product have a corresponding R&D product that can be tinkered with without affecting your revenue? This is a good role for your freemium or single user product. (Heck, Facebook does this for their core platform, although DataHive does not recommend the level of iteration that Facebook provides unless you have a monopoly or duopoly of your core market.) This new use of heart rate and other physical information will provide insights on team tactics and performance if used correctly, thus leading to not just Big Data, but interactive and social Big Data where each player’s metrics are dependent on each other.

Second, and more interestingly from a tactical perspective, this measurement will allow basketball teams to more closely align physical effort with results. It is easy to simply believe that hustle and effort lead to better results, but these metrics may actually show that a lack of hustle could be one of several things. It could be a health issue or laziness or it could be good strategy in saving energy for key moments. Hustle and physical movement should not be measured in isolation, but in context of results. If a “clutch” player ends up moving less than an average player or saves exertion for peak moments, the economics of movement may actually state that excessive “hustle” is detrimental to performance. These sensors may also show that specific team tactics lead to greater efficiency, just as our analysis of shot taking shows how important it currently is to take shots from within 4 feet of the rim or on the sides of the three point line.

From a business perspective, most of us do not put out the physical effort of a professional athlete for a prolonged basis at work. But do we waste time and energy by going in the wrong direction? Are we getting stressed because our managers are not telling us the right information? There is a key challenge of understanding how to use this information productively rather than punitively. It can be easy to fall into the trap of simply stating that more time at work equates to greater productivity, but it may actually be that after a certain point, the error rate or lack of clear thinking outweighs the incremental productivity that would be expected. Follow the real business metrics rather than pure resource utilization.

However, as this occurs, one of the biggest challenges will be to translate sports analytics to business analytics. Keeping score is very easy in a rule-based sports environment, but more difficult in a business environment when it can often be difficult to define KPIs. Based on personal experience and interviews with multiple basketball analysts, DataHive has found that the academics and number crunchers conducting this analysis are largely unaware of the value that these findings could provide in the sports world. Although business analysts can quickly see how the heat and activity maps associated with basketball could translate into greater retail, field, and manufacturing success, one of the great challenges is that the sports analysts currently doing this work do not understand how their work could be translated to other fields. In our role of supporting Social Big Data for Human Insight, DataHive serves as a Sports Data Whisperer that wrangles the findings and techniques used in the sports world and brings them to the business world.

DataHive’s principals have long believed that the structured world of sports serves as a natural testing ground for the predictive, geolocated, and biometric data that is being introduced to the corporate world. Video feed metadata and sensor-based data are the Next Big Things in Big Data and it is only a matter of time before the corporate world follows suit. Regardless of your personal interest in sports, Big Data professionals should keep track of the surveillance and sensor data being used in the basketball world to see how this controlled setting provides potential insight for future enterprise technology efforts.

My Introduction to Enterprise Software at IBM Connect 2014

I’m a social consumer technologist. My daily routine includes Twitter, Facebook, Instagram, Flickr, Pinterest, Tumblr, Pinboard, and a fistful of other social and collaborative information-gathering tools; some of these, I use on their own (such as Pinterest), others, I manage through HootSuite, an integrated social media tool. I’ve spent little time working with enterprise-level tools and companies larger than “medium.” So I was intrigued by the opportunity to be introduced to an enterprise social software, IBM Connections, at Connect 2014, and to compare it to the consumer and SMB environments that I was accustomed to working with.

The common ground between enterprise and SMB companies is that they are all aware that they need to be doing social media now. The enterprise is waking up to the fact that social is something the majority of their employees do anyway – and that there needs to be attention given to the policies surrounding that, and that this applies across all strata in a given company – as far down as front-line, and as far up as C-level officers. The attention IBM is giving to design and its Designcamp is a pertinent example to demonstrate a pervasive business initiative, since Designcamp has been deemed so important across IBM that even C-level officers are attending to ensure everyone in the company’s on the same page. A similar initiative for external social at IBM offices could yield similarly intriguing results.

IBM Connections will be significantly easier to learn if it heads in the direction of Mail Next, announced at IBM Connect, via a similar IBM Designcamp initiative. The Mail Next dashboard is where software design has been headed for awhile – being able to see the most important things up front is better than having to dive through layers of nested contextual menus to find it. (Granted, simplification for comprehension vs. options for power users is an ongoing tension.) I found myself in the weeds a fair bit trying to absorb as much as I could regarding IBM’s existing software, but Mail Next stood out as something more modern and easy to grok.

However, some stark differences also showed up in comparing enterprise and SMB social. When you join an enterprise, there’s traditionally not a lot of sanctioned opportunity to bring your own tools. So whatever you have used at home may be very different from what you get to use in an enterprise, and frequently, enterprise tools are so complex that lengthy training sessions are recommended for their effective use. I’ve tested a large number of consumer tools, both for my workflow and for others’, and the ones that remained useful over the long term typically had a combination of great software design, concise demonstrations or explanations, and benefits so obvious that it motivated me to keep using them. If something felt too complex, it was hard to motivate myself to keep up with using the tools. Bridget van Kralingen, SVP of IBM Global Business Services, pointed out that 50% of employees would pay for better and more collaborative tools. This is revelatory.

At this point, businesses small and large need to have a social presence; it’s expected, and this point was made across the board at Connect 2014. IBM certainly knows the importance of social; they encouraged everyone to tweet and post Instagram photos (and IBM applied appropriate gamification throughout the show for fun and glory). But IBM’s software mostly doesn’t reflect that connection yet; it’s so focused on “internal social,” with “external social” feeling somewhat bolted on. Even though they mentioned that you could invite your partners and clients to participate in your internal social spaces, overall, most of the software came off as IBM-social-centric, when smaller businesses are accustomed to sorting out what types of social initiatives go in varying spaces.

The division between “internal” and “external” social isn’t nearly so vast outside the enterprise world. It’s why the IBM-HootSuite partnership will be intriguing to watch – 80 different social networks are already integrated into HootSuite, allowing you to participate in external social both as a reader and a writer. That’s a lot of third-party social integration! IBM Connections, on the other hand, is just starting to integrate third-party social, and so far, primarily as a means to bring external social data into Connections.

So despite the way social is divided into “internal” and “external” for large enterprises, there’s still a lot of common ground between SMB social and enterprise social, particularly with regards to social being a necessity for all businesses at this point. And Mail Next proves that enterprise social software doesn’t have to be complex nests of menu options to be powerful, yet easy to understand, like the most popular consumer social software out there today. I look forward to IBM Design working its way through the rest of IBM’s software; it’s key for making IBM software easier to learn and close the usability gaps between consumer and enterprise software.