“Big Data is at risk of becoming one of those tech industry buzzwords that blows up before we’ve seen the benefits of it.”
This is a statement Richard Waters, West Coast Editor of Financial Times made at the FT Innovate America event last month that really hit home.
It makes me think of the internet meme of Dr. Evil using finger quotes in the image above. I have to admit, it still makes me laugh.
Not to ignore the full range of implications that we must solve for with the influx of Big Data, but for this post, I purposely focused on innovative leaders that are delivering value to companies through the use of Big Data, and share responses to the talent shortage or pressing need to functionally address the Big Data expertise gap.
Mashable’s Velocity – a viral prediction platform
“Three Mashable stories are shared every second across social networks.”
This is what Robyn Peterson, the Chief Technology Officer of Mashable shared at FT Innovate America last December as he described finding ‘the secret sauce’ of Mashable’s Velocity.
Velocity is a proprietary system that predicts what content is going to go viral next. The platform has crawlers, ingests data, content, Facebook public feeds, and data directly from Twitter while using artificial intelligence and classification systems. And then Mashable uses all this to listen...deeply listen.
One might even call it the art and science of listening.
Peterson took us back to their beginning -- how the company was founded by Pete Cashmore who, at 19 years old, started Mashable in his bedroom at his parent’s house. He built the business ‘manually’ as he listened (devoured) social platforms and wrote stories and content based on what people wanted to know about next. Peterson said,
“This system [Velocity] is basically a robotic Pete Cashmore that operates at a high quant level.”
Velocity tracks when a story is going to peak. The system looks at data and makes predictions with high accuracy rates. For example, within 5-10 minutes, it can make a very strong prediction of what is going to go viral next. Based on its accuracy, Mashable is now licensing Velocity to advertising, marketing and media agencies.
See press: Mashable signs Partnership with Leading Media Agency MEC to License its proprietary Velocity Technology and Mashable and 360i Forms Strategic Partnership to Bring Mashable’s Velocity Technology to Brand Marketers
You can check out Robyn Peterson’s informative story by forwarding to 22:00 in the video. Peterson possesses the gift of taking a technical subject and making it accessible to a wider audience. He shares how the viral prediction platform Velocity was conceived and developed, while engaging his audience with humor, insight and ease. I really enjoyed his talk along with the other case studies featured here:
I encourage you to view the array of videos from the FT Innovate event on their site. I’d like to point out that Financial Times did an incredible job with the selection of speakers and pacing of this event. Thank you to the FT Innovate team for the invitation to attend.
Bringing Military Intelligence and Actionable Decision Analytics to Corporate
Another company that is advancing Big Data outcomes is Signals Group, a Tel Aviv decision analytics firm that works with corporations to reduce risk and shorten time in the development and launching of new products.
“Decision-makers today operate in conditions plagued by constant uncertainty. It takes courage to ‘read the world’ and make mission critical decisions about the future. Evidence creates courage.”
This is how Kobi Gershoni compares the intelligence community to those in commercial enterprise. Gershoni, a former military intelligence officer, is the Co-Founder and Chief Research Officer of Signals Group.
The Wall Street Journal published an article titled, In Corporate Intelligence, Think Like Israel, where Tom Davenport (a Signals Advisor) writes, “One of the reasons that modern Israel has prospered for over 60 years is that the country’s leaders believe that knowing as much as possible about its enemies and friends is critical to survival. Companies can learn a lot from Israel’s example, and can get some help from intelligence-savvy Israelis in doing so.”
As a team of former intelligence experts, you can image how Signals’ capabilities can extend far beyond some of the “listening platforms” being used via social media in recent years. They have built a system that goes even deeper across all open web services including multiple source types such as business news, patent registries, scientific and academic journals, social media, e-commerce…and the list goes on. So in addition to deep listening, comes deep and timely decision-making.
In essence, the Signals platform ingests multiple sources of structured and unstructured data, then converts the information to actionable insights that help clients make critical business decisions across the entire value chain in real time.
What I find most intriguing is the alert system that they have in place, which uses 24/7 monitoring and alerting. Their platform includes prioritized, rule-based alerts that deliver crucial early-warnings to businesses. It also allows users to interact with the underlying analyses and data at granular levels.
Both Kobi Gershoni and Tom Davenport will be part of an upcoming webinar that I am partnering on with Signals and Innovation Excellence. Signals is sponsoring this web event on 1/29, which is titled, How Big Data is Changing New Product Development. During this time, we will go deeper into the history of information eras and discuss the practical challenges facing organizations today. You can click here if you are interested in learning more.
The Human Side of Big Data
Mashable’s Velocity and Signals’ Playbook are two examples of some very powerful technologies, but what I can’t help but be drawn to is the talent and brilliance behind the platforms.
As a data-driven Marketer for over 15 years who entered the innovation space in 2011, I have been entrenched in the data space in one form or another throughout my career. The special skills and brilliance required by the experts who actually handle that data, analyze it and convert it into something meaningful is a unique talent, requiring multiple skillsets – even more so today as the ‘next era’ of Analytics 3.0 is taking shape.
Tom Davenport dedicates a chapter of his most recent book, Big Data at Work: Dispelling the Myths, Uncovering the Opportunities, to “the human side of big data”. Here he speaks to the skills required today, which can be hard to find and retain, based on the increasing demand. In it he says,
“The skills of talented human beings are the single most important resource in successfully exploring big data. They extract the data from obscure locations, write programs to turn unstructured into structured data, analyze the data, interpret the results, and advise executives on what to do about it – all in short order and with a sense of urgency.”
What is becoming increasingly clear for many is that, in addition to understanding the key traits of Data Scientists, the future is dependent on having the right decision makers, management, culture, team, processes, agility and infrastructure in place.
Given this, if done well, we are more likely to capture what Tom Davenport defines as the three classes of value of Big Data:
- Cost Reduction
- Decision Improvement (faster/better)
- Improvement in Products and Services
The Data Scientist’s Toolbox and Closing the Talent Gap
Professors Jeff Leek, PhD, Roger D. Peng, PhD and Brian Caffo, PhD, who teach at Johns Hopkins University, echo the value and talent requirements in a course I recently completed on Coursera: The Data Scientist’s Toolbox. It is the first in nine-part series of a Data Science Specialization track.
The course provides an overview of the data, questions, and tools that data analysts and data scientists work with and offers an introduction to the ideas behind turning data into actionable knowledge.
Being aware of the talent requirements needed to fulfill Big Data outcomes, what has become even more visible, is the serious talent shortage. In a report from McKinsey Global Institute titled, Game Changers: Five Opportunities for US Growth and Renewal the authors write,
“By 2018, the United States will face a shortage of up to 190,000 data scientists with advanced training in statistics and machine learning—and this specialty requires years of study.
More broadly, an additional 1.5 million managers and analysts will need enough proficiency in statistics to ask the right questions and consume the results of the analysis of big data effectively. A significant amount of retraining may be necessary to develop the skills of those already in the workforce.”
This begs the pressing question:
What are our options for addressing the talent shortage?
As author Gill Press points out in the Forbes article, $16.1 Billion Big Data Market: 2014 Predictions From IDC And IIA, “IIA commented that there are now well over 100 programs at universities in the US where analytics and data science are in focus (see his list of graduate programs here). IDC, for its part, cautioned that these programs will bear fruit only in four to five years, referring obviously to the newly-established data science programs.”
Exploring More Options --
Massive Online Courseware (MOOCs) and Data Science Boot Camps
Are there additional ways to properly teach and access larger pools of talent more quickly? And while in the search of this instruction, how can we go beyond theory to create a meaningful level of hands-on practice and evaluation?
In addition to the current university programs listed above, I am interested to see if MOOCs can become a viable option for addressing some of the current challenges businesses are facing.
I am not suggesting that a 9-month program on its own will produce a PhD level Data Scientist, but I do wonder if there are ways to leverage these platforms more regularly to assist our professional development or retraining.
We need to keep in mind that Big Data impacts team members beyond IT and Data Scientists. In a press release published by Gartner, Big Data Creates Big Jobs: 4.4 Million IT Jobs Globally to Support Big Data By 2015 Peter Sondergaard, Senior Vice President and Global Head of Research points out that,
This is a staggering number if you consider the 4.4 Million IT jobs predicted.
Through my own exploration of the Data Scientist Toolbox course mentioned above, I found the Data Science specialization and a signature track comprised of 9 courses and a capstone project is offered on Coursera. It is worth checking out – if not for yourself, perhaps for incentivizing, motivating or growing talent within your current organization. Or, as a consideration for identifying talent for future hiring.
Upon completion, these courses provide you with a certificate and option to share access to your course records. Having personally completed MOOC courses to explore the possibilities hands-on, I feel encouraged that there are learning opportunities for companies here; or for you and your team members.
I’ve looked through MOOCS that offer structured curriculums with real projects. In addition to Coursera, Udacity offers a Data Analyst Nanodegree and states that they have designed the projects with expert Data Analysts, Data Scientists, and Hiring Managers.
MOOCs are being debated statistically and otherwise, i.e level of engagement, exam completion rates, etc. I’d like to believe that the action learning possibilities haven’t been fully explored or supported by leadership as well as they could be.
Since the launch of these platforms, I have taken several courses – the Good and the Bad. So far, I have found them to be a effective way keep up with the latest trends, language and capabilities, which has allowed me to partner better with my team, colleagues and clients.
Here in New York, incubators, fellowships and boot camps are offered at places like the The Data Incubator and NYC Data Science Academy (promo video below). These offer 6- and 12-week intensives and Boot Camps for persons with advance degrees and include real projects and job placement opportunities. Other offerings include corporate training and weekend classes.
As we move into the next phase of data-enriched capabilities, we will continue to see exciting new products and services. With each wave come new implications that will change the way things are approached and done. We are at a place where we need new solutions, so what better time to start preparing, experimenting, and seeking new avenues for learning, discovery and advancement.