If you think that you work in an industry or a department where data is not yet pervasive, think again. You may be surprised to learn that data-based decision-making is so wide spread it reaches from the warehouses, to the front line sales teams, to Human Resources and the C-suite.
You may also assume that most data analysis focuses on operational tasks like logistics, or procurement, or marketing metrics like web traffic and downloads but in reality, data is flowing farther and deeper into our organizations than many of us really know. And, data analysis isn't that new. We've been surveying people for decades. Now, we have the tools to be smarter, faster and more efficient with the questions we ask, when and to whom.
Google is a great example of how our behaviours have dramatically changed when it comes to the speed of which we access information. Hummingbird (named for its precision and speed) was unveiled as one of their first search algorithms to provide even more direct answers to complex questions. Since Hummingbird, we've seen Penguin, Panda and Pigeon deployed. An unnamed update will be occurring on April 21st, extending to mobile so that speed of search will be optimized on the go.
Academic researchers are working in tandem with many of these data companies, including Harvard, MIT and Stanford. What is most exciting is that the involvement of academia doesn't just rotate around the world of computer sciences; researchers from all disciplines are utilizing the data to improve many important social and corporate interests.
Dr. Vanessa Buote has a PhD in social psychology and acts as a research bridge between Plasticity Labs and Wilfrid Laurier University. The partnership explores large-scale, highly applied research questions, such as the impact of well-being and happiness on turnover, productivity and engagement. The outcomes of the research drive product development and decision-making on the corporate side, and the shaping of policy and social innovations on the academic side.
And data is going beyond just looking at the past. With the growing field of "predictive analytics" companies are now learning to tell the future, too. For example, Plasticity can now predict if there is a likelihood that employee happiness will be up or down. By sharing with leaders, at what point the company sits inside the annual survey – they can estimate whether their people are on the up or downswing of that annual survey sentiment graph. Data can suggest whether companies are low in inspiration or high in optimism, stable in gratitude and empathy. This anonymous, aggregate data helps leadership teams focus their spending on retention programs versus over-spending on budget to attract new hires. It also helps them to see EQ data as the most intelligent predictor of attrition.
More importantly, and way beyond the ROI, true culture leaders can use data to identify why specific cycles or workplace events will diminish motivation. Leaders who are truly committed to the success of their people will want to know when and why their employees are demotivated to find new ways to inspire them again.
Of course, in response to the increasing accessibility to data and growing questions about how it is (and will be) used, it is valuable to ask, "how far do we take this?”
Every 2 Days We Create As Much Information As We Did Up To 2003. - Eric Schmidt, Google CEO
According to Google CEO, Eric Schmidt, "...every two days now we create as much information as we did from the dawn of civilization up until 2003...that’s something like five exabytes of data."
We are in the midst of a massive evolutionary jump as it pertains to the way that we gather information. Never before have we made so many data-based decisions before me make a purchase, have conversations, make travel decisions, parent our children. Although there is some concern about how much data we absorb and disperse - what we need to know is where we can use data for good. .
Take companies like Splunk who built a corporate giving arm in an effort to use data for social good. Some of their projects include partnerships with non-profits like Rock the Vote to improve voter turnout with the FEMA Think Tank on Innovations in Emergency Management. This project took >7M tweets related to Sandy from 10/22/12-10/31/12 and provided analysis that showed:
1) How fear changed as Hurricane Sandy approached
2) How many people asked for help over time and what the sentiment analysis showed
3) Critical Supplies over time and what the sentiment analysis showed
4) Rate of people evacuating the area over time.
According to the Splunk4Good’s blog, "FEMA was indeed using social media during Sandy, but mostly for external communications and to control the rumor mill. They were not using it for real-time analysis that improved operational decision making."
And, if you look at the projects undertaken by the group Data Science for Social Good, you'll see the big social issues under the data microscope like effectiveness strategies for homelessness, improving graduation readiness, reduction in maternal mortality rates, and the list goes on.
With 70% of our waking hours spent at work - how are you going to use data to improve your life or the lives of others? By examining the use of data for good, we can leverage the opportunities for extracting and sharing information in ways that help people to be their best.
How are you using data for good? Share your story by sending me an email to email@example.com.