How Companies Use Big Data & The Quantified Self Movement For Insight

The Emergence of Quantified Self in Enterprise

The quantified self-movement (QS) is a hot topic in 2013 and focuses on using sensors and other trackers to acquire self-knowledge for the end goal of gaining deeper insight about personal habits. For example, I use Nike+ to log my daily run performance. I also make a list of my diet for that day and compare it to how well I performed. I am hoping that after a couple of months of use, I can figure out what the optimal diet is for me before I go for a run or engage in physical activities such as sports. Other examples can include measuring coffee intake vs. productivity or sleep activity vs. diet. With the inclusion of Big Data—the ability to process large amounts of data quickly—people are looking to contextualize all the data available on their laptops, mobile devices, or even social media platforms.

Whether or not you are actively participating in the QS movement, companies are adopting the method to find new ways to measure performance metrics. By measuring employee activity through sensors, these new metrics will be aggregated to redefine what being a successful worker means. Here are 3 examples with some added commentary:

DARPA

• The goal of DARPA is to implement soldiers with biometric chips to measure levels of cortisol (stress), histamine (inflammation), and diet. Doing this will allow the military to keep real-time health records of all their soldiers. This is a vital change as processing urine/blood samples takes time and money and is prone to contamination from overnight shipping to the lab. This biometric chip would be a cost-effective solution to monitoring health.

IBM

• Corporate executives are always worried about their employees going rogue and divulging company secrets. IBM’s Security Intelligence with Big Data crunches all inter- and intranet activity done on their servers. As it is collecting data, the program conducts sentiment analysis on message contents to determine if an employee is disgruntled or not. A disgruntled employee gets “flagged” if (s)he is perceived as a threat to corporate intellectual property and security. This could provide the basis for firing someone, but also raises the ethical question of what happens if you falsely accuse someone?

Salesforce

• Salesforce has integrated their version of Twitter to be used at work. Called Chatter, it is a company message stream that employees can use for various purposes, namely providing co-workers with valuable information. If a worker is recognized for bringing fresh insight to Chatter, they are rewarded with extra compensation. The downside to this system is that there isn’t necessarily a direct correlation between information provided and business value. By attaching an external reward as great as extra pay, Chatter is encouraging certain behaviors. But, is social media activity enough to measure an individual’s personal contribution to business value? The upside is that it is now imperative that companies use social media as part of their daily work lives. Chatter provides the motivation to use social media, but it should be complemented with other systems of measurement to provide a more accurate look of employee contributions.

From these examples, it is clear that if something can be measured, someone will measure it. Chris Dancy, a director in the officer of the CTO at BMC software, thinks that someone should be you. Dancy always has sensors running to measure pulse, REM sleep, skin temperature, bathroom activity, and even decibels from his phone calls. He claims, “If I’m on a [conference] call and my voice gets over 50 decibels, my phone notifies me. After the call, I can check my heart rate to give me better insight on my true feelings about the conversation.” He claims this to be the augmented self—a part of him that lives online and among the data. Understanding your augmented self allows you to engage in more effective online activity. Building a strong online presence will serve to benefit your offline life whether it be related to relationships, work, or leisure.

Business strategist Michael H. Goldhaber predicted in 1997 that the economy was shifting from the industrial market to an attention market. In his paper The Attention Economy and the Net, he explains that the advent of the Internet has literally created a cyber “space” where commodities are exchanged and shared. Since the Internet detaches you from physical reality, you rely on your presence to be heard. This implies that since the Internet, the underlying intangible commodity has been attention. Employees who work for employers using the QS movement will see these metrics as the numbers they need to achieve to gain and keep that attention. But are these numbers true predictors of productivity such as in the case of Chatter?

This QS movement is by no means perfect and is subject to a few human errors that everyone should be made aware.  These issues are raised in psychology, and they are called the third variable problem and the directionality problem. The third variable problem states that there is an unintentional third variable that influences the two variables that are being measured (ex. Cortisol levels from stressing over schoolwork could also affect my Nike+ and diet separate variables). The directionality problem states that X and Y will be statistically related if X causes Y or Y causes X. Even statistical significance from big data needs to undergo another step of inference to properly understand what the data is telling. If you choose to implement big data into your company or personal life, just make sure the numbers are telling you an accurate story.

via Wired | image by Mark Morgan Trinidad A