Passive Data Collection and Actionable Results: What to Know

Passive data collection happens when organizations gather information without the direct involvement of the people studied.

It can be a useful strategy for gaining actionable data that supports the decision-making process. However, those who collect and use passive data must keep some things in mind when determining when or if to use this method to gain insights.

Image by Yan Wong from Pixabay

Passive Data Can Complete a Customer Picture

 
Surveys can capture active data from willing participants. Yet the trouble is that people often don't correctly remember all the things they do. Such memory lapses could lead to incorrect data that ultimately restricts the ability to use the information for actionable results.

However, researchers used a combination of active survey data from participants and passive data gathered with a meter on a person's mobile phone.

The goal was to see if the outcomes of the two methods matched when assessing what people did during their time online. The findings showed different results across the survey and meter data, leading researchers to suggest using combined methods when possible. 

If companies find that their current analytics strategies fall short, combining several methods with the same goal in mind may be the way forward. Even when people have pure intentions and want to submit survey data correctly, their recall abilities may not allow it. In those cases, passive data collection could fill in the gaps and aid businesses in completing their customer profiling efforts.

Passive Data Can Gather Statistics Average Users Cannot

 
Another instance where passive data collection may lead to valuable data insights is if the average user base is unable to provide the kinds of statistics required. A specialized device could do it for them, continually working in the background. 

The medical industry is ripe with opportunities in this regard. For example, when people participate in clinical trials, they often have to answer questions about which circumstances exacerbate their symptoms. A patient might admit that they feel worse when exercising or after eating spicy food, but what about the contributing factors that are likely not as obvious?

A company called monARC Bionetworks recently launched an app that lets patients submit their health data to clinical trial representatives. However, there is also a passive data component that grabs information related to weather and air quality. Those are two things that patients may not immediately connect with worsened or improved symptoms. 

Getting this kind of information allows clinical trial managers to make actionable conclusions that could shape the futures of drugs that are not yet on the market. The data may also reveal aspects that could otherwise remain hidden, such as that certain interventions are most effective for people in particular climates.

Passive Data May Improve Competitor Analysis

 
Company leaders often ask data analysts to assist them in scrutinizing the competition. Knowing about competitors' activities reduces the element of surprise, enabling other marketplace players to respond when or before a competitor does something significant that affects other brands' business. 

There are several legal ways for brands to monitor what their competitors do without those parties knowing about it. Actionable data, in the case of competitor analysis, relates to organizations that know how to use the information at their disposal for developments and decision-making. However, statistics show that only 31% of respondents say they work at data-driven companies.

Becoming a company that uses data to its advantage is not a straightforward process. Yet it's one that can begin if company leaders learn to ask questions about the information they obtain through passive methods. For example, they might want to know more about how data professionals sourced the material and how they analyzed it. Asking what the information does not show is also as crucial as determining what it contains. 

Passive Data May Improve Pre and Post-Operative Assessments

 
Medical researchers have dug into data to figure out how preoperative conditions affect surgical outcomes. For example, a Swedish study determined that a person's physical and mental health impacts their recoveries from outpatient surgery. The authors, therefore, recommended that surgeons provide patients with counseling about both aspects of their well-being before surgical procedures. 

Passive data collection could help surgeons reach more informed conclusions about whether a patient is physically ready for surgery, or if they're recovering at the expected rate. A company called BioIntelliSense recently announced a wearable that tracks symptomatic episodes as patients use it. 

The company's BioSticker adheres to the skin and provides up to 30 days of continual monitoring. Besides tracking aspects like resting heart rate, skin temperature, gait and activity levels, the tracker can detect falls and certain symptomatic events, such as sudden bouts of vomiting. 

It can also catch things that patients don't notice, and therefore, don't mention to their doctors. For example, a traditional preoperative assessment may involve a doctor asking a patient if they've had a fever in the last two weeks. It's possible that, even if the person doesn't realize it, they may have experienced a high temperature within that time.

If so, a wearable that passively tracks health data could pick up on it. Then, the information becomes actionable by encouraging health care providers to make decisions that affect a patient's well-being before or after surgery. 

Smartphones Can Work Well for Passive Data Collection Efforts

 
Something else that professionals should be mindful of regarding passive data collection and analytics strategies is that most modern smartphones have built-in tools that make them suitable for gathering information. The material collected could eventually become actionable data that a business uses to grow or change. 

Getting data passively can start by depending on the sensors found on a smartphone. Researchers developed an algorithm that boasted an overall classification accuracy of 99.96% when using smartphone data to infer which transportation mode the device owner used. 

App developers could also benefit from passive data collection if they want to see how long a user played an app, the number of times they launched it during a given day and the sections of the software that kept them the most engaged. 

These examples show that fancy or expensive equipment is often not necessary to make passive data collection succeed. Data analysts only need to start with the smartphone, a device that most people own and regularly use around the world. 

Actionable Results Do Not Come Naturally

 
As this overview shows, there are plenty of ways to get actionable results by using passive data. However, such an outcome will not happen without careful forethought.

Data analysts must consider several crucial specifics, including what questions they want and expect the information to answer, and how they'll apply the findings to aid the business. 

 
Bio: Kayla Matthews discusses technology and big data on publications like The Week, The Data Center Journal and VentureBeat, and has been writing for more than five years. To read more posts from Kayla, subscribe to her blog Productivity Bytes.

Original. Reposted with permission.

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