Data collection for predictive analytics: Throwing our IT dollars away?

Every keystroke you make, every movement you take, someone is watching you. More accurately, someone or something is collecting data on behaviors gathered when interacting with technology. Those of us working in the field of information technology know that the uses are varied and many. We can use the data to understand consumer behavior and adjust advertising and target markets to maximize profits. Through the global pandemic, we learned that we could track behaviors and locations to predict higher risk areas to be better prepared to handle the impending challenges. And, of course, we can use the data to assess feedback to improve our products and services. This is called predictive analytics, and through the use of complex algorithms, the theory is that we can use the data collected to predict future behaviors. Technology leaders today are committing substantial budget dollars to be able to better capitalize on the data that we have been collecting and to leverage that data to predict consumer behavior, buying patterns, and even employee attrition.

We live in a world measured by clicks, keystrokes, motion detection, and location tracking. As IT professionals, we have been largely integrated into the development, management, and analysis of this data collection. But as the world of data warehousing evolves, so has human behavior. This leaves us to ponder, is the data we are collecting of any value?

predictive analytics

Please sir, may I have some more data?

Given the vast amount of information being voluntarily shared, we assume that the data is accurate and therefore of value. But as requests for data collection and feedback increase, so does the correlation to data manipulation. A negative result of the constant barrage of questionnaires, feedback, and surveys that hits us daily is that the quality of the responses is lowered. A very common practice is that of survey begging. Often adopted in cases where positive feedback has a direct correlation to bonuses, survey begging results when the respondent is coached on how to respond to survey questions. Comments such as, ‘We strive to always deliver an above-average product. If you feel that your results were less than above average, please give us the opportunity to resolve your issue so that we can ensure the survey best reflects our efforts.’ Coaching respondents with comments indicating that the organization does not accept feedback less than a 5-out-of-5 would also fall under the category of survey begging. Not wanting to cause any waves or hardship for others, some willingly respond with high scores that do not reflect the true experience.

Incentivizing respondents

When a respondent is rewarded for entering positive responses by way of discounts, coupons, or points toward a free trip, the result is that we may be misled into believing that our product or service is top-notch. Thereby we invest in growth rather than research and development to ensure our product or service is truly meeting the needs of our prospective clientele. Other examples include non-monetary rewards as well as promised rewards in the event that a certain level of success is achieved.

Fear of retribution

Freedom of speech is defined by Wikipedia as “a principle that supports the freedom of an individual or a community to articulate their opinions and ideas without fear of retaliation, censorship, or legal sanction.” As citizens of the free world, the theory is that we are free to express our thoughts and opinions without repercussion. Add to that the adoption of social media as a means of communication, and it would seem that we have limitless terabytes of collected human behavior data to analyze and with which to base our future technology investment decisions. However, freedom of speech is now loaded with a plethora of caveats. We can express our opinions, but only if they are in alignment with the current list of politically correct expressions that may live within the enterprise, the municipality, the greater geographical region, or even globally. The issue is that many live with a fear of expressing an actual opinion. And so, to stay under the radar and not risk fear of retribution, many rank all feedback as awesome, and, although with prejudice, click the accept button on every “terms” document that flashes across the screen. After all, if one does not agree to terms and conditions, one can often not access the service. And so, as individuals, we maneuver through the world of reverse freedom of speech. It is time for the enterprise to be aware that the quality of data collected may be compromised — thereby compromising our predictive analytics.

Finding the right balance

Business productivity and IT security

The challenge that arises in the world of technology is the balancing act as to how much we are willing to invest without confirmation that the data we are collecting for predictive analytics will even be of value to the decision-making process. There are a couple of options. The obvious one is to not invest because we know that overall, there is a high likelihood that the data may be compromised. However, that is an extreme measure and statistically speaking, there is still value in the analysis of a percentage of the data. One option is to partner with an organization that has the talent and has invested in the research and development to ensure that their algorithms compensate for the analyzed percentages of compromised data. TechGenix’s Twain Taylor identifies such companies in his September 2020 article 4 breakthrough data science startups transforming data management. While it is important to be cautious of the spend that would be required to develop accurate algorithms in-house, note that using Big Data to make business decisions is not limited to big business. There are options for the small and medium-sized players as well.

Awareness is the greatest agent for change

Eckhart Tolle said that “Awareness is the greatest agent for change.” In terms of using Big Data for predictive analytics, it is important that there is a high level of awareness that reporting on pure, unanalyzed data can return flawed information that could result in inaccurate decision-making. Engaging the right subject matter experts will ensure that the information that is returned is of value to the enterprise.

Featured image: Shutterstock

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