In this guide I’d like to talk about the importance of data management along with what properly managed data should look like and the effect it can have on a company. It’s an important topic because over the past few decades we’ve seen a massive increase in automation, resulting in data quickly becoming a foundational building block in business strategy. When we compile that with cloud-based platforms, even the smallest business can utilize automation at some scale. Our reliance on data is only going to increase, causing companies to lean more heavily on machine learning to help guide them in decision making. With all that being said, it’s fair to assume data management will soon become a major factor in determining the success or failure of a company.
When we talk about companies becoming more data driven, I think it’s important to understand just how encompassing the process really is and how it shapes a company. The first step should always begin with the leadership team establishing a clear data strategy, giving the company guidance on how it will leverage their data to make or save money in the future. With a road map in place the company can move forward with the development of sound data management systems. This includes acquiring, validating, storing, protecting, processing and managing the accessibility of data for its entire life cycle. When managed properly, companies are able to develop a strong culture that embarrasses data driven decisions, leading to a great deal of success. When poorly managed companies open themselves up to unnecessary risk and possibly jeopardize their future success. Now, let’s take a look at a couple different companies and how data management affected them.
Netflix is a great real world example to use because when their media platform first launched their success hinged solely on how well they were going to be able to manage their data to produce a truly individualized user experience. I’m pretty sure we all know how it turned out for them, but let’s take a look at an infographic that was published in 2018 by FrameYourTv that illustrates how Netflix uses big data to enhance consumer experience.
Netflix has done an amazing job with their data management systems and it’s pretty remarkable that after ten years they are still using only a slightly modified version of their original predictive algorithm, their system influences about 80% of the content played, they accurately predicted the success of their first original series House of Cards all the while saving a billion dollar a year on customer retention cost. I think it’s also cool to note that through all their success they don’t share or sell data, and have managed to avoid any major security breach.
In our second example I’d like to talk about a web service Google released back in 2008 called Google Flu Trends. The idea stemmed from Google’s previously collected data that suggested that when people got the flu, they started searching for flu-related information. So, with some help from the Centers for Disease Control and Prevention, Google began mining data records of flu related search terms to produce a results model that almost exactly matched the CDC’s data. Flu Trends started off okay, but came across its first big problem when it underestimated the 2009 outbreak of “swine flu.”
Google attributed their inaccuracies to changes in flu-related search behaviour, so in an attempt to fix that they decided to revise their algorithm by expanding and modifying their search query.
Needless to say, the revisions over corrected a little too much because four years later, during flu season, their algorithm overestimated flu levels by about 140 percent.
Google ran into the same issue as before with its query searches. Because searching for terms like “sore throat” or “stuffy nose” didn’t necessarily mean people were searching for flu-related symptoms. For all Google knew people were doing research on how data collection from search queries could potentially produce inaccurate models. I think it’s important for us to discuss a case like this because it shows that even a billion dollar company like Google is susceptible to improperly managed data. With no real way for Google to determine the intent of every query search, it made it nearly impossible for them to know if they were getting quality data or not.
Hopefully these examples show the importance of data management and how relevant, complete, accurate, and meaningful data can help a company grow. And if data isn’t managed well it can prove to be useless and even harmful to an organization.
How Netflix Uses Big Data to Drive Success
Assessing Google Flu Trends Performance in the United States during the 2009 Influenza Virus A (H1N1) Pandemic
When Google got flu wrong
