Are Millennials the Answer to Your Company's Data Analytics Problem?
Ready to embrace the millennial mindset for your data analytics? We offer five tips for encouraging the budding data analysts in your own organization.
By Paul Ross, Vice President of Product and Industry Marketing, Alteryx
Bashing millennials is very much in vogue. Articles complain about millennials or offer advice on how to manage your "problem millennial" workers. Many of the grievances seem to fall under three recurring themes: millennials have no respect for authority or hierarchy, they refuse to follow directions, and they have a rebellious nature and question everything.
As a member of Generation X, I can recall similar complaints being lodged against my cohorts and me when we first entered the workforce. The truth is, the newcomer generation is never all bad, and, in fact, many of the millennials' so-called shortcomings may actually be assets for data-driven companies. In particular, the character traits and profiles of millennials align exceedingly well with the evolving skill set and workplace demands for data analysts. Are you ready to entrust your company's most strategic data analysis and decisions with a millennial?
Growing Demand for Big Data Analytics
Before we answer that question, consider that in the era of big data, customer engagement, unique offerings, and smarter processes are just some of the important goals companies want to achieve through better insights into their data. Businesses are eager to hire data scientists -- elusive workers who possess a rare combination of technical engineering and statistical reasoning skills -- but these data scientists are extremely hard to find and very much in demand. As a result, there is a gap between big data dreams and the reality that many companies still struggle to analyze their data.
Fortunately, two key factors are emerging to deal with this challenge. First, the legacy approach to analytics is being abandoned in favor of tools that promise to simplify big data by making analytics accessible to more line-of-business users. Second, millennials are beginning to disrupt the workforce. These factors are causing a huge shift in the 30-year-old data analytics market.
A new guard of technology vendors is outpacing the old guard with innovation driven by end-user requirements (including what millennials are demanding -- more on this later) such as intuitive interfaces that do not require a Ph.D. or years of dull SAS coding in order to manipulate data. New self-service analytics platforms are empowering data analysts in every line of business to discover problems and identify solutions. With better tools and data at their disposal, today's analysts are discovering critical insights with the potential to shift entire industries. Increasingly, companies live and die by their data, and this has changed the perception of data analysts. In many of the organizations I work with, data analysts are the ones driving change -- they are ones making a difference and carving a role out for themselves in the new data-driven economy.
Millennial Data Analysts
How does this relate to the arrival of millennials in the role of analysts? Raised in the tech era, millennials are digital natives who learn new technology and tools quickly. This trait is a perfect accompaniment to the new analytics tools that put the power of data into users' hands immediately without requiring IT intervention. In the same way that millennials taught themselves to use their iPhones, they can easily learn to manipulate data in the new user-friendly analytics platforms without extensive and time-consuming training. With the right tools and a quick study of the technology, new "millennial-minded" data analysts can immediately begin to provide value from data, uncovering essential business intelligence to guide enterprise decision makers.
Let's take a look at the three traits of millennial data analysts mentioned earlier.
1. Millennials have no respect for authority or hierarchy
This "shortcoming" is actually an asset. The positive spin on this trait is that millennials are eager to jump in without concern for the long, laborious traditional model. They feel no need to work their way up the ladder until someone gives them the keys to the data kingdom; they are ready immediately.
What does this characteristic mean for the data analyst role? The best data analysts are eager to dive right into data exploration to uncover new insights. Rather than waiting for authorization, data analysts hit the ground running to discover the secrets hiding within records. New self-service tools make this agility possible.
2. Millennials refuse to follow directions
Don't turn your back on this signature millennial trait: millennials hate simply being told what to do; they want to know the why so they can pave their own path to the goal.
The best data analysts think creatively and need context. This critical millennial trait is perfect for data analysts, who must creatively look at data to think of new questions no one has asked before. Because there is minimal value in siloed datasets, analysts must creatively blend disparate data to uncover the key insights that decision makers need. For example, a millennial-minded data analyst presented for the first time with an important business problem may decide to combine two completely unrelated datasets, resulting in a viable solution a company never would have expected.
3. Millennials are rebellious in nature and question the status quo
If you've grown weary of this well-known and well-publicized millennial trait, then you might be missing out on your next great hire. By questioning everything, millennials are able to spot ineffective business practices and other issues that other workers might overlook. Big-picture and analytical thinking come naturally to this generation.
In the data analyst role, a millennial mindset can uncover new and surprising insights: For example, if asked to solve a given business problem, the millennial-minded data analyst may question whether the problem truly exists in the first place and prove through data that the perceived issue is not, in fact, a problem at all.
Just as generational workforces shift, I expect there will be a cultural shift in the workplace to value these millennial traits that today may seem counterproductive but are actually important attributes for enterprise data analysts. Millennials arrive without what writer Merlin Mann describes as "expectational debt"—a crippling effect caused by overly ambitious goals or unrealistic expectations—so they can cut through the slow process that analytics has required until now. The fusion of big data demands and self-service analytics will have a huge influence in the business world as data analysts increase their organizations' value.
Far from being "problem" workers, millennial-minded data analysts are quickly becoming the heroes of the enterprise, driving change and economic growth through fact-based decision making. The most successful companies in the new data-driven economy will be those that encourage a "millennial" mindset and cultivate employees at all levels into modern data analysts.
If you're ready to start embracing the millennial mindset for your data analytics, here are five tips for encouraging the budding data analysts in your own organization:
- Give them the tools they need to be independent (empowered data blending and advanced analytics without IT handholding).
- Give them data that matters.
- Give them the tough problems that haven't been cracked yet.
- Let them know that data analysts have a very important role in the organization. The insights they uncover from data have the potential to sway major company decisions.
- See what happens. You just might be surprised.
Paul Ross is vice president of product and industry marketing for Alteryx. Paul has spent the past 15 years of his career helping users and decision makers connect with the value of technology, especially the value of making analytics and using data as simple as possible. You can reach him at email@example.com.