WYNTK in Analytics Right Now
The demand for data scientists is quickly surpassing the rate at which students are training and entering the workforce, and everyone in the tech sector should take notice. According to a recent LinkedIn Workforce Report, there is currently an estimated shortage of 151.7K data science professionals in the U.S. alone.
This shortage is becoming an immense problem as more companies recognize the value of data and analytics in making informed business decisions. In a recent Forrester survey, 90% of global data and analytics decision-makers indicated that the use of data insights in business decision-making would be a priority for their firm over the next 12 months. It’s clear that businesses want to shift from gut-driven to data-driven decision-making, but they lack the talent and tools to do it.
The talent gap isn’t getting smaller anytime soon. In fact, the lack of an adequately trained workforce will continue to worsen over the coming years.
According to the World Economic Forum, by 2022, there will be 58 million net new jobs. While 75 million jobs will be eliminated due to technological obsolescence, the rise of digital enterprises will create 133 million new jobs.
Critically, the most in-demand jobs include data analysts and scientists, AI and machine learning specialists, software and applications developers and analysts, and big data specialists. In other words, don’t worry about being replaced by robots, but do consider whether your skill gap is widening.
Challenges Data-Focused Organizations Face
The world is becoming more and more data-centric, with an estimated 2.5 quintillion bytes of data created every day, according to an IBM study. As the amount of data for processing, analyzing, and operating business continues to grow at an exponential rate, businesses are frantically searching for a solution to automate manual data analysis and processes.
Businesses are facing key issues of analysts not having adequate technical support from data scientists, along with the need for processing and analyzing spatial and consumer data. As innovation continues to increase at a faster pace, these companies are struggling to implement a data-focused approach. The bottom line is that businesses need to develop a workforce that is able to address these growing needs.
Yet these are the toughest jobs to fill, as they demand premium salaries and advanced degrees, and businesses are subsequently having to recruit external talent in order to fill the gap. In fact, 51% of decision-makers engage external services or strategic business consultants for data and analytics or insights services, and another 22% expect to in the next 12 months. Additionally, faster-growing firms are more likely to reach out for help, with 62% of high-growth companies engaging insights services providers, versus only 45% with slow to no growth.
What Companies Have to Say
At Inspire Europe 2018, a roundtable of Alteryx customers, partners, and Alteryx for Good champions who help nonprofits make smarter decisions with data came together with local London press to discuss the growing chasm in data science and analytics. Although there was a clear undercurrent of uncertainty across the general market, some interesting stories emerged on how these companies are using Alteryx to address the talent gap from within by leveling up the skills of data analysts and allowing them to advance along the way using self-service analytics. These companies recognized the opportunity to leverage existing talent and build best practices and communities internally.
Both Sainsbury’s and COPA Airlines took advantage of the quick learning curve of the Alteryx Platform to build and extend skills internally within data science and analytics. By thinking outside the box around how they are growing talent within their organization, they have demonstrated a passion for creating a data-driven culture within their communities.
COPA Airlines began by looking for younger employees with a different way of thinking when it came to creativity and math. Senior intelligence analyst at COPA Airlines, Isacar Racine Rodriguez, said, “Young people tend to be more willing to learn new things — that’s a really key skill because the rate of new tech coming out is so high — no single person can learn it all … companies should be helping their younger team members get to grips with things like AI and its potential.”
Echoing the sentiment of empowering the younger workforce with technology like Alteryx to simplify data and analytics, Samantha Hughes, analytics systems developer at Sainsbury’s, said, “I didn’t know SAS or any other complex technology when I took on this role but was able to learn Alteryx quickly. It is important to have a tool that people can use — it is not about overcomplicating, it is about simplifying."
"It is important to have a tool that people can use — it is not about overcomplicating, it is about simplifying."
According to Hughes, a key element of enticing the younger generation to embrace data science and analytics is showing them that the process is enjoyable. “I think part of the problem is that the data role isn’t fun, but there's no better thrill than uncovering something new in the numbers and making a ton of progress,” said Hughes.
Breaking on Through
Millennials and Generation Z — fast coming up through college and entering the workforce — are part of the answer to data engineering shortages and rising IT and data compliance challenges. They are completely digital — understanding data, being analytical to data sources, and holding a wider view on making the best use of data assets than previous generations.
Combined with the experience of leadership, who can identify the highest-value problems in the organization and create the strategy for solving them, the latter workforce will empower the entire organization to take on bigger and more meaningful data and analytics challenges and foster a data-driven company culture. The data-driven generation needs to be paired with experienced members of the workforce who can see the forest — identify the highest-value problems to be solved and create the strategy for solving them. Both are important, both are valuable.
Companies need to develop data science and analytics culture across the business. This applies to all companies, not just those in the tech sector. As the world becomes increasingly driven by data, all businesses will need to leverage data in some way, shape, or form in the coming years. Businesses can address the gap by preparing the next generation of data experts, searching from within to leverage home-grown talent, and enabling self-service automation tools that allow all levels of employees to develop their data science and analytics abilities.
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