The tech industry is facing an alarming shortage in data-savvy talent. Despite reports showing men and women earning STEM degrees now more than ever, the hunt for experts in areas of machine learning, data science, and other “hard sciences” fields continues. Gartner reveals that “50% of organizations will lack sufficient AI and data literacy skills to achieve business value by 2020.” A shortage of people is not the underlying problem. The root issue is a lack of data literacy available among potential—and current—talent.
What is data literacy?
The Massachusetts Institute of Technology (MIT) defines data literacy as “the ability to read, work with, analyze and argue with data.” In short, it’s a skill that has been promoted by Gartner, FastCompany, and other leading companies as the most influential predictor of business success in tech today.
While data may be the underdog champion for any business intelligence strategy right now, confidence in data is low. Organizations are losing their competitive edge because greater data literacy increases higher enterprise performance—85% of data-literate workers say they are performing “very well” at their jobs, compared to 54% of the rest of the workforce (Qlik).
Even for digital natives like Millennials, Forbes indicates data literacy sat at only 22%. If you think that’s unsettling, the Wharton School of the University of Pennsylvania discovered in the same study that just 24% of senior decision-makers passed standard data literacy tests.
Yikes.
That’s not to say businesses aren’t trying. It’s a high-quality problem, one where we are moving a lot faster than the upcoming workforce and the rest of the current enterprise system can keep up. And not to much surprise, slower-to-innovate industries like commercial air travel, retail, education, and government are getting hit the hardest. In fact, Getting Smart reveals that “just one-fifth of students ages 16 to 24 years feel comfortable interpreting and applying data.”
What’s preventing data literacy from becoming widespread?
Sure, the majority of research facilities like universities, labs, and data-driven companies are making strides in technological advancements. The Society of Experiential Graphic Design reveals a few common barriers to adopting data literacy within certain organizations:
- Current big data software is already complex thanks to new waves made in deep learning and other data science
- Certain enterprises do not have the computational or talent infrastructure to store, analyze, and make full use of big data, and
- The concept of data is still foreign and even dry to many non-technical audiences, both in and out of enterprise culture
Barriers don’t just stop at technology—politics and even socioeconomic systems are factors too. (For example, Sweden has the highest percentage of enterprises where everyone is empowered to use data at 33%; Japan is at only 13%.) Barriers to data literacy include access to technological resources around the world, the rapid evolution of technology before humans can keep up, and the lack of current experts available worldwide.
If data is as obscure to most C-suite and senior management figures as research indicates, companies not innovating sooner will be in a lot of trouble at the turn of the decade. Neglecting consumer trends and demand is not only costly but bad for entire industries. Airbnb is a classic example of a business that took advantage of design, performance management initiatives like BPM, and data to understand users needs to build a better solution for its customers. Because of Airbnb’s proactivity in leveraging data’s power in its business model, the entire hotel industry is now threatened.
Fortunately, there are initiatives you can take to improve data literacy in your organization so this doesn’t happen to your business.
(Sourced from Unsplash)
Encourage a data-driven culture
Data literate professionals have always been hired by data-driven companies. The problem is addressing the organizational silos that occur as a result of keeping those experts confined to only IT or intelligence departments. Since departments and teams are becoming more interdependent on one another to generate more customer satisfaction (and thus, profit), companies need to include these experts where the decision-making is happening—for most larger enterprises, that’s in the boardroom.
What happens when that doesn’t occur? The scary reality is that the majority of enterprises today won’t exist in the near future due to a lack of prioritization about data.
Due to changes in the digital landscape of business, approximately half of the companies currently on the S&P 500 will be replaced over the next decade (Inc).
Microstrategy’s Content Director Tricia Morris attributes this to what she calls “digital Darwinism,” or business’ ability to adapt successfully in the age of the information revolution. Companies with a “future-back strategy” that understand the future is now may have a better chance at surviving, according to Innosight research.
Often, the main hurdle to changing a less-technical company privy to the power of data starts with mindset. Many enterprises have embraced C-suite titles like Chief Intelligence or Innovation Officers, but these titles tend to focus more on leveraging business intelligence strategy, not necessarily leveraging the power of data to boost revenue strategy.
A lack of qualified leadership and ethical business decision-making on the executive board can undermine the authority and confidence of an entire enterprise (Uber is still recovering from this issue). To combat this, enterprises can focus on building stronger relationships among external and internal stakeholders, and as well as the nurture of a future Chief Data Officer (CDO) among its network, an organizational head that can help mitigate common pitfalls found as a result of data illiteracy.
But change cannot happen overnight. These processes require a change from within from the leadership board to inspire growth within a business. CDOs cannot give marching orders to their employees expecting to spur change. Instead, they must “use emotional and rational arguments” to win over stakeholders, counteracting the often unsexy perceived nature of data among non-technical team members. Failure to educate your current employees and consumer base could result in becoming one of ten known companies to go out of business because of lack of innovation, as found by Collective Campus.
It’s not just about losing a competitive edge on the organizational level. Not taking care of current employee talent leaves dangerous wiggle room for employees to fall behind. And this change as to come top-down, CMS Wire suggests.
“Stop believing in unicorns,” warns Tamara Dull, Director of Emerging Technologies for SAS Best Practices. “Big data deserves a seat at the table, but it doesn’t need its own table.” Dull doesn’t believe in a one-stop-shop solution. Instead, she opts for companies to change their approach to developing a culture that encourages data literacy. Soft skills like leading by example, effective communication, and understanding KPIs in relation to business strategy can transform a company’s current elasticity to innovation.
So, we know that encouraging human-centric basics in business can ripen a data-resistant workforce to change. But what about closing the data literacy divide in technical skills? One strategy involves being proactive rather than reactive in regard to on-the-job training.
Invest in current talent
Instead of reinventing the wheel by searching for top talent elsewhere, Mike Gavin believes enterprises can take advantage today by investing in current employees.
Gavin leads Corporate Training at Metis, a data science and analytics training company. As a far “upskilling” non-technical talent, the lessons “enable broader staff to identify and scope problems within the business and to perform initial analysis without needing the help of a highly technical person, “ he says in an interview with Burtch Works. “It also improves communication and collaboration between teams.”
Metis isn’t the only company to hop on the coding Bootcamp or analytics academy train. Popular EdTech companies like Coursera, Udemy, and General Assembly specialize in offering certificates in data science, programming, or Business Analytics 101 for the not so data-savvy individual. Even cloud technology giants like Microsoft Azure, AWS, and Google Cloud now offer certifications in data science.
But don’t worry about these companies not delivering top-notch value. Students can expect to earn industry-recognized credentials that boost salary earnings on top of skills learned. Udacity takes this one step further by partnering exclusively with Google to offer nano degrees, or small degree-like programs designed to address the lack of technical talent available in current enterprise institutions.
The result of these training initiatives? Recruiters are seeing improved data literacy among job candidates with new skills recycled back into the workforce, all at a fraction of the cost associated with employee churn. Retraining may cost a lot up front, but the savings payoff is estimated in the millions thanks to happier employees and increased job satisfaction from the new skills acquired.
It sounds like a win-win to us.
Build a data literacy program
Finally, the last strategy to improving data literacy in businesses is by investing a little elbow grease into developing easily accessible data literature designed to educate multidisciplinary teams, both in and out of the C-suite.
For companies in the SaaS space like Business Process Management software (BPMS), quantitative metrics relying on data are key performance indicators of efficiency in the customer’s eyes. Teams outside of the IT department need to be able to communicate the business value of such software, a task that requires time and attention across an entire organization.
Typically, translating technical jargon is done through hiring a knowledgeable technical writer or relying on the acumen of a highly-trained Product Manager. While these practices aren’t discouraged, implementing data literature on a regular basis is an effective alternative to just relying on a data-fluent liaison to play the role of the messenger.
For implementing, Qlik recommends following a four-step process: communication, assess, train, and iterate. It’s not going to happen overnight, but making the effort at least gets the transformation started.
A look to the future
Data literacy is becoming one of the most sought-after skills an organization can have in lieu of technological advancement. While current reports show that the majority of senior-level executives, employees, students, and the wider workforce is not data confident, there are initiatives and resources available to encourage greater fluency in interpreting data across the enterprise system.
Bottom line: Don’t let your company fall behind because of not prioritizing this critical (and proven) predictor of business success. Invest in the resources you need to overcome the challenges against barriers today by adopting data-driven practices that drive forward your business intelligence strategy, like Business Process Management (BPM).
About ProcessMaker:
ProcessMaker is an American international SaaS corporation headquartered in Raleigh-Durham, North Carolina. We provide total customer support, training, and professional services to larger enterprises requiring highly-customized workflow solutions with our Business Process Management (BPM) software. Our flagship Low-Code product is the preferred choice for our customers due to its deep customization ability with little programming knowledge needed, making Low-Code an easy-to-use solution among non-technical teams.
