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Upskilling in a Data-Driven Workforce

Upskilling in a Data-Driven Workforce

Organizations across the globe have recognized the need for digital transformation to compete in the current business environment. Gartner reports that less than 50% of business strategies reference data skills as a vital factor for supplying organization-wide value. According to Mike Rollings, Research Vice President at Gartner, “leaders need to look at data first to succeed in their digital initiatives, rather than treating them as an afterthought to help with ad hoc projects.”

Upskilling has become imperative. According to the World Economic Forum, 54% of existing employees will require considerable reskilling and upskilling by 2022. Of those requiring new skills, 35% will need additional training of up to 6 months or longer. Several organizations are now realizing the importance of upskilling and reskilling employees to cope with the demanding and changing landscape of employee roles and practices. However, there is also a huge delay when it comes to reinvesting in employees for many others.

WEF’s Future of Jobs Report for 2020 says that the window of opportunity to reskill and upskill employees is becoming shorter in today’s market. With the recent economic downturn, organizations need to provide stronger support for those needing to be reskilled or upskilled. By 2025, 73% of organizations state they will provide reskilling and upskilling opportunities in order for employees to perform their jobs correctly and efficiently.

Common Trends Driving the Need for Data Upskilling

With the advancements in technology and digital transformation being at the forefront of strategic initiatives, there is a need for more tech-savvy, data-specific roles for most everyone within an organization. The COVID-19 pandemic has sped that transformation for most organizations.

With technology heavily influencing the way organizations are run, the requirement to upskill current employees’ data science competence has begun to emerge. Now and in the future, organizations need to be aware of these trends so they can future proof their teams and be more attractive and competitive for prospective talent. Here are some of the most important points to keep in mind.

1. Data analytics is universal. Instead of just being stored, data is an enterprise-wide asset that can be leveraged by just about everyone to generate profit. As the volume of available data increases rapidly, organizations must continuously assess and evaluate the best way to use it. Having team members that are skilled in data analytics is imperative.

2. Emergence of AI. With artificial intelligence and machine learning, systems are getting smarter and doing more every day. The potential for AI to automate mundane and repetitive tasks means a significant shift in the workforce. While we worry about the displacement of the workforce, many opportunities will exist for employees to transition to higher-level roles. Start upskilling your team now to stay ahead of the curve to show value and ROI.

3. Data-driven performance. Employees and organizations are continuing to fall behind on performance as the skills required to decipher big data are lagging. Upskilling your team to understand and interpret will help your organization sustain itself for the future.

4. Skills gaps and shortage of talent. According to a McKinsey survey, data analytics is the biggest skill gap noted throughout organizations. McKinsey states that over 40% of organizations confirm it is an urgent priority and crucial for overall success to upskill these gaps.

5. Cross-functional teams. In order to reach company-wide success, it has become imperative that data analytics crosses various teams throughout an organization. Incorporating a diversity of skillsets combines teams working towards the same goals.

6. Bottom-line cost. Hiring and onboarding new employees is expensive. Organizations are finding that it is a lot more cost effective to upskill current employees instead of hiring new talent. Keep in mind, with data skillsets come higher salaries as well.

As the demand for data skills increases, and talent shortages continue, it is imperative to upskill your teams now. By upskilling current employees instead of searching for high-salary new talent, most organizations will come out ahead.



Create a Foundation for Development

Creating foundational skills in data science will not happen overnight. Organizations need a plan to succeed and imagine the big-picture scenarios of how developing skillsets and upskilling current employees will benefit the organization. Leadership needs to fully understand the current skill levels of their teams, understand where the gaps in skills really are, and decide which format will be best for learning and development through upskilling. Create individual job-based development and training plans specific to individual learning need and ensure that success can be tracked and measured.

Steps for Successfully Upskilling your Employees

  1. Identify and predict your organization’s data skill needs, identify competence gaps (knowledge, skills, behaviors, attitudes, etc.), and create learning paths for successful upskilling.
  2. Invest in, develop, and provide effective training for all employees.
  3. Anticipate and adapt to changes your organization may face and make L&D a vital part of every employee career path.

Keep in mind the need to upskill for both hard skills and soft skills. Not only is data science critical for future business success, but it cannot happen without the broader soft skills such as communication, problem solving, relationship building, and adaptability. Having comparable soft skills training enables employees to enhance their technical skills and improve their ability to learn and absorb more strategic information.

The ability to make data-driven decisions is and will continue to be a core competence. By committing to upskilling programs for your workforce, you can help position your organization for success. The most effective leadership teams lead by example and keep their skills sharp. Establish data-related skill building priorities and invest in training. Empower your employees to embrace a data-driven workforce and always remember that the most important investment for your organization is in your people.

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