New research from the Multiverse Skills Intelligence Report found that employees in the UK and US are spending an average of around 14.31 hours each week – equating to 36% of their working week – on data-related tasks. However, 4.34 of these hours are unproductive because they lack the skills needed to do their job. To help clarify the math, the roughly 4 hours per week on average multiplied by 52 weeks in a year yields 208 hours per year; when you divide 208 hours per year by an 8-hour workday, that yields 26 days.
According to Multiverse, the report indicates an inconsistency in today’s data-driven companies, where data has become essential in most positions yet many employees have not learned the basic skills necessary to effectively utilize data that they have access to. The study found that half of those surveyed find it challenging to conduct data analysis efficiently and nearly the same number struggle to use data to tell the company’s story.
Overcoming skills gaps in data-driven decision-making is critical for employee development and organizational success. Here are some best practices to address this looming concern:
1/Assess Skill Gaps: Start by identifying specific data-related skills employees lack. Use surveys, self-assessments, or performance evaluations to understand gaps in data literacy, analytics tools, or decision-making abilities. Tailor training programs to address these specific areas.
2/Provide Tailored Training: Invest in training programs designed to enhance data literacy. Workshops, online courses, and certifications can teach employees how to analyze, interpret, and communicate data effectively. For instance, focus on practical tools like Excel, Power BI, or SQL, and teach foundational statistical concepts.
3/Promote Hands-On Learning: Theoretical knowledge alone isn’t enough. Encourage employees to work on real-life projects involving data. This could include analyzing sales trends, evaluating customer feedback, or optimizing internal processes. Hands-on practice helps bridge the gap between learning and application.
4/Foster a Data-Driven Culture: Cultivate an organizational culture where data is integral to decision-making. Leaders should model this behavior by basing their decisions on data and encouraging teams to do the same. Regularly share data-driven success stories to demonstrate its value.
5/Leverage Mentorship and Collaboration: Pair employees with data-savvy mentors who can provide guidance and support. Cross-functional collaboration can also help employees learn from colleagues experienced in using data effectively.
6/Adopt User-Friendly Tools: Choose tools and platforms that are accessible and intuitive for employees with varying levels of expertise. Simplified dashboards and automation features can reduce the learning curve and empower employees to focus on analysis rather than data processing.
7/Encourage Continuous Learning: Make skill development an ongoing process. Offer access to resources like webinars, articles, and e-learning platforms. Incentivize employees to stay updated with emerging trends in data analytics.
8/Measure Progress: Track improvements in employees’ data skills through regular assessments or monitoring decision-making quality. Use feedback loops to refine training efforts and ensure alignment with organizational goals.
By systematically addressing skills gaps, organizations can empower employees to confidently use data in their roles, leading to more informed decisions and better business outcomes.