Effective approaches to consider when upskilling teams
This article is originally published at https://www.mango-solutions.com
“Education is the passport to the future, for tomorrow belongs to those who prepare for it today”. Malcom X
As Nelson Mandela acknowledged, education is truly the most powerful weapon which can be used to change the world. This year especially, we’ve all experienced the need to be agile, to adapt to changing circumstances and recognise how upskilling and learning is essential to expanding our capability to meet an ever-adapting environment.
It is upon foundations such as these that Mango has built education solutions on; working with data science teams to build future proofing skills aligned to strategic objectives.
A recent survey by Udemy noted the recent and specific emphasis on upskilling and reskilling as a result of the pandemic, with 62% of organisations aspiring to close their skills gap. A key starting point for business is in assessing the skills needed to meet their strategic aims and business objectives. In addition, they need to consider the diverse capabilities across their teams, to truly embrace the right learning culture. Team building and upskilling is an integral part of embracing change for a data-driven future. According to the report by Udemy – data literacy is the new computer literacy.
Workforces with strong data skills across the organisation, not just limited to the analytics team, can help embrace these positive changes. Quite often, it’s the business stakeholders who own the targets and processes who are most empowered by engaging in the data & analytics conversation.
As educators in data science and advanced analytics, we’d like to share some of the most effective strategies when looking to upskilling teams and business stakeholders appropriately:
- Ensure a dynamic, facilitated learning environment – This year, like no other before, saw providers going virtual. Whilst nothing replaces face to face contact, any method that brings your teams together virtually into a real classroom setting, is the next best thing. Applying learning to a workflow requires a mentoring-based approach to help build lasting and best in class capability. Self-learning or pre-recorded lectures have their place but lack the interactive ‘in person trainer’ approach, where wider questions can be answered.
- Apply a unique learning experience so that it is tailored to the market or industry – the ability to adapt to the needs of a diverse group is a core skill as a trainer. Practice exercises tailored to help beyond the classroom will allow newly applied their skills to be incorporated into a daily workflow.
- Ensure training partners have real world experience from industry – the ability to showcase relevant examples and not just the theory, can really help bring a programme to life. In our experience, the ability to share and provide value via real-world applications, combined with practical, proven approaches and best practice advice, is key.
- Choose courses as an integral part of a leaning pathway – courses for individuals and teams should be chosen as part of learning pathways to fill any capability gaps. Processes which invest in capability, with ongoing development of skills are proven to help staff retention. There should also be processes in place to retest these new skills.
- Demystifying data science – the ability to establish a common language between all functions of an organisation is essential to a collaborative partnership. This depth of understanding will then ensure a close alignment between analytics and strategy, supporting any barriers to change.
Following the delivery of a recent training programme delivered to AstraZeneca, Gabriella Rustici-Data Science Learning Director, commented:
“Having worked with Mango previously on a training project, we reached out to them as a trusted partner to assist us with a data science training initiative which involved helping cohorts from our R&D data science function embark on their R journey. We were also looking for a workshop to help our scientists ‘demystify’ data science and understand the terminology – establishing a common language between scientists and data scientists.
Mango helped us create a remote virtual classroom R training program, which included support surgeries designed to enable participants to really absorb what they had learnt from the program. Feedback received from course participants was excellent, with comments such as: “ The instructor was great, really patient”, “The instructor was very enthusiastic, clearly knew their topic and the learning material was great”, “ I got a lot from the course” and “I’m keen to learn more R, hopefully with Mango”. The workshop was well received and has certainly given us a good start to increasing awareness of what data science can do.”
About Mango Training
Whether you’re seeking R training courses, Python training courses or more, our comprehensive training programmes are specially designed to guide practising data scientists and data engineers from breakthrough to mastery level in R programming, Python, Shiny, AI/ML and more.
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