Chief Data Officers continually cite lack of relevant skills or staff as one of the top internal organisational roadblocks to success. The Gartner 2018 CEO Survey finds this too, with respondents listing a “lack of appropriate talent and capability in the workforce” as the biggest barrier to digital business progress.
Typically siloed teams in modern businesses mean managers are often unaware of what their existing teams are capable of, or what new skills are needed to plug the gaps - data and analytics ranked first among tech-related skills that CEOs seek most.
“By 2023, data literacy will become an explicit and necessary driver of business value, demonstrated by its formal inclusion in over 80% of data and analytics strategies and change management programs” – Gartner analyst Andrew White
When it comes to data analytics, building the winning team is all about aligning business objectives, demonstrating value and ROI to the organisation, high performance at the task, and then retaining that team talent to fight another day, on another project.
Quite a balancing act, and no mistake. For an L&D lead in data science or manager of the team, solving the problems boils down to:
At Mango Solutions, we know a thing or two about the issues faced by the implementation of data analytics and the importance of building a data-driven culture and an effective analytics capability to meet those challenges; one step towards tackling these is through building an internal analytics community and understanding the three key challenges that companies currently face in becoming data-driven.
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That’s exactly why Mango Solutions has created Data Science Radar. Combining nearly 20 years of consultancy experience with our own SaaS (software-as-a-service) platform, Data Science Radar is a full service package with everything you need to assess competence in your team members’ data science skills, while determining and building unique profiles.
Blending team requirements with business objectives, swiftly understanding skills and capability of your data science teams, and planning their developmental journeys mean you can fully resource projects large and small with total organisational alignment.
You can’t be a data-driven business if your teams can’t work with the data, and you can’t build data teams unless you understand the skills required, and how to leverage them.