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With over half of Analytics teams struggling to find and retain talent, the battle for talent rages on. The pace of development in the data space and tech giants hoarding talent complicate things further. Partnering with a solutions provider to keep up with the pace of technology advancement and empower current employees may be far more sustainable in the current environment.

The leadership a Center of Excellence (CoE) provides in terms of platforms, best practices, support and training for different focus areas can be a game changer, empowering organizations in their transformation journey.

Take a look inside first…
Current team members already know the business processes and may not only have the baseline skill Current team members already know the business processes and may not only have the baseline skill sets, but more importantly, the interest to grow into certain high-demand roles. The first step is to identify current employees who want to learn a new role or increase their data science responsibilities. Many managers have been surprised by what they find about their employees on LinkedIn once they’ve looked, especially since their own employees often have a better sense of growth opportunities outside of their own organization.

By empowering your teams with specialized platforms and systems for them to scale across the organization, a Center of Excellence can become your secret weapon.

Support with better tools and processes…
There are significant inefficiencies affecting the potential of data science teams, and menial tasks like data cleansing & processing that steal the focus of specialized data scientists. In many cases, companies have the necessary staff but lack efficient processes. Strategic vendors can often manage certain tasks more efficiently than internal teams with specialized platforms that can improve the organization of such projects.

A completely different approach to the losing battle of acquiring talent is to make more strategic investments into technology adoption to achieve digital transformation goals. By shifting from a DIY approach with AI adoption to working with strategic vendors that provide higher-level solutions, these companies are both reducing cost and augmenting their own talent. These solutions can include the expertise required to deploy and maintain them, and more importantly, should enable up-skilling. Freeing up a company’s data scientists to focus on the toughest challenges and a better all-round use of existing resources means immediate ROI.

CoEs & Flexible Delivery Models are key
A CoE, or a central bureau model that embeds within other departments to complete a project and move on, has the effect of incubating pockets of data science talent throughout the company. Regardless of how ‘advanced’ or grand the vision for digital transformation can be, it all hinges on adoption. Consultancies or solution providers that have an ‘empowerment’ approach are usually differentiated by two propositions. The first is flexibility in the delivery model, from an end-to-end solution to advisory or implementation & support. The second is the experience of working with multiple technologies and deep understanding of digital transformation at an organizational level in order to help with ensuring adoption. A platform, practices and support for both data and business functions can be far more effective than hiring to create a solution that ends in disuse. Early successes can also have other positive knock-on effects in terms of hiring as well. There’s no single path to stronger recruitment, but technology advances that are both creative and consequential always draw the greatest talent.