Authors: Hanns Aderhold and Bastian Halecker

More than 75% of western companies predict their industry will be significantly affected by digital transformation in the next three years. Automation and rapid increase in data volumes are the drivers here, even in the most traditional industries. In the light of this, organisations themselves should become the force for digital transformation in their respective industries by iterating and evolving strategies, products, services, and business models in ever shorter cycles. To achieve that, organisations must become good at quickly learning how to do new things and how to experiment rapidly, frequently, and economically. Learning how to do new things means focusing on the adaptability of talent both for the organisation and for each employee of the workforce.

With new talent analytics and management tools that combine data from internal talent pools and external talent trends intelligently, organisations are starting to manage their talent resources with an accuracy and immediacy comparable to stock brokerage or online banking. This is showing a direct impact on their capacity for adaptation and innovation:

1. On an organisation level managers are using these new talent analytics and management tools for steering the geographic and organisational distribution of talent pools, identifying relevant talent gaps for talent building initiatives, prioritising and tracking learning and recruiting efforts, and managing the ongoing integration of the growing temporary workforce.
2. On the employee level these new tools allow for a personal and fine-grain support in individual talent build up — Comparable to the development of individual online ad targeting. As these tools continuously analyses existing data sources within the enterprise, they require much less effort in manual documentation of skills by each employee, instead they can re-focus employee interaction on selecting and tracking automatically recommended talent-building focus areas and training offers.

Next to putting above mentioned new software tools to work, companies must set up a culture that inspires and supports rapid learning and new talent adaptation:

1. Provide infrastructure, governance, and budget that allows for implementation of new experimental digital technologies on top of data lakes and product samples dedicated for experimentation.
2. Incentivise ubiquitous data-driven decision making and provide open and easy access to self-service data analytics tools within every employees workspace.
3. Advocate for cross-disciplinary collaborative project teams between different departments, external partners, customers, suppliers and freelancers. These types of small teams are frequently the origin for strong innovations, but also help employees discover new skills that they could end up adding to their personal skill profile.
4. Implement personal skill tracking and management wherein each employee can access a digital skill, training, and work profile of herself/himself, so that the employee has full control of her/his talent-data.

Figure 1: Shifting demands, competing priorities: Adjusting to the new talent realities in financial services

Talent adaptability is a key foundation for achieving continuous and fast digital transformation cycles that are a core requirement for an organisation’s survival today and for its growth tomorrow. A culture that supports learning new things and data-driven software tools for managing talent resources in real time are crucial companions on that path.

Hanns Aderhold is the CEO and CoFounder of Cobrainer — A machine learning-based expertise management solution that helps easily identify, track and manage expertise strengths and gaps both for individuals as well as for entire organisations.

Bastian Halecker is the CEO of Nestim – A company that match entrepreneurs, managers and ecosystems to create innovations at the core of the digital age.