- September 6, 2021
- Posted by: Aanchal Iyer
- Category: Big Data Analytics
T-Shaped Teams – The Future
In a McKinsey Global Survey report published recently, 87% of leaders admitted to having skill gaps in their workforces – and despite this admission, more than half of the leaders who responded to the survey didn’t have a plan to overcome this issue. The pandemic has only made this issue more serious – the need to upscale employees has increased. We are now staring at a hybrid model where the most valuable employees are interdisciplinary. A T-shaped person is a Subject Matter Expert (SME) in one area at least and skilled or knowledgeable in several others.
A T-Shaped Team
The vertical bar on the letter T indicates the depth of an employee’s expertise and skills in one field, while the horizontal bar is an employee’s capability to collaborate across multiple disciplines with experts in different areas and apply their knowledge to other fields. In simple words, T-shaped employees are excellent in their main/primary tasks and also perform other tasks efficiently. Along with technical skills, such as design expertise or proficiency in programming, T-shaped employees also have cognitive skills, such as creativity and emotional intelligence.
For AI and Big Data Adoption
AI and data science will result in the most significant changes in the financial services industry. However, at present, a lot of financial institutions are still finding it hard to begin their AI journey. Incorporating big data techniques and AI in the investment process is vital for the success of future investment professionals and investment firms alike. And as many financial firms are finding it hard to start adopting AI, these firms are not sure what to do to prepare themselves for the expected change. This is where T-Shaped teams can help. Developing cross-functional T-shaped teams that improve collaboration between the technology functions and investment, accomplished by building on an individuals’ T-shaped skills in data science and investment can enable various investment organizations to adopt AI and big data successfully.
The idea is in fact, quite simple: technology, more specifically data science and Artificial Intelligence is such a different discipline from investments that it takes an additional function, which we call the innovation function, to join them and form a consistent AI-age investment team. Globally, the financial services industry is enthusiastically trying to transform from Stage 0 in AI adoption to Stage 1 (where the organization has implemented at least one AI project). Not to underestimate the talent, cost, and technology hurdles in AI adoption – the single most impactful factor in this transition is the management vision. Senior executives will have to make a jump at this stage and turn champions of data science and AI. It is only then that the organization can ensure that it develops and also implements a comprehensive AI strategy to introduce big data and AI into its functioning.
In this process, the leaders will be required to set up a T-shaped team, especially its innovation and technology functions from the ground up, staff the team with proper talent, allocate sufficient resources to their projects and also ensure support of the top executives at the organization.
In summary, financial institutions’ entering the AI age will need a commitment from their leaders. With their continued support, T-shaped teams will help the organization maneuver through the multiple stages of AI adoption to accomplish its long-term objectives. Technology will play an essential role businesses and thus the data science function will turn into a permanent part of the investment team..