To become a data-driven asset manager, firms must attract a new data savvy workforce. Our industry has always enjoyed the success of being able to recruit top talent from colleges. Recent graduates have gained experience creating data solutions using Python, big data, statistics, and the cloud and are perfectly prepared to help us achieve our ambitious data strategies. However, there is one big problem – our data platforms are not ready.
Flipping the data preparation/solution ratio: 80/20 to 20/80
Current employees complain they spend up to 80% of their time preparing data before doing any analysis (their job). The problem is our data platforms were primarily developed on legacy technology to support the integration of business functions (portfolio management, trading, risk, accounting, compliance, etc.).
Little effort was put into creating data platforms to facilitate data analysis and as a result we are seeing newly hired data scientists, data engineers, and other data/tech savvy employees becoming quickly frustrated as they struggle to prepare data (cleansing, organizing, and collecting data) instead of building AI and ML solutions. Top college hires experience the same frustration and feel transported back in time to an age of non-cloud data platforms lacking prepared datasets, APIs, and the latest data analysis and visualization tools.
A data-driven asset manager must prepare and provide easy access to high quality data to attract and retain data scientists and top college talent or risk losing them to other industries. Modern data platforms are required to compete in the digital age and the efficiencies gained will empower all employees.
In Part 3 of the 4-part Data-Driven Asset Management Insights series, we will explore how to best leverage data to generate alpha and increase sales and data platform solutions.
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