Pre-pandemic, firms were already grappling with a series of unparalleled challenges, including increasing margin pressures, shifts in customer demand, more regulation, increasingly complex markets, skills shortage and rising costs.
While operations teams may have recognized these challenges, many have focused on the short-term implementation of local band-aids and workaround projects, instead of wholesale projects to rectify the root causes of inadequate management of market and reference data. Others have taken a more strategic approach, investing heavily in multi-year data management projects, which – oftentimes - have failed to deliver the type of business benefits that are truly market-differentiating.
Now, due to the market volatility sparked by the COVID-19 pandemic, existing challenges have been further exacerbated, highlighting the weaknesses in data management operating models. The issues many firms face around scalability have intensified, with operational models creaking under the weight of ever-changing business demands, requiring far greater agility and speed of change.
Inadequate market and reference data management has been one of the top operational headaches for buy-side organizations for some time now. Increasingly, firms are recognizing the gaps in their existing data management set-up and are subsequently considering new, more holistic approaches to addressing their data management headache, including Data as a Service (DaaS). But what constitutes a true DaaS offering? And how does this approach differ to other solutions available on the market for managing market and reference data?
In this whitepaper, we explore the key factors influencing how buy-side firms need to think about data and examine the shortfalls of existing approaches to market and reference data management. We will then define the three pillars of a true DaaS offering and build a case for Data as a Service as the optimal operating model for firms that want to be successful in the post COVID-19 world.