Overcoming Data Barriers
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Overcoming Data Barriers

Farouk Ferchichi, Group President, Envestnet Data and Analytics
Farouk Ferchichi, Group President, Envestnet Data and Analytics

Farouk Ferchichi, Group President, Envestnet Data and Analytics

Having access to data is pivotal to understanding and serving customers, yet the potential of most data is not fully utilized. In fact, according to Forrester, on average, between 60% and 73% of all data within an enterprise goes unused for analytics. Too often, businesses are relying on outdated infrastructure that causes data gaps, inconsistency, and inaccuracies, and makes it difficult to track historical lineage. This inability to evaluate data over time or accurately splice information across data sets creates barriers to optimization and can hinder business performance.  

The Data Challenges

In the wealth management industry, data analytics plays an instrumental role in helping wealth advisors deliver the best advice to clients. But all too often, wealth management firms have disconnected systems that make it difficult for wealth managers to generate analytical insights at scale. Common issues include data gaps and concerns with accuracy, consistency, and traceability.

These challenges directly impact the users and beneficiaries of data. For example, enterprises are committed to making data and analytics accessible for their advisors without the operational burden of building new systems – which come at a price and require developing capabilities that have a high risk of failure. Advisors are both overwhelmed (and underwhelmed) by the amount of data available to them and the lack of actionable insights to best serve their clients. This ultimately affects their clients; in order to best optimize their financial wellness needs across spending, saving, and investing, advisors need a full and connected picture of clients’ finances.

  ‚ÄčThe retail industry also has vast amounts of information being logged from many different places, such as multiple departments in stores, factories, and more  

Even when firms can overcome these obstacles, they often face another set of challenges from a business standpoint. They rely heavily on specialized data practitioners to analyze data and uncover insights, which limits scalability to a firm’s entire customer base. Efforts to automate insights and remove humans from the process often fall short due to issues with the business intelligence applications— the outputs are typically either too generic to inform specific recommendations, too technical to be consumed by wealth managers and their clients, or too narrow in focus by only covering parts of the business and not providing a holistic view.

Beyond the wealth management industry, most business intelligence applications across industries deliver data in silos without the context of the overall business, making them less impactful and not very actionable.

Solutions to Drive Business Transformation

We have witnessed digital transformations in many industries, yet many enterprises are not taking full advantage of the data. The healthcare industry has come a long way by adopting electronic health records. Yet, there is not one central location where records are housed, creating barriers to how data can be used to best understand the type of care a patient needs. The retail industry also has vast amounts of information being logged from many different places, such as multiple departments in stores, factories, and more. Yet, all this information is useless unless it can be accessed and analyzed in one readable format, enabling retailers to create a unique, tailored experience for each customer.

Solutions that connect multiple data sets in one platform while providing a differentiated user experience and seamless business integration points are key to better understanding customers and integral to transforming how businesses act to better serve them. By unifying business decisions, analytics, and data sources, an integrated solution could provide a deeper analysis based on tangible data, a strong basis on which tough business-driven decisions can be made, and ultimately, a true return on data.

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