Data integrity, operational risk, and firm reputation are key considerations in how a firm develops its client reporting & pitch book production processes. To protect these interests, the standard practice is to create and manage a structured data such as performance, holdings, transactions, and attributions in a single source of truth. But what about unstructured data, which accounts for at least 50% of the content in these reports and books?
Unstructured data refers to any data that is descriptive in nature or third-party market research data. It can be sourced externally or created internally and typically it is not found in commonly used data models. This includes footnotes & disclaimers, market commentary, investment strategies, and professional biographies & photographs.
How Firms Treat Structured Vs Unstructured Data:
Historically, firms have viewed unstructured data as “cut & paste” data and not data that could be stored in a data mart for reporting purposes. The data lives in multiple environments, which cannot all be maintained for accuracy. This “cut & paste” data is treated as an afterthought and is not automated. This lack of automation creates room for numerous inaccuracies in logos, commentaries, disclaimers, investment strategies, biographies, and third-party graphs & charts.
By leaving unstructured data in its current state, firms take on risk to their reputation and data integrity, while also maintaining a cumbersome process to creating client reports. So the question needs to be asked, Why take this risk with your data?
Contrast how firms treat structured data, and you see a data governance model that maintains a firm’s data integrity & reputation. Structured data is bound to a strict data governance process, where it lives under a single source of truth, which allows the manager to maintain compliance systemically and reduces human error from potentially harming the firm. These automated data governance processes do the following:
- Ensure data ownership
- Have an automated review, approval process, & audit trail
- Data is then sourced from a single source of truth
Unstructured data can be put in the same workflow as your structured data, allowing the same data governance processes your firm already has in place to also manage your unstructured data, putting all aspects of a client report under a single source of truth.
The cost of moving to a warehoused solution for your unstructured data requirements is greatly outweighed by the inefficient labor costs and reputational risk of providing inaccurate or non-compliant data to clients and other outward-facing consumers. By investing in the warehousing of unstructured data, organizations can reduce operational risk and improve report production processing time by removing manual processing through automated data calls, streamlined data governance, and audit reporting.