Structured data resides in your databases and, in industries like insurance and financial services, these likely are numerous siloed databases established to accommodate every line of business, the various departments within your company and legacy data inherited through mergers and acquisitions. Monitoring and controlling structured data is straightforward, but problematic largely because it is often stored in so many disparate databases and archives. It is generally accessible and “readable” for regular authorized users, who know where it is, where it came from and should know who is using it and for what purposes. Governance policies always apply to structured data.

It is more challenging to manage unstructured data, often referred to as dark data, which is all data that is not within a database, living within your business and digital systems. This runs the gamut from SMS text messages recording customer queries and CSR responses, to Excel spreadsheets, PDF files, emails and so on, to what might be considered “semi-structured data,” the formatted information from statements, invoices, Explanations of Benefits, premium notices and other types of transactional documents. Correspondence in any format can provide a record of customer concerns, changes in their family size, property ownership, changes of employment and more. It is important to note, too, that this unstructured or semi-structured data is likely to be the most up-to-date and accurate customer information you have. It includes current customer names and addresses, current contract information, the latest payables calculations, changes in beneficiaries and so forth.

Although some of the information in these semi-structured documents may be drawn from various databases across your organization, transactional data consolidated as an aggregate document is distributed as print or other outgoing communication channels. This type of data is usually stored in some manner but is often overlooked in terms of attempts to control it through governance policies. However, it is important to keep track of all this for several reasons.

On a more positive note, when this type of unstructured or semi-structured data is organized and controlled — that is, when it falls under a reasonable governance policy — it can be made easily accessible to authorized staff and provides a strong platform for responding to customer queries and complaints quickly and accurately. Something as simple as noting that the customer regularly contacts your company by mobile phone may indicate his or her preferred communication channel and should be indicated in the customer file, if not in a formal preference management system your company has adopted.

Combining all these types of data into your databases can be done with software solutions designed to recognize the various formats the dark data and information takes, breaking it down and directing it to back into your existing systems. An enterprise content management (ECM) or enterprise report management (ERM) system can provide a solution for both governance and extended use of the data contained within documents stored. This kind of solution can include data mining software capabilities that allow users to access, search, extract and analyze formatted document content. Recognizing that the reports and other documents stored in an ECM or ERM system can be used for data acquisition and not just data and information distribution is an important paradigm shift. Once such a system is implemented, it can open the door to reduced costs, improved operational reporting and a practical, pragmatic way to leverage existing infrastructure.

Learning more about internal processes, manufacturing timelines, quality control, customer purchasing patterns, customer satisfaction levels and a host of other valuable information is readily available in the reports, invoices, Explanations of Benefits and statements that are produced on a normal everyday basis throughout business and industry. Timely acquisition of this verified, substantiated data can help increase revenue and reduce costs.

Something to consider, too, are solutions that use artificial intelligence (AI) to actually harvest new information from these documents, including things like records of customer queries about altering their current policies or adding different lines of insurance coverage. The more information you have about your customers, the easier it is to develop a 360-degree view of them as individuals. Knowing your customers means you can anticipate their needs in many cases, and this enables stronger, long-term relationships.

Developing a practical and useful governance policy must cover all types of data: structured, dark unstructured and semi-structured data. Ideally, the first step requires executive-level support in decisions about what you need to keep and where, who can access it and for what purposes, how long it should be held and when it should be destroyed. This planning can make all the difference in the world when it comes to both operational risk on the internal side and the customer experience on the external side.