Why a Business Intelligence Data Strategy Needs Machine Intelligence

Published On August 21, 2020

With machine intelligence, intelligent content services can automate a business intelligence data strategy and extract value from unstructured information.

There’s a lot more to a business intelligence data strategy than just gathering information. Most organizations have become well-versed in creating and storing data, but they struggle to derive value from it — and that’s a problem. Machine learning may be their salvation.

A new software category called intelligent content services uses machine intelligence to automate tasks that are too overwhelming to accomplish manually. Machine intelligence allows organizations to scan large volumes of data at laser speeds — rates that would be impossible for humans to match — and then classify, tag and organize it for easy analysis and smooth integration into their digital workflows.

Benefits of Intelligent Content Services

Having large amounts of unstructured information is a growing problem for organizations. According to International Data Corp, documents, emails, videos and images will constitute 80% of the data the business world creates over the next five years. With this new breed of automated tools in their arsenals, organizations can optimally organize existing and future data gluts.

A new Iron Mountain e-book, “Now Is the Time: Take the Next Step in Deriving Real Value From Information,” describes how by extracting and integrating data from unstructured sources, intelligent content services can automate an organization’s business intelligence data strategy and, in turn, propel them along the path to digital transformation.

Here are some of the most beneficial functions of this new technology as well as why every business intelligence data strategy needs machine intelligence.

Creating Form and Structure

With intelligent content services, organizations can derive nuggets of knowledge from unstructured data sources. For example, machine intelligence can be used to conduct preliminary document reviews for completeness and consistency. Algorithms can pore over large amounts of unstructured data and identify elements such as dates, part numbers and customer names. This makes it possible to classify and store that data in structured form for improved business intelligence.

Extraction and Classification

Machine intelligence can also be combined with technologies such as optical character recognition (OCR) and video recognition to extract value from sources that would be otherwise inaccessible. For example, machines are already as adept as people at recognizing objects and faces in photos and videos. This capability can be applied to classify images automatically and attach them to relevant records, such as insurance claims and facilities documents.

Companies with a large accumulation of legacy paper documents can especially benefit from intelligent content services. When paired with OCR, this technology can recognize the content of paper documents for classification purposes and even extract individual data elements, such as names and dollar amounts, that can be loaded into structured databases for analysis. This means paper records can be both organized and made searchable thanks to machine intelligence.

Consistency and Compliance

The Iron Mountain report provides examples of how intelligent content services work within a business intelligence data strategy. In the document-intensive field of loan processing, machines can ensure that necessary records have been gathered and that they comply with regulatory requirements. These consistency checks can spot errors and omissions such as unsigned documents. Machine intelligence can even be applied across entire loan origination and resell processes to identify opportunities and manage risks.

Identifying Discrepancies

Contract management is another document-focused discipline that can greatly benefit from intelligent content services. Algorithms can be trained to spot departures from standard language, identify potential risks and automate error-prone workflows. Machine intelligence can compare contracts against legal and regulatory standards and flag any discrepancies that indicate potential risks.

Finding the Right Solution

While the e-book recommends that organizations move quickly to evaluate available intelligent content services solutions, it also emphasizes that this core technology will find its way into a broader range of workflows and processes over time. For now, the best choice is a single solution that can access a broad range of data sources, provide simple drag-and-drop programming and display rich visualizations of complex data. The solution should come with out-of-the-box classification algorithms and the option to expand for functions or industries.

Good enterprise solutions also adapt to an organization’s information governance and security practices and include rich application program interfaces that support value-added ecosystems. Intelligent content services will only become smarter and more capable over time, so now is the opportune moment to investigate them and consider what value they could bring to your organization.