Bridging the Gap Between Big Data and Big Content

To be competitive, food businesses need to leverage their business information more efficiently than their competition. However, one of the biggest challenges facing companies today is effectively leveraging the vast amount of business-critical information that falls into two distinct categories: Big Data and Big Content.

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Mika Javanainen, Senior Director, Product Management, M-Files CorporationMika Javanainen, Senior Director, Product Management, M-Files Corporation

Building a profitable food business can be challenging. While management must be ever-vigilant in monitoring and optimizing efforts related to sourcing raw materials, logistics, waste management, etc. — successful manufacturers also recognize where other efficiencies can be gained and potential risks mitigated in other areas of the business.

To be competitive, food businesses need to leverage their business information more efficiently than their competition. However, one of the biggest challenges facing companies today is effectively leveraging the vast amount of business-critical information that falls into two distinct categories: Big Data and Big Content. And for many, it’s the disconnect between Big Data and Big Content that is creating risks and operational inefficiencies.

What is Big Data and Big Content?

Big Data refers to the structured data that resides within database applications. Typical Big Data systems in a food manufacturing environment include ERP and CRM applications. Big Content refers to unstructured content, which can be anything from emails and videos to spreadsheets, reports, presentations, photographs and even call center recordings. In short, Big Content consists of every file or document that doesn’t reside within a database application.

The fundamental information disconnect

Enterprise information assets represent huge potential for driving business results, but only if the data is accurate and the details can be found, analyzed and easily extracted from it. In other words, organizations need to balance extracting the business value from information with managing risks, especially in the heavily regulated arena of food manufacturing.

To find the information needed to do their jobs, employees typically must search through multiple, disconnected systems and repositories, siloed systems, on-premises applications and cloud-based systems. It’s no wonder information technology research firm Gartner Group points out that professionals spend 18 minutes to locate each document on average. 

Many industry experts have agreed that the volume and complexity of Big Data and Big Content have created an environment of content chaos. Organizations mired in content chaos struggle to ensure the accuracy, efficacy, and timeliness of their structured data and unstructured content, and overall confidence in decisions made from the information is greatly reduced. The key is the ability to deliver the right data that is relevant to the decision-maker in the right context, and at the right time.

Metadata intelligently links information across the enterprise

The key to making all information assets relevant and valuable is the ability to intelligently link content and context. Without the ability to identify relationships between unstructured content and their associated Big Data (structured data) counterparts, food manufacturers are left with only a fragment of the entire information puzzle.

A metadata-driven approach to information management can help food manufacturers unify their Big Data and Big Content assets and harness the value across disparate information silos.

While structured data (Big Data) inherently is easier to analyze than unstructured content because it already typically has metadata associated with it, metadata often needs to be added to documents, e-mails, and other unstructured content. Many unstructured content files already contain basic metadata information, such file size, file type, date created, etc. The ability to add custom metadata (such as author, expiry date, electronic signatures, etc.) enables users to easily find accurate and precise information faster. Moreover, the ability to intelligently link content and context across structured data systems and unstructured content repositories via metadata can expose hidden value by mapping previously disconnected information assets that reside in separate information silos.

Metadata also helps to ensure that workflows and business processes are properly followed and administered. For example, metadata may include information on the development and lifecycle of a document, including the users, processes and applications involved in its creation and revision, as well as its ultimate archival, retention and destruction. This can include granular details that drill down to the exact timestamp of changes and actions, such as reviews and approvals, as well as the access permissions involved in performing them.

Metadata-based enterprise information systems (EIM) are an optimal platform for to connecting Big Data systems with Big Content repositories. Metadata organizes and tracks the entire digital lifecycle of important business information, including the processes, procedures and users associated with it. EIM solutions also provide a precise audit trail that can prove invaluable, particularly in the highly-regulated food manufacturing sector.

However, one of the most important benefits metadata provides is the ability to create associations and relationships between various types of information across repositories or business applications, such as ERP or CRM systems. These relationships establish relevancy in ways that the actual content of the information may not. For instance, an article about the popularity of low-carb diets might be important and relevant because it is related to a specific product segment (cereal products). With metadata, the EIM system can alert the product managers to adjust the production of those products and to develop alternative products for customers.

Food manufacturers need to excel to produce products that customers want and be able to deliver these products when they want them. The good news is that metadata-driven EIM systems can deliver a similar value proposition for internal teams - deliver the right Big Data and Big Content assets to the right users when they want it.

About the author

Mika Javanainen is Senior Director of Product Management at M-Files Corporation. Javanainen is in charge of managing and developing M-Files product portfolio, roadmaps and pricing globally. Prior to his executive roles, Javanainen worked as a systems specialist, where he integrated document management systems with ERP and CRM applications.

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