Learn the core components and best practices for implementing seamless digital asset management processes, and how AI plays an integral part.
As industries shift toward a digital future, physical documentation and assets are becoming a thing of the past. In today’s dynamic environment, change is constant and innovation is key. As a result, the demand for agile document management systems, processes and solutions has never been more crucial.
Digital asset management (DAM) solutions have become an important, albeit less well-known, tactic for businesses looking to modernize and grow. DAMs centralize, manage and safeguard large, diverse volumes of digital files online via storage solutions like cloud-based storage or external hard drives.
Let's take a closer look at how DAM works, its core components and how artificial intelligence (AI) capabilities can be leveraged to enhance its efficiency.
A digital asset management (DAM) solution is a system used by organizations to store, organize, retrieve and distribute digital assets in a centralized and efficient manner. The ‘digital’ can encompass a wide range of digital files, including images, videos, audio files, text and other types of multimedia.
By implementing and following an effective DAM process flow, organizations can streamline organizational workflows, improve collaboration and communication, ensure compliance and maximize the value of their digital assets.
> Read more | Everything you need to know about DAM
Hyland’s Nuxeo Platform for DAM was named a Leader in the DAM space in this 2023 report. The solution achieved the maximum score for advanced capabilities and solution breadth, and Omdia placed Hyland’s market momentum as above average for the field.
DAM processes require core components to manage and streamline digital assets throughout their lifecycle, ensuring that workflows run efficiently. These components include:
Think about traditional physical storage options: They are siloed, distributed across different locations and even when in the same place, the files are often scattered, disorganized, shelved and boxed.
Digital asset management changes this. DAM solutions support centralized storage, ensuring assets are stored and managed in a single, unified location accessible to multiple users across devices or applications.
Modern DAM solutions leverage cloud computing. Unlike physical entities such as external hard drives, cloud computing enables virtual storage and provides users access to multiple data centers across a wide range of users. Through a global server network, cloud computing environments allow users to scale, safeguard and access content easily without worrying about storage costs.
Besides simply centralizing information, assets need to be organized efficiently for smooth data identification and retrieval.
DAM systems offer categorization tools that utilize attributes, criteria and keywords, such as content type, project, department, campaign and so on — this is known as metadata.
With these tools, crucial information is sorted into folders or files. This is critical for timely project and service delivery, so relevant staff can easily locate the data needed.
> Read more | Reduce image hide-and-seek with AI
Today’s fast-paced industry demands quick communication and seamless collaboration. DAM facilitates the secure sharing and distribution of digital assets, ensuring the right content can be accessed by the right people, especially those working on cross-functional tasks, from various channels, platforms or devices.
DAM systems are equipped with progressive security features and access controls to protect digital assets from cybertheft and other forms of unauthorized access or misuse. They’re also either able to integrate with third-party compliance tools, or come with built-in governance frameworks, automated regulatory compliance checks and other tools to facilitate compliance.
Digital assets and the metadata associated with them are managed within a DAM system throughout their entire lifecycle, from creation to its archival stages. This can involve updating metadata fields, adding or modifying attributes or enriching the data and metadata with additional information.
These are done through processes like version control, expiration management and archival. DAM process workflows ensure that assets are always up to date for staff perusal, allowing accurate information delivery.
Leading DAM solutions use AI to autotag assets, removing both human error and lag time from the process.
Here's what a typical DAM process flow looks like:
The first step of the DAM process is asset creation. This involves the creation and preparation of a multimedia file — producing written, visual, audio and other types of copy using standardized templates and file formats. This is done so later, DAM software can easily capture, recognize and sort documents for smooth search and retrieval.
Next, metadata — descriptive information and identifiable attributes — needs to be added to the assets for context, creating indexes that group these assets with common tags that improve categorization and organization.
Metadata plays a pivotal role in the DAM process as it helps with indexing, the process of systematically cataloguing and organizing digital assets with a DAM system. This further simplifies asset search and identification through rule-based workflows.
The third step is to integrate digital assets into relevant workflows, projects or processes within the DAM system. This may involve linking the asset to specific tasks, projects or campaigns, assigning responsibilities and tracking progress through workflow management features.
As digital assets have been assigned metadata and gone through the indexing process, task and process automation can be applied to streamline DAM.
In constantly changing business landscapes, documents and data are bound to change. It’s typical for a company to experience regular inflow and outflow of staff, customer acquisition, promotions, restructuring and the likes — in dynamic environments like these, data needs to be consistently updated.
That’s why version control is so important: It ensures the most up-to-date assets are utilized and workflows remain consistent. Having version control allows you to track changes, revisions and updates over time, especially when there are multiple versions or iterations of a digital asset.
In this step of the DAM process flow, establish policies, procedures and guidelines to govern the creation, use, management and lifecycle of digital assets to authorized personnel, protecting resources against unauthorized use, corruption or loss.
DAM systems can facilitate this in several ways, including allowing administrators granular control and permissions, role-based access control (RBAC) so permissions are assigned based on specific user roles within the organization and access controls based on metadata associated with the digital asset.
Regular internal and regulatory audits are necessary to evaluate how effective your DAM system is — particularly in regulated industries like finance and healthcare, which require strict compliance with industry standards.
DAM systems maintain detailed audit trails that record user actions, access attempts and modifications to assets. Administrators have access to audit logs, so they can track who accessed which assets and when, providing visibility into user activity, and facilitating compliance with governance requirements.
An essential step to remember is the implementation of disaster recovery strategies and software for digital assets. Having this in place means that in case of system failures, hardware issues or natural disasters, all digital assets are preserved and can be restored without loss or damage.
Much of the efficiency of the workflow in your DAM process hinges on AI-powered features, which include automatic tagging, categorization and metadata extraction.
The AI capabilities that enhance DAM include:
Machine learning (ML) supports the majority of DAM process workflows, from automatic metadata tagging to indexing and categorization.
Essentially, ML is the process of using data algorithms to help a computer learn without direct or much manual input. It uses algorithms to recognize patterns, including different types of digital assets and their attributes, keywords, categories and other metadata.
ML in DAM works by analyzing existing assets to learn patterns and apply them to new assets, facilitating automatic tagging and categorization. Over time, a DAM’s pattern recognition capabilities will be enhanced, continuously improving system performance.
An additional ML capability includes analyzing usage patterns and the DAM system’s historical data to further automate and optimize workflows involving asset versioning, approval and task distribution. These predictive capabilities can also provide valuable insights for future trends and asset performance, enabling organizations to make data-driven decisions for DAM strategies.
For governance, ML models can also be used to automatically detect sensitive content within digital assets, helping to ensure compliance with regulations and company policies. This is particularly useful in industries where content moderation is essential.
Natural language processing (NLP) is another key AI-powered feature that enhances DAM. NLP focuses on enabling computers to process languages, just as humans do.
Using NLP, DAM systems can comprehend word usage and sentence contexts, piecing together textual data to determine their meaning, then predict and generate additional content.
NLP is a particularly important feature for DAM because it can be used to understand keywords, attributes and categories within existing, text-heavy asset descriptions — automatically generate metadata for new assets as it does so. By eliminating the need for manual tagging and categorization, employees save time generating and searching for assets, as well as ensure consistency in metadata across systems.
Optical character recognition (OCR) technology works by automating data extraction from text (written or printed), taken from scanned documents or image files, and then converting the extracted text into a machine-readable form, i.e. digital format.
The first step for image-to-text conversion is to obtain the scanned document or image file, a process known as document capture. Document capture software can combine scanning, importing and integration capabilities to capture incoming documents into a central repository.
Next comes document scanning, which uses OCR technology to process the image files saved in the central repository and extract the needed information in text format. Once this is done, document indexing comes into play by optimizing the text captured for search by identifying and categorizing documents and applying search criteria.
> Read more | What is document scanning and indexing software?
OCR can be an extremely handy tool for industries and businesses that rely heavily on visual information. Take the e-commerce industry, now a key focus for many product companies.
Product photography and video are staples for these companies to drive sales on various channels. And this requires product photoshoots, which are tedious to organize and update. In fact, these processes oftentimes still rely on emails, phone calls and manual handoffs, causing delays and extra work for teams.
A DAM platform makes it easier to initiate, set up and control photoshoots and resulting image files, providing visibility and transparency organization wide. Additionally, cloud-native DAMs allow teams to locate files quickly, even within multiple global repositories.
> Read more | Upgrading photo studio processes with digital asset management (DAM)
AI can revolutionize DAM by enhancing metadata, search functionality and automating tasks. It can free up time and decrease company operational costs over time. The benefits of having an AI-powered DAM system include:
Hyland’s Nuxeo Platform is an intelligent, AI-powered DAM solution that manages all types of digital content including rich media assets, documents, emails, web content and more within a single, centralized platform.
A leading apparel company used Hyland’s Nuxeo Platform for DAM to optimize and automate workflows, while also reducing costs, eliminating digital siloes and strengthening partnerships.
Using Nuxeo’s configurability, the company also created a branded portal for retailers to access their current e-commerce photography, and it allowed Hyland’s customer to track use within the portal.
Effective DAM isn't just about organizing digital assets. It’s about having control over your data, expediting internal document management processes and fully leveraging the data collected for decision-making and service delivery. Strategically, having an efficient DAM process flow can give companies a competitive edge in any industry.
DAM software plays a crucial role in successful DAM strategy implementation, serving as a central repository and control center for your data. With its AI-enhanced capabilities, DAM systems have evolved into intelligent content management solutions to meet modern organizations’ business needs.
With Nuxeo Platform, you can implement a comprehensive metadata management strategy that encompasses both rich media assets and other types of content, providing end-to-end content lifecycle management and ultimately managing content more effectively throughout its lifecycle.
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