Social. Mobile. Analytics. Cloud. Big Data. These are the buzzwords that have been used to describe the transformation of all technologies over the past decade. With the evolution of these technologies, we have fundamentally moved from a basic client-server model of computing to a highly distributed, scalable, contextualized and scrutinized computing environment. But how does this concretely affect the future of Digital Asset Management?
DAM was initially created to handle the flood of digital media created in enterprise and business environments. As the tools for digital creation became increasingly democratized and easier to use, media creation flourished. Digital media became increasingly important not only for outbound media, but also for inbound marketing efforts to the point where digital media is now considered a de rigeur marketing component for any large campaign.
As the volume of and demand for digital media has grown over time, the DAM market has been caught up in a feature and function battles where each company tries to one-up each other for decision management, analytics, metadata support, workflow management and other contextual business capabilities. But in fighting these battles, the players in the DAM market needs to look at the big picture and start figuring out where they fit into the Social, Mobile, Analytic and Cloud (SMAC) world that now represents the new world of technology.
Looking Into the Future
It is easy enough to talk about these new functionalities in terms of having a “Social DAM” or “Mobile DAM” and to think that these functions will provide differentiation. But simply adding comments, sharing capabilities and basic collaboration is common sense in a world where Facebook is now over a decade old.
Instead, we need to look at these trends in conjunction and see how these larger forces are creating a splintering of DAM functionality. Since DAM lacks a true market leader, this means that vendors need to start picking and choosing their path to the future as no one company will be able to go into all of these directions at the same time without investing time and resources that will most likely be unprofitable.
To better understand how these trends will affect DAM in the future, it makes sense to group multiple trends together and to look at the potential outcomes for DAM in these amalgamated contexts. Rather than look at each part of SMAC in a vacuum, start looking at these parts in conjunction. For instance, by grouping categories together, amalgamated trends start to become clearer. In doing this exercise, three sets of categories stand out in the way that they will transform DAM going forward:
- Social, Mobile, Cloud
- Social, Mobile, Analytics
- Big Data, Analytics, Cloud
Each of these trends means something different in the DAM world and will require specific new functionalities and support capabilities.
Social Mobile Cloud DAM
When applications are assumed to be shared and social, multiple people can interact with each other, annotate, comment and work on a shared problem. Mobility allows this collaboration to happen ubiquitously and at any time. And the cloud provides infinite scalability from a volume and processing perspective. The end result is a world where every asset can potentially have the best human-guided context, be launched in a timely manner, and be provided as many times as needed in whatever format is needed.
This means creating DAM that is focused on immediacy and context. It needs to be intelligent enough to take in the metadata and context provided by every stakeholder and to take the next step and understand which metadata is most relevant to specific users in specific circumstances. And this exercise needs to happen on demand rather than on a scheduled basis. The Social Mobile Cloud DAM is about supporting end users at the speed of thought and ideation and will require enterprise and mass media scale of asset delivery along with commercial search and artificial intelligence. And it has to be easy to use, with a user experience that is at least roughly comparable to popular commercial applications. The 128-button interface with 13 different tabs isn’t going to cut it in this world.
But imagine a DAM that actually collects social and mobile metadata as it is created. For instance, as a picture is shared on Facebook and Twitter or a video is shared on YouTube, who is collecting the comments associated with that asset and bringing it back into DAM to guide iterative improvement and potential alerts? Mobile observations could be used to actually view the observers of digital signage and read the body language and behavior for new metadata. And, of course, all of this would be stored and analyzed in the cloud. Although there is a backend need for analytics here, the goal is not to provide immediate reporting but to immediately respond to employee and client requests on an ad-hoc basis.
SaaS-based vendors are best suited to execute on this vision, as they have started to develop both the functionality to support this on-demand world and have the internal corporate culture to adapt quickly to customer demands. However, this future also requires a level of search and pattern-based cognitive analysis that is still not commonly available. Companies moving in this direction can provide a more responsive and human DAM for their clients.
Social Mobile Analytic DAM
How is this different from Social Mobile Cloud? Analytics is fundamentally about discovering new and insightful findings within data. This means that DAM not only needs to collect the data and metadata associated with an asset, but also needs to provide the visualizations, social graphs, mobile traffic and demand, and business metric associated with the use of the asset. Currently, these analytics are scattered throughout the organization or not collected at all.
For instance, where in your company can you find out the collection of employees who have either viewed or edited a digital asset? Would it be useful to see this analysis and understand which employee community is associated with that specific asset, especially as your company needs to update the asset or the underlying product or service?
Or how much mobile traffic does each digital asset consume and which aspects of the digital asset are providing the greatest interest? Currently, there are ways to look at web traffic or server traffic and determine this information, but this is really an asset management and asset performance question. The server itself is a commodity; it is the value of the digital asset that drives traffic. In addition, with phones such as the new Amazon Fire, companies can start to track eyeballs the same way that they track web behavior and clicks. Even if the Fire does not end up being a market changer, this functionality will eventually make its way into other mainstream phones such as the iPhone and Samsung devices.
Even with the coupling of DAM and Web Content Management, there is still room for improvement and advancement in asset-based analytics that can lead to greater strategic and tactical insights. The DAM companies willing to create data standards that can be better analyzed will be able to take advantage of this Social Mobile Analytics world to a greater extent.
We have already seen adjacent spaces that have seen the value of focusing on analytics, such as Ooyala, a video analytics company recently purchased by Telstra. There is latent demand for understanding the explosion of digital media being created and used. By thinking social-first and mobile-first, data-driven DAM companies can move in this direction and provide a smarter and more quantitative DAM.
Big Data Analytics Cloud DAM
Big Data is different from analytics in that Big Data focuses on the challenges of storing and organizing semi-structured and unstructured data that exist in large volumes and must be rendered and delivered quickly. For instance, a standard database can grow to enormous sizes, but the technology to scale is typically provided by an Oracle or Microsoft without too much of a challenge. But with digital assets, a standard database approach is less useful. For instance, how do you compare pictures on a pixel by pixel basis or with facial recognition through a standard database?
As we start to truly treat digital assets as data that can be analyzed on a bit by bit basis, DAM will start to truly support Big Data. And, contrary to some beliefs, Big Data is not just about handling the petabytes of data that Facebook and Google handle. Some Big Data efforts are at the terabyte level and some are even in the hundreds of gigabytes due to the complexity of dealing with the management of video and pictures and the need to stream these assets at high velocity.
In the present, we handle outdated or obsolete digital assets simply making sure that outdated assets are identified and appropriately tagged to meet any compliance or licensing issues. While a legal officer or procurement officer may need proof that these assets still exist, a marketing or sales executive may just see outdated assets as useless or even harmful.
But in the future, the development of Big Data means that the technology to automate searches for similar documents can now be started. If your organization has a number of duplicates that need to be consolidated or removed from the active DAM repository, future Big Data DAM providers will actually start to recognize these assets and find similar assets based not just on metadata but based on the actual content itself.
Of course, the outputs of this approach will require both social collaboration and the ease of mobile use to access these results from a delivery and interaction perspective, but the key here is the evolution of Big Data, which will provide a more accurate and compliant DAM for environments where digital assets have become unwieldy even in the context of a DAM system.
The Future is Happening Now
It is easy to get buried in the buzzwords of social, mobile, analytics, cloud, Big Data, scalability, leverage, etc., etc., etc. But behind the hype is a new world of capabilities that we have yet to fully see in digital asset management. As DAM companies prepare for the next feature and function skirmish, they also need to remember that we live in a new world of application functionality and expectations. DAM will need to fundamentally change to meet our expectations or be left behind as users look for peripheral solutions that are easier, faster and smarter to use.