This website gives examples of business intelligence methodologies and strategies that studios and content creators can use to start thinking analytically about expanding their workflows to accommodate extended reality (XR) projects. Examples are presented through the lens of a theoretical studio looking to expand it’s extended reality (XR) capabilities by adding several new segments to its production and business processes.
Let’s begin by looking at several ways that business processes differ from strictly cinematic production workflows to more IT-heavy extended reality (XR) cinematic production workflows. Further, let’s identify what aspects may be improved by preparing for scaling and efficiency early on in the transition or startup stage.
As the Extended Reality (XR) sector is realized, many content creators are seeking to transition from producing traditional content to creating deeper, more immersive experiences. Studios and startups branching into this area are likely to be creating content for virtual reality (VR), augmented reality (AR) or mixed reality (MR) projects for the first time. For these creators, this will mean expanding their capabilities to include;
- handling large repositories of 3D assets,
- implementing positional tracking and advanced compositing workflows,
- processing 360° (stereoscopic/3D) video, and
- adding layers of interaction.
There are a number of major differences between standard workflows versus those that support XR production, which can be difficult to plan for. Being unaware of missing workflow processes can dramatically impact the overall success of the transition. Proper planning and strategic assessment is key to minimizing disruption to the business.
Analyzing the Typical Workflow Process
The current production process begins with obtaining any specified client files, setting up the project’s file structure and storing the original client files on the server. Then, if needed, editing and creating pre-visualizations from the client files, capturing video content in the field and/or generating any needed CGI, VFX, titles, sound and other art files. Then the files are composited, rendered and sent to the client(s) for approval. If the client(s) approve files, aside from following up, the project considered concluded. If the client(s) requests additional edits, files are re-delegated to team members and then reenter the pipeline for editing, compositing and rendering. They are then resent to the client(s) for final approval, and so on.
Production Flow Chart
Experienced programmers and technical directors may realize there is quite a bit left off of the above flowchart. The missing processes represent the beginning of numerous missed opportunities. As the workflow stands currently, there is;
- no mechanism for data collection, mining or analysis,
- no production scheduling/queues,
- no code or interaction implementation,
- no game play, bug and/or quality testing.
In some instances, these production processes are not included for reasons, such as budgetary concerns and/or a lack of perceived value. Despite publicly available and low-cost tools for collecting data, many smaller studios believe that they may not have the labor, budgets or capability to handle data collection tasks and further data analysis. Additionally, stakeholders and other staff may have a purely cinematic backgrounds and thus may be somewhat less aware of the nuances and challenges of the programming-side of the industry.
In order to gain support for data cultivation initiatives, it is imperative that stakeholders find value in incorporating new and modified business processes. For these reasons, ensuring a solid understanding of the business requirements and moreover educating stakeholders on the areas of the Extended Reality (XR) pipeline that apply to them is vital to gaining their support.
Proposed Production Workflow Revision
In order for our studio to expand, it is time to consider an improved production pipeline. This means introducing several new processes into the workflow. Let’s take a look at the differences below.
Revised Production Workflow
This lifecycle of extended reality (XR) media content creation still has room for improvement, but now it is much closer to being on the right track. Segments were put in place to denote the distinct phases of the production workflow. The eight new segments are;
- Principal Photography + Audio Capture,
- Art & Audio Creation, Conversion,
- VFX & Credits, Compositing,
- Code & Interaction,
- Testing and Final Edits & Client Submission.
These phases can be further used for aid in the creation of production queues and to identify particular processes for affecting scheduling.
“The transition occurring in the… media production industry is a profound game changer. It is one of the most dramatic and significant changes that impacts every aspect of creation, production, management, distribution and monetization” .
Under design documentation, workflow planning is the first piece of our first new data capture and analytics layer. This layer feeds into collaboration enablement and creates a mechanism for the files to be shared seamlessly across the entire production workflow. While the files are being created across the process, this new workflow gathers the data that allows for rich indexing. This will lead to savings later on, in terms of speed and efficiency. Additionally, this workflow planning process addresses media and format obsolescence and how to handle legacy files.
One of the biggest wastes of time for staff is looking for lost or misplaced files. By adding rich indexing to our workflow, the process now allows for rapid and accurate retrievals and more in-depth queries. Over the years, rich media has been gaining in usage and is now commonplace online. In light of this, the issue of “facilitating efficient access” of rich media has become a formative research problem . Using our solution, we can limit the separation of versions as a barrier and easily complete tasks, such as normalizing formats.
Cognitive & Game Play Analytics
Under the code and interaction and testing section another layer has been added to capture cognitive and game play analytics. Here the goal is to secure real-time capture and analysis of game play performance data, while working out any bugs and/or quality issues. This data analysis will inform our ability to make more engaging experiences and to add adaptive learning mechanisms into future processes. This particular process has been set-up to be seamlessly woven into the experience to capture “play-based competency development” . In this way, the system is setting the foundations for “targeted and dynamic learner support” . This is key to generating more revenues and creating more relevant and enjoyable immersive experiences.
Uncontrolled Variation, the Enemy of Quality
For many small start-ups and studios adding basic analytics to a variety of areas can be done with free or low cost tools, like Google Data Studio for dashboards and using free tiers of service on platforms like Amazon AWS. Unless you really have an aversion to learning this is something you can do yourself and should because it is a lot of fun. However, business today is all about data. As you get into more complicated XR projects, however, this is something you might want to outsource or hire a team to assist with.
“Without data, you’re just another person with an opinion.”― W. Edwards Deming.
Waiting to capture data for mining from the onset of a business can be a critical and costly mistake. You need to be prepared to meet with angel investors, venture capital firms and banks. Rich reports with valuable metrics and dashboards with real time information can make a substantial difference in outcomes of key meetings. There are a number of tools and languages that studios can leverage for little or no upfront cost. Even just using spreadsheets and Python, quite a bit can be accomplished. On the next section of the site, we will look at some examples of business processes relating to studios and some related analysis.