Business Process & Pricing Analysis

Business Process Analysis

Rendering is one of the most expensive, time consuming, error prone and challenging tasks of any content creation studio. This is a recurrent task that multiple departments must complete. After principle photography, audio creation, animation, visual effects the resulting files are rendered if quality is subpar or the file needs artistic edits, then the process has to be started over again.

This high-level chart shows all the files being created in the top left box. Then, the files are rendered out, which typically involves a heavy computing process. Lastly, the files are composited into a single project and movie file. During the entire process, artists, programmers and other staff members need to be able to access the files for editing, collaboration and review.

As a small to mid-size production studio, there are very real limits to the amount of capital that can be invested in hardware. Moreover, software licensing is also limited, as well. Our project structure may be predefined by client or may be self-defined and thus set by company protocols. Just like all production studios, maximizing our time and resources is a major priority. We have large scale computing needs and may face challenges as the project elements are put together, due to use the lack of hardware.

In order to offset these challenges, the studio is planning to leverage Amazon AWS, where we can get a price of =<$0.01 per core/hour [6]. This will not solve all of our issues, bandwidth and storage will still need to be considered [6]. In order to save money on licensing the studio will use elastic licensing models via Thinkbox (The Foundry’s Nuke) and Autodesk. Amazon S3 and elastic files systems with EFS will drive the shared file system. AWS direct connect will be used to transfer the files from our local storage. Finally, the AWS will run NVIDIA GPU based EC2 Instances, along with windows and Linux (VCN + VirtualGL) to facilitate a cloud-based artist workflow [6].

Event Simulation Flowchart

The proposed business model has many events which can be drilled down further for analysis. Let’s take a look at the new testing phase of the model and the all new bug testing capability that has been added in. Whenever, coding, quality and game-play testing is occurring our team and outside testers will submit bugs, or errors/glitches in the system, as they occur.

To the right is an event simulation flowchart (DES), featuring an in-depth look at the reporting process and event flow from start to for the bug testing phase of our proposed business model. Looking at the model, note that the process begins when a new defect is found by the team. A ticket is opened and a team member from the development team is assigned to attempt to correct the issue. The team member creates a formal description of the problem and begins to do some preliminary research.

After the data is gathered, and the developer attempts to reproduce the error. If the error, cannot be reproduced then the developer will attempt to determine why and gather more data.  If the developer cannot determine why after gathering more data and concludes that it’s not a bug, after gathering the data then the bug will be rejected.

If the bug is able to be reproduced, then the developer will attempt to find the root cause of the bug and select it to begin bug analysis. During bug analysis, that developer will determine one of three things.  Is the error genuine?  If not, the bug will be rejected. Is the bug fixable?  If not, the issue will be escalated to a manager and removed from the queue. Is the root cause a genuine issue and what can be done to fix it?

Next the developer, will propose one or several new solutions to fix the error.  When the developer believes that error is corrected, another member of the development team will retest the solution. If the solution fails to fix the problem during the retest, the issue will be sent back to the original developer for further analysis and new solutions.

If this solution works on the retest, then the error will be reviewed by another member of the development team. If a solution fails during the retest, then the ticket is reopened, and sent to an entirely new member of the development team to restart the process again. If the solution works, then the case is closed and the error or fixed is considered to be fixed.

Sales Strategy

Our proposed business process model is all about creating the most fun and highest quality immersive mixed reality experiences possible. Throughout the entire process, the data capture and analytics layer in our proposed business process model is steadily working in the background to provide valuable decision-making information, tracking KPIs and measure performance. As more data is captured, the ability to build more advanced and accurate prediction models will also grow. [7] Let’s take a look at the sales strategy to better understand where our sales data will be coming from and what our goals are for success.

Our mixed reality exhibitions attract a large and very diverse group of excited visitors, each year. Many who are eager to try virtual reality (VR) for the first time. Our visitors encompass all age groups, gender, nationality, race, and income levels. Visitors might be local residents or tourists seeking adventure. This is why our marketing plan hinges on creating value. At our exhibitions, our staff sells fun, educational and whimsical experiences for the whole family, not tickets for a ride.

The first goal of our sales strategy is to align with the diverse pool of visitors and the channels by which they find our exhibitions. For this reason, making sure the experience looks fun for a broad range of people is a top priority.  Our foremost metric for success is by how much a person can enjoy themselves and emotionally connect with the mixed reality experiences at our facility. By monitoring and engaging on business review boards, we can monitor and manage our reputation. This way in the unfortunate event that someone has a poor experience, a staff member can engage with them to learn about and rectify the situation.

Our approach begins with becoming highly visible in the places that people are most likely to find out how our exhibitions. This includes submitting and updating our profile data with various directories and search optimization lists. Additionally, a mobile marketing campaign will be set up to maximize reach.

Moreover, the sales strategy includes using hyperlocal content to create brand awareness, while creating unique rewards that target our local audience. By creating relevant incentives, the sales strategy will assist in facilitating the return of local visitors to the exhibition, time and time again. Perhaps, inspired to bring out of town relatives and guests or local school, community and church groups.

The next goal of our sales strategy, is to create value for our visitors. Our company is looking to profitably grow business revenue by carving out a substantial share of the highly competitive $40 BN+ plus global theme park market. One of the ways to create value is to motivate visitors to check in on social media. By checking in on social media, our visitors can interact with people they don’t yet now to make and meet new friends, recommend places they like, keep track of places they have visited, and receive valuable incentives.

Lastly, we will invest and resources and allow us to modify our approach, as needed, and to deploy tools that will aide in agent training and support for the overall sales program. This includes investing in team development, skills development and funding augmentations to make the sales strategy and proposed business process more effective over time.

Sales & Pricing Analysis

To analyze our sales approach and adjust our pricing accordingly, a model of the “next most likely exhibition ticket purchase” will be built around the input data of recent exhibition visitors, who purchased at least two ticket or passes to an exhibition over the course of the past year. Next, a predictive model will be constructed to predict the next most logical ticket purchase based on purchasing history and the buying behavior of other exhibition visitors. Moreover, a conditional probability model will be built using a Bayesian-style approach P(A/B)=P(A ? B)/P(B), where A and B represent the exhibition ticket categories.

  • Category A = Single Use or Short Stay, Low Volume, Low Cost Tickets i.e. single, all-day pass, three-day pass
  • Category B = Multi Use, High Volume, High Cost Tickets i.e. month/season passes, family/multi-ticket packages, specialty experience

Viability and Feasibility

For the most part, this is a very routine set up for prediction. As long as the data is correct and captured consistently, this approach should yield a successful prediction with 95-99% estimated accuracy, depending on validation model. In order to perform this analysis there are a few things that need to happen;

  • an analysis of the historical sales data must be conducted,
  • the development of a purchase affinity matrix must be completed, based on accurate historical sales records,
  • a prediction of the next most likely exhibition ticket package must be created, and
  • back-end analysis to validate the accuracy of the prediction must be set up.

If all of these tasks are performed well, then theoretically sales revenue should increase over the course of the next 6 months.

Probability of Success

Finally, a conditional probability matrix will be created to understand the probability that a visitor will buy category (A) given the visitor has bought another category (B) in the past. This model will be set up in RapidMiner and will leverage either Naive Bayes, a Single Vector Machine (SVM) or Neural Networks for validation depending on rates of accuracy, which are easily achieved using the ROC node.

Using this methodology, there is a very high probability of a successful outcome. This is a very standard and straight-forward approach that has been time tested and used to solve many similar types of predictions. Typical outcomes for this style of prediction are around 97-98% accuracy or above.

Causal Loop Diagram

Below is the featured design for the domestic sales of the company. The key areas driving our domestic sales are R&D, Pricing, Visitor Happiness, Advertising and Branding, Promotions and Competition. Consider that by studying at the all the “interactions of the variables, the behavior of the entire system is discovered” [8]. Additionally, by using a causal loop diagram, our analysts will be able to “identify and visually display intricate processes and root causes” [9].

Stock and Flow Diagram

This is our stock and flow diagram for foreign sales. It offers us a qualitative look at the relationships and interactions happening with our foreign sales. “In system dynamics modeling, dynamic behavior is thought to arise due to the Principle of Accumulation. More precisely, this principle states that all dynamic behavior in the world occurs when flows accumulate in stocks” [10].