This article originally appeared in the M&E Journal: The Age of Data Transparency Issue, June 2018.
Data and Analytics
The benefits of data analysis can be used internally or externally
By Ramón Bretón, Chief Technology Officer, 3rd i
Abstract: When thoughts turn toward analyzing data, the notion of offering data review and analysis as a service outside of one’s organization often comes first. However, it is of equal value to apply analytics inward by measuring and quantifying internal performance metrics, with the goal of streamlining operations and improving efficiency. Furthermore, service providers collect much data that is of interest to their clients and partner companies, but this dataset is often an unmined resource. Interpreting this data often reveals new insights that can be offered as an additional service, requiring little-to-no extra investment.
To say that computers are ubiquitous in today’s business world is a vast understatement. One byproduct of the computerization of enterprise is data, and plenty of it. In fact, businesses generate so much data that they don’t realistically have time to inspect even a small portion of it via manual methods. Unless a business’s milieu is data analysis, a company may overlook its data and not see it for what it is: a valuable resource from which important insights can be gained. The knowledge discovered from data analysis can be internal, helping improve business efficiency, or external, offering insights to clients based on observations of their products and workflows.
The kinds of data generated will of course vary on a case-by-case basis. A consumer-facing business will generate different kinds of information than a business-to-business enterprise. Any media and entertainment service provider engaged in the business of consultation typically issues a report as its end product, the content of which is rich with valuable data to be mined.
Use case: Quality control consultants
To demonstrate the benefits of analyzing internal data, as well as the potential of providing knowledge gleaned from years of data as a new income source to clients, the use case of a media and entertainment quality control company can be examined.
A company performing quality control for home entertainment products – including physical discs, master files destined for broadcast or OTT transmission, and virtual and augmented reality applications – reviews content and flags any potential issues that may negatively impact the viewer. These issues are recorded and disseminated via a reporting system, which organizes the errors by specific classes and sub-classes while assigning severity ratings to the issues. All ancillary data for the content, such as technical details and the vendors responsible for creating the component assets, is tracked as well. In addition to the data revealed to the clients and partner vendors, the quality control company also tracks internal information, such as the operators involved in the review of the project, the time spent by the operators, the equipment and materials used, and financial information such as client billing and employee compensation.
An efficient reporting system also allows for client and vendor input. For example, an issue may be flagged by the quality control operator, commented on by the post-production vendor, followed by a decision to correct or waive the issue by the content owner. Finally, an indication by the quality control operator of the issue’s remediation status is recorded. The aggregation of this data spanning numerous projects over multiple years yields a vast amount of data to be mined.
Optimizing internal performance
Of primary concern for any intelligent business is improving efficiency. In the example of the quality control provider, analyzing the data housed in its reporting system readily serves this end. In looking for patterns in its data, the time and resources spent on the projects of particular clients can be measured against the income received for those projects. In this way, a metric can be established for the profitability of working with various clients. Acting on this data can lead to expending more effort to increase business from more profitable clients, while looking for efficiencies in the evaluation of the less productive content as a means of increasing earnings.
One place to find workflow efficiency is by establishing employee performance metrics. For example, for each operator, a correlation can be plotted for the number of issues they note versus the percentage of issues that are either acted upon or waived by the client. Operators with more efficient ratings can be shifted towards projects likely to be less profitable to help improve margins.
Client action or inaction on flagged items is also a helpful data point when it is grouped by issue classes. Using this info, account managers can direct staff to put more focus on certain issue types over others, as indicated by the importance placed on these issues by the client. Shifting operators to projects that better suit their work style, while offering clear directives based on the empirical evaluation of established data, can noticeably impact the expenditure of resources versus profits made.
Turning analysis outward
When a media and entertainment service provider has a relationship with a client spanning multiple years, the resulting data is a source of rich insights to mine. One example of knowledge to be imparted is the performance of the vendors responsible for creating certain components of the client’s content. The client may have a certain notion of a vendor’s performance, but this may be partially based on and influenced by casual information, such as personal relationships, ease of communication, and industry reputation of the vendor. While these are all important factors, an objective analysis of the data housed in the quality control consultant firm’s reporting system can offer a more impartial measure of a vendor’s performance. For example, metrics can easily be established for the accuracy of initial deliveries, redelivery rates, response time for inputting comments, and the time between requests for new assets versus delivery dates. While these factors may be noted in a casual sense by the client, oftentimes a comparison between the client’s informal rating of a vendor and the knowledge gleaned by an objective analysis of the data offers surprisingly different results.
When presented with knowledge gleaned from an unbiased review of concrete data, most content owners will be likely to act, leading to improved efficiencies in their distribution chain. This client-centric data analysis made by a media and entertainment service provider can either be offered as a bonus to strengthen client relationships or as an additional service offering for a new revenue stream.
Making data smart
Although the specific example of a media and entertainment quality control service provider has been demonstrated here, the principles involved can be applied to companies involved throughout the home entertainment production, post-production, and distribution chains. Data analysis can yield substantial benefits to internal performance, while offering new insights into the relationships between clients and the partners who help bring their content to consumers. All companies in the media and entertainment industry generate data – the smart ones make the most of it.
Ramón Bretón has 15 years’ tenure at 3rd i, a pioneering company in the field of quality assurance for the home entertainment industry. Prior to this, he spent ten years in the music business as an audio mastering engineer, giving him over twenty-five years’ experience contributing to quality entertainment for the consumer.
In addition to the physical journal, this also appeared on the Media & Entertainment Services Alliance (MESA) website.
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