Opportunities of Leveraging ’Big Data’ for Entravision

Adoption of ‘Big Data’ initiative for Entravision began as a result of the meeting between Franklin Rios and Walter Ulloa on March 2012 in Santa Monica. Franklin Rios was an independent professional who dealt with digital marketing. On the other hand, Walter Ulloa was the founding chairman of Entravision Communications Corporation (EVC). EVC was a Latino-based broadcasting company that focused on Spanish –language. EVC focused on Latinos, which referred to origin and ethnicity of the targeted Americans and not race.  The Latino market was heterogeneous, and the majority were people with the Mexican Heritage. Latinos group of Americans did not blend with other groups such as the whites, but instead, they opted to carry their indigenous ancestry as a significant source of their differentiation.

After the meeting, Rios was able to secure Ulloa’s agreement Luminar division at Entravision. Luminar was to be a data analytics division that Rios believed will be able to leverage ‘Big Data’ for Entravision using corporate entrepreneurship. Perhaps the media industry in the United States of America was complex and required digitization of broadcasting services. The analysis of U.S broadcasting industry was majorly categorized into four groups, i.e., publishing, advertising, movie production, and entertainment. Advertising was a significant source of revenue for EVC due to viewership. Although advertising seemed to be the best media category for EVC, it faced several challenges such as a rapid increase in social media platforms such as YouTube and also consumerization of media technology as far as Hopper product is concerned.

Rios summed up these media challenges into three main triggers for leveraging ‘Big Data.  This database issue as per Rios’s analysis includes sample error, sample size issues and sample biasness in database analysis. Perhaps the remedies for database issues include the adoption of customized content to view customer needs to make the whole process interactive, adoption of crowdsourcing content that cuts on operating costs and concise identification of new strengths of revenue by changing the accompanying additional fee for media transactions. Rio had a different concern on leveraging ‘Big Data’ which he believed would secure internal buy-in, ensure there is structure fit between Luminar and EVC, an issue on performance milestones and Luminar sustainability. Therefore, Ulloa agreed for Luminar to operate as a division within EVC under the leadership of Rios on the account that Luminar will increase Entravision’s revenue, i.e. generate 10% revenue within five years of its operation.

Problems/Important Issues

The decision for Rios to leverage ‘Big Data’ for Luminar at Entravision comes with a concise study of the problems that the United States of America’s Media Industry face. Also, Rios’s decisions are based on an analysis of the most critical issues that deem necessary for EVC to adopt the ‘Big Data’ system. For U.S media industries, the following are theoretical problems that called for the need EVC to digitize its broadcasting activities;

1. The issue of sample error in quantitative analysis

2. Overreliance on the qualitative type of data analysis as opposed to adopting a quantitative approach to data analytics

3. The existence of sample biasness in data analysis.

On the other hand, the most critical issues that call for EVC to leverage ‘Big Data’ using the Luminar division are bestowed upon Rios’s arguments for adopting the new technology. These issues include;

1. Securing internal buy-in and removing internal roadblocks inside EVC. Rios believes that it will be difficult to build a support base at EVC since analytics has never been part of the company’s DNA

2. The need for defining goals/targets and performance metrics/KPI (Key Performance Index) to measure EVC’s success

3. The issue of selling ‘Big Data’ solution to clients without any record for successful projects

4. The issue of establishing EVC performance milestones

5. The problem of sustaining a first mover advantage for the Luminar division, e.g. by building an entry barrier to potential competitors in the market.

6. Establishing a structural fit between Luminar and EVC which Rios believes that the whole process comes with an analysis of both the advantages and disadvantages of operating as one body or separate entities.

7. The issue of how “Big Data’ will be leveraged at EVC, i.e. will Luminar exploit the novel commercial opportunities or what kind of clients will it address?

Analysis of the Case

Assessment of Opportunities

The luminar division is the best strategy that EVC could use to digitize its broadcasting services. Sample error, sample size, and sample bias issues were prevalent for EVC, and thus leveraging of ‘Big Data” is necessary. The urge for the adoption of ”Big Data” technology makes Rio’s concerns valid, creating the need for the establishment of Luminar Division by Entravision. As defined by McKinsey, ‘Big Data’ refers to those sets of data whose size is considerably beyond the ability of a typical database software tool used for capturing, storing, managing and analyzing large sets of data. ‘Big Data’ requires high-volume, high-variety, and high-velocity data assets which usually need cost-effectiveness and innovation forms of data processing for enhanced decision making and insight.

Rio assessment of opportunities regarding leveraging of ‘Big Data’ as a counter-strategy for the challenges that EVC is facing is the best approach for the broadcasting company. Rio highlights three success factors in his assessment of the opportunities that Entravasion has by leveraging the ‘Big Data.’ These factors include;

Generation of Relevant Programming

Rio’s ”Big Data” analytics will assist Entravision company to generate a useful programming technique that will help in analyzing collected data. Perhaps there is the need for using a quantitative approach in analyzing broadcasting data as opposed to the analog qualitative manner that EVC uses. Big Data analytics will assist EVC to examine vast amounts of data to uncover hidden correlations, insights, and correlations in broadcasting operations. This effectiveness in the generation of data programming is based on high-velocity characteristics of Big Data analytics. For instance, it is possible for EVC to analyze data and immediately get intelligent solutions to questions. Therefore, I agree with Rio’s success factor of Big Data analytics generating relevant programming for EVC.

Having A Clear Market Position

 I agree with Rio that leveraging ‘Big Data’ analytics will assist EVC to create a transparent market stand in the broadcasting industry. One of the growth strategies that Rios had was to develop a mechanism for sustaining the mover advantage for Luminar. This sustainability is to be built through creating high entry barriers for potential competitors trying to adopt the same technology in the broadcasting industry. Through utilizing the new business model, EVC will have a higher competitive advantage in the broadcasting sector since its services will be faster and of high quality, and hence they will be able to have a precise and reliable market position in the entire broadcasting industry. Big Data analytics will assist in reducing the costs associated with marketing the company. Perhaps Big Data technologies such as cloud-based analytics and Hadoop bring significant benefits when it comes to storing large sets of data. These technologies also can effectively identify the most cheaper ways of doing business and looking for market hence maintain the market position of the company.

EVC will be able to maintain its market position based on the faster and effective decision-making process brought by Big Data analytics. With the high speed of in-memory data analytics, combined with a robust ability to analyze new sets of data, EVC will be able to process information immediately, and thus decisions will be easily made based on exactly what has been learned. Swift service delivery by EVC to clients will increase customer loyalty to the company, and hence a clear market position will be created. ‘Big Data’ analytics will also assist EVC in creating new products and services for the customer’s satisfaction. The technology can gauge the customers’ demands and satisfaction, and hence the company will know how to handle customers’ needs who will intern remain loyal to the company creating a clear market position for EVC in the entire broadcasting industry.

Keep Pace with New Technologies

According to Rios, ‘Big Data’ analytics will assist EVC to keep pace with the advancement in technologies within the broadcasting industry. I agree with Rios in the sense that Big Data analytics is a continuous technology which is not rigid like the analog programming techniques for analyzing data that was anciently used by EVC. Big Data analytics was not part of Entravision’s DNA, and the company solely depended on conventional tools for analytics to analyze data. These traditional tools include data warehousing(DW) and the business intelligence which differed significantly from the Big Data analytics. Rios believes that by adopting Big Data, EVC will be updated with the newest technologies that have advantages such as high volume, value, variety, and velocity.

Rios believes that the success of the Big Data analytics project is also built on the foundation of a higher competitive advantage that EVC enjoys in the American broadcasting arena. Perhaps EVC’s competitive advantage is Latino-focused programming which Rio believes is further-grained only to the needs of specific communities. EVC has been able to build its brand identity as one of America’s broadcaster by considering the local nature of its news and features which considerably separates Cuban Latinos programming from that of Puerto Rican Latinos and the rest of the Latinos. The Success of the Big Data analytics also is based on the advantage that EVC is located in geographical areas which are fast-growing and densely populated. Emphasis is on Latinos whose growth statistics indicates that there will be a 162% increase in their number. An increase in the number of Latinos translates to an increase in the number of customers for EVC and hence the success of Big Data in the Luminar division.

Applications and Process Issues

Big Data installation is a technology that replaces the ancient way of analyzing broadcasting data which was only qualitatively oriented. Within the United States of America’s media, T.V and broadcasting were the old and largest broadcasting category which consisted of cable, terrestrial and satellite broadcasters for both analog and digital TV programming. The programming was highly regulated by FCC (Federal Communications Commission) which aimed encouraging competition and use of spectrum technology. IN June 2009, FCC mandated media companies to switch from analog to digital broadcasting, enabling many players to come into the industry.

Therefore, Multicasting technology became common due to the digitization process by FCC. Multicasting technology involves communication between a single information sender and multiple receivers. Multicasting technology is supported by wireless data networks which act as part of the Cellular Digital Packet Data technology (CDPD). Digitization became a challenge to broadcasters and their revenues reduced as far as advertising is concerned. These challenges include the use of Youtube to advertise and also consumerization of technology, i.e. the Hopper product. To remedy this situation broadcaster adopted new techniques such as crowdsourcing of content in the attempt to reduce operational costs. The companies customized media content to view clients’ needs making the whole process interactive. Broadcasters also designed technology for remote ordering of products in a commercial set up.

            Big Data analytics was a replacement for conventional tools of analytics. These tools include Business Intelligence(BI) and Data warehousing (DW). BI and DI processed a low sized set of data which were measured in terabytes, but Big Data can manage large units of data up to geopbytes. EVC has been using the qualitative tool of analyzing data, based on sampled and self-reported strategy to compile all viewership ratings in the Research and Development (R&D). Also, cloud computing is a current technology that is used in analyzing and storing huge-sized data. Cloud computing technology uses a number a network of remote servers that are hosted on the internet to manage, process and store data, rather than a personal computer or a local server. Cloud computing requires minimal management efforts and provides a higher-level service over the internet.

Suggested Approaches for Generating Revenue

Rios proposed adoption of ‘Big Data’ analytics for EVC to add value to the company by providing a specialized consultancy service to all corporations that seek detailed market research concerning Latinos. Rios suggested the following approaches which perhaps makes sense as far as a value addition for EVC is concerned.

1. Luminar to contact clients asking them concerning purchasing patterns of the Latinos. Many clients had unanswered questions concerning the way Latinos make purchases. Rios indicates that the clients will be able to provide feedback using the data that trickles down to household level and the zip code. These level of data will enable Luminar to assist its clients in solving longstanding and classic attribution marketing problems, and thus advertising will increase, sales increase and the general value of the organization will also increase.

2. Luminar to help clients process the data that they possess.  Clients can maintain data as either a Luminar’s Big Data or as a stand-alone. Through assisting clients to process their data, EVC will be able to generate valuable new information which the company can, in turn, utilize in marketing their products.

3. Luminar to offer client firms with additional insights and information concerning potential market opportunities which they had not encountered. It is indeed possible for Luminar to provide relevant evidence that the client possessed a currently untapped, valuable and unrecognized market opportunity provided they market a particular product brand, a specific location and for a given price. Big Data will assist Luminar to predict consumer buying patterns by merely tapping a vast array of information concerning purchasing on segments that are comparable. Through the creation of accurate insights in purchasing, clients will remain loyal to the company and hence the company generates value as far as market share in the broadcasting industry is concerned.

Recommendations

 It is possible to generate value at EVC using Big Data by merely changing the organizational culture. The technology needs to create incentives and behavior for managers who think of using data to drive decisions. Perhaps corporate culture translates to skills within the company regarding data visualization or data science skills. These skills need to make sense and harness off of ‘Big Data.’ EVC should also know how to embark on the first project and how to use technology to leverage value out of ‘Big Data’

Conclusion

After the meeting between Rios and Ulloa, Rios was mandated to begin his ‘Big Data’ project using Luminar as a division of Entravasion. Ulloa provided funds inform of capital and operational costs for ‘Big Data’ at Luminar. Luminar became operational although Rio had worried that maybe the returns from ‘Big Data’ investments would not meet the leveraged value from EVC. Presently, Luminar still exists at Entravasion although it was rebranded to Pulpo. Therefore, Pulpo mainly targets the Hispanics and it has the most massive Hispanic reach in the current times as measured by comScore.  As indicated in their official website, Pulpo reaches to approximately 40 million Hispanics monthly.   Pulpo places device-compatible and targeted ads on mobile, web, social media, or video. Pulpo is unique as compared to the ancient Luminar in the sense that Pulpo is committed to reaching out to Hispanics across all acculturation levels. Pulpo is perhaps a proprietary segmentation and targeting algorithm. Pulpo offers precision tools to ensure there are maximum returns on investments (ROI). Pulpo leverages its Proprietary modeling technology and proprietary analytics that reflects the attitudes and behaviors of the current Hispanics and Latinos in general. Therefore, Pulpo continually utilizes a combination of radio, digital operations and television to reach out to Latino consumers across the United States of America and also Mexico and other U.S borders.