Netflix Case Study On Environmental CSR Issues
This assessment task is divided in two parts:
Part A: You are required to prepare a Netflix case study report including the following points:
- Goals/strategies (you can reorder these sections if it flows more logically). Evaluate the organisation’s goals/strategies relating specifically to the chosen product/service type, including CSR-related aspects of their goals/strategies.
- Products/services Evaluate the selected product/service type which it sells to customers, including any CSR-related characteristics of the product/service.
Part B: You are required to write a 500 word Feedback Reflection Report summarising how you sought, interpreted and utilised the feedback, including providing evidence that your interpretation of feedback is accurate.
The report on Netflix case study aims to analyse the product and service delivery practices of Netflix and create a consultancy report based on CSR activities undertaken. Netflix is a tech and entertainment mass media industry that offers subscription-based streaming services to its users as a product (Rahe et al. 2021). It provides film production, distribution and television production distribution services as well. The current video streaming industry has a market size of $342.44 billion in 2019, where Netflix has 29% of the market share and is worth $25 billion. The chosen CSR regulation is environmentally responsible for reducing carbon footprint.
2. Client background
2.1 Products and services
Netflix provides on-demand online video streaming services to customers globally. They provide distribution and production services of films and television as well (Widdicks et al. 2019). Netflix has over 204 million subscribers and to provide seamless services to the customers, it costs 94,285 Mwh of total energy consumed in 2020. In 2019, Netflix consumed 81,136 MWh of energy. The increasing energy consumption indicates a high impact on the environmental footprint of hardware infrastructure (Marks et al. 2020). Netflix used 100% grid electricity in 2019 and 20202. Netflix continued to provide services that documented an annual carbon footprint of 51,467 MTCO2e in 2019. The carbon footprint decreased to 30,883 MTCO2e. The total emission is 2019 was 1,208,205 MTCO2e and in 2020 it was 997,457 MTCO2e (Cunliff, 2020.). Half of the company’s carbon footprint is generated from the physical production of content, corporate operation, purchased goods (content) and streaming services using data centre providers. It accounts for 50% in content, 45% for corporate and 5% in streaming in carbon footprint business activity.
2.2 Goals and strategies
Netflix is committed to sustainability motivated to bring sustainable changes in the organisation. The organisation will use science-driven carbon reductions to achieve Net Zero and Nature (Do et al. 2015). Under this initiative, Netflix has goals to achieve net-zero greenhouse gas emissions by the end of 2022. Netflix plans to reduce internal emissions by upto 45% by 2030. Netflix has a carbon footprint of 1 million metric tons in 2020. Netflix has defined environmental sustainability and corporate responsibility by defining three strategies- reduce, retain and remove.
3. Deliver tasks
(Attached framework :PPT)
Figure: Task delivery process under CSR initiative by Netflix
(Source: Lucidchart )
4. CSR problem
Netflix is currently facing environmental problems in CSR and trying to achieve compliance in CSR activities. The problem concerns the reduction of carbon footprint for Netflix. In the past few years, Netflix is facing issues to manage carbon emissions and has a high carbon footprint (Benjaafar et al. 2012). Netflix uses direct and indirect energy through electricity for operating the data centres and using AWS to run the data streaming services which consumes a high amount of electricity (Marks et al. 2021). Netflix needs to be vigilant and address environmental CSR issues. To address the environmental challenges of tackling carbon footprint, Netflix has devised a three-fold strategy to address the environmental issue. The strategy includes reducing, retain and remove. The Intergovernmental Panel On Climate Change in 2018 has declared that global temperature must not exceed 1.5 degrees C above pre-industrial temperature to check greenhouse gas emission and reduce carbon footprint. The company is striving to achieve global temperature without exceeding 1.5 degrees C and achieve GHG emission reduction to net-zero by 2050 (García and Freire, 2014). This will help them to reduce emissions when they achieve the set temperature. Netflix will retain existing carbon storage by neutralising them to prevent carbon from entering the environment by undertaking conservation-at risk projects. By 2020, Netflix will incorporate investment to regenerate critical natural ecosystems and achieve net-zero carbon emission. These projects will include restoring grasslands, remove carbon from the atmosphere and restore healthy soils. Netflix uses cloud services from Amazon web services and Open Connect content delivery network for streaming which accounts for 5% of carbon footprint.
At present, Netflix has recognised the importance of carbon emission and following Paris Agreements and compliances according to IPCC,2018. However, they face challenges like direct and indirect emission from Scope 1 and Scope 2 which is market-based and location-based carbon emission (Sotos, 2015). Netflix has Greenhouse Gas offsets of 36,506 MTCO2e in 2019. Netflix has limited operational control in many categories which creates challenges in measuring and reducing carbon emission when using direct or third-party production companies. Netflix has not included internet transmission and energy used in user devices by omitting it from Scope 3. This is seen as non-compliance with CSR as it does not generate an accurate measurement of carbon emissions created. Furthermore, Netflix understands that the present guidance for voluntary corporate Net Zero claims is not available (Deutch, 2020).
Significance of CSR regualtion
Achieving CSR compliance with reducing Carbon emissions and achieving Net Zero is critical for Netflix. Netflix understands the importance of sustainability by integrating storytelling as a concept to practice ethical CSR. Netflix is a growing company that has a huge market share. The growth of the company and agreeing to environmental policies are correlated and challenging for Netflix. Failing to comply with industry regulations can incur a huge fine for Netflix and a loss of trust from customers. Furthermore, Netflix needs to optimise to achieve operational efficiencies. Optimising will help Netflix to have cost-effective reductions and help to contribute to reducing its carbon footprint (Mahapatra et al. 2021). The company needs to decarbonize through electricity consumption and use a fuel source of zero emissions. Using non-renewable sources of energy can contribute to environmental pollution, degradation and wastage of scarce resources (de Souza et al. 2018). Reducing greenhouse gases is a significant challenge for Netflix as it is contributing to rising in global warming and climate change other than increased carbon emissions. This can disrupt the environment and fall under non-compliance with governmental regulations. Netflix can face negative impacts in operations, finances and create an additional burden of sourcing precious and expensive sources for fuel, electricity, and maintaining the data centres. The environmental degradation will cause Netflix to come under negative light under environmental protestors, activists, and people who care about preserving the environment. Non-regulation of CSR activities that harm the requirement can incur additional wrath from different governments where Netflix is operating. In the worst-case scenario, Netflix can get banned; temporarily or permanently in those regions. Netflix does not have proper initiatives to decarbonise and use renewable sources of electricity or using renewable fuels. Netflix has not disclosed any CSR activities or reports that describe the activity taken or how they can contribute to achieving Net Zero carbon emission by 2050 (Setoet al. 2021).
The negative impact of non-compliance
Netflix needs to comply with environmental agreements while undertaking CSR initiatives. While creating content Netflix does not optimise and does not use local crew. Netflix needs to install delivery caches close to members to reduce traffic or transmission of networks to optimise their resources. Although Netflix is 100% electrified, teh company lacks additional power to use clean mobile battery units and need to reduce the use of diesel generators. Netflix is dependent on non-renewable sources of energy which is increasing the cost of operation and slowing the process for achieving zero carbon reduction (Materazzi and Foscolo, 2019). Managing the value chain partners and supply chain management is critical for Netflix. Netflix does not have green SCM practices which increase the cost of production, procurement, and increases emissions from energy consumption like fuel and electricity. It impacts the supply chain production in material purchases, equipment and digital and post-production services.
5.AI solution evaluation
5.1 AI solution
To collect relevant data to address the CSR issues of carbon emission, Netflix needs a comprehensible strategy and must be able to collect relevant data types to analyse the solution. Netflix uses Kyoto Protocol to calculate their carbon footprint (Miyamoto and Takeuchi, 2019). The collected data is converted into metric tons of carbon dioxide equivalent according to the GHG protocol.
Netflix uses different data sources like live camera feed when doing delivery tasks to analyse the amount of electricity used against duration engaged by employees to carry out tasks like repairing, modifying network services, installing network devices or regulating network caches (Zhou et al. 2019).
The company maintain electronic records and log records to keep track of electricity usage, net hour consumption of internet and network services. The company maintains inventory and supplies for diesel and any other fuel sources outsourced, purchased or spent.
The inventory records help the organisation to restock inventory and regulate the supply chain. It can be noted that Netflix does not have a green SCM. the company maintains IoT sensors to track data from multiple sources, a well-designed ERP system and ERP log data that helps to monitor CSR compliance and actively calculate carbon emission in Scope 1 and Scope 2 including market-based and location-based guidance.
The analysis of data will be performed after data is gathered from different sources. The data collected will undergo supervised machine learning AI algorithm to study the data sets on carbon emissions, carbon reduction stages, carbon control. Using AI tool SkitLearn, Python and machine learning packages, a regression analysis will be conducted on supervised learning to generate trend analysis and forecast the rate of carbon emission and carbon reduction.
Predict cost incurred for noncompliance
It will cost around $2000 on average on monthly periods to run high and efficient calculations. Non-compliance with carbon emission can incur a fine starting at $30,000.
Identify cost incurred for non-compliance
The cost will be levied based on penalty charges, carbon tax, taxes on diesel. Using diesel will require 2.67 k/L and the tax per unit of fuel is $0.032/L or $0.12/US gal. furthermore, the company has to be vigilant in utilising electricity to manage operational costs which are charged at $6.66/kW/hour.
Alert in real-time
The company will get real-time alerts for non-compliance by realising the data and using the prediction score generated from regression (Gao et al. 2021).
Prediction of non-compliance
A feasible AI solution that is real can be obtained from big data analysis that can be conducted internally. Using patterns, trends and NLP toolkits, AI will use functional libraries to analyse the big data volume of records and datasets gathered as data input or sources by Netflix.
Likelihood of non-compliance
It will be able to statistically measure the compliance and non-compliance ratio by tracking carbon emission, global environmental projects undertaken, carbon reduction statistics, soil preservation among other biodiversity preservation activities.
5.2 AI solution viability evaluation
Alignment of client objectives
The AI solution is viable with the current strategic goals and objectives of Netflix. Netflix has targeted two-phase reductions, by 2030 and 2050. The AI algorithm will track if the conditions are met and check carbon reduction by 45% in the first phase and achieving Net Zero or 100% reduction by 2050.
However, it can meet different challenges when validating the data. The first challenge will be collecting updated data every year. The large volume of data can have difficulty in collecting from all the branches. Furthermore, the biggest challenge lies in incomplete data, null data or data duplicates, there will be data outliers among the useful data sets that can deviate the results and show false positive or false negatives that can disturb the offset of data gathered. Collecting the data will require precision and honest disclosure from the organisation. Data manipulation can be challenging when trying to track the non-compliance factors. Employee resistance can have a significant impact on the data collection process. The possible resolution for data collection and data analysis is using AI to back up old data. Using data modelling to train the data sets without having issues of underfitting or overfitting (Koehrsen, 2018). The data will be cleaned and checked for noise or incomplete data. Data complexities can be handled using experienced staff and analysts who can train the data for scalability and high performance. When new data will be given to the program, using data modelling, the same algorithm can be run with little changes. employee resistance can be addressed with proper training and guidelines set by the company.
It is possible that Netflix has issues to implement new AI technology. In this scenario, the company can outsource a team or have official recruitment to handle the data analytics section. Although Netflix uses advanced technology like IoT, Big data, and Cloud computing, the organisation will be able to train employees to handle complex data sets and run algorithms to check carbon emission, projected carbon levels, prediction scores, errors and calculations related to datasets. They can use neuro-fuzzy models for carbon prediction in the next few years to contrast and compare with previous emissions. They can implement PCA testing to forecast carbon emissions over the next 10 years and handle strategies to implement them in real-time(Huang et al. 2019).
Client’s capacity to afford AI solution
Netflix’s capacity to afford the AI solution will reflect how they use data analysis to implement the CSR strategy positively and execute it regularly. A realistic solution through AI-driven technology works best for Netflix. It may not require cost-benefit analysis or financial analysis, however, doing the analyses will help the organisation to effectively track areas that contribute to most carbon emissions. It can be explained through content and corporate use of Netflix that contributes to 50% and 45% of carbon emissions respectively. As Netflix deals with a large volume of media content that requires cloud technology involving the use of electricity and network usage, it will increase the carbon emission if not tracked or reduced using alternatives.
The present circumstances dictate that AI-based solutions are more realistic and financially achievable for Netflix to address the carbon emission. Using AI-based solutions are economical, time-saving, is accurate and high precision. The chances of error percentage are very minimal in comparison to non-AI methods or traditional methods. It can be justified through AI which produces high-end results with greater accuracy, precision, and ways to resolve error issues without wasting time. If the data analysis is conducted using traditional approaches, it has issues of data duplicates, erroneous data and unable to handle complex data. The current CSR issues can be examined using AI technology which uses different data sources, solve complex calculations and provide graphical representation along with advanced visualisation. Therefore, for Netflix, it is feasible to use AI solutions.
This consultancy report addresses the environmental CRS issues of Netflix and carbon emission reduction. Netflix is a global streaming giant that offers subscription-based content to people globally along with production services. Netflix adheres to set limits in Paris agreement for greenhouse gas emission control and carbon emission reduction as set to achieve zero carbon by 2050. The company is compliant with the norms set, however, still needs to achieve the required targets set by 2030 to achieve zero carbon emission. Netflix is not successful to reduce carbon emission through scope 1 and scope 2 due to direct and indirect emissions used by data centres powered by AWS cloud services. They are dependent on diesel generators and have no sources for renewable sources of energy for electricity grids, although have achieved 100% electricity grids in some countries. It is strongly recommended for Netflix to limit the use of fossil fuels and use renewable sources in electricity consumption and limiting the use of international networks. Employee resistance can be handled with the participation and involvement of employees in the data collection and data analysis process. With understanding and explanation, resistance to data collection can be overcome.
List of references
Benjaafar, S., Li, Y. and Daskin, M., 2012. Carbon footprint and the management of supply chains: Insights from simple models. IEEE transactions on automation science and engineering, 10(1), pp.99-116.Available at:https://ieeexplore.ieee.org/abstract/document/6248180
Cunliff, C., 2020. Beyond the Energy Techlash: The Real Climate Impacts of Information Technology. Information Technology and Innovation Foundation.Availableat:https://itif.org/publications/2020/07/06/beyond-energy-techlash-real-climate-impacts-information-technology
de Souza, E.S., de Souza Freire, F. and Pires, J., 2018. Determinants of CO 2 emissions in the MERCOSUR: the role of economic growth, and renewable and non-renewable energy. Environmental Science and Pollution Research, 25(21), pp.20769-20781. Available at:https://link.springer.com/article/10.1007/s11356-018-2231-8
Deutch, J., 2020. Is net zero carbon 2050 possible?.Joule, 4(11), pp.2237-2240.Available at: https://www.sciencedirect.com/science/article/abs/pii/S2542435120304050
Do, C.T., Tran, N.H., Pham, C., Alam, M.G.R., Son, J.H. and Hong, C.S., 2015, January. A proximal algorithm for joint resource allocation and minimizing carbon footprint in geo-distributed fog computing. In 2015 International Conference on Information Networking (ICOIN) (pp. 324-329). IEEE. Available at:https://ieeexplore.ieee.org/abstract/document/7057905
Gao, M., Yang, H., Xiao, Q. and Goh, M., 2021. A novel fractional grey Riccati model for carbon emission prediction. Journal of Cleaner Production, 282, p.124471.Available at:https://www.sciencedirect.com/science/article/abs/pii/S0959652620345157
García, R. and Freire, F., 2014. Carbon footprint of particleboard: a comparison between ISO/TS 14067, GHG Protocol, PAS 2050 and Climate Declaration. Journal of cleaner production, 66, pp.199-209.Available at: https://www.sciencedirect.com/science/article/abs/pii/S0959652613008494
Huang, Y., Shen, L. and Liu, H., 2019. Grey relational analysis, principal component analysis and forecasting of carbon emissions based on long short-term memory in China. Journal of Cleaner Production, 209, pp.415-423.Available at:https://www.sciencedirect.com/science/article/abs/pii/S0959652618331445
Koehrsen, W., 2018. Overfitting vs. underfitting: A complete example. Towards Data Science. Available at:http://www.pstu.ac.bd/files/materials/1566949131.pdf
Mahapatra, S.K., Schoenherr, T. and Jayaram, J., 2021. An assessment of factors contributing to firms’ carbon footprint reduction efforts. International Journal of Production Economics, 235, p.108073.Available at:https://www.sciencedirect.com/science/article/abs/pii/S0925527321000499
Marks, L.U., Clark, J., Livingston, J., Oleksijczuk, D. and Hilderbrand, L., 2021. Correction: Streaming Media’s Environmental Impact. Media+ Environment, p.21985. Available at:https://mediaenviron.org/article/17242-streaming-media-s-environmental-impact
Marks, L.U., Clark, J., Livingston, J., Oleksijczuk, D. and Hilderbrand, L., 2020. Streaming Media’s Environmental Impact. Media+ Environment, 2(1), p.17242.Available at:https://ieeexplore.ieee.org/abstract/document/7057905
Materazzi, M. and Foscolo, P.U., 2019. The role of waste and renewable gas to decarbonize the energy sector. In Substitute Natural Gas from Waste (pp. 1-19). Academic Press.Availableat:https://www.sciencedirect.com/science/article/pii/B9780128155547000015
Miyamoto, M. and Takeuchi, K., 2019. Climate agreement and technology diffusion: Impact of the Kyoto Protocol on international patent applications for renewable energy technologies. Energy Policy, 129, pp.1331-1338.Available at:https://www.sciencedirect.com/science/article/abs/pii/S0301421519301363
Rahe, V., Buschow, C. and Schlütz, D., 2021. How users approach novel media products: Brand perception of Netflix and Amazon Prime video as signposts within the German subscription-based video-on-demand market. Journal of Media Business Studies, 18(1), pp.45-58. Available at:https://www.tandfonline.com/doi/abs/10.1080/16522354.2020.1780067
Seto, K.C., Churkina, G., Hsu, A., Keller, M., Newman, P.W., Qin, B. and Ramaswami, A., 2021. From Low-to Net-Zero Carbon Cities: The Next Global Agenda. Annual Review of Environment and Resources, 46.Available at:https://www.annualreviews.org/doi/abs/10.1146/annurev-environ-050120-113117
Sotos, M.E., 2015. GHG Protocol Scope 2 Guidance.Availableat:https://www.wri.org/research/ghg-protocol-scope-2-guidance
Widdicks, K., Hazas, M., Bates, O. and Friday, A., 2019, May. Streaming, multi-screens and YouTube: The new (unsustainable) ways of watching in the home. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (pp. 1-13). Available at:https://dl.acm.org/doi/abs/10.1145/3290605.3300696
Zhou, Y., Fan, X. and Son, J., 2019. How and when matter: Exploring the interaction effects of high?performance work systems, employee participation, and human capital on organizational innovation. Human Resource Management, 58(3), pp.253-268. Available at: https://onlinelibrary.wiley.com/doi/abs/10.1002/hrm.21950
Netflix Net Zero report(2020). https://ir.netflix.net/governance/ESG/default.aspx