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MGMT20130 Operations Management And Business Analytics

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MGMT20130 Operations Management And Business Analytics

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Course Code: MGMT20130
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Question
Task Summary (what is it I am going to do?)
You will write a concise business report aims to report the latest issues of operations management (OM) and technology development. We all face that industry has changed dramatically in the past two decades since the Information and CommunicationTechnology (ICT) revolution, which has ushered in the era of Industry 4.0. Under Industry 4.0, mobile computers and machines are connected through the Internet, and smart enabling technologies (i.e. Cyber Physical System (CPS), Internet of Things (IoT), Big Data, etc.) are created through automatic identification physical sensors equipped with tiny computers. Data stored and located in physically separated places are processed and analysed quickly by numerous computers and applied to manufacturing and/or services, for example, computerembedded machines and equipment enable the production of the right products/services to be delivered to the right customers at the right time. On the other hands, from the business perspective, Industry 4.0 drives management research towards creating new concepts and methodologies to realise synergy effects across industries that work together on the same business platform and/or system. To stay competitive, all firms need to consider and adopt new approaches of innovation, manufacturing, procurement, and logistics.
Relevance (why am I doing this and how is it relevant to my learning?)
The task will develop your skills and the application of latest OM concept and theory in a real world context or firm (manufacturing or service industries) in which you are regularly involved. Specifically, you are expected to select and answer one of the following core questions for Industry 4.0 and smart enabling technologies (choose one):-
Q1: How do firms exploit smart enabling technologies and digitisation to yield competitiveness?Q2: How do firms utilise Big Data to improve the effectiveness and efficiency of production and services?Q3: How does Industry 4.0 implementation influence the design of manufacturing and service systems, and the workplace?

Answer

Smart Technologies and Digitization of Agricultural Farms

Introduction
The modern market and industries, customers were expecting more digitization from firms than never before. Their direct and indirect digital expectations were packaged in terms of products and services and convenience, accuracy, productivity, and speed respectively (Walter, Finger, Huber & Buchmann, 2017). But digitization and other technologies had a significant role in influencing the organization’s operation management (Howard, 2015). This is because the organization attached more attention to the time, resources, and leadership for improving operations, thus it was a matter of integrating every aspect of the operations management and digitization to work harmoniously.
Digitization had an impact on the human resource in operations management. In this case, developing human capabilities became critical. Adopting modern technologies to take over repetitive tasks created efficiency in operations (Karmarkar & Apte, 2007). Also, the personalization of technologies such as machine learning had revolutionized the roles of people in operations which may call for new skills. For instance, the use of various sensors in the farm fields assists in creating efficiency, accuracy, speed, and convenience.
Modern farming required seizing the digital moment in operations management (Klerkx, Aarts & Leeuwis, 2010). In this case, we say that farm operations management needed digital as much as the digital needed operations management. Digitization of operations made management of farm activities more effective and competitive. The commitment to embracing and integrating modern technology innovations and operations management in agriculture was a major breakthrough in remaining competitive in the market. By use of internet of things, data centers, computer systems, integrated computing, agriculture became competitive than before. This is because production became quality and customer service convenient.
Digitization in production was only a part of the larger operation, as automating irrigation processes in the farm (Le Gal, Merot, Moulin, Navarrete & Wery, 2010). It needed to be done in the whole firm and every operation oriented its operations exhibited digital characteristics. This included integrating technology in all the departments and aspects of the farming organization. That was, investing in machinery, computer systems, and other hand wares couples with appropriate training of the people in the organization. The management pays attention to acquiring these technologies for the ease of interoperability.
For the purpose of this business report, much on industry 4.0 initiatives and smart enabling technologies in the agricultural industry, were explored. It was discussed in connection with operations management for the achievement of market competitiveness. Further, digitization of farming operations and seamless integration of product, people, place, and processes will be discussed. It also continued to develop on the types of digital technologies that have created value in the modern agriculture, besides exploring both sides for using technology in farm operations. For further illustration, I used a case study of the agricultural firm to have an insight on the digitization and application of smart technologies in various areas of operations to improve its competitiveness. And lastly, I outlined the trends in digitization of agricultural operations management.
Digital farming
This reviewed basics on the digitization and use of smart technologies in farming, the values attributed to the use of these technologies as well as the downsides, a case study on the smart farming, and trends in modern agriculture.
Automated application of seeds and fertilizers, system steering, field robots and drones (Tripicchio, Satler, Dabisias, Ruffaldi & Avizzano, 2015), and sensors for soil analysis are the new adoptions in farming operations and management. There are many questions being asked by many is whether it is a curse or a blessing. But one thing remains certain, digitization of farming operations and production create a successful agricultural farm. Digitization and use of smart technologies in agriculture are growing at an exponential rate close to none. Statistics in agriculture have shown that back in 2015, more than 30 percent of the total value created worldwide comes from software, electronic, and sensors. This is more and over three times the value created in the automotive industry. Therefore, it has become essential for farmers to integrate modern digital technologies in agricultural operation systems to create efficiency and sustainability in production and thus competitiveness (Walter, Finger, Huber & Buchmann, 2017).
Value creation through digitization and smart farming
Agriculture constitutes interconnection of complex individual operation activities. To create competitiveness, operations management tasks needed to be organized to ensure a smooth flow for efficiency and better productivity (Greenstein, 2010). For an agricultural farm to be successful it comprised of the farmer, technology, and other services like consulting.
To explain the value created through digitization and use of smart technologies, there were two important terms the crop up, which were precision farming and smart farming. Smart farming is an evolution in the agricultural activities from precision farming to digitized and more connected operation management system. In smart farming, precision farming tools were used together with intelligence networks and data management. In particular, digital farming aimed at leveraging all the available information and knowledge for the automation of agricultural operations.
Precision farming became possible because of the availability of GPS signals to the general public. It enabled specific site-monitoring and control by tools in the farm fields. The use of precision farming increased accuracy in agricultural and in-field operations. The aim is to improved productivity and product, customers’ satisfaction, create efficiency, and ultimately culminate to competitive advantage (McBratney, Whelan, Ancev & Bouma, 2005).
Precision farming
In precision farming data about the farm-specific locations and crops were collected and used in making new production and management decisions (McBratney, Whelan, Ancev & Bouma, 2005). It involved the use of sensor technologies and application methods to accelerate production and growth conditions. Compared to traditional agricultural practices, precision farming utilizes the farm resources and creating efficiency. This practice was important also in improving human productivity and quality outputs.
Farms electronically retrieved information about different parts of the farm with different soil properties and productivity making decision making and response to be real time. This information about the farm and soil properties were recorded and stored electronically for easy retrieval. Farms also used the satellite-controlled system to accurately guide agricultural machinery along the lanes with intelligent sensors to controlled and targeted seed, fertilizers and pesticides applications. This digitization was cost-effective in terms of controlled wastage and fuel consumption by machinery as well as making time-saving.
Farmers were not talking about the size and volume because they have realized that future farming technology concepts are about features like “smaller”, “more intelligent”, “and more efficient”. This was a forward-looking digitization that consumes less space, power and saves on time and cost. Majority of modernized farms are using drones to capture aerial images of the farm fields (Tripicchio, Satler, Dabisias, Ruffaldi & Avizzano, 2015). These images provided valuable information about the farm including soil quality and the presence of weeds and diseases. The farmers were able to retrieve these data within the shortest time and take appropriate measures to mitigate any situation in the field (Jhuria, Kumar & Borse, 2013). The use of farm robots to for soil treatment and application of pesticides on plants was another innovative method in the farms especially because they are light and fast. These devices were remotely controlled and information stored in the cloud from which patterns and variations in sowing and fertilization can be established. The robots were also used to remove single weeds.
It had been observed that the use of drones and robots in farming has greatly improved the productivity levels as well as the quality of the produce (Tripicchio, Satler, Dabisias, Ruffaldi & Avizzano, 2015). Besides that, they have solved the problem of workers safety while operating machinery which they substituted. The use of these tech tools had also saved on time in production operations. Thus, the farms which had adopted these farming practices have remained competitive aspects of the quality product, customer satisfaction, and general internal efficiencies.
Smart farming
This was also referred to as Farming 4.0 and digital farming. Smart farming is the use of agricultural information and data technologies to upgrade the farming systems (Campbell, Thornton, Zougmoré, van Asten & Lipper, 2014). Those farms that had integrated smart agricultural technologies and data centers have enabled seed planting to be adapted to a specific field to ensure that the production process is efficient. Through the use of information and data technologies available farmers were able to make informed decisions based on data those data.
Smart farming also involved controlling of other devices in the farm. Farms which had adopted device control have created a web where agricultural machines were able to communicate among themselves (Fukatsu & Nanseki, 2009). For these devices communicate, they had to access electronic field record files. However, farmers had a lot of information to process from these devices, that why there were farm management systems, farm apps, and other online farmers’ supports. In this case “smart farming” is not about a single machine operation but the whole farm operations. The information and data from these devices were accessed from a centralized mobile app or farm management support in their mobile phones or tablets (Kaloxylos et al., 2014). These data included soil and plant conditions, field terrains, climate, weather, resource usage, labor, and finance needs.
Smart farming was a modern choice for farmers. It was worth noting that modernizing operations in the farm was an important orientation for creating competitive agribusiness firm. Smart farms were digitally accessible and farmers were able to control the operations of their firms as well as being able to make informed decisions. Therefore, when operations management is well optimized by the use of appropriate technology, the farm became competitive.
To small farmers
Modern technology farming was dominant in large farms because small-scale shies away from it (Kalusopa, 2005). The Augustenberg Agricultural Technology Centre (LTZ) (n.d), a state agency of the Baden-Württemberg Ministry of Rural Affairs and Consumer Protection, had tested the precision farming for years and concluded that it had both economic and ecological benefits for agricultural businesses. The advantages that accrue to the farms as identified by LTZ improved product quality, high productivity, reduced cost of production, and farming documentation.
Farmers had also engaged in an external partnership for investment cost reduction especially in acquiring machinery and smart agricultural technologies. For instance, The Baden-Württemberg Machinery Rings Association offered shared use of machinery and other farm services. These services were tailor-made for specific farm and assisted the farmer to navigate to big data which is more efficient, economical, and sustainable. Service providers made information and data collected, analyzed, and automated, available to the farmers at their request to make appropriate operation decisions (Wolfert, Ge, Verdouw & Bogaardt, 2017). Small farmer also used digital technologies for the place of staff. The field records and information therein was used to eliminate some steps in farming operations.
Importance of digital technologies
The use of digital technologies in agriculture had a significant contribution to the growing global needs for food. This also led to sustainable primary production. The projects on “smart agriculture” also found funding from such program as The EU’s Horizon 2020 Programme for Research and Innovation (n.d).
The many new markets were opened up by increased use of digital technologies in the agricultural industry. Because of changes in demand and market knowledge by the customers, through digitization and smart technologies, farmers were able to own production chain for their product. In this regard, start-up companies were able to produce creative products by use of smart technologies and digitization. Using these systems made documenting planting, field preparations, milling, and processing possible and ease of use by the customers.
Another important point to give smart technology upper hand is the continuous development of novel products in the agricultural industry. The revolutionary products provided farm owners with the opportunity to satisfy the need for food in the world whilst made their farms successful. For instance, agricultural GPS systems (e.g. AGCO, Claas, CNH, John Deere, Krone, Lemken, Rauch, etc.) had significantly resulted to a reduction in the level of pesticides and fertilizers used in the farms. The farmers were able to conserve the environment by use of own electricity to power tractors which are battery-powered, emission-free with lower noise. Development in digital technology has led to growth in the introduction of farm sensors, optical recognition systems, and digital positioning. In harvesting, farmers were almost left with monitoring role as harvesting machines were becoming autonomous and available to farmers.
Recommendation and Conclusion
The need for promoting digitization in operation management
Recommendation
Many farmers around the world had realized the need for using smart technologies in modern farming. A survey carries out by Bitkom (n.d), Berlin, an industry association, showed that more than 85 percent of all agribusinesses view digitization as a way to efficient use of resources. Many companies which participated in the survey were using smart agricultural technologies and farm management utilities. The trend predicted that the shift to smart agricultural technology was growing rapidly around the world.
To accelerate this rapid growth in adoption of smart technology, there was a basic prerequisite for expanding internet connections event to the rural areas. By implementing network wider coverage, the digital field record system in a database will be accessible in real time. The real-time accessibility of database was not only for operational efficiency but also sensor control of the machines on the farm fields. This was important for detection of barriers in the farm.
Economic initiatives on policies should be instituted to create a better environment for agricultural digitization to thrive. Interdisciplinary programs should be used to approach the development of smart agriculture technologies to solve changing problems in farms fields. Such programs like funding of farmers to see the benefits of these technologies, extending agricultural support programs to remote areas to enlighten the farmers on the need to embrace modern farming in their operations, and having agricultural clusters that look into the needs of the farmers as far as technology supports are concerned.
Conclusion
Operation management in agriculture has really changed and tasks made efficient and convenient, that is with the rate at which information processing converted to cloud systems is unprecedented (Buyya, Yeo, Venugopal, Broberg & Brandic, 2009). A farmer who had embraced the smart agricultural technologies is able to automatically collect, analyze, and store farm data in the cloud system. The data in the cloud was retrievable at any time by using mobile devices. One of the advantages that accrued to the cloud system was the shared data with the service providers and suppliers, making it an easy and convenient way for farmers to get extensive assistance and recommendation for any issues with their farm. These data belonged to the farmers, thus it was at their discretion to choose the people who share in the data.
The shift in agriculture was long overdue if it was not embraced fully and effectively. This is because it had not only affected production in the field, but also the management of the farm in general. Every operation undertaken in a smart tech-farm had an impact on the general decision made in regard to the data (Howard, 2015). The smart farm was an integration of activities which are interdependent and have share information and control. However, proper use of technology was to be observed to ensure that the natural state of the farm is maintained and conserved. This is because destroying soil biology and soil compaction and erosion will never be the effective and efficient use of technology.
References
Agricultural Technology Centre Augustenberg (LTZ). (n.d). Retrieved from https://fisaonline.de/en/find-institutions/funding-institutions/?tx_fisaresearch_fundinginstitutions%5Bi_id%5D=502&tx_fisaresearch_fundinginstitutions%5Baction%5D=institutionDetails&tx_fisaresearch_fundinginstitutions%5Bcontroller%5D=Institutions&cHash=3a858f93cd7ce1e0b6445e1a36ca4f05
Bitkom, Germany’s digital association. (n.d). Retrieved from https://www.bitkom.org/EN/index-EN.html
Buyya, R., Yeo, C., Venugopal, S., Broberg, J., & Brandic, I. (2009). Cloud computing and emerging IT platforms: Vision, hype, and reality for delivering computing as the 5th utility. Future Generation Computer Systems, 25(6), 599-616. doi: 10.1016/j.future.2008.12.001
Campbell, B., Thornton, P., Zougmoré, R., van Asten, P., & Lipper, L. (2014). Sustainable intensification: What is its role in climate smart agriculture?. Current Opinion In Environmental Sustainability, 8, 39-43. doi: 10.1016/j.cosust.2014.07.002
Fukatsu, T., & Nanseki, T. (2009). Monitoring System for Farming Operations with Wearable Devices Utilized Sensor Networks. Sensors, 9(8), 6171-6184. doi: 10.3390/s90806171
Greenstein, S. (2010). Digitization and Value Creation. IEEE Micro, 30(4), 4-5. doi: 10.1109/mm.2010.64
Horizon 2020 – European Commission. (n.d). Retrieved from https://ec.europa.eu/programmes/horizon2020/
Howard, M. (2015). Digital Ubiquity: How Connections, Sensors, and Data Are Revolutionizing Business. CFA Digest, 45(2). doi: 10.2469/dig.v45.n2.8
Jhuria, M., Kumar, A., & Borse, R. (2013). Image processing for smart farming: Detection of disease and fruit grading. 2013 IEEE Second International Conference On Image Information Processing (ICIIP-2013). doi: 10.1109/iciip.2013.6707647
Kaloxylos, A., Groumas, A., Sarris, V., Katsikas, L., Magdalinos, P., & Antoniou, E. et al. (2014). A cloud-based Farm Management System: Architecture and implementation. Computers And Electronics In Agriculture, 100, 168-179. doi: 10.1016/j.compag.2013.11.014
Kalusopa, T. (2005). The challenges of utilizing information communication technologies (ICTs) for the small?scale farmers in Zambia. Library Hi Tech, 23(3), 414-424. doi: 10.1108/07378830510621810
Karmarkar, U., & Apte, U. (2007). Operations management in the information economy: Information products, processes, and chains. Journal Of Operations Management, 25(2), 438-453. doi: 10.1016/j.jom.2006.11.001
Klerkx, L., Aarts, N., & Leeuwis, C. (2010). Adaptive management in agricultural innovation systems: The interactions between innovation networks and their environment. Agricultural Systems, 103(6), 390-400. doi: 10.1016/j.agsy.2010.03.012
Le Gal, P., Merot, A., Moulin, C., Navarrete, M., & Wery, J. (2010). A modelling framework to support farmers in designing agricultural production systems. Environmental Modelling & Software, 25(2), 258-268. doi: 10.1016/j.envsoft.2008.12.013
McBratney, A., Whelan, B., Ancev, T., & Bouma, J. (2005). Future Directions of Precision Agriculture. Precision Agriculture, 6(1), 7-23. doi: 10.1007/s11119-005-0681-8
Tripicchio, P., Satler, M., Dabisias, G., Ruffaldi, E., & Avizzano, C. (2015). Towards Smart Farming and Sustainable Agriculture with Drones. 2015 International Conference On Intelligent Environments. doi: 10.1109/ie.2015.29
Wolfert, S., Ge, L., Verdouw, C., & Bogaardt, M. (2017). Big Data in Smart Farming – A review. Agricultural Systems, 153, 69-80. doi: 10.1016/j.agsy.2017.01.023
Walter, A., Finger, R., Huber, R., & Buchmann, N. (2017). Opinion: Smart farming is key to developing sustainable agriculture. Proceedings Of The National Academy Of Sciences, 114(24), 6148-6150. doi: 10.1073/pnas.1707462114

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