Usage of Big Data Analytics at McDonalds
Today, majority of the organizations are aiming for expansion. However, they need to focus more on their strengths so that they can overcome the internal weaknesses and focus on the new market opportunities present in a given environment. Researchers however have noticed that to capture such opportunities there is a need of better technological platforms that will assist the top-level management of these companies to capture the intended markets.
The recent advancement in the field of Big Data is helping organizations to gather more insights about their business practices and also about the performance of their products and services in a given operational environment. This report will thereby focus on the utilization of Big Data analytics system in the organization and will provide an overview regarding how they can be implemented in the case of McDonalds. McDonalds is one of the leading fast food companies operating in more than 100 nations of the world. Hence, to meet the different customer needs and also to improve the quality of their services they need to use such big data systems in a given market environment.
This report will thereby provide a descriptive analysis on it and will also provide recommendations to the management team of McDonalds on using Big Data and improving future performance.
Big Data is a combination of all the processes and different techniques through which the organization will be able to analyze their data-sets. It will thereby allow them to understand the current product trends, the different customer needs, and the changing demands in a given competitive market environment.
However, for the purpose of analyzing these huge data-sets, the organizations will need to have proper technological systems at the workplace that will provide them with the required analytical functioning in a given environment.
Through Big Data systems, the organization will not only be able to outperform the competition but also will be able to establish a direct dialogue with the customers, can perform risk analysis and also can revamp the current marketing strategies in a given operational environment (Mergel, 2016). Big Data plays a vital role in integrating the digital and physical shopping spheres and hence the organizations can accordingly suggest new ways of shopping from their respective outlets.
This report will focus on how Big Data Technologies can be implemented within a given organization. It will be considering the case of McDonalds so that a proper implementation plan and the benefits out of it can be discussed in this report. Also it will provide visualization examples that can be used by the technological team at McDonalds to identify the different trends and accordingly frame their business strategies in the organization.
McDonalds is one of the leading fast food companies that are operating as a fast food restaurant since 1940. It was started in California, US, and since then it is now operating in 37,241 locations in different parts of the world. The major products served by the company include hamburgers, French fries, milkshakes, soft drinks and other beverages, wraps, coffee, breakfast items, and even salads.
As per the financial reports of 2017, the total revenues of the company were around US $22.82 billion. There are nearly 235,000 employees working across multiple branches of the organization. The headquarters of the company are located in Chicago and it is considered to be the world's largest restaurant chain by revenues.
It is serving nearly 69 million customers on a daily basis across more than 100 countries in the world. The company is focusing on the different needs of the people and accordingly is customizing the products to suit to their tastes and preferences in a given environment. However, they need to utilize additional technological options for analyzing the data that will provide them with a better overview of the current food trends in the different food markets around the world.
Key Business Priority
Today, with the advent of different forms of technologies and platforms, it is found that the organizations are leveraging on such technological options in a given working environment. It is thereby recommended to first identify the needs of the organization and accordingly decide on the technologies that can be used in a given working environment (Mergel, 2016).
However, companies like McDonalds are looking out for technological options that can be provide them with better customer insights and other associated details. It will thereby help them prepare the products that will meet the different taste criteria of the customers. It is due to these reasons that technologies like Big Data are nowadays used by the organization (Wolfe, 2013).
The major applications of Big Data helps the organization in understanding the needs of the customers in a better way, helps in reducing the operational costs, detects major risks in a given operational environment, checks for frauds, and also makes all the business processes more efficient. The organization thus needs to structure the different business processes, focus on market opportunities, and subsequently gain competitive advantage in a given environment.
Information and Sources
Big Data is a term used to refer to large data sets; these data-sets are then used for traditional data-processing and the results are analyzed by the senior level management of the organization. The data will be capturing several attributes of given processes and hence it becomes easy for the organization to work on predictive analytics, user behavior analytics, and also focus on advanced analytics to increase the net sales of the organization (Wolfe, 2013).
As per the research reports, it is noticed that the major benefits delivered through Big Data include - better decision making, business transformation, implementing new business frameworks, training the employees on the modules of leadership and management to improve multi-tasking in the organization, focus more on innovation, lowering the operational costs, providing more security to the data-sets of the organization, and also assisting the top-level management in guiding them regarding the future expansion plans in a given environment (Pavolotsky, 2013).
There are also certain other benefits observed of Big Data that include - trend prediction, price formation, demand forecast, personalized approach, service improvement, and net sales increase in a given environment (Pavolotsky, 2013). Companies like McDonalds thereby will be able to determine the trends of their products in a given market scenario.
They will be able to meet the needs of the customers based on their tastes and other preferences. Second, they will be able to determine the pricing trends of the different customers and accordingly will set the prices of the different products (Pavolotsky, 2013). Further, they will be able to determine the demands of the different products on country-wide basis. It will allow them to improvise their supply chain function accordingly in a given working environment. They will also implement personalize approach with an objective to deliver customer-centric services in the organization (Pavolotsky, 2013).
By implementing Big Data systems in the organization, McDonalds will be able to improve their net sales. Further, Big Data systems are able to provide faster analysis of the different trends; they are generating reports that will provide a better overview of the current market conditions (Soranno & Schimel, 2014).
Even, the marketing team will be able to gather more insights into this system and accordingly design the new marketing campaigns for the organization. They will thereby be able to developer better relationships with the customers and subsequently overcome the market competition in a given working environment (Soranno & Schimel, 2014). Also, they will be able to steer the operational processes to achieve the desired objectives of expansion in a given environment.
Further, there are four major characteristics of Big Data that include - volume, variety, velocity, and veracity. Volume refers to the quantity of data stored in a given environment. Variety reflects to the nature and type of data captured (Soranno & Schimel, 2014). Velocity refers to the context and the speed at which data is generated in a given environment.
And, finally, veracity refers to the data quality of captured data in a given working environment. Big Data will thereby help the organizations through different perspectives such as - cost savings, time reductions, new product development, understanding of the market conditions, and also controlling online reputation. McDonalds in this case thereby first needs to capture the data related to customer trends and food trends and accordingly serve them with better quality products and services. It will thereby help them increase their net sales in a given challenging work environment.
Big data Technologies
McDonalds is a massive global food service retailer operating in nearly 34,000 local restaurants around the world. They are serving nearly 69 million people on a daily basis. It can be observed that they are selling 75 burgers every second. As per one of their research reports, it was found that Americans alone are consuming one billion pounds of beef at McDonalds on annual basis.
There are several other such data-sets generated and obtained in this organization. McDonalds is thereby trying to become an information-centric organization that will take decisions based on this data. However, they will need Big Data technologies that can help them serve through proper analytics and reports.
Before identifying the major technologies in the Big Data, it is important to understand the following Gartner Hype Cycle that will provide an overview on how the technologies get matured, adopted, and are used for different business applications in a given environment.
It provides an idea regarding the innovation brought by these technologies in a given business scenario (Cukier & Mayer-Schoenberger, 2013). Based on this the follow diagram shows the major technologies that have developed in the Big Data segment.
The major technologies that can be used by the firms include - repetitive analytics, NoSQL databases, Search and knowledge discovery, stream analytics, in-memory data fabric, and data virtualization. There are several more technologies that have developed for the purpose of providing desired speed of processing, providing ease of use to the end users, and also ensuring sophisticated analytics in a given environment (Soranno & Schimel, 2014).
Apache Spark is one of such technologies that can be used by companies like McDonalds for the purpose enabling applications in Hadoop clusters, allowing quickly writing of applications in different technologies, and also supporting SQL queries to fetch the data from the database 100X faster from the memory (Landon-Murray, 2016). It will thereby make sure to McDonalds that they will be grow their customer base, optimize their operations, maximize their insights with related to customer's data, and subsequently develop new business models to adhere to the needs of the customers.
Big Data Approach
The purpose of implementing big data systems in the organization is not only to understand the customer trends but also to implement new services, improve decision making for the top-level management, optimize the current business practices, and thereby achieve desired level of working efficiency across the organization.
The approach to implement Big Data within the organization will begin after analyzing the current needs of the organization. The IT department along with the Operations department needs to determine the commercial objectives of the organization. They can accordingly deploy the right IT capabilities associated with the Big Data systems in the organization. It will thereby allow them to link the business objectives with the IT capabilities of these systems.
It will thereby allow them to first gather the desired data set, extract the key information out of it and store them in the index database of the systems. Later, the analysts and the management team can analyze this data to gain the required business insight about a required process in the organization. It will thereby help the top-level management to re-frame the business strategies to achieve desired objectives in a given environment.
Big data visualization examples
Today, in a given challenging and constantly changing work environment, it is found that there is a need of technologies that will allow the business companies to revamp their strategies from busies perspectives (Landon-Murray, 2016). There is a need of more personalization and working on analytics that will allow the companies to understand the needs of the customers before they actually demand for in a given environment.
It is due to these reasons that Big Data applications are built with an objective to target customers in real-time and also offers them with desired services and products that will exceed their expectations (Landon-Murray, 2016). Further, it will also ensure customer loyalty toward the respective organization. It will also improve decision making for the organization, improve relationships with the customers, generate better financial performance, and also enable key strategic initiatives in a given operational environment (Hampton et al., 2013).
As per one of the recent research reports, it was noticed that majority of the CIOs (Chief Information Officers) are ranking analytics as #1 factor that contributed to the performance and competitive of the organization. In a survey conducted of 100 such CIOs, they mentioned that 64% of them are using Big Data analytics system for supply and demand purpose (Hampton et al., 2013). Also, 8 out of 10 CEOs of the organization are expecting that the complexity of such information will increase in the near future.
Hence, they need to embrace such analytics system that will assist them in outperforming them in a given competitive environment (Hampton et al., 2013). As discussed, there are also other options available but it will depend on the type of requirements of the organization and the type of data analytics that the top-level management of the organization is expecting from such outcomes.
Big data adoption challenges and Governance
First, there are three major challenges for big data that include - volume, velocity, and variety. From the volume perspective, big data technologies will require a large amount of storage space and hence organizations need to scale their hardware and software processing capabilities in the organization (Hampton et al., 2013). They need to accommodate such large systems in a given functional environment.
From the velocity perspective, new data needs to be created quickly and organizations will be required to respond to it in real time. There will be need of specific IT experts that can perform on such data-sets and provide quick results to the management team of the organization. From the variety perspective, the IT team needs to filter the data and obtain only those data-sets that will be useful to the organization (McGregor, Calderón, & Tonelli, 2013).
In another review, some of the researchers in this direction have determined the major challenges pertaining to big data integrating. They have not only identified big data talent gap but have also determined problems related to big data structure, syncing across data sources, uncertainty of data management, extraction problems, and other miscellaneous challenges (McGregor, Calderón, & Tonelli, 2013). Hence, there is a need to determine issues related to each of these in greater detail and accordingly prepare the risk mitigation plan in a given operational environment.
With recent increase in the Cybersecurity challenges, the IT team also needs to make sure of protecting these data-setts in a given environment. They need to implement data security tools through which they will be able to overcome the operational challenges and will also be able to secure the data-sets in the organization (McGregor, Calderón, & Tonelli, 2013). They can subsequently use them for different analytics purpose and extract the desired information for the top-level management. The top-level management can thereby use this information and take better decisions for the organization in the near future.
The IT team also needs to check on skill availability in the organization, the volume of data collected, the rate of transformation of data, and the validity of data after the implementation of Big Data system in the organization (McGregor, Calderón, & Tonelli, 2013). They accordingly need to train the staff so that they can deliver the work tasks as per the expectations of the organization. Companies like McDonalds will be looking for data-sets that can help them improve their current processes, overcome the business gaps, and also help them manage the other business routines in the organization (Bail, 2014).
They also need to determine the demands of the customers across different locations and subsequently provide them with food products that will meet the taste criteria of the customers. Only then McDonalds will be able to achieve their desired objectives in a given environment. The role of the HR team and the Operations team is equally important as they will be dealing with the different reports and data-sets of the Big Data systems in the organization (Bail, 2014). However, they need to monitor these practices and ensure security of the IT assets and architecture in a given challenging work environment (Cukier & Mayer-Schoenberger, 2013).
There are also other challenges such as data privacy, governance issues, compliance issues, and integration problems. Hence, the IT team in association with the top-level management of the organisation needs to deploy risk mitigation plan that will take care of each of these issues. They not only need to develop structured data but also ensure ethics and integrity in a given environment (Varian, 2014). From the governance perspective, they need not breach privacy and ethical integrity of any individuals or customers or any other entities in a given environment. Only then such systems should be installed in the organization.
There are several benefits observed and found after the implementation of Big Data analytics system in the organization. For a given case of McDonalds, the major benefits include - on-time delivery, operational efficiency, sentimental analysis, better quality, personalization, market-based analysis, and focusing more on customer services (Tinati et al., 2014).
McDonalds needs to develop a data-drive culture by leveraging this trend-analytics system to better understand the situation and needs of the customers. They can accordingly deploy best ways to improve their service quality and food products served to the customers (Tinati et al., 2014). It will subsequently optimize the experience for the customers and on the other hand will improve drive-thrust, ordering patterns, video data, point-of-sales data, and sensor data in a given environment.
However, the Human Resources (HR) department of McDonalds needs to train the employees on these modules so that they can perform as per the expectations of the organization (Tinati et al., 2014). McDonalds thus will be able to use Big Data to automate and optimize the different business process of the organization. It will thereby achieve desired objectives in a given challenging environment.
These report discuses about the usage of Big Data Analytics at McDonalds. Today, with increasing competition and changing customer trends, it has become mandatory for companies like McDonalds to deploy such systems in a given working environment. It will thereby provide them with better information about the people and the future expectations.
McDonalds also needs to determine the purchasing behavior, the average processing time, and the total quiet time. They can accordingly take decisions for future improvement. Second, they also need to train the employees as per the outcomes of these reports (Cukier & Mayer-Schoenberger, 2013). It will identify certain gaps that can be covered through proper training and work schedule management.
Today, McDonalds needs to focus more on their quality of products and services offered in a given environment. It will thereby make sure of delivering personalized touch to their products and providing customer-centric experience to all their customers across the world (Cukier & Mayer-Schoenberger, 2013). The top-level management however needs to monitor each of these strategies and accordingly suggest recommendations wherever required. It will thereby help them achieve desired objectives in a given working environment.