SWOT analysis is probably one of the most common methods of evaluating the performance of a business. If you are struggling to assess the competitiveness of your business, you can always use this method to identify any opportunities or challenges that are affecting your operations. This article will inform you what SWOT Analysis is, and how you can carry out one for your entity.

What is a SWOT Analysis?

SWOT analysis refers to Strength, Weakness, Opportunities, and Threats analysis. Therefore, SWOT analysis refers to a tactic used by organizations to assess the internal and external threats and opportunities. This simple method of assessing an enterprise can help managers identify any advantages or disadvantages in their internal and external business environment that are vital for enabling them to realize their strategic plans. With the information provided by a SWOT Analysis, you can identify the strengths and weaknesses that competitors have over you. Interestingly, you can use this information to create new strategies that can allow your firm to distinguish itself from competitors.

How to Do a SWOT Analysis?

The easiest method of undertaking a SWOT Analysis is by using a SWOT Analysis matrix. This matrix has 4 templates where you fill in your company’s or competitors- strengths, weaknesses, opportunities, threats.

A SWOT Analysis Matrix

SWOT ANALYSIS MATRIX
SWOT Analysis Matrix

The easiest way to develop a SWOT analysis at work is by brainstorming with colleagues from various departments. Using the brainstorming technique, you can get various views regarding the operations of the company and its competitiveness in the market. Also, you will have an opportunity of learning its weaknesses and things that threaten its existence when looked at from the perspectives of stakeholders in various departments. Properly classify each of the identified ideas as either strengths, weaknesses, opportunities, or threats in the SWOT analysis matrix.

For proper classification, it is essential to consider think of strengths and weaknesses as internal factors that relate to an organization’s assets, people, and processes. Meanwhile, opportunities and threats are external factors that are influenced by the market, competition, and changes in the wider economy.

Strengths

This attribute refers to the specific things that your entity does exceptionally well when compared to other players in the market. When identifying your strength, you should think of the advantages that your entity has over your competitors. Some of the strengths can be patency rights or the presence of skillful employees. The primary criteria for including a “strength” is by assessing the clear advantages that the attribute gives your business in your market.

Weaknesses

Each organization has its weaknesses, which limit its attainment of various strategic goals. Therefore, it is important to be honest with yourself when identifying your enterprises’ weaknesses as they will help you know specific areas in your firm that you should improve. Weaknesses are internal organizational features and they center around the human resources, systems, procedures, innovation, leadership, among others.

Opportunities

Opportunities are influenced by the external environment, and they simply inform a firm on the chances of something positive happening in its daily operations. Opportunities normally arise from changes in a business’ working environment. You should be critical and open to new concepts and ideas when identifying opportunities because they are always dynamic, changing with developments in the industry, or the emergence of new technologies.

Threats

This attribute refers to external factors that can adversely affect your organization’s business. Any business needs to anticipate threats so that it can establish appropriate measures of countering them or stopping their occurrence. Some threats may be impossible to counter, such as a change in technology. In such events, the business should be aware of oncoming threats to establish important strategies, including evolving the entire business to allow it to adapt to the new realities in the market.

How to Use a SWOT Analysis

A SWOT analysis can act as an important mirror to the business, which can show its current position and the available challenges and opportunities in the market. Therefore, it can inform the management on the appropriate strategies to undertake given the changes in the firm’s business environment. The following are the steps an individual should undertake from the information in the SWOT analysis:

SWOT Analysis Matrix

Making Effective Use of Your SWOT Analysis

Total Time: 4 days, 10 hours and 15 minutes

Conduct a SWOT Analysis

First, conduct a thorough SWOT analysis of your business by brainstorming with colleagues and experts.

Deal with internal attributes.

Having identified the strengths, weaknesses, opportunities, and threats in the firm, focus on first dealing with internal attributes of the firm (Strengths and weaknesses). Since a business has direct control over its internal operations, it is much easier to make significant changes in this area.

Focus on low hanging fruits. (Prioritize simple internal issues)

The easiest and quickest method of making positive changes to an organization is by dealing with easy tasks. You should try making changes to simple routine issues that have a positive or negative effect on the business. For example, the SWOT analysis can reveal that employees in a firm are always late to report to work. Fixing a clock-in system in the company can easily lead to timely reporting to work, and this can enhance productivity.

Deal with complex internal issues

Deal with complex internal issues (strengths and weaknesses). Some internal issues may require the participation of various stakeholders. Dealing with issues such as poor recruitment strategies leading to the presence of incompetent and unproductive workers can need a serious discussion with the management.

Deal with External Issues

Dealing with external issues (opportunities and threats). Almost all external issues are complex because they may require a firm to make lasting paradigm changes to its operations. These issues should be dealt with last because they are usually complex and require a lot of time to implement. However, if some of these issues can have a quick impact on the business, such as missed opportunities or undermining a company’s operations, it is vital to tackle them quickly. You may almost certainly need to involve the management when tackling these problems.

Estimated Cost: 100 USD

Supply:

  • Detailed review of your SWOT analysis

Tools:

  • SWOT Analysis Matrix

Materials: SWOT analysis matrix

A Detailed Research with an Example of a SWOT Analysis

Strategic Management of Business Analytics

Section 1: Emerging Data Technology

Introduction

Business analytics is crucial for success in the current market. The strategic management of business analytics gives firms a competitive advantage over other players in various industries. Different data technologies are available for use by players in multiple industries, including blockchain, Internet of Things, RFID, and Cloud Computing. There are also emerging technologies that organizations can use to enhance efficiency and revenue, such as drones, robotics, smart buildings, and automated vehicles. Firms can leverage business analytics and emerging physical technology to attain a competitive advantage in the market. This paper will evaluate the adoption of business analytics in the retail sector, the use of the Internet of Things and the use of drones in various industries.

Background of the Retail Sector

The retail sector is progressively undergoing changes that players have to adapt to remain relevant. Retailing typically revolves around purchasing services or products from merchandisers, manufacturers, importers, agents, or any other retailer and selling them to end-users for personal utilities. Retailers charge the products or services in a manner that covers their expenses along with generating profit for them. The retail sector consists of specialty and general stores, departmental stores, and also discount stores.

The retail sector is converging online and offline channels to enhance the experience of the end-user. The adoption of omnichannel is the current trend in the retail industry, with consumers having the option of purchasing in-store or placing orders online and having services and products delivered to their homes (Krishnamoorthi & Mathew, S.K., 2018, p. 657). Instant payment methods are making it possible for consumers to buy what they need online, for instance, the use of mobile payment and credit cards. As a result, the retail sector is gradually incorporating technologies to supplement the brick-and-mortar stores. The paradigm shift is shaping the face of retail, requiring players in the industry to respond to the change or risk going out of business.

The global retail sector is booming, contributing significantly to the economy. Physical boundaries no longer bind retailers as they can reach the customers. Numerous brands in the different industries distribute their products and services globally, where players from the food, agriculture, and apparel industries participate in global retailing (Jeble et al. 2018, p. 521). An example of a worldwide business in the food industry is Starbucks; an agricultural organization is Bayer and in the clothing industry, there is Zara. However, there are various businesses concerning themselves with selling a variety of products and services to consumers, for example, Walmart, Amazon, and Alibaba, all of which have a global presence.

The retail sector has a long history, dating back to the 18th century in the United States, for instance. The first stores were typically family-owned establishments. The industry has encountered significant changes, with the sector currently being characterized by grocery stores, convenience stores, department stores, e-tailers that sell products online, among others. The retail industry continues evolving as new technologies arise along with business analytics. The leading retailers utilize the business analytical tools to collect crucial information about the consumption of their products, enabling them to respond appropriately to demand and supply needs (Krishnamoorthi &Mathew 2018, p.657). Retailers fulfill customer needs conveniently, for instance, through using RFID to establish the products that are out of stock and supply them.

Lifestyle retailing is among the prevailing trends, particularly common in the stores selling household and apparel items. Retailers are also pursuing sustainability as consumers become more aware of the environment, with a substantial number of them having concerns about eco-friendliness and conservation. An example of a retailer currently pursuing a sustainability campaign is H&M, which is a Swedish multinational apparel-retail firm (‘Sustainability Reporting’ 2018). Many companies are ‘going green’ in a bid to retain consumers and attract new customers. Another trending phenomenon in the retail sector is self-checkout in stores, decreasing the need for human labor.

Literature Analysis

The retail sector is attracting the attention of many scholars. The impact of the retail industry is profound, especially on the economy. The industry employs millions of workers around the world; thus, it is a crucial source of employment. Also, the retail sector indicates the state of economic growth in a country. Numerous authors have written on issues associated with retailing, adoption of business analytics, and its impact on performance. This section will explore the literature on the retail sector and its related aspects of presenting a more in-depth insight into the issue.

Mining data in customer behavior is crucial in efficiently fulfilling demand and supply in the retail sector. In a study conducted by Griva, Bardaki, Pramatari, and Papakiriakopoulos (2018, p. 8) on retail business analytics, it was found that market basket data is crucial in establishing customer visit segmentation. Consumers’ buying patterns can be determined through the use of business analytics, i.e., customer basket data (Brinch 2018, p. 1599). Establishing customer segments is essential in making business decisions such as marketing, product recommendations, and the store’s layout (Brinch 2018, p.1599). Business analytics consists of potent tools that retailers can utilize to acquire a competitive advantage over other players in the sector.

Business analytics contribute to the performance of a company. When organizations adopt technology in business operations to collect and analyze market data, they relatively sound decisions that contribute to their performance levels (Fosso Wamba, Ngai, Riggins & Akter 2017).  The implementation of business analytics relates to performance, such as environmental sustainability. The level of business analytics adoption, trust, and information technology integration moderate the link between performance and business analytics (Ramanathan, Philpott, Duan & Cao 2017, p. 991). Large corporations can collect, manage, and process as well as analyze consumer data to generate actionable insights into value delivery and performance measurement (Fosso Wamba, Ngai, Riggins & Akter 2017).

Business is becoming more data-driven currently than during any other time in history. The universal value of data is recognizable, contributing to the extensive use of data in the retail sector. The implementation of data-driven organizational models is attracting comprehensive study and application (Vassakis, Petrakis & Kopanakis 2018, p. 9). Businesses use data to remain competitive in the current market as a matter of necessity, strengthening the old saying that ‘knowledge is power.’ The extraction, refining, and capitalization of data determine a firm’s competitiveness, market retention and ultimately the survival of a business (Jeble et al. 2018, p. 521). The output and productivity of firms utilizing data-driven business models are comparatively higher, indicating the significance of business analytics. The use of big data in business enhances a brand, shortens the supply chain, facilitates expansion, enables consolidation, and increased processing speed (Brownlow, Zaki, Neely & Urmetzer 2015, p.4). Business analytics additionally promotes differentiation.

For big data to be an asset for retailers, there is a need to incorporate derived data mining and data analytics. Businesses can utilize data analytics applications available for commercial use. There are numerous advantages of adopting data analytics (Vassakis, Petrakis & Kopanakis 2018, p. 11). Data mining is particularly crucial in business analytics in the retail sector as it presents relevant pieces of information. The practice of mining data enables firms to collect information that they can use in enhancing customer experience and relationships, reduce operating costs, increase revenues, decrease risks among other functions (Brownlow, Zaki, Neely& Urmetzer, 2015, p.8). The different data mining techniques are clustering, classification, regression, and association rule discovery. Data mining is crucial in developing marketing strategies.

Business analytics, however, presents challenges to both the consumers and corporations (Vassakis, Petrakis & Kopanakis 2018, p. 20). Retailers encounter numerous hurdles as they attempt to implement business analytics, such as data integrity and inadequate technical skills in the workforce, data maintenance, and security, along with acceptance by the workforce. The inability to solve complex issues is another problem relating to business analytics (Vassakis, Petrakis & Kopanakis 2018, p. 11). Consumers have concerns regarding data privacy during the era of big data analytics. Big data is vulnerable to security breaches from cybercriminals and other third parties. Big data analytics exposes consumers to addictive shopping by providing numerous options for the customers, who may end up purchasing items they do not need entirely (Le & Liaw 2017, p. 798). The dimensions of shopping addiction are post-purchase feeling and the buying tendency

SWOT Analysis

The application of business analytics requires critical evaluation. Similar to any other process in a corporation, data analytics presents opportunities and threats; thus, it can be a strength or a weakness. SWOT analysis provides a framework through which firms can evaluate both internal and external aspects, which contribute to shaping the future of the business, such as data analytics. Big data and data analytics are phenomena that are prevalent in retail operations currently. Business analytics do not create new data but rather enables retailers to use the available information through analysis, evaluation, and presentation of the knowledge. This sub-section of the papers explores the opportunities, threats, strengths, and weaknesses associated with business analytics applications within the retail sector.

Strengths

The retail sector is developing in new ways, and the players require executing the necessary changes to keep ahead in a competitive market. The global retail sector landscape can benefit from business analytics through the internal strengths of the firms in the industry. The retail sector in the countries mentioned uses advanced tools in mining consumer data and analyzes it to acquire understanding into the needs of the consumers. Among the strengths found in the retail sector relating to the utilization, business analytics is the existence of database systems, technological advancement, and the presence of automated retail systems.

The availability of automated systems in the retail sector is a strength that can facilitate the successful adoption of business analytics. China, for instance, has a robust retail industry characterized by automation (Li, Wang & Zhao 2018, p. 89). There are numerous digital points of sale where consumers can pay for products through mobile payment or even facial recognition. Online retail enables firms to collect large amounts of data through the facilitation of already existing automated retail systems. Another strength is advancement in technology. Innovativeness is leading to the creation of new technologies that can enhance the retail sector, such as the use of RFID and drones. The nature of new technologies enables retailers to leverage big in making crucial business decisions and drawing of the various business strategies.

Database systems’ existence is an additional strength relating to business analytics in the retails sector. Generally, retailers keep a record of consumer information in individual databases, which are viable for the use of business analytics.  Besides, the existence of business websites and social media provides a rich source of big data that retailers can mine to assist them in developing strategic plans. All the established global retailers have a presence in various social media platforms such as Instagram, Weibo, and Facebook, which they use to engage their customers. Conversations with clients and potential customers provide a rich source of data for retailers.

Weaknesses

Firms encounter setbacks in a bid to execute data analytics. The weakness associated with the implementation of business analytics includes insufficient funding for creating the requisite infrastructure. There are physical resources such as communication devices, and intangible assets such as interconnectedness to the internet. Another weakness is the adequacy in employees’ skill sets, thus obstructing the process of data analytics implementation. Additional limitations include weak technical infrastructure, inadequate specialized training, and the fact that not all retailers are open to implementing business analytics.

Opportunities

High quality and advanced data analysis are prospects that business analytics present to firms. Various opportunities are presented through the implementation of data analytics in the retail industry. When firms adopt business analytics, they acquire additional prospects. Data analytics provide a potent means of competitive advantage for retailers in the global market. The opportunities attain as a result of utilizing business analytics include high-quality data analysis, efficient situational analysis, and the acquisition of actionable business insight as well as enhancing the decision-making processes. Firms can leverage opportunities to become competitive and thrive in the global scene.

Decision-related opportunities are identifiable through positive visualization. Data analysis simplifies seeming complex datasets, enabling retailers to fulfill demand and supply efficiently through strategic management. Analyzing data highlights possible consumer trends that retailers can exploit to their advantage. Other prospects include predictive analytics for actionable insights and better decision-making processes, along with current situational analysis through prescriptive analytics.

Threats

The risks that business analytics can present to retailers include high equipment costs, consumers’ reservation in exchange information, and the fear of data exploitation along with targeting.

Section 2: Emerging Technologies

An example of our Research Papers:

Part A: Internet of Things and Business Competitiveness

Data Technology Choice Rationale

Among the data technologies firms utilize for business analytics is the Internet of Things (IoT). IoT refers to a system of interconnected computing devices, machines, tools, and objects (animals or people), each with its own unique identifiers (UIDs), and with the ability to communicate over a network without the need for human-to-human or human-to-computer intervention (Rouse, 2019). Firms can use IoT to augment their operations as they collect crucial information regarding consumer needs and wants. IoT also enables production systems to become more responsive as a result of real-time data collection and data analysis. Therefore, IoT has numerous benefits that grant businesses a competitive advantage in the market (Lee & Lee 2015, p. 437). Among the benefits of data technology is quality control, predictive maintenance, supply chain, and inventory management, along with workforce safety.

The purpose of focusing on IoT is to gain a more in-depth on how machines can independently interact with each other or humans to make businesses efficient. The concept of IoT is receiving significant attention from different quarters due to its immense impact on business and personal life of individuals. On the contrary, other systems require some of extent of human intervention.  Internet of Things is profoundly changing how companies in various sectors operate; hence it is crucial to acquire a better understanding of it. As a consequence, IoT is taking over many aspects of corporate functions, and more knowledge about the subject enables a person to understand business analytics better.

Another purpose of studying is exploring how the Internet of Things contributes to business analytics. IoT has is a more recent technology that can incorporate other technologies such as RFID, cloud computing, and blockchain in its operations, such as real time data analysis. Therefore, the focus on IoT will provide a robust view on the effects of technology in businesses. Numerous processes interact for organizations to function that includes production, development and research, marketing and purchasing. Incorporating IoT within the operations enhances efficiency, productivity and ultimately profits.

Corporations can monitor products and establish consumption patterns through IoT. IoT’s ability to integrate the whole operating process of an organization, from production, supply, sale, customer review, enables it to provide a detailed view of consumer behavior. Other systems such as cloud computing or RFID do not have this ability. Due to ease in information collection, businesses can determine the exact of supplies, for instance, and take the necessary actions (Dijkman et al. 2015, p. 678). Monitoring has benefits to the firms; for example, retailers can determine the expiry date of products in a store and replenish with new supplies when the need arises. Moreover, machine communication through establishes process transparency, along with enabling a fast response to emergencies (Li, Da Xu & Zhao 2015, p. 249).

Literature Review

There are numerous studies available on the Internet of Things subject. Different scholars have explored the issue as it has received immense attention in the recent past. Within the last decade, the number of connected devices exceeded people (Borgia 2014, p. 15). Among the aspects explored by scholars relating to IoT includes pervasive and ubiquitous computing and computer communications in the establishment of smart buildings, manufacturing servitization possibility and IoT applications (Wortmann & Flüchter 2015, p. 222). Servitization enables firms to extend their value chains, serving consumers in an enhanced manner, consequently driving profitability. Businesses in various industries are keen on adopting IoT in their operations to benefit from the emerging technology.

The Internet of Things incorporates various aspects. Madakam, Ramaswamy, and Tripathi (2015, p.164) provide an overview of IoT by delivering geneses, definitions, aliases, essential characteristics, and basic requirements. Internet of things refers to the interconnected devices possessing unique identifiers and are capable of communicating through a network without the necessity of human interactions. The basic requirements for IoT to function appropriately include data and device security, executing and running security operations and meeting compliance needs along with requests. The essential characteristics of IoT constitute heterogeneity, intelligence, connectivity, dynamism, security, communication and enormous scale.

Internet of Things technology is applicable in various fields such as retail, healthcare, and agriculture. By interconnecting devices, organizations and individuals can communicate efficiently, without the necessity of human interaction (Vassakis, Petrakis & Kopanakis 2018, p. 18). In healthcare, for instance, mobile applications and wearable devices facilitate health education, fitness, care coordination, collaborative disease management, and symptom tracking. Telehealth and telemedicine utilize health IoT digital tools along with mobile apps to enhance service provision (Caputo, Marzi & Pellegrini 2016, p. 398). The big data analysis continues to directive digital disrupts in healthcare and businesses. Also, smart firms use IoT technology to optimize productivity and agricultural competitiveness.

Business processes management and IoT incorporate different technologies. IoT technical contribution indicates the technology evolution that constitutes the learning process and application procedures (Wang et al. 2019, p. 5). Standardization initiatives support both the learning and application processes. Configuration, standardization, stoutness, convenient installation, and servicing are all crucial elements in keeping IoT operational; thus, presenting value to corporate process management across industries. Value creation from IoT to technological regenerations is vital and is bound to affect how firms conduct business across various sectors on a relatively large scale (Le & Liaw 2017, p. 45). Through investigating the role and impact of IoT with business process management, companies can establish knowledge flow promotion, competitiveness, and innovativeness. Corporations can foster innovation within an organization through IoT, ensuring that firms acquire competitiveness.

IoT is progressively changing as it establishes itself as everyday objects become ‘intelligent’ with the ability to share information with other objects and people. There is a profound business decision-making procedure. Internet of Things is a phenomenon bent to affect marketing perspectives. Further, IoT reverberates across other application fields and the effect of the same on firms. Li, Da Xu & Zhao (2015, p. 257) presents a survey exploring the fundamental technologies, definitions, architecture, and IoT applications. IoT implementation incorporates emerging technologies. Internet of Things is technology gradually taking a central position in all industries generally.

Data Technology Adoption Case Study

Coca-Cola is a global beverage company with its headquarters in Atlanta, Georgia, in the United States of America. The corporation is a pioneer in the adoption of IoT technology in distributing its products (‘Why retail giant Coca-Cola’ 2016). Coca-Cola uses IoT connected vending machines in its distribution chains across many locations. The smart vending machines incorporate a cashless payment system, and the devices notify the managers when stocks decline, as well as the provision of personalized communication and consumer rewards. IoT presents various advantages to the firm, including less operational costs as the machines do not require human presence for them to operate. Customers service is also excellent as there is no shortage of supply of products.

The corporation has made substantial initiatives in implementing IoT, having connected approximately a third of its vending machines to the internet to facilitate data collection and analysis (Drinkwater 2015). The firm can determine the devices that are the busiest, as well as the most selling drink varieties. Coca-Cola uses a smart connected fleet to facilitate the digital vending and use of a seamless method of payment. By ensuring that the machines are replenished conveniently, the firm enhances customer service. Managers are in a better position to manage inventory through the use of the vending machines, facilitating better decision-making capability.

The corporation utilizes IoT to modify consumer engagement strategies, to enable the provision of self-service with a click, and to gain a more in-depth insight into consumer purchasing behavior (Vyas, Jain, Choudhary & Chaudhary 2019, p. 738). Establishing customer loyalty becomes convenient, as well as tracing consumption perks to enhance target marketing. The data that vending machines collect is used for determining profitability, inventory levels, and the most popular products. There is an instance where Coca-Cola created a new flavor after vending machine data, establishing that consumers were frequently mixing Vanilla Coke and Cherry. The beverage company has numerous partnerships with players such as Saleforce, SAP and AirWatch, realizing the business-critical capabilities. The partners assist in gaining a more in-depth insight into dispenser profiles.

My Coke Reward platform is an initiative seeking to establish customer loyalty. The platform communicates with consumers through push messages, for instance, reminding one to pick a bottle of water before heading out to work or get a sports beverage before going to the gym and a protein shake afterward (Drinkwater 2015). Functionality ensures continuous customer engagement. The beverage is working towards incorporating student ID cards as a means of purchasing drinks. Besides, the corporation is implementing coolers that are IoT-enabled across the US. The coolers assist with stock optimization, preemptive equipment maintenance and personalized customer communication. IoT helps the firm meet multiple targets within its operational and sales strategies.

Part B: Emerging Physical Technologies

Businesses are incorporating emerging physical technologies to facilitate data analytics, for instance, the use of drones. Governments regulate the use of drones, and the technology is gaining prominence in today’s industries. Drones can be used in a variety of sectors to enhance efficiency and saving costs. In the agriculture industry, for instance, drones can be used to survey crops conveniently. Crewless aerial vehicles are fitted with sensors enabling farmers to collect crucial and useful data, such as information about pest infestation, soil composition variation, and soil hydration (Huuskonen & Oksanen 2018, p. 35).  Crop surveillance by drones is done within the specified intervals, enabling optimal pest control, fertilization and irrigation. Consequently, operational costs reduce significantly while the business attains a competitive advantage.

The health sector can use drones to optimize care in the future. Containing outbreaks can become easy through timely delivery of supplies, medications, and vaccines. Drones can deliver portable shelter, mobile technology and communication equipment.  In medical care, drones can facilitate home hospitals, remote telemedicine, and marine telemedicine (Wulfovich, Rivas & Matabuena 2018, pp. 159-168).  Within search and rescue missions, drones can become handy in locating survivors, disaster and AED delivery. Further medical use of the crewless aerial vehicle is the transport and delivery of lab samples, medical supplies, medications, blood products, and vaccines. Drone technology can transform the healthcare sector, though there are obstacles such as strict regulations.

Drones are revolutionizing the retail sector. The use of emerging physical technology can be beneficial to both the business and the consumers. Drones have various applications in the retail industry that include stock and inventory such as warehouse management (Ramaswamy & Ozcan 2019, p.19). Additionally, drones are useful in real estate planning, for instance, while finding a location to build a new warehouse.  Photography marketing is another application of drones in retail. Retailers can use drones in-store to capture data about their products without interfering with consumers’ activities. Studying consumer behavior and movement inside retail stores is possible through the deployment of drones. The data the drones collect can be used in planning and stocking products.

The use of drones is revolutionizing the media industry. Journalists can use drones to cover new in dangerous areas while photographers can capture photos while it could be otherwise impossible to take. Filmmakers are using drones to capture dramatic actions that seize the attention of the viewers (Jurriëns 2019, p. 456. Drones help create an enhanced mental picture of the land’s surface up to the ground level without air disturbance and shadows. The use of drones is transforming photography and videography arts by enhancing mundane scenes into something spectacular.

The construction and architecture industry is utilizing drones in new ways. Architects and constructors can use drones to track project progress, monitor resources and survey sites (Ashour et al. 2016, p.3). The photographs the drones capture are capable of generating full-color digital models through photogrammetry. Scanning large construction sites is more comfortable, faster and cheaper through using drones than traditional surveying methods. Developing more powerful drones with the capability of carrying construction materials can transform the sector profoundly.

Conclusion

Business analytics is a study area eliciting attention from various quarters. Organizations in multiple sectors, such as retail, healthcare, healthcare, and agriculture, are utilizing data analytics to collect and analyze crucial data. Technologies in data analytics include RFID and the Internet of Things. An example of a corporation that is using IoT is Coca-Cola that uses IoT in its smart vending machines. There are also emerging physical technologies that include drones, which can be used in different industries. Physical technologies facilitate the collection of data and delivery of products to consumers in the retail sector. Overall, businesses use data technologies and physical technologies collectively to attain a competitive advantage in the market.

References

Ashour, R., Taha, T., Mohamed, F., Hableel, E., Kheil, Y.A., Elsalamouny, M., Kadadha, M., Rangan, K., Dias, J., Seneviratne, L. and Cai, G., 2016, October. Site inspection drone: A solution for inspecting and regulating construction sites. In 2016 IEEE 59th International Midwest Symposium on Circuits and Systems (MWSCAS) (pp. 1-4). IEEE.

Borgia, E., 2014. The Internet of Things vision: Key features, applications, and open issues. Computer Communications, 54, pp.1-31.

Brinch, M., 2018. Understanding the value of big data in supply chain management and its business processes: Towards a conceptual framework. International Journal of Operations & Production Management, 38(7), pp.1589-1614.

Brownlow, J., Zaki, M., Neely, A., and Urmetzer, F., 2015. Data and analytics-data-driven business models: A blueprint for innovation. Cambridge Service Alliance, 14 (4), pp. 4-10.

Caputo, A., Marzi, G., and Pellegrini, M.M., 2016. The internet of things in manufacturing innovation processes: development and application of a conceptual framework. Business Process Management Journal, 22(2), pp.383-402.

Dijkman, R.M., Sprenkels, B., Peeters, T., and Janssen, A., 2015. Business models for the Internet of Things. International Journal of Information Management, 35(6), pp.672-678.

Drinkwater, D., 2015. Coca-Cola drinks to the future of the Internet of Things. Retrieved from https://internetofbusiness.com/coca-cola-drinks-to-the-future-of-the-internet-of-things/

Fosso Wamba, S., Ngai, E.W., Riggins, F., and Akter, S., 2017. Guest editorial: transforming operations and production management using big data and business analytics: future research directions.

Griva, A., Bardaki, C., Pramatari, K., and Papakiriakopoulos, D., 2018. Retail business analytics: Customer visit segmentation using market basket data. Expert Systems with Applications, 100, pp.1-16.

Huuskonen, J., and Oksanen, T., 2018. Soil sampling with drones and augmented reality in precision agriculture. Computers and electronics in agriculture, 154, pp.25-35.

Rouse, M. 2019. Internet of Things, Available at https://internetofthingsagenda.techtarget.com/definition/Internet-of-Things-IoT.

Jeble, S., Dubey, R., Childe, S.J., Papadopoulos, T., Roubaud, D., and Prakash, A., 2018. Impact of big data and predictive analytics capability on supply chain sustainability. The International Journal of Logistics Management, 29(2), pp.513-538.

Jurriëns, E., 2019. The Countryside in Indonesian Contemporary Art and Media: From Distant Horizons to Traversing Drones. Bijdragen tot de taal-, land-en volkenkunde/Journal of the Humanities and Social Sciences of Southeast Asia, 175(4), pp.446-473.

Krishnamoorthi, S., and Mathew, S.K., 2018. Business analytics and business value: A comparative case study. Information & Management, 55(5), pp.643-666.

Le, T., and Liaw, S.Y., 2017. Effects of pros and cons of applying big data analytics to consumers’ responses in an E-commerce context. Sustainability, 9(5), p.798.

Lee, I., and Lee, K., 2015. The Internet of Things (IoT): Applications, investments, and challenges for enterprises. Business Horizons, 58(4), pp.431-440.

 Li, S., Da Xu, L., and Zhao, S., 2015. The internet of things: a survey. Information Systems Frontiers, 17(2), pp.243-259.

Li, X., Wang, Y. and Zhao, H., 2018. Research on the Synergy Development of China’s IOT Industry. The Journal of Grey System, 30(1), pp.81-96.

Madakam, S., Ramaswamy, R., and Tripathi, S., 2015. Internet of Things (IoT): A literature review. Journal of Computer and Communications, 3(05), p.164.

Ramanathan, R., Philpott, E., Duan, Y., and Cao, G., 2017. Adoption of business analytics and impact on performance: a qualitative study in retail. Production Planning & Control, 28(11-12), pp.985-998.

Ramaswamy, V. and Ozcan, K., 2019. Digitalized Interactive Platforms: Turning Goods and Services into Retail Co-Creation Experiences. NIM Marketing Intelligence Review, 11(1), pp.18-23.

Sustainability Reporting, 2018. Retrieved from https://sustainability.hm.com/

Vassakis, K., Petrakis, E., and Kopanakis, I., 2018. Big data analytics: applications, prospects and challenges. In Mobile Big Data (pp. 3-20). Springer, Cham.

Vyas, S., Jain, S.S., Choudhary, I. and Chaudhary, A., 2019, February. Study on Use of AI and Big Data for Commercial System. In 2019 Amity International Conference on Artificial Intelligence (AICAI) (pp. 737-739). IEEE.

Wang, S.C., Hsu, H.W., Dai, C.G., Ho, C.L., and Zhang, F.Y., 2019, October. Use Product Segmentation to Enhance the Competitiveness of Enterprises in the IoT. In 2019 IEEE 10th International Conference on Awareness Science and Technology (iCAST) (pp. 1-6). IEEE.

Why retail giant Coca-Cola is using IoT connected vending machines, 2016. Retrieved from https://internetofbusiness.com/supply-chain-iot-coca-cola/

Wortmann, F., and Flüchter, K., 2015. Internet of things. Business & Information Systems Engineering, 57(3), pp.221-224.

Wulfovich, S., Rivas, H., and Matabuena, P., 2018. Drones in Healthcare. In Digital Health (pp. 159-168). Springer, Cham.

YongYan, L., and LiFeng, G., 2012. Status Quo and Development Bottleneck of Internet of Things [J]. In Forum on Science and Technology in China (Vol. 4).