Information Systems in Global Business Today

Abstract

Facts and figures show that companies that embrace cutting-edge solutions have a greater chance at accelerated growth and better survivability. Today, the information technology industry offers diverse products and services for all levels of management – operational, tactical and strategic. Transaction processing systems (TPS), management information systems (MIS) and decision support systems (DSS) work together to implement major decisions made by the senior management and maximize profits. For all their advantages, many technologies solve pre-existing problems but create new ones. Thus, their implementation requires more research on a larger scale, while individually, companies may benefit from financial planning and staff training and continuing education.

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Introduction

The advent of technology is transforming the business world beyond recognisable. Indeed, the age of information has changed all aspects of the business from manufacturing and supply management to marketing and customer relationships. What the drastic rapid changes also contributed to is customers’ and business partners’ preferences and expectations of service and collaborations. If previously, a company’s savviness in tech would give it a competitive advantage, today, it is a bare minimum to withstand fierce market competition. The current report covers the role, advantages and challenges of information systems in global business today. The literature review presents the pyramid model of the organisational level of a typical enterprise: operational, tactical and strategic management. It goes into detail regarding the types of information systems used at each level and the implications of and barriers to their use. The analysis section draws on the existing evidence cited in the literature review and provides overarching, generalised insights on the subject matter. Lastly, this essay’s implementation part discusses the practical implementation and gives recommendations regarding adopting information systems for business.

Literature Review

Current Environment

Today, information systems play a variety of roles in business. Valacich and Schneider (2010) highlight three ways an information system can be employed in a corporate setting. First and foremost, when used correctly, an information system helps to improve metrics such as speed, cost, accuracy, precision and consistency at all managerial levels. Secondly, information systems are an indispensable part of any business that is committed to a continual improvement process, or an ongoing, incessant effort to better its products, services and processes (Valacich & Schneider, 2010). In other words, a system not only automates a specific task but also creates an opportunity at learning more information about the said task and refining its administration. A company can use historical or real-time data to make meaningful changes to its day-to-day activities. Lastly, information systems may be an essential component of a corporate strategy that would elevate an enterprise to a new level (Valacich & Schneider, 2010).

It should be noted that digital transformation, automatisation, online marketing and other concepts that have been gaining traction for the last two decades are not just buzzwords. In fact, their impact is well-researched and grounded in real-life data. A comprehensive report by Deloitte (2016) shows that companies that make big data, cloud technology, cybersecurity and mobility their priority see a 53% increase in their speed growth. Information systems help to manage human resources in the most effective ways possible. For instance, with the introduction of a mobile app, a small business can save hundreds upon hundreds of work hours, amounting to $725 million on the national scale (Deloitte, 2016). In addition, by switching to new ways of doing the same operations such as using VoIP (voice over the Internet protocol), companies can spare themselves 40 percent of local and 90 percent of international phone calls (Deloitte, 2016). All in all, information technologies are making businesses more competitive and effective, allowing them to pass milestones that would otherwise be outside their reach.

Unless a company uses exclusively proprietary software and hires in-house specialists, the chances are that it either outsources IT tasks or buys hardware and software. The global IT market easily catches up with the rising demand for new solutions. This year, the global technology industry is projected to reach the capitalization of a whopping $5.2 billion (CompTIA, 2019). The United States remains the undefeated leader with a 32% market share and Europe – the second-best contributor, taking up 20% of the market (CompTIA, 2019). With the estimated growth rate of 3.7%, the IT market keeps launching and marketing new products (CompTIA, 2019). Information systems constitute a highly homogenous field that offers solutions for each level of management – operational, tactical and strategic. However, such diversity of choice comes at a cost as companies are not always sure about what would be the best investment and make sense for their particular type of operations. For all the benefits that technology presents to businesses, it also poses difficult questions of maintenance and implementation.

Pyramid diagram of organisational levels of a typical enterprise
Image 1. Pyramid diagram of organisational levels of a typical enterprise (Laudon & Laudon, 2015).

Operational Management

Operational management entails the selection and administration of business practices with the purpose of achieving the highest level of performance within an enterprise. In other words, this type of management is concerned with input and output – converting raw material and human resources to ready-to-use products, goods and services. One of the main purposes of operational management is finding a balance between value creation for the customer and the company’s profit maximisation (Reid & Sanders, 2019). Operational management is important as it is responsible for the overall productivity of a business, which is why it needs technical support to better serve its goals. At the operational level of the organisation, transaction processing systems (TPS) are the most basic information systems. In essence, a TPS is a computerised system whose main functions are to log and monitor the daily routine transactions necessary to conduct business. For example, such a system can help a business keep track of sales orders, hotel bookings, payroll and shipping goods. Below is a table with the most common types of TPSs, their functions and their applications (see Table 1).

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Type of TPS systems Sales/ Marketing systems Manufacturing/ Production systems Finance/ Accounting systems Human resources systems Other types (e.g. educational systems)
Functions of the system Customer service;
Customer care;
Dealer and partner communication;
Pricing and price changes;
Promotion management;
Sales management.
Scheduling;
Purchasing;
Shipping;
Manufacturing operations.
General ledger;
Billing;
Accounting.
Staff records;
Benefits;
Remuneration;
Labor relations;
Training.
Applications;
Admissions;
Grade records;
Credits;
Course information;
Scheduling;
Alumni records.
Applications of the system Sales support system;
Sales order information system;
Sales commission system.
Machine control systems;
Purchase order systems;
Quality control systems.
Funds management systems;
Accounts receivable/ payable;
Payroll;
General ledger.
Employee records;
Benefit systems;
Employee skills inventory.
Registration system;
Student transcript system;
Curriculum class control system;
Alumni benefactor system.

Table 1. The most common types of TPSs, their functions and their applications (Laudon & Laudon, 2017).

It is important to note that transaction processing is a distinct type of processing. It is an information system whose main factions are data collection, storage, modification and retrieval. Users are only allowed to make predefined, clearly structured transactions while running arbitrary programs as time-sharing is not possible (Bog, 2015). The processing activity for each transaction is preprogrammed, which allows the system to respond to requests within a predictable time period (Bog, 2015). In this sense, transaction processing is often contrasted with batch processing that allows executing multiple requests at the same time. While TPSs typically require user involvement, batch processing systems do not. However, the result of each transaction is not immediately available as it takes time to organise, store and execute requests.

The use of transaction processing systems can make or break a business. Alternatively, it can make it the trailblazer of the industry and cause a disruption on the market. From this perspective, it is compelling to take a look at Amazon’s global strategy that has won millions of customers and left other e-commerce companies far behind back in the day. In 1999, Amazon secured a patent for One-Click technology that only expired three years ago. Before this patent, entering payment information into the system only once was unheard of (Knowledge @ Wharton, 2017). Implementing the new transaction technology was a breakthrough and spared millions of users the hassle of Internet shopping. One-Click appeared in time: a year later, Amazon expanded to create Amazon Marketplace and evolved from a reseller to a retailer, giving a platform to many third-party buyers and sellers (Knowledge @ Wharton, 2017). As a result, consumers felt comfortable enough shopping at the Marketplace due to the convenience of the new transaction method.

Tactical Management

In essence, tactical management is a medium between operational management and strategic management levels (Laudon & Laudon. 2017). The success of a company depends on its ability to translate higher-level strategic decisions into daily operations. However, bridging this gap is a challenging task, which is why tactical management is needed to integrate the two components. For example, a tactical manager may set minor, short-term goals for what each department needs to achieve by the end of the week, month, or year. This level of management might not have the leverage of the executive “layer,” but they do enjoy greater flexibility than operational management (Laudon & Laudon, 2017). When looking for ways to embody the shared vision, tactical managers can question practices and propose new solutions.

At the tactical managerial level, the information systems that best meet a business’s needs are management information systems, commonly abbreviated as MIS. MISs provide managers with reports and facilitates access to the enterprise’s ongoing performance metrics and historical data. It should be noted that MIS typically do not concern themselves with environmental events such as other businesses’ position on the market, the competitive landscape, external threats and opportunities. This is because the primary function of MIS is to analyze internal events to do the planning and controlling and inform decision-making at the tactical management level (Zhang et al., 2020). TPS and MIS are intrinsically connected: MIS compresses TPS data to present it in the form of reports produced on a regular basis.

Strategic Management

In the field of management, strategic management concerns itself with the formulation and implementation of major goals and objectives of an organisation. Strategic managers make forecasts and predictions to inform decisions that would impact a business in the long haul. For this type of management, it is critical to understand the competitive environment as well as the social, cultural and political context in which a business is operating. In addition, strategic management includes the evaluation of the internal organisation of an enterprise and ensuring that it is on track with regard to its goals.

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As one can readily imagine, when making major, non-routine decisions, senior managers have to take into account a whole lot of factors. Indeed, it is becoming a must to make sure that the corporate decision-making process is data-driven and, hence, does not overlook the most influential determinants and predictors. In this sense, decision support systems (DSSs) have been of great help to senior management as they use the input from both internal and external sources and can put together a complete picture. DSSs have come a long way from the inflexible, unintuitive software of the 1960s and 1970s that generated vast amounts of irrelevant information creating a “mirage” of decision support (Arnot & Pervan, 2015). Today, DSSs are interactive and insightful for the user all due to packing sophisticated mathematical models under the hood.

It should be noted that DSS is not a homogenous field with uniform solutions. There exist not only different approaches but different technologies to meet the needs of the senior management at the highest level of decision-making. Besides, as pointed out by Arnot and Pervan (2015), DSSs even vary based on what kind of managerial constituencies they serve. Interestingly enough, the appearance of personal decision support systems (PDSSs) was a logical continuation of the individualisation of the West in the 1960-1970s and the democratisation of the decision-making power. In contrast, in group support systems (GSS), it is multiple people that engage in “decision-making communication (Arnot & Pervan, 2015, p. 134).” Today, the group decision-making environment is made of a number of characteristics such as group, task, context and electronic meeting systems (EMS) (Arnot & Pervan, 2015). One of the branches of GSS that has since evolved into an independent field is negotiation support systems (NSS). NSS draws on game theory, that supports many modes of negotiation and social choice theory.

In recent years, intelligent decision-making systems have carved quite a niche in the world of business technology. Arnot and Pervan (2015) describe two generations of intelligent DSSs. The first was rule-based as a human still had to provide the machine with a set of rules for data processing and analysis. The second generation refined the method, resulting in unsupervised techniques such that use neural networks, genetic algorithms and fuzzy logic.

The world’s biggest corporations, such as Amazon, Netflix, Facebook and Apple, use artificial intelligence (AI) and machine learning (ML) to inform their strategic management decisions (Duan et al., 2019). For instance, the largest coffee company Starbucks has gathered vast amounts of data that it leverages to improve its operations. As of early 2020, the US-based coffee giant had more than 30,000 outlets in 70 countries on five continents (Marr, 2018). Further expansion is still in plans, and as Marr (2018) explains, Starbucks does not choose new locations blindly. In fact, it uses Atlas, a mapping and a business intelligence tool, that has the capacity to process terabytes of data. Atlas takes multiple dimensions, such as proximity to other Starbucks outlets, demographic variables and traffic patterns, to choose the most convenient and profitable spots to open new coffee shops.

Discussion and Analysis

The literature review made it obvious that the great diversity and customisation of information systems create an even greater responsibility for seamless integration. All managerial levels are interdependent, meaning that a technical accident at one level may launch a series of unfavorable events affecting a company on the whole. It is especially relevant for global businesses where the complexity of operations, the scope of leverage and the number of partners and customers mean a heavy burden of control and maintenance.

Maciel et al. (2017) claim that today, it is the issue of interoperability that prevents enterprises from exploiting the full potential of information systems. The scholars define interoperability as the ability of diverse applications and data procedures to communicate with each other, despite being responsible for different pieces of equipment and platforms (Maciel et al., 2017). Maciel et al. (2017) cover some of the rapidly evolving fields of research that seem to solve the problem of interoperability such as the Internet of Things (IoT) and cloud computing. However, there is a possibility that the new solutions will address some pre-existing challenges while simultaneously creating new ones. For instance, many businesses are not ready to replace their outdated hardware and software to embrace IoT technologies. In the case of cloud computing, Marciel et al. (2017) express concerns about security, autonomy, availability, scalability, and standardisation. Indeed, a transition to advanced information systems is not going to be smooth, especially for small and medium enterprises with limited resources.

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Another issue concerns the use of intelligent systems and harnessing their potential without creating new risks. Arnot and Pervan (2015) argue that there has been a fundamental tension between artificial intelligence and DSS since they seem to use conflicting approaches to meet the same ends. DSS has the aim of supporting humans in their decisions, empowering them with data and allowing for better precision. On the other hand, AI techniques have the potential of removing the human decision-maker out of the equation. Duan et al. (2019) explain that the said tension is far from being the only problem of AI application for business. There are problems stemming from big data themselves such as its volume, variability and heterogeneity. In contrast, sometimes data is too scarce to be suitable for machine learning algorithms (Duan et al., 2019). Lastly, AI may still replicate and amplify human bias as it is taught by imperfect humans.

When discussing the role of information systems in global business, it is also important to look at the challenges that businesses have to deal with individually. Firstly, information systems come with the purchase, installation and maintenance costs. As pointed out by Mustafa and Yaakub (2018), a company that wishes to adopt more technology is likely to need devices such as servers, tablets, laptops and desktop computers. Another almost inevitable expense is a good network to connect all these devices and ensure the effective functioning of the whole system. Furthermore, managers often do not fully understand the needs of their company, nor can they foresee future changes and how an information system will handle them (Mustafa & Yaakub, 2018). Lastly, the majority of staff ranging from entry-level workers to top managers are not adequately trained to use information technologies.

Implementation

Information systems in business require careful introduction and implementation, otherwise, a business will not be able to reap all the benefits that they present. This section leaves the technical issues of future information system development out of its scope and focuses on what businesses can do with existing solutions. First and foremost, monitoring systems pose a risk to employees’ and managers’ privacy and security in the workplace (Müller, 2020). For instance, software, known as “bossware,” can collect sensitive information such as logins, passwords and mail, which is why installing it without making a person aware is unethical. What a business can do is create a clear code of conduct and guidelines that employees and managers need to abide by. All parties should also be informed about software, what it does and what type of data it collects. It is critical to create an atmosphere of trust and make transparency one of the key corporate values.

The second recommendation for information system implementation is understanding the needs of a particular business when making a purchase. It is true that any information system measures performance in one way or another, but key performance metrics (KPI) will vary from company to company. Even before talking to vendors, a business needs to decide how its business goals translate into KPIs. For instance, the question may be what elements goals such as boosting sales or improving employees’ performance may be broken down into and quantified. The literature review section touched upon the differences in the use of information systems in business. These theoretical underpinnings should inform real-life decisions: it is critical to take into account the industry to which a business belongs to before setting expectations for information systems. A retail company may want to track stock turnover, customer satisfaction and average customer spend while a SaaS startup would be more interested in churn, lifetime value and monthly recurring revenue. Only a clear understanding of how an information system may be aligned with an enterprise’s strategy can help to make the right decision amidst thousands of options.

Since choosing an information system is such an important but challenging task, in recent years, there have evolved frameworks for accomplishing this task while mitigating risks and maximising profits. Henriques de Gusmão and Medeiros (2016) write that multicriteria decision-making/aiding (MCDM/A) methods are gaining traction because they offer a straightforward way to compare and contrast alternatives. Interestingly enough, a decision support information system can help with identifying other suitable information systems. Henriques de Gusmão and Medeiros (2016) propose a Fit Tradeoff DSS that uses mathematical modeling and existing data to assign weights to different options and find the most satisfactory one. Therefore, selecting the right information system may be based on both quantitative approaches and human intuition and a deep understanding of business and the market that cannot always be expressed in numbers.

The last recommendation draws on one of the key ideas expressed in this report. For now, no matter how intelligent, information systems support humans in their decisions as the former’s level of reliability is not sufficient for leaving them unsupervised. Therefore, it means that human interpretation, involvement and ultimate decision-making are necessary. However, the question arises as to whether staff are prepared to work with technologies. Data suggests that they are not: for instance, PwC’s (2020) Digital IQ report demonstrated that only 20% of executives considered their companies well-equipped to deal with artificial intelligence. Only 55% of surveyed respondents can call their leaders as digitally savvy and as PwC points out, innovation needs to start from the top. Hence, information systems need to be implemented in the right environment and handled by staff that are well-trained and incentivised to be lifelong learners.

Conclusion

The competitiveness of today’s market makes the adoption of information systems a necessary strategic element. The field of information systems is diverse and rapidly growing, which allows it to produce cutting-edge solutions for all organisational levels of management. DSS helps with major decisions, TPS takes care of daily operations, while MIS serves as a medium between the two layers, providing reports. For all their advantages, information systems are an investment that does not automatically become an asset. Indeed, there are issues that a business may encounter when it tries to elevate itself to the next level via technology. The risks may be mitigated through clear ethical guidelines, goal-setting and developing KPIs and staff training and education.

References

Arnott, D., & Pervan, G. (2015). A critical analysis of decision support systems research. In Formulating Research Methods for Information Systems (pp. 127-168). Palgrave Macmillan, London.

Bog, A. (2015). Benchmarking transaction and analytical processing systems. Springer.

CompTIA. (2019). IT industry outlook 2020. Web.

Deloitte. (2016). Deloitte’s 2016 global outsourcing survey. Web.

Duan, Y., Edwards, J. S., & Dwivedi, Y. K. (2019). Artificial intelligence for decision making in the era of Big Data–evolution, challenges and research agenda. International Journal of Information Management, 48, 63-71.

Henriques de Gusmao, A. P., & Pereira Medeiros, C. (2016). A model for selecting a strategic information system using the FITradeoff. Mathematical Problems in Engineering, 2016, 1-7.

Knowledge @ Wharton. (2017). Why Amazon’s ‘1-Click’ ordering was a game changer. Web.

Laudon, K. C., & Laudon, J. P. (2017). Management information systems: Managing the digital firm, global edition. Pearson.

Maciel, R. S. P., David, J. M. N., Claro, D. B., & Braga, R. (2017). Full interoperability: Challenges and opportunities for future information systems. Grand Research Challenges in Information Systems in Brazil 2016, 2026, 107-116.

Marr, B. (2018). Starbucks: Using big data, analytics and artificial intelligence to boost performance. Forbes. Web.

Mustafa, H. K., & Yaakub, S. (2018). Innovation and technology adoption challenges: Impact on SMEs’ company performance. International Journal of Accounting, 3(15), 57-65.

Müller, V. C. (2020). Ethics of artificial intelligence and robotics. Web.

PwC. (2020). 2020 global digital IQ. Web.

Reid, R. D., & Sanders, N. R. (2019). Operations management: An integrated approach. John Wiley & Sons.

Valacich, J., & Schneider, C. (2010). Information systems today; Managing in the digital world. Pearson Education,Inc.

Zhang, W., Zhang, C., Han, C., & Li, H. (2020). Development trend analysis of computer management information system. Journal of Electronic Research and Application, 4(1), 7-13.

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