Intelligent data analysis approaches to churn as a business problem: a survey

Globalization processes and market deregulation policies are rapidly changing the competitive environments of many economic sectors. The appearance of new competitors and technologies leads to an increase in competition and, with it, a growing preoccupation among service-providing companies with creating stronger customer bonds. In this context, anticipating the customer’s intention to abandon the provider, a phenomenon known as churn, becomes a competitive advantage. Such anticipation can be the result of the correct application of information-based knowledge extraction in the form of business analytics. In particular, the use of intelligent data analysis, or data mining, for the analysis of market surveyed information can be of great assistance to churn management. In this paper, we provide a detailed survey of recent applications of business analytics to churn, with a focus on computational intelligence methods. This is preceded by an in-depth discussion of churn within the context of customer continuity management. The survey is structured according to the stages identified as basic for the building of the predictive models of churn, as well as according to the different types of predictive methods employed and the business areas of their application.     

Harnessing Artificial Intelligence to Deliver Real-Time Intelligence and Business Process Improvements

As demand for data scientists in audit/Governance, risk management and compliance (GRC), and industry in general, outpaces supply, data science in a box—packaged analytics powered by artificial intelligence (AI) and guided machine learning—can bridge the gap to bring analytics to every major enterprise. Packaged analytics harness the power of AI and machine learning technologies to help operations, finance executives, and GRC professionals do their jobs better; optimize business processes; and deliver actionable insights for better decision making. This article will explore real-world case studies of how companies have used packaged analytics to achieve process improvements, better oversight over financial spend, and significant return on investment. It is a guide to internal auditors and their GRC counterparts on what is available and suggests they can partner or use the products independently and significantly contribute to their companies.     

Service-oriented computing

Service-oriented computing using Web services has emerged as a major research topic in recent years. Strong support from major computer companies including IBM, Microsoft, Hewlett-Packard, Oracle, and SAP has accelerated the acceptance and adoption of SOC using Web services. With SOC, enterprises can define and execute transactions across multiple business. Companies can use SOC's plug-and-play interoperability to compose business processes and integrate different information systems on the fly to enable ad hoc cooperation between new partners. Thus, SOC reinvents the way enterprises work together: common tasks in a business process or supply chain can be easily outsourced to external service providers for both performance and cost reasons.     

Properties that influence business process management maturity and its effect on organizational performance

BPM maturity is a measure to evaluate how professionally an organization manages its business processes. Previous research provides evidence that higher BPM maturity leads to better performance of processes and of the organization as a whole. It also claims that different organizations should strive for different levels of maturity, depending on their properties. This paper presents an empirical investigation of these claims, based on a sample of 120 organizations and looking at a selection of organizational properties. Our results reveal that higher BPM maturity contributes to better performance, but only up to a point. Interestingly, it contradicts the popular belief that higher innovativeness is associated with lower BPM maturity, rather showing that higher innovativeness is associated with higher BPM maturity. In addition, the paper shows that companies in different regions have a different level of BPM maturity. These findings can be used as a benchmark and a motivation for organizations to increase their BPM maturity.     

Business–IT alignment maturity of companies in China

Business–IT alignment has been consistently ranked as the number one concern of IT and business executives. Maintaining the alignment has been found to lead to stronger business performance, higher perceived value of IT and improved IS strategic planning; therefore addressing the issue is both important and timely. The economic growth in China in the last decade has led to greater availability of IT and its widespread use as a critical resource. Despite the increasing interest in Chinese IS issues by both researchers and practitioners, empirical research focusing on human- and organization-related IS issues in China is scarce. Using data collected from 130 business and IT executives from 22 companies in China, 11 of which were multinationals operating in China, we explored several questions in the area of business–IT alignment. An instrument designed to measure the six dimensions of business–IT alignment maturity was cross-validated using a sample of companies in China. Then, the instrument was refined to develop a measurement method that offered better reliability and validity in the context of Chinese companies. The relationship between the alignment maturity dimensions and IS strategic alignment was then examined. Finally, the alignment maturity of companies in China was assessed to provide a snapshot of business–IT alignment in China. A comparison between the 11 Chinese domestic companies and 11 multinational operating in China provided insight into the different IT practices of the two types of companies. Implications for researchers and practitioners are discussed.     

Data analytics and firm performance: An empirical study in an online B2C platform

Data analytics has become an increasingly eye-catching practice in both the academic and the business communities. The importance of data analytics has also prompted growing literature to focus on the design of data analytics. However, the boundary conditions for data analytics in creating value have been largely overlooked in the literature. The objective of this article therefore is to examine the business value of data analytics usage and explore how such value differs in different market conditions. We rely on an online B2C platform as our empirical setting and obtain several important insights. First, both demand-side and supply-side data analytics usage has a positive effect on the performance of merchants. Second, when merchants’ product variety is high, the influence of usage toward demand-side data on performance is strengthened, whereas such impact is weakened for supply-side data analytics. Third, when competitive intensity is high, the performance implication of demand-side data analytics usage is strengthened, whereas such impact is not strengthened for supply-side data analytics. This study contributes by advancing the overall understanding of business value of data analytics.     

Multi-behavior agent model for planning in supply chains: An application to the lumber industry

Recent economic and international threats to western industries have encouraged companies to increase their performance in all ways possible. Many look to deal quickly with disturbances, reduce inventory, and exchange information promptly throughout the supply chain. In other words they want to become more agile. To reach this objective it is critical for planning systems to present planning strategies adapted to the different contexts, to attain better performances. Due to consolidation, the development of integrated supply chains and the use of inter-organizational information systems have increased business interdependencies and in turn the need for increased collaboration to deal with disturbance in a synchronized way. Thus, agility and synchronization in supply chains are critical to maintain overall performance. In order to develop tools to increase the agility of the supply chain and to promote the collaborative management of such disturbances, agent-based technology takes advantage of the ability of agents to make autonomous decisions in a distributed network through the use of advanced collaboration mechanisms. Moreover, because of the highly instable and dynamic environment of today's supply chains, planning agents must handle multiple problem solving approaches. This paper proposes a Multi-behavior planning agent model using different planning strategies when decisions are supported by a distributed planning system. The implementation of this solution is realized through the FOR@C experimental agent-based platform, dedicated to supply chain planning for the lumber industry.     

A review of soft computing applications in supply chain management

It is broadly recognised by global companies that supply chain management is one of the major core competencies for an organisation to compete in the marketplace. Organisational strategies are mainly concentrated on improvement of customer service levels as well as reduction of operational costs in order to maintain profit margins. Therefore supply chain performance has attracted researchers’ attention. A variety of soft computing techniques including fuzzy logic and genetic algorithms have been employed to improve effectiveness and efficiency in various aspects of supply chain management. Meanwhile, an increasing number of papers have been published to address related issues. The aim of this paper is to summarise the findings by a systematic review of existing research papers concerning the application of soft computing techniques to supply chain management. Some areas in supply chain management that have rarely been exposed in existing papers, such as customer relationship management and reverse logistics, are therefore suggested for future research.     

Establishment-level occupational safety analytics: Challenges and opportunities

In occupational safety and health, big data and analytics show promise for the prediction and prevention of workplace injuries. Advances in computing power and analytical methods have allowed companies to reveal insights from the “big” data that previously would have gone undetected. Despite the promise, occupational safety has lagged behind other industries, such as supply chain management and healthcare, in terms of exploiting the potential of analytics and much of the data collected by organizations goes unanalyzed. The purpose of the present paper is to argue for the broader application of establishment-level safety analytics. This is accomplished by defining the terms, describing previous research, outlining the necessary components required, and describing knowledge gaps and future directions. The knowledge gaps and future directions for research in establishment-level analytics are categorized into readiness for analytics, analytics methods, technology integration, data culture, and impact of analytics.     

The effects of collaboration on build-to-order supply chains: with a comparison of BTO,MTO, and MTS

The initiative of collaborative planning, forecasting and replenishment has generally provided rich options of strategies for build-to-order (BTO) supply chain members. In this study, we examined collaborative activities across BTO, make-to-order (MTO), and make-to-stock (MTS) supply chains. We draw upon the results from an empirical research from 126 manufacturing companies to illustrate what collaborative activities will enable companies to achieve better market performance, given their particular production circumstances. We have provided three major findings in this study: (1) identified a set of activities that are viewed as important for collaboration by business managers; (2) recognized various effects of collaboration on BTO, MTO, and MTS; and (3) illustrated the association between collaborative activities in BTO, MTO, and MTS supply chain and firm’s market performance.     

Business analytics maturity of firms: an examination of the relationships between managerial perception of IT,business analytics maturity and success

This study develops a measure for business analytics (BA) maturity and empirically examines the relationships between managerial perception of IT, BA maturity and BA success. The findings suggest that (1) BA maturity can be measured via BA integration & management support, process-level benefits of BA and technology & data analytics capabilities, (2) BA maturity positively affects organizations’ overall BA success, and (3) managerial perception of IT positively influence organizations’ achievement of BA maturity.     

Challenges in business systems integration

Four main frameworks for intercompany relationships (SCOR, CPFR, ISA95 and OAG) are discussed and compared. The link between the frameworks and different supply chain integration applications such as ERP, CRM and VMI are pictured. Finally the state-of-the-art, future state and challenges of the supply chain integration applications are discussed. It is concluded that the main challenge with respect to frameworks supporting business systems integration is to extend them with implementation functionality to better support business system application development. An example of this is customer requirement fulfillment processes such as product development and order fulfillment. Not only do they cross the borders of the company's departments (sales, logistics, purchasing, etc) but also various companies in the supply chain. In spite of this development, business integration across systems and borders are still not matured and to a large extend based on human interaction.     

Productivity paradoxes revisited

The adoption of quality assurance methods based on software process improvement models has been regarded as an important source of variability in software productivity. Some companies perceive that their implementation has prohibitive costs, whereas some authors identify in their use a way to comply with software development patterns and standards, produce economic value and lead to corporate performance improvement. In this paper, we investigate the relationship between quality maturity levels and labor productivity, using a data set containing 687 Brazilian software firms. We study here the relationship between labor productivity, as measured through the annual gross revenue per worker ratio, and quality levels, which were appraised from 2006 to 2012 according to two distinct software process improvement models: MPS.BR and CMMI. We perform independent statistical tests using appraisals carried out according to each of these models, consequently obtaining a data set with as many observations as possible, in order to seek strong support for our research. We first show that MPS.BR and CMMI appraised quality maturity levels are correlated, but we find no statistical evidence that they are related to higher labor productivity or productivity growth. On the contrary, we present evidence suggesting that average labor productivity is higher in software companies without appraised quality levels. Moreover, our analyses suggest that companies with appraised quality maturity levels are more or less productive depending on factors such as their business nature, main origin of capital and maintained quality level.     

Interactions of agents in performance based supply chain management

To acquire a competitive advantage in the expanding market, manufacturing companies should be able to manage their supply chain as much effective as possible. Measuring the supply chain performance is one of the main indicators of business success. Supply chain management (SCM) involves managing the flow of materials from suppliers to manufacturing units. This paper proposes a SCM model with performance measurement capabilities. The model is designed in such a way that it well suits to multi agent systems and related implementations. This paper highlights the components of the model especially pointing out the key parameters of performance indicators.     

Development of Wafer Warehouse Management System for Semiconductor Manufacturing Foundry Supply Chain

Efficiency of supply chains management mostly depends on the process coordination and information integration between the supply chain companies.The well-known integrated circuit design houses,the wafer fabrication industries, and the integrated circuit packaging/testing business has together formed a contiguous supply chain from materials to system in Taiwan during the past decades.Logistic management of the wafer hence becomes the key linkage in the semiconductor foundry supply chain.The objective of this paper is to develop the wafer warehouse management system for global wafer logistics.Current operations for wafer logistics management are firstly reviewed. The system requirements are analyzed by the model-driven business transformation approach.The business operation model and the platform-independent solution architecture for the wafer logistics management are constructed.A prototype information system is also developed for validation.Results of this research can improve the effectiveness and efficiency in wafer logistics management for the semiconductor foundry supply chain.     

Performance of supply chain collaboration – A simulation study

In the past few decades several supply chain management initiatives such as Vendor Managed Inventory, Continuous Replenishment and Collaborative Planning Forecasting and Replenishment (CPFR) have been proposed in literature to improve the performance of supply chains. But, identifying the benefits of collaboration is still a big challenge for many supply chains. Confusion around the optimum number of partners, investment in collaboration and duration of partnership are some of the barriers of healthy collaborative arrangements. To evolve competitive supply chain collaboration (SCC), all SC processes need to be assessed from time to time for evaluating the performance. In a growing field, performance measurement is highly indispensable in order to make continuous improvement; in a new field, it is equally important to check the performance to test conduciveness of SCC. In this research, collaborative performance measurement will act as a testing tool to identify conducive environment to collaborate, by the way of pinpointing areas requiring improvements before initializing collaboration. We use actual industrial data and simulation to help managerial decision-making on the number of collaborating partners, the level of investments and the involvement in supply chain processes. This approach will help the supply chains to obtain maximum benefit of collaborative relationships. The use of simulation for understanding the performance of SCC is relatively a new approach and this can be used by companies that are interested in collaboration without having to invest a huge sum of money in establishing the actual collaboration.     

Creating business value with process mining

Information systems research has a long-standing interest in how organizations gain value through information technology. In this article, we investigate a business process intelligence (BPI) technology that is receiving increasing interest in research and practice: process mining. Process mining uses digital trace data to visualize and measure the performance of business processes in order to inform managerial actions. While process mining has received tremendous uptake in practice, it is unknown how organizations use it to generate business value. We present the results of a multiple case study with key stakeholders from eight internationally operating companies. We identify key features of process mining – data & connectivity, process visualization, and process analytics – and show how they translate into a set of affordances that enable value creation. Specifically, process mining affords (1) perceiving end-to-end process visualizations and performance indicators, (2) sense-making of process-related information, (3) data-driven decision making, and (4) implementing interventions. Value is realized, in turn, in the form of process efficiency, monetary gains, and non-monetary gains, such as customer satisfaction. Our findings have implications for the discourse on IT value creation as we show how process mining constitutes a new class of business intelligence & analytics (BI&A) technology, that enables behavioral visibility and allows organizations to make evidence-based decisions about their business processes.     

The effects of business systems leveraging on supply chain performance: Process innovation and uncertainty as moderators

Rooted in the profit-seeking motives of social exchange theory, this study aims to investigate the factors that facilitate leverages of firm’s business systems and their sharing of information with group members, as well as the impacts of business systems leveraging (BSL) on information sharing and supply chain performance. Simultaneously, the moderating effects of uncertainty and the degree of process innovation on the relationship between BSL and supply chain performance are also estimated. The analytical results indicated that proactive technological orientation, information technology (IT) connectivity, supply chain member pressure, and member relationship quality encourage firms to combine their business systems with those of other business partners. Interestingly, in a situation where there is high demand and an uncertain supply, the impact of BSL on supply chain performance is low, while the moderating effect of process innovation on the relationship between BSL and supply chain performance is significant. Finally, it is suggested that firms implementing BSL work to upgrade their technology maintain tight relationships with supply chain partners and create innovation in all aspects of their business processes in order to survive in the highly competitive IT environment.