Mary E. Helander

Using Software Repositories to Investigate Socio-technical Congruence in Development Projects

We propose a quantitative measure of socio- technical congruence as an indicator of the performance of an organization in carrying out a software development project. We show how the information necessary to implement that measure can be mined from commonly used software repositories, and we describe how socio-technical congruence can be computed based on that information.

Seeing inside: Using social network analysis to understand patterns of collaboration and coordination in global software teams

One of the pervasive challenges facing any software development team is getting the right level and timing of communication to ensure that people are able to coordinate their work effectively. Communication issues are difficult to address because important aspects of communication are largely invisible to both management and the individuals on the team. Communication challenges are further exaggerated in global software teams, because of the different time-zones, cultures, and working environments. Social Network Analysis (SNA) is an established method for revealing patterns of human communication and decision-making. This tutorial introduces students to basic concepts in SNA, illustrates how SNA can be used to understand the dynamics of and address common communication problems in global software teams, and provides structured exercises in data capture, analysis and interpretation.

Ensemble: a recommendation tool for promoting communication in software teams

Successful software development requires effective coordination among developers. In this paper, we propose Ensemble, an approach and a set of tools that aim to help developers better coordinate their work. Built on IBM Rational Team Concert, Ensemble helps developers select the right people to collaborate with, the right times to collaborate with them, and to stay coordinated with them over time.

Assistance: the work practices of human administrative assistants and their implications for it and organizations

Assistance - work carried out by one entity in support of another - is a concept of long-standing interest, both as a type of human work common in organizations and as a model of how computational systems might interact with humans. Surprisingly, the perhaps most paradigmatic form of assistance - the work of administrative assistants or secretaries - has received almost no attention. This paper reports on a study of assistants, and their principals and managers, laying out a model of their work, the skills and competencies they need to function effectively, and reflects on implications for the design of systems and organizations.

Financial text mining: Supporting decision making using web 2.0 content

Enabled by Web 2.0 technologies, online social media in the forms of discussion forums, message boards, and blogs has become a prevalent channe lof communication for consumers and businesses. Online social media allows consumers to share their product opinions and experience at an unprecedented pace and scale. This user generated content, or online word of mouth (WOM), has the potential to influence product sales and firm strategy. Consequently, as Web-mining and opinion-mining tools and technology continue to proliferate, it is critical to examine how WOM information can be measured and used to improve managerial decisions.In this article, we explore the predictive validity of various text and sentiment measures of online WOM for the market success of new products. From the firms’ perspective, it is important to effectively predict the sales of new products in the product development process. The earlier such a forecast can be made, the more useful it will be, since marketing strategies can then be adjusted accordingly. We thus examine online WOM that appears at different stages of the new-product life cycle, such as before production, before introduction, and after introduction. New-product development is a highly risky process, and it is useful to examine different aspects of its success. In addition to examining product sales directly, we also study product evaluation by third-party professionals and how the product would receive marketing support from the firm, both of which could influence sales. The context of our study is the Hollywood movie industry. The forecast of movie sales is highly challenging and has started to incorporate online WOM. We collected online WOM information from the message board of Yahoo Movies for a total of 257 movies released from 2005 to 2006. We used Senti Word Net and Opinion Finder, two lexical packages of computational linguistics, to construct the sentiment measures for the WOM data. We will first examine the evolution patterns of online WOM over time, followed by a correlation analysis of how various sentiment measures relate to the metrics of new product success.When Adam Smith wrote the Wealth of Nations in 1776, he concluded that individuals, firms, and nations obtain comparative advantage by specialization. Markets worked as the invisible hand to efficiently allocate resources between specialized parties. During the Industrial Revolution, manufacturing organizations helped the nation become wealthy by creating mechanisms for the internal allocation and integration of resources to produce largely tangible output. Today, both markets and organizations are undergoing a phase transition.to the “skills, technologies, applications, and practices used to support decision making” (http:// en.wikipedia.org/wiki/Business_intelligence). On the basis of a survey of 1,400 CEOs, the Gartner Group projected BI revenue to reach

Network location of a reliable center using the most reliable route policy

3 billion in 2009.1 Through BI initiatives, businesses are gaining insights from the growing volumes of transaction, product, inventory, customer, competitor, and industry data generated by enterprise-wide applications such as enterprise resource planning (ERP), customer relationship management (CRM), supply-chain management (SCM), knowledge management, collaborative computing, Web analytics, and so on. The same Gartner survey also showed that BI surpassed security as the top business IT priority in 2006.1 BI has been used as an umbrella term to describe concepts and methods for improving business decision making by using fact-based support systems. BI also includes the underlying architectures, tools, databases, applications, and methodologies. BI’s major objectives are to enable interactive and easy access to diverse data, enable manipulation and transformation of these data, and give business managers and analysts the ability to conduct appropriate analyses and then act.2 BI is now widely adopted in the world of IT practice and has also become popular in information systems curricula.3 Successful BI initiatives have been reported for major industries—from healthcare and airlines to major IT and telecommunications fi rms.2 As a data-centered approach, BI relies heavily on various advanced data collection, extraction, and analysis technologies.2,3 Data warehousing is often considered the foundation of BI. Design of data marts and tools for extraction, transformation, and load (ETL) are essential for converting and integrating enterprise-specifi c data. Organizations often next adopt database query, online analytical processing (OLAP), and advanced reporting tools to explore important data characteristics. Business performance management (BPM) using scorecards and dashboards allow analysis and visualization of various employee performance metrics. In addition to these well-established business analytics functions, organizations can adopt advanced knowledge discovery using data and text mining for association rule mining, database segmentation and clustering, anomaly detection, and predictive modeling in various information systems and human resources, accounting, fi nance, and marketing applications. Since about 2004, Web intelligence, Web analytics, Web 2.0, and user-generated content have begun to usher in a new and exciting era of business research, which we could call Business Intelligence 2.0. An immense amount of company, industry, product, and customer information can be gathered from the Web and organized and visualized through various knowledge-mapping, Web portal, and multilingual retrieval techniques.4 By analyzing customer clickstream data logs, Web analytics tools such as Google Analytics provide a trail of the user’s online activities and reveal the user’s browsing and purchasing patterns. Web site design, product placement optimization, customer transaction analysis, and product recommendations can Business Intelligence (BI), a term coined in 1989, has gained much traction in the IT

Carbon management in assembly manufacturing logistics

This paper considers a single location on an undirected network with unreliable edges that maximizes the lowest performance level of the network service with respect to all nodes. The problem is termed the reliable 1-center problem and finds applications in telecommunication and computer networks. The users are concerned with the network capability of establishing a route to some service provider. The objective function is formally stated as either minimizing the maximum expected number of unsuccessful responses to demand requests over all nodes, named the reli-minmax problem, or maximizing the minimum expected number of successful responses to demand requests over all nodes, named the reli-maxmin problem, as sub-problems of the most general reliable 1-center problem. Solutions are presented that solve the problem in polynomial time or reduce it to the 1-center problem when it is applied on general networks using a pre-designated route policy, e.g. the most reliable route policy.

Supply Chain Scenario Modeler: A Holistic Executive Decision Support Solution

In this paper, we present the IBM Carbon Analyzer Tool, a software solution that models and quantifies carbon emissions and explores ways to reduce emissions through advanced analytics. The tool is designed to manage carbon emissions associated with the support logistics for an assembly manufacturing operation. The tool has four analytical modules. A shipment analysis module calculates carbon emissions from transportation activities and analyzes opportunities for reducing emissions by changing fuel types of vehicles and using larger vehicles that permit consolidated shipments. A sourcing analysis module compares sourcing alternatives, including changes to supplier locations, routing of shipments, frequency of orders, and transportation modes. A scenario analysis module explores various consolidation policies to minimize transportation, inventory, and carbon costs, subject to inventory availability requirements. A sensitivity analysis module quantifies the effects of changes to uncontrollable and uncertain inputs, such as manufacturing demand for components, carbon prices, and supplier reliability. The tool makes use of a Javae™- based graphical user interface and an IBM® DB2t (Database 2e) platform to manage input and output data. A pilot implementation of the solution, using actual customer data, showed that emissions and transportation costs can be reduced simultaneously by optimizing vehicle use, fuel types, and shipment consolidation. Achieving a 20%-30% reduction in emission was possible with minimal cost increase.

The gravity of an edge

McKesson is Americas oldest and largest healthcare services company. IBM Research developed an innovative scenario modeling and analysis tool, supply chain scenario modeler SCSM, for McKesson to optimize its end-to-end pharmaceutical supply chain policies. Through integrated operations research OR models, SCSM optimizes the distribution network, supply flow, inventory, and transportation policies, and quantifies the impacts of changes on financial, operational, and environmental metrics. The modeling work spawned a roadmap of projects with quantified opportunities, including a new air freight supply chain path, and provided new insights that have been critical to improving McKessons performance as a pharmaceutical industry leader. A structured data model supporting the OR models has provided a basis for additional improvement projects. The model directly links OR modeling results to a detailed profit-and-loss statement by product category for the different supply chain paths that McKesson uses. Since this effort began in 2009, McKesson Pharmaceutical division has reduced its committed capital by more than

Framework for managing mycotoxin risks in the food industry.

1 billion.