Kamal Bhattacharya

Modeling business contexture and behavior using business artifacts

Traditional process modeling approaches focus on the activities needed to achieve a business goal. However, these approaches often pose obstacles in consolidating processes across an organization because they fail to capture the informational structure pertinent to the business context or contexture. In this paper, we discuss business artifact-centered operational modeling. Artifacts capture the contexture of a business and operational models describe how a business goal is achieved by acting upon the business artifact. Business artifacts, such as Purchase Order or Insurance Claim, provide business analysts an additional dimension to model their business. With operational models, they can describe how a business operates by processing business artifacts and adding business value to the artifacts. This approach has been successfully employed in a variety of customer engagements. We summarize our best practices by describing nine operational patterns. Furthermore, we develop a computational model for operational models based on Petri Nets to enable formal analysis and verification thereof.

The Social Compute Unit

Social computing is perceived mainly as a vehicle for establishing and maintaining private relationships and thus lacks mainstream adoption in enterprises. Collaborative computing, however, is firmly established, but no tight integration of the two approaches exists. Here, the authors look at how to integrate people, in the form of human-based computing, and software services into one composite system.

Workload Migration into Clouds Challenges, Experiences, Opportunities

The steady drumbeat of Cloud as a disruptive influence for Infrastructure Service Providers (ISP’s) and the enablement vehicle for Software As A Service (SAAS)providers can be heard loud and clear in the industry today. In fact, Cloud is probably at the peak of the hype curve, and already there are identified challenges associated with effective deployment for business critical applications (so called Production Applications) in mature enterprises. One of these challenges is the smooth migration of workload from the previous environment to the new cloud enabled environment in a cost effective way, with minimal disruption and risk. In this paper we introduce extensions to an integrated automation capability called the Darwin framework that enables workload migration for this scenario and discuss the impact that automated migration has on the cost and risks normally associated with migration to clouds.

Static Analysis of Business Artifact-centric Operational Models

Business artifacts are the core entities used by businesses to record information pertinent to their operations. Business operational models are representations of the processing of business artifacts. Traditional process modeling approaches focus on the actions taken to achieve a certain goal (verb-centric). Business artifact-centric modeling starts by identifying what is acted upon (noun-centric), and constructs business operational models by identifying the tasks/actions that business actors execute to add business value. In this paper, we identify important classes of properties on artifact-centric operational models. In particular, we focus on persistence, uniqueness and arrival properties. To enable a static analysis of these properties, we propose a formal model for artifact-centric operational models. We show that the formal model guarantees persistence and uniqueness. We prove that, while checking an arrival property is undecidable in general, under a restricted version of the formalism, an arrival property can be checked in EXPTIME.

Estimating business value of IT services through process complexity analysis

In this paper we propose a methodology to estimate business value of IT services. We investigate how to apply quantitative studies for IT service management processes that allows us to link measurable performance improvements with concrete business value. Specifically, we follow an Information Technology Infrastructure Library (ITIL) defined strategy combined with process complexity analysis techniques. This helps to reason about inefficiencies in IT service processes due to problems with coordination of different roles, lack of support for task execution, and complexities for getting the source of information. Our approach consists in (1) identifying the process context using ITIL as a reference framework, (2) quantifying process baseline with typical task execution time and underlying complexity, (3) estimating performance improvement achieved by tooling deployment or process transformation, and (4) estimating business value derived for various business cases. We illustrate our methodology using the change management process as defined in IBM Tivoli Unified Process (ITUP) and estimating the business value of implementing an application discovery tool and a change management tool.

A technical framework for sense-and-respond business management

In this paper we present a technical framework that supports sense and respond (SaR), the approach that enables an enterprise to adapt to a rapidly changing business environment. To implement the SaR approach, an enterprise proactively monitors trends and uses effective decision-support tools to help it act in a timely manner. We describe two pilot projects in which we implemented SaR prototypes and applied them to solve business problems. In the first pilot project we helped the IBM Microelectronics Division deploy an automated inventory management system based on our inventory optimization model. In the second pilot project, we helped the IBM Personal Computing Division deploy a SaR system in support of demand/supply conditioning. One of the components of this SaR system is an order trend model that provides early warning of constraints and excesses in the supply chain and helps make demand/supply conditioning more effective. Early results from these projects are encouraging and show that significant gains in profitability are possible.

Change scheduling based on business impact analysis of change-related risk

In todays enterprises, the alignment of IT service infrastructures to continuously changing business requirements is a key cost driver, all the more so as most severe service disruptions can be attributed to the introduction of changes into the IT service infrastructure. Change management is a disciplined process for introducing required changes with minimum business impact. Considering the number of business processes in an enterprise and the complexity of the dependency network of processes to invoked services, one of the most pressing problems in change management is the risk-aware prioritization and scheduling of vast numbers of service changes. In this paper we introduce a model for estimating the business impact of operational risk resulting from changes. We determine the business impact based on the number and types of business process instances affected by a change-related outage and quantify the business impact in terms of financial loss. The model takes into account the network of dependencies between processes and services, probabilistic change-related downtime, uncertainty in business process demand, and various infrastructural characteristics. Based on the analytical model, we derive decision models aimed at scheduling single or multiple correlated changes with the lowest expected business impact. The models are evaluated using simulations based on industry data.

Who do you call? problem resolution through social compute units

Service process orchestration using workflow technologies have led to significant improvements in generating predicable outcomes by automating tedious manual tasks but suffer from challenges related to the flexibility required in work especially when humans are involved. Recently emerging trends in enterprises to explore social computing concepts have realized value in more agile work process orchestrations but tend to be less predictable with respect to outcomes. In this paper we use IT services management, specifically, incident management for large scale systems, to investigate the interplay of workflow systems and social computing. We apply a recently introduced concept of Social Compute Units, and flexible teams sourced based on various parameters such as skills, availability, incident urgency, etc. in the context of resolution of incidents in an IT service provider organization. Results from simulation-based experiments indicate that the combination of SCUs and workflow based processes can lead to significant improvement in key service delivery outcomes, with average resolution time per incident and number of SLO violations being at times as low as 52.7% and 27.3% respectively of the corresponding values for pure workflow based incident management.

Decision support for service transition management Enforce change scheduling by performing change risk and business impact analysis

In IT service delivery, alignment of service infrastructures to continuously changing business requirements is a primary cost driver, all the more as most severe service disruptions can be attributed to poor change impact and risk assessment. An IT service, defined as a means to provide value to a consumer, may be realized by a network of shared application and other resources that are invoked in the context of business processes. In the spirit of service-oriented architecture (SOA) we consider each application or resource as a service. Changing services or service definitions in such an environment includes exceptionally high risk and complexity, as various business processes might depend on a service. In this paper we propose a model for analyzing the business impact of operational risks resulting from change related service downtimes of uncertain duration. The proposed solution takes into account the network of dependencies between services where services may or may not be realized through business processes. Based on the analytical model, we derive decision models in terms of deterministic and probabilistic mathematical programming formulations to schedule single or multiple correlated changes efficiently. Preliminary experiments are described to illustrate the efficiency of the proposed models. Using these decisions models, organizations can schedule service changes with the lowest expected impact on the business.

Optimizing Change Request Scheduling in IT Service Management

Enterprises of today face the challenge of managing large, complex IT eco-systems consisting of software applications, servers, network routers, and other type of resources. Change management, especially scheduling of changes, is known to be one of the most challenging problems in managing IT operations. In this paper, we propose an optimization model for IT change scheduling that takes into account the constraints and cost factors typically encountered in a service provider environment. In particular, we formulate the model in a way that can be solved using standard mathematical programming techniques (i.e., mixed integer programming). This not only results in strictly optimal solutions, but also provides a scalable means for scheduling a large set of change requests with complex constraints. Furthermore, having a computational efficient optimization solution facilitates the study of the scheduling sensitivity with respect to parameter inaccuracy and leads to more robust change schedules. Finally, we demonstrate the effectiveness of the proposed approach in an IT change management example which is built using insights from a large service delivery account and over two hundred thousand change instances.