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Optimizing Business Processes with BTM

The Role of Business Transaction Management

Gartner's Senior VP Research, Peter Sondergaard, recently spoke at Gartner Symposium 2010 about four trends changing computing. As part of this, he emphasized that, while IT departments have been internally focused on optimizing internal processes and costs for the past 20 years, it’s now more about IT’s involvement in optimizing business processes.

IT’s forward motion towards optimizing business processes and controlling their costs is aimed at empowering businesses to be more competitive at a lower cost and with an improved customer experience. This is crucial in today’s economy.

The key here is to enable IT teams to instantly see technology issues situationally in the context of their business and to automatically predict, and even prevent, the issue’s business impact. This allows companies to optimize the IT implementation of their business processes, and as a result, achieve greater productivity at a lower cost.

The Great Convergence

IT thought leaders have begun to realize that in order to successfully optimize business processes, they need to converge the disciplines of Business Transaction Management (BTM), Application Performance Management (APM) and Complex Event Processing (CEP). This convergence enables the correlation of operational metrics for IT applications, middleware and infrastructure with the real-time visibility into business transactions and the business processes they comprise.

Using this new convergence, businesses can avoid the all too common scenario where, following a serious technology problem, representatives from each IT silo gather in a room for several hours to determine what the root cause of the problem was with no clear consensus on whether this problem is of IT interest only or in fact impacts an important business process.

More effectively, this new approach uses the CEP engine at its core to constantly scan for patterns foretelling a transaction is heading for a “business abnormal” state and thus, via an “early warning system,” prevent the unnecessary costs optimization involved in cleaning up the damage of a transactional mishap.

Typically, when IT staff resolves a complex problem, they describe the resolution and share this process with the other members of support. The next time the problem occurs, this resolution is reused by the assigned member of support. This is a reactive approach, and an expensive one. While the mean-time-to-repair the problem is reduced after the first occurrence, support is still utilizing a manual process to detect, and then resolve, the problem. The side effect of this might be personally painful where an IT administrator is woken up two days in a row to deal with the same problem. At this point a problem has been detected, a ticket is open and most likely users and business processes are already impacted. This is an expensive approach to problem management.

A better approach would be the following: after the first time the problem has occurred, it could be described as a situation to the converged BTM solution along with appropriate business rules describing how to resolve this issue before it has business impact. This approach is, in effect, adding inference in order to predict problems, the ultimate key to being proactive monitoring of business transactions and the business processes they realize.

In this scenario, the pattern describing the problem is detected and immediately, an automated resolution is initiated before users are impacted or a business process is disrupted. Essentially, the mean-time-to-know a multi-tier composite application is no longer performing or behaving within a business normal state and the mean-time-to-react to the issue have both been reduced. Furthermore, the impact of the problem has been prevented via automated dynamic invocation of business rules. This is a much better business outcome with contained cost, but one that can only be leveraged when utilizing a solution that can, in real-time, detect the patterns and dependencies occurring across your complex composite applications and dynamically take action.

Over time, the system’s capabilities and value continuously improve. This approach continues to help optimize business processes by automatically learning and adjusting to what is normal and abnormal for your business via analysis of the real-time data provided by BTM and its integration with legacy event monitoring systems. Imagine a spiral where a complex problem occurs; its resolution is specified and over time, the system is learning to behave better and to handle more issues automatically. The 360-degree situational awareness this provides reduces costs and streamlines business processes and does this in a cycle of continuous availability improvement. The key points here are an increase in automation, prediction, prevention and a resultant decrease in operational cost and business process disruption.

Calculating ROI on the Ground and in the Clouds

Cloud Computing, one of the four trends Sondergaard discussed, is no longer a future direction and is being readily implemented today. While the benefits of Cloud Computing are many, the difficulty in managing the availability and performance of applications, business transactions and the business processes they actualize becomes incalculably more difficult to do. Why? This complexity is due to the very benefit of flexibility the Cloud provides – elasticity through virtualization. It is now much harder to achieve the 360-degree situational awareness a business needs in order to reduce support costs, improve service levels and achieve its desired ROI. In a Cloud Computing environment, the challenge of transaction, application and middleware message detection in real-time is much harder to do as the number of places they can be greatly expands and may constantly be in flux.

So how does one assess the benefits of business transaction management and whether or not it is yielding results in terms of optimizing business processes? ROI is calculated by a reduction in capital and operational expenditures, an avoidance of the lost revenue hidden in order fallout and customer attrition. This translates into the following benefits: fewer tickets at the service desk - reducing labor costs, improved customer experience - preserving customer loyalty, reduced disruption to business processes - maintaining profitability and compliance with service level agreements - steering clear of penalties.

Achieving these benefits enables a business to focus on using IT as it was intended for - to deliver more services to customers, grow market share and no longer spend the majority of the time and money allocated to IT on merely fixing problems in order to maintain current availability and performance levels.

In summary, with the recent worldwide recession, layoffs and cost-cutting efforts have turned the spotlight on IT infrastructure and how utilizing advancements in enterprise technology can optimize business processes. This new thought-leading approach to converging BTM with CEP and APM helps IT personnel find ways to squeeze stealth waste out of business processes by providing the full visibility prediction and performance that is necessary to reduce costs, improve service and manage risk.

About Charley Rich

Charley Rich is VP Product Management and Marketing at Nastel Technologies and has over 28 years of technical, hands-on experience working with large-scale customers to meet their application and systems management requirements. Prior to joining Nastel, Charley was Product Manager for IBM's Tivoli Application Dependency Discovery Manager software, where he co-authored an IBM Redbook, charted the product roadmap, managed an agile requirements process and was recognized for his accomplishments by winning the Tivoli General Manager's Award. Recently, Charley was granted a patent for an Application Discovery and Monitoring process.

Related Links:

www.nastel.com

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Optimizing Business Processes with BTM

The Role of Business Transaction Management

Gartner's Senior VP Research, Peter Sondergaard, recently spoke at Gartner Symposium 2010 about four trends changing computing. As part of this, he emphasized that, while IT departments have been internally focused on optimizing internal processes and costs for the past 20 years, it’s now more about IT’s involvement in optimizing business processes.

IT’s forward motion towards optimizing business processes and controlling their costs is aimed at empowering businesses to be more competitive at a lower cost and with an improved customer experience. This is crucial in today’s economy.

The key here is to enable IT teams to instantly see technology issues situationally in the context of their business and to automatically predict, and even prevent, the issue’s business impact. This allows companies to optimize the IT implementation of their business processes, and as a result, achieve greater productivity at a lower cost.

The Great Convergence

IT thought leaders have begun to realize that in order to successfully optimize business processes, they need to converge the disciplines of Business Transaction Management (BTM), Application Performance Management (APM) and Complex Event Processing (CEP). This convergence enables the correlation of operational metrics for IT applications, middleware and infrastructure with the real-time visibility into business transactions and the business processes they comprise.

Using this new convergence, businesses can avoid the all too common scenario where, following a serious technology problem, representatives from each IT silo gather in a room for several hours to determine what the root cause of the problem was with no clear consensus on whether this problem is of IT interest only or in fact impacts an important business process.

More effectively, this new approach uses the CEP engine at its core to constantly scan for patterns foretelling a transaction is heading for a “business abnormal” state and thus, via an “early warning system,” prevent the unnecessary costs optimization involved in cleaning up the damage of a transactional mishap.

Typically, when IT staff resolves a complex problem, they describe the resolution and share this process with the other members of support. The next time the problem occurs, this resolution is reused by the assigned member of support. This is a reactive approach, and an expensive one. While the mean-time-to-repair the problem is reduced after the first occurrence, support is still utilizing a manual process to detect, and then resolve, the problem. The side effect of this might be personally painful where an IT administrator is woken up two days in a row to deal with the same problem. At this point a problem has been detected, a ticket is open and most likely users and business processes are already impacted. This is an expensive approach to problem management.

A better approach would be the following: after the first time the problem has occurred, it could be described as a situation to the converged BTM solution along with appropriate business rules describing how to resolve this issue before it has business impact. This approach is, in effect, adding inference in order to predict problems, the ultimate key to being proactive monitoring of business transactions and the business processes they realize.

In this scenario, the pattern describing the problem is detected and immediately, an automated resolution is initiated before users are impacted or a business process is disrupted. Essentially, the mean-time-to-know a multi-tier composite application is no longer performing or behaving within a business normal state and the mean-time-to-react to the issue have both been reduced. Furthermore, the impact of the problem has been prevented via automated dynamic invocation of business rules. This is a much better business outcome with contained cost, but one that can only be leveraged when utilizing a solution that can, in real-time, detect the patterns and dependencies occurring across your complex composite applications and dynamically take action.

Over time, the system’s capabilities and value continuously improve. This approach continues to help optimize business processes by automatically learning and adjusting to what is normal and abnormal for your business via analysis of the real-time data provided by BTM and its integration with legacy event monitoring systems. Imagine a spiral where a complex problem occurs; its resolution is specified and over time, the system is learning to behave better and to handle more issues automatically. The 360-degree situational awareness this provides reduces costs and streamlines business processes and does this in a cycle of continuous availability improvement. The key points here are an increase in automation, prediction, prevention and a resultant decrease in operational cost and business process disruption.

Calculating ROI on the Ground and in the Clouds

Cloud Computing, one of the four trends Sondergaard discussed, is no longer a future direction and is being readily implemented today. While the benefits of Cloud Computing are many, the difficulty in managing the availability and performance of applications, business transactions and the business processes they actualize becomes incalculably more difficult to do. Why? This complexity is due to the very benefit of flexibility the Cloud provides – elasticity through virtualization. It is now much harder to achieve the 360-degree situational awareness a business needs in order to reduce support costs, improve service levels and achieve its desired ROI. In a Cloud Computing environment, the challenge of transaction, application and middleware message detection in real-time is much harder to do as the number of places they can be greatly expands and may constantly be in flux.

So how does one assess the benefits of business transaction management and whether or not it is yielding results in terms of optimizing business processes? ROI is calculated by a reduction in capital and operational expenditures, an avoidance of the lost revenue hidden in order fallout and customer attrition. This translates into the following benefits: fewer tickets at the service desk - reducing labor costs, improved customer experience - preserving customer loyalty, reduced disruption to business processes - maintaining profitability and compliance with service level agreements - steering clear of penalties.

Achieving these benefits enables a business to focus on using IT as it was intended for - to deliver more services to customers, grow market share and no longer spend the majority of the time and money allocated to IT on merely fixing problems in order to maintain current availability and performance levels.

In summary, with the recent worldwide recession, layoffs and cost-cutting efforts have turned the spotlight on IT infrastructure and how utilizing advancements in enterprise technology can optimize business processes. This new thought-leading approach to converging BTM with CEP and APM helps IT personnel find ways to squeeze stealth waste out of business processes by providing the full visibility prediction and performance that is necessary to reduce costs, improve service and manage risk.

About Charley Rich

Charley Rich is VP Product Management and Marketing at Nastel Technologies and has over 28 years of technical, hands-on experience working with large-scale customers to meet their application and systems management requirements. Prior to joining Nastel, Charley was Product Manager for IBM's Tivoli Application Dependency Discovery Manager software, where he co-authored an IBM Redbook, charted the product roadmap, managed an agile requirements process and was recognized for his accomplishments by winning the Tivoli General Manager's Award. Recently, Charley was granted a patent for an Application Discovery and Monitoring process.

Related Links:

www.nastel.com

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I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

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In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...