Control-M SaaS Starter Pack

Control-M has many use cases with four or five very critical use cases within Bupa. The first is to manage the payment gateway and payment domain. The second is to manage the integration of end-to-end file transfer with many different critical Bupa partners because it is very critical to maintain seamless file transfer for them. Control-M uses this in a very extensive way. The third one is to obviously manage Control-M in such a way that it is up and ready for all the customers who are using Control-M. We have some end users, such as service desk who use many different applications including add user, modify user, and many other functions. All these are automated by Control-M with no human interaction. We are trying to do agent-based automation as well with Control-M, but that is something for the future.

The primary use cases are very different and vary from day to day. One of the most critical use cases is manage file transfer, which basically allows Bupa to connect and interact with various partners and vendors who are sitting outside Bupa. Everything is governed by security, but it reduces the manual effort, allowing us to automate everything, so basically no human interaction is required when it comes to sending or receiving very critical information files from different vendors. Other critical use cases include payment gateway and payment file transfer, which allows Bupa to talk with different payment providers. The whole workflow is automated and orchestrated by Control-M.

For Kubernetes, we have not explored that part yet. However, we are moving towards Kubernetes-related deployments in Control-M. We are open to exploring that in the future.

We do use cloud-native workflows with traditional batch processing. For example, the main system of Bupa, including payment and claims systems, is still running on-premise. We have many integrations moving data and information from the cloud to different environments, specifically payment providers or third-party providers.

We are not currently using Control-M to support AI or ML workloads, but we plan to. We have a dashboard feature that utilizes our own created AI which leverages Control-M automation API to provide job failure notifications. We look forward to using Control-M's workflow creation magic or JetAI whenever we transition to SaaS. Currently, we are still on-premise, but we are looking to move to a SaaS version very soon.

There are many benefits to using Control-M. As I mentioned before, the main use case is file transfer. Control-M allows businesses to send many information items to third parties with whom Bupa has contractual agreements. However, due to security reasons, these tasks cannot be done via email or any other means when the volume is large or when manual effort is required. Control-M seamlessly automates these processes and orchestrates every file transfer with a very high level of encryption, offering a secure platform.

I estimate that we have sped up our processing via Control-M by about 80%. For example, consider a business user who is making numerous changes in a sensitive Excel sheet or CSV. They may contemplate emailing or placing it in a shared drive, but what about security? The security is nowhere; there is no encryption, no PGP encryption, nothing. Control-M can easily handle this task, ensuring security and encryption, which is very much needed in our organization, especially one dealing with many sensitive information items.

The features of Control-M that I appreciate the most include the managed file transfer protocol, which Control-M comes with as a native feature. What we basically do with managed file transfer is that Bupa has many different very critical partners sitting outside Bupa, and it is very difficult to maintain the file transfer or maintain the communication in a manual way. Control-M seamlessly automates everything from Bupa to the partners and vice versa.

Control-M can easily integrate with a cloud environment. For example, we have a Microsoft Azure-based platform. We have different containers inside Azure and have a business requirement that an upstream process creates some data flow into a container, into a blob directory. We need to log into the blob directory, send the file, encrypt the file, and send it to a different business owner. Control-M can easily automate that because it has seamless integration with Azure Cloud, including service principals, allowing us to orchestrate that flow with very minimum effort.

Control-M is already operating at a very advanced level when it comes to communication between cloud-native and batch processing. The main focus is on easier connection. Control-M, with service principal access or CyberArk-related access, can easily provide different authentication methods to connect to the cloud. This makes my job as an integration engineer much easier, as a seamless connection allows us to execute many tasks effectively, making the whole organization operate in a faster environment.

Control-M has various methods for addressing compliance requirements. What we use extensively for auditing is Control-M reports. We have an external reporting vendor, and for auditing purposes, we need to comply with their requirements every six months. They come back with numerous questions, and with Control-M's reporting feature, it is so easy to generate the report and provide all critical failures and changes that happen within Control-M planning domain or Control-M database. Control-M reports is the go-to platform for us for any audit or security review.

Control-M is doing enough to keep up with modern technologies. However, there is always room for improvement in every tool. If Control-M can integrate more seamlessly with AI, which was announced at the BMC roadshow, particularly in the on-premise version, that could be a significant enhancement.

My name is Soparna Chatterjee. I work as a Control-M integration engineer and Control-M lead in Bupa. Bupa is the largest private health insurance provider in Australia. I have been working in association with Control-M for the last 12 years. I manage a team of two people who work extensively on Control-M. We use many very critical integrations in Bupa, and I look forward to sharing my experience.

I would assess the reliability of Control-M as very robust. Control-M has a three-layer architecture, with Control-M server at its core, which is very reliable. We do not see any downtime apart from during upgrades. Our current infrastructure is managed entirely by us, so I am not counting infrastructure-level downtime for Control-M, but as a tool, Control-M remains quite robust and reliable. We have provided many end users, including business users, with access to load their own jobs and execute functions with very few complaints, mostly limited to technical issues from the code perspective rather than the platform itself.

Control-M scales up really well. For example, within our technology team, we focus on integration, working on Azure integration, AWS integration, and a range of technical capabilities. With the growing demand for Azure integration, I believe Control-M can adapt well, especially since we use a data factory model. Control-M now has out-of-the-box job types that simplify orchestration, allowing leaders to be aware of minimal downtime as we transition to Control-M, thereby enhancing the platform's reliability.

I utilize BMC support as my go-to guide. We run a critical business, particularly concerning payments orchestrated inside Control-M. If any issues arise, I raise a critical ticket with BMC support, and someone calls immediately. Just yesterday, we experienced this; support reached out promptly and we began troubleshooting the issue via a Teams call. I find that the intelligence level and technical expertise of BMC engineers are exceptional, which aligns well with our platform.

I have been part of Bupa for eight years, and I believe Control-M was onboarded around 14 years back. Since then, there has been no looking back.

As for realizing a return on our investment, I can provide an example involving our Control-M and ServiceNow integration. ServiceNow is the ITSM platform used for generating various priority tickets. With Control-M, we manage many critical jobs, and if one fails, it can immediately escalate to a priority one incident, requiring the technology team to resolve it without leaving the room. This can be quite hectic, but with Control-M and ServiceNow integration, critical failures generate real-time incidents by calling ServiceNow API. Moreover, the L1 monitoring team can see alerts easily. Consequently, our SLA response time has significantly reduced; for instance, if the L1 team has a 50-minute SLA for a response, they can now respond within five minutes.

We evaluated similar solutions. We ran a few POCs with other orchestration provider tools, but Control-M consistently proved superior, particularly as an enterprise-level solution offering comprehensive integration with tools such as ServiceNow and various APIs.

We evaluated several different tools, including JAMS Scheduler and Apache Airflow. What we noticed is that while they offer orchestration capabilities, Control-M stands out due to its criticality and user-friendly GUI features. Additionally, when comparing costs, Control-M offers a competitive price for the services provided along with the package, especially as Control-M continuously evolves towards modern technologies.

I would rate Control-M very high on a scale of 10. This is not just an emotional connection developed over 12 years, but also due to the advanced technology Control-M is implementing, including new AI, data orchestration, security standards, and governance perspectives. Control-M is innovating rapidly with technology. I would rate Control-M as nine out of ten, leaving one point for improvement, as I believe every software has some scope for enhancement. I wish the whole Control-M team all the best. They are moving very fast towards advanced technologies, and I fully support their efforts as we look forward to utilizing all the features. My overall rating for Control-M is nine out of ten.

Our primary use case for Control-M at UniSuper is workload automation and orchestration, which involves different business processes such as getting a file from a third party, extracting some data from that file, and finally uploading that file to the database.

In this way, the primary use case is managing the workload and being a central point of scheduling in UniSuper.

Currently, our usage of cloud environments is very limited, as we are migrating Control-M from an on-premises environment to a SaaS environment.

After we migrate to SaaS, we will be more focused on utilizing cloud integration or cloud-based features.

Control-M is playing a major role in UniSuper for integrating with different applications.

We have integrated Control-M with CyberArk for security purposes, ensuring that all passwords are stored securely and retrieved automatically rather than being copied as plain text.

We are also in the process of integrating Control-M with Azure Key Vault to securely manage connection profiles for transferring files to Azure Blob storage, which is a best practice.

In the future, we are planning to integrate Control-M with AI and ML workloads, utilizing AI features mainly for workload automation, such as using the inbuilt AI agent, Jet, to create jobs, dependencies, and workflows.

Control-M plays a very critical role in UniSuper's compliance, especially with PayDay Super coming in Australia by July 2026.

Control-M is essential for processing employer contributions from third parties and ensuring timely responses under the SLA.

Some benefits which we have seen by using Control-M is that it serves as a central point of scheduling in UniSuper.

Previously, I saw different applications running jobs individually, with dependencies on other applications.

If a job inside a particular application failed, the other application SME had to check the issue.

After bringing in Control-M, it has become centralized, meaning if a first job for X application fails, the second job will not run, and we will know why it has not run, allowing us to easily identify and fix the reason for the failure.

Personally speaking, I value the Managed File Transfer functionality of Control-M the most because we have been using it vastly in our organization, as we receive a lot of files from third parties, process them, and send back the files to the third parties.

Apart from that, we also run OS jobs, which are basically running some commands and running scripts on Control-M.

Control-M is a well-maintained platform, but one improvement I can suggest pertains to the administrative part.

As we are migrating Control-M from on-premises to SaaS, easier methods for migrating all components such as calendars and connection profiles would be beneficial.

I have been using Control-M for five years.

Control-M has great reliability and stability.

After we move to SaaS, we will experience zero downtime during upgrades, facilitating continuous workflow operations, which is a significant improvement over on-premises environments.

In 2025, 50% of people at UniSuper were not aware of what Control-M is beyond being a scheduler.

After increasing visibility and scaling by 20% in the number of jobs created over a year, we believe moving to SaaS will enhance our use of Control-M features.

I have worked with BMC Support, and I would rate their support nine out of ten.

They help us resolve issues quickly, and their documentation is self-explanatory, often allowing us to solve problems without direct support.

From an operational perspective, there is a huge benefit and vast increase since we brought Control-M into the picture, centralizing all individual scheduled jobs that were previously managed by different applications.

For operational purposes, having a centralized point of monitoring and scheduling is very important.

If one job fails for a certain application, a centralized point allows us to easily identify which job has failed, its related application, and what the issue is.

Control-M serves as a central point for workload automation and orchestration, aiding in the creation and monitoring of business workflows.

The only improvement I see is the need for better migration methods.

I rate Control-M nine out of ten.

Control-M is primarily used for process automation in our organization.

We have not utilized the policy, approval, or risk-gating capabilities within our automated workflows, and these features do not influence how our business operates.

Control-M does not contribute to our governance requirements, such as workflow audit trails or lineage tracking.

We have SAP working with Control-M, including SAP S/4HANA and BW.

We currently do not utilize specific functionalities within Control-M for compliance trail generation or regulatory reporting.

Integrating Control-M with our ITSM or change management tools like ServiceNow is in the pipeline but has not yet been completed.

Control-M definitely supports our DataOps and DevOps initiatives.

Control-M helps free up our IT staff to focus on essential operations, which is definitely the end goal eventually.

Control-M has freed up approximately 30 to 40% of our time.

Control-M definitely helps consolidate our job scheduler tools.

In my opinion, the best features in Control-M are the options it provides.

The workflow is the most valuable aspect.

With Control-M, I think it is mostly possible to integrate AI or machine learning workloads in the cloud version, the SaaS model. Currently, we have not utilized this capability in the on-premises version.

I think the integration with SAP is seamless and comfortable to use.

Overall, Control-M integrates seamlessly with our DataOps and DevOps stack, with no challenges.

I think Control-M is fine as it is and is one of the best tools from my perspective so far, and I do not have any specific suggestions for improvement.

We have struggled a bit using Control-M's Python client or APIs in terms of getting integrations completed with some systems, and that is where support could have been a bit better. We do tend to get that support eventually, but sometimes we have to wait for US hours to open up.

I have been working with Control-M for approximately three years.

I rate the stability of Control-M a perfect 10 out of 10.

Approximately 100 users use the solution.

I rate the scalability of Control-M a perfect 10 out of 10.

I think the technical support is mostly available in the US time zone, which is where we struggle a bit. If we had a contact for support in India or Asia, I think that would have been much better, and we feel it is an opportunity.

I rate the technical support an eight.

I have only used Control-M so far, so I cannot compare it with other solutions such as IBM, ActiveBatch, or Stonebranch.

The on-premises deployment for Control-M is easy.

It takes about a day in general, depending on how many systems you want to connect to, as our updates and other tasks are quite easy.

It is easy to maintain Control-M.

I do maintenance monthly.

Control-M has definitely saved us time, money, and resources by allowing a lot of automations that save the time and effort needed to do it manually, so there is definitely a lot of ROI on that.

We have seen approximately a 70% return on investment.

Regarding pricing, I rate it an eight for now, with one being cheap and ten being expensive.

I think a proof of concept is necessary for every tool that any organization wants to adopt. It is best to look at ROI or total cost of ownership, whether you want to go for an on-premises model or a SaaS model, and then make that rightful decision. I rate Control-M a 9 out of 10.

The main use cases in Control-M for VicRoads involve moving from the old infrastructure to the new infrastructure. VicRoads previously operated on mainframe systems and went through a transformation to modernize the mainframe, which is where Control-M came into the picture. The organization was using an old product called CA 7, and it has been migrated to Control-M. The mainframe itself has been migrated to AWS on Linux. Control-M is primarily used for processing all data overnight, around 800 jobs, of which 500 are critical, making it important for operations.

Currently, AI is not being used in Control-M, but the organization is planning to use AI in the future through Jet in Control-M. From research, Jet is already included in the SaaS version, but VicRoads is running a standalone version that requires additional configuration. The organization has identified that Jet could be utilized going forward, with some configuration required. Enabling Jet would be the first step to using AI in Control-M, which would help not only from a creating perspective but also provide insights about the schedule and assist in managing the batch.

In terms of integrating Kubernetes or cloud-native workflows with traditional batch processing, Control-M plays a role as the organization is in the process of identifying what else is running outside Control-M. There could be a cloud-based scheduler, a bot-based scheduler, or an RPA-based scheduler. Control-M has different connectors that could be used going forward. The organization is gathering information from VicRoads to identify which other schedulers can be taken into consideration, and a plan will be created to move those into Control-M eventually. The goal is to see everything in Control-M as a one point of orchestration. Control-M has many features and connectors that can connect to existing legacy or systems running schedules, such as CloudWatch or JAMS, which is another scheduler. RPA can also be migrated to Control-M, and Control-M assists in this integration.

The current organization has realized many benefits since implementing Control-M, including significant cost savings in the sense that the amount of work required to achieve something has been reduced because the number of processes required to define has reduced significantly compared to the old system. In terms of hiring extra people, that has also been reduced because Control-M allows fewer people to manage complex systems. The old system required involving more people because of more complexity and more manual tasks to be completed. Control-M is also quicker than the old system in terms of efficiency.

Estimating in terms of percentages, at least 20 percent more efficient has been achieved in terms of cost savings. Approximately 50 percent time saving has been realized. About 50 percent reduction in labor required has also been achieved.

The main feature of Control-M is the interface itself, which is quite easy to navigate. When managing thousands of automation programs, the layout in Control-M makes navigation really easy. A tree view, network view, and flow diagram are available for different perspectives. The second most important feature is the viewpoint that helps identify the critical path of the whole process. Multiple tools in Control-M can map out the critical path easily, allowing identification of the most critical jobs needed to get from one point to another. Control-M can isolate everything else and show a filtered view so focus can be placed on the critical path. The third most important feature is reliability. Control-M works as designed approximately 99 percent of the time. The time feature also allows going back in time to see what happened, which enables pinpointing where problems occurred.

The importance of the first two features mentioned is because they make navigation easier. Control-M visualizes from point A to point B on the screen similar to how Google Maps shows routes, providing easy navigation so users understand what to do next and where to look to find problems easily. The user-friendly interface makes work easier.

In terms of managing the integration and sequencing of data processing across diverse data platforms and cloud environments via Control-M, File Watcher is used, which is an innovative feature of Control-M. File Watcher makes work easier because multiple parameters can be defined to determine whether the file or data has been received. Multiple things can be done around it and customization can be completed per requirements. As soon as something is managed by File Watcher, it has the ability to pass on to the next process. The organization has been using File Watcher at VicRoads, and it is working well and is quite stable.

In terms of compliance requirements such as SOX, audit trails, or regulatory reporting, Control-M plays a significant role. The main feature used from Control-M is Control-M reports, which is a built-in feature, and any report can be pulled out as needed. Actions can be tracked to see what was done during the time, and logs can be pulled out from Control-M to help with auditing. If any changes were made to the schedule, the version history feature of Control-M can be used to track changes and determine what went wrong or what happened in the past at specific times of the day or year.

There is always room for improvement. The web interface of Control-M needs improvement. When comparing the web interface versus the desktop interface, the web interface lacks many things that the desktop interface has. If Control-M and BMC could examine the desktop version of Control-M versus the web application and attempt to match those things, that would be a significant achievement.

Control-M has been used since 2008, totaling 18 years of working with this product. Each time working with this product, it feels like a perfect match in terms of how things should work and personal interests, which are all part of the role and the product.

In terms of stability and reliability of Control-M, it is at approximately 99 percent reliability. Control-M has hardly ever crashed, and most of the time if there is a problem, it comes down to either the system, a network issue, or some other issue not related to Control-M in most cases. Control-M uptime is more than 99 percent, making it highly reliable. In terms of stability, Control-M is on a quite high scale. The architecture of Control-M is designed to be most stable because it has three different components: the enterprise manager, the server, and the agent. Due to this design, it functions as a fail-safe where if one thing goes down, it does not affect the other thing. There is hardly a situation where all three things would go down, making Control-M pretty stable by design.

Control-M scales quite well with the growing needs of the organization. When working with Coles, 15,000 jobs were running at one point. At ANZ, the team had 8,000 jobs, but the overall ANZ organization had a total number of jobs of approximately half a million. In terms of scalability, Control-M is enterprise-level. That is the reason most Fortune 500 companies have adapted Control-M as an automation tool. Control-M is definitely scalable and improving every day, with each new version containing many features.

Although not directly looking at the accounting side of things in Control-M, from what is known, it has paid off in terms of career development and inclination towards Control-M. There is always more inclination towards Control-M because all repetitive tasks can be automated and Control-M is one of the best tools that has been worked with. Control-M is the only tool that has so far matched expectations or actually exceeded expectations in terms of automation. From that perspective, it has definitely rewarded in terms of career investment into Control-M.

I would rate Control-M at nine out of ten on a scale of one to ten. Nothing is perfect in this world, and there is always room for improvement. The web interface definitely needs improvement, and there may be other areas like a Batch Impact Manager that need improvement as well. In terms of reliability and user experience, Control-M is ten out of ten, but in terms of the overall product, it is nine out of ten because it has room for improvement.