As companies strive to keep pace with and get ahead of the competition during a time of rapid, continuous digital transformation, cloud adoption is no longer a nice to have, it’s a must-have. But it’s not a straightforward process.

When choosing the right public cloud provider, you should also consider the importance of right-sizing resources against service demand to avoid service slowdowns and disruptions. Another critical factor is determining your resource requirements. You want to balance provisioning versus cost because overprovisioning can unnecessarily drive up costs and underprovisioning can risk service quality.

Without accurate insights, or an understanding of how cloud services will be used, a migration of on-premises workloads to the cloud, or a migration between cloud providers, could set you up for service failures, budget overruns, and overspending.

With the above complexities in mind where do you start?

BMC can help, with the free BMC Helix Cloud Migration Simulator. With this tool, you can reduce the time, complexity, and costs of migrating servers and workloads to the cloud and improve the accuracy of your planning process by evaluating and right-sizing your workload migration before you select a service provider. This gives you the insights you need to understand your resource requirements against the cost of maintaining your service levels—and stay within your budget.

The BMC Helix Cloud Migration Simulator allows you to compare the costs and resource requirements of leading public cloud providers like Amazon Web Services (AWS), Microsoft Azure, Google Cloud, and IBM Cloud, absolutely free.

• Increased insight: Keep budget owners, project owners, and stakeholders informed and in control of their cloud spend and budgets with self-service views.
• Actionable recommendations: Optimize cloud resources and eliminate wasted spend with artificial intelligence and machine learning (AI/ML)-driven recommendations and actions.
• Increased visibility and control: Get thresholds and alerts on spend, keep budget owners informed and in control of their cloud spend, and prevent budget overruns.
• Views of resource utilization: Create views customized for the cloud resources, budget, and spend that are important to budget owners, business owners, and stakeholders.
• Automated resource optimization: Receive automated recommendations and actions for right-sizing resources and terminating unused resources, such as idle or unused virtual machines, databases, and elastic block storage (EBS) volumes.
• Management of reserved instances: Analyze usage patterns of both reserved instances and on-demand resources to ensure efficient usage and get automated recommendations for converting on-demand instances to reserved instances to increase cost savings.

And so much more!

No Reservations is the late Anthony Bourdain’s Emmy Award-winning series chronicling his travels around the globe to explore the cities, villages, and countries that offer life’s truest surprises, without requiring reservations. However, in IT service and operations management, not having reservations could lead to negative implications that can impact service, reliability, costs, and customer satisfaction.

What are reservations and why are they important?

The ability to accurately estimate future resource requirements and align with ever changing business demand is critical for service assurance without overprovisioning, which can increase costs, or under provisioning, which can put service quality at risk. Reservations help ensure that the resources for new applications and business services are available when they’re needed, without incurring costs, until deployment.

So, what is a reservation? A reservation is a method of allocating resources at the time of the project, instead of pre-allocating resources and associated costs before they are needed. Examples of events that would require reservations are Black Friday, health insurance open enrollment periods, marketing campaigns, and product launches. Planning for these events requires input from multiple sources: marketing, sales, customer sentiment—and not just historical data.

Artificial intelligence (AI)- and machine learning (ML)-driven predictive analytics aligned with business key performance indicators (KPIs) helps enterprises identify the required resources they need to support increases in business demand due to special events or business growth. However, additional insight is required to determine how and when to allocate a given resource or set of resources for use by an event, specific workload, instance, project, user, department, or tenant for a specific period in time.

How and why reservations work

Reservations enable IT to deploy applications and services on time and understand which resources are available at the time of release. Viewing current resources—both used and available—along with future onboarded and offboarded resources, enables IT to accurately reserve resources for future needs without incurring costs ahead of time.

The more accurately and efficiently that IT departments can right-size resources with demand, the less they need to overprovision and waste resources. That also reduces the risk that services, applications, end-users, and customers will experience performance issues related to cost concerns and under provisioning. Actively aligning resources with demand also improves service while reducing both cost and risk, rather than pitting one goal against the other. This can result in significant savings without sacrificing service, workload, and application performance.

The benefit of reservation-aware resource management is that it provides detailed, projected saturation information to manage capacity based on future resource commitments. IT departments can manage resource reservations and increase future capacity by onboarding. This enables them to automatically evaluate and predict the spare capacity to optimize resources and costs while also reducing the trap of overprovisioning and underprovisioning.

To learn more about reservations and efficient resource, capacity, and cost management in today’s complex IT environments, download the e-book, “Service Assurance and Optimization with AIOps”

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One of the prevalent issues service owners, site reliability engineers (SREs), capacity planners, and cloud administrators face is how to accurately determine the cost effectiveness of migrating servers and business services that are hosted on-premises to the public cloud.

When evaluating cloud migrations, there are several factors to take into consideration to avoid negative implications, including:

• Cost of workload migration: Estimating the projected costs of moving servers and services to the public cloud versus the cost of keeping them on-premises
• Balancing cost versus risk: Determining the appropriate balance of cloud resources to stay within budgets while ensuring service assurance
• Single server versus multiple server migration: Determining the impact and cost of migrating a single server or all servers that a business service requires to the public cloud
• Forecasting resource requirements in the cloud: Managing multiple diverse, disconnected tools to analyze and forecast the capacity requirements in the cloud
• Optimizing servers to maintain service quality: Aligning cloud server resources with business services to maintain service quality and service level agreements (SLAs)
• Planning for future resource requirements: Identifying resources required to support future business demand and key performance indicators (KPIs)

If you don’t consider these potential hurdles, your cloud migrations could experience budget overruns, poor service quality, service interruptions, and slower onboarding of new services—all of which can affect profitability, customer loyalty and satisfaction, and competitive positioning in the market.

The good news is you can use “what if” simulations to estimate the costs of migrating workloads quickly and accurately to the cloud and aligning resources with business demand. “What if” migration simulations evaluate the opportunity and cost effectiveness of migrating on-premises infrastructure to the cloud and deliver right-sized recommendations to help reduce cloud cost and budget overruns and ensure service assurance. The “what if” simulation results enable you to:

• Quickly determine the projected cost of using the public cloud versus the cost of your on-premises infrastructure
• Have the flexibility to simulate the migration of selected servers or all servers that a business service uses
• View optimized recommendations for instance sizes and other associated characteristics on the public cloud
• Modify characteristics and evaluate the impact of the change on the overall migration cost
• Accurately compare costs of migrations between cloud service providers including Amazon Web Services, Microsoft Azure, Google Cloud, and IBM Cloud

To Learn More

Check out the following resources to understand effective strategies for accurately sizing and migrating on-premises resources to cloud.

• Service Assurance and Optimization with AIOps (e-book)
• IDG: Meeting the Challenges of Optimizing IT Cost and Capacity Management (whitepaper)
• BMC Helix Continuous Optimization (datasheet)
• It’s Time to Shift from Capacity Optimization to Resource and Cost Optimization (blog)

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Today’s enterprises are adopting new technology resources such as Kubernetes, containers, and Pods at a rapid pace to deliver modern applications and service assurance; onboard new workloads; and keep pace with business demand. However, Kubernetes administrators, service owners, and site reliability engineers (SREs) face challenges with right-sizing deployments to meet service level agreements (SLAs) and control costs against increasingly tight budgets. How do you analyze existing capacity, identify potential risks and bottlenecks, and accurately predict the resources required to support future changes in business demand? Where do you start?

Visualize resources you have to meet business and customer expectations

Do you have the right resources to satisfy business and customer expectations? Without insights into risk, efficiency, and cost, delivering quality services that meet your SLAs could be a challenge.

BMC Helix Continuous Optimization provides Kubernetes administrators, service owners, and SREs with the insights to understand the overall health and status of business services and gain visibility across all current enterprise resources to help maximize their performance, availability, and service. It also helps quickly identify overallocated Pods and containers, while automating optimizations to reduce service slowdowns and deliver service assurance.

Optimize existing infrastructure resources to meet business key performance indicators (KPIs) and SLAs

One of the primary challenges is determining how to make the most of the investments that run your business today.

BMC Helix Continuous Optimization provides artificial intelligence (AI), predictive analytics, machine learning (ML), and automation to help you dynamically optimize modern application resources based on Kubernetes, microservices, containers, and Pods. Predictive insight and recommendations for prescriptive actions can help you increase efficiency and lower costs.

AI- and ML-automated recommendations are based on historical resource use data, providing insight into unused or underutilized resources that can be terminated or reclaimed. Predictive saturation alerts and notifications help you adjust and optimize resource configurations to increase performance and efficiency while resolving resource constraints to prevent business service disruption.

Accurately plan to support changes in business demand

increasingly complex IT service and operations management (ITSM/ITOM) environments make it difficult to accurately predict and align resources to support business demand and innovation.

BMC’s Helix Continuous Optimization makes it easy to run “what if” simulations and reports to accurately predict resource requirements with before and after usage models. “What if” modeling provides insights into the best resource configurations, location, and cost so you can make informed decisions and prevent application performance slowdowns or failures.

To learn more about aligning Kubernetes resources to support business demand and innovation download the e-book, Service Assurance and Optimization with AIOps

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In today’s complex business environment, organizations are striving to accelerate innovation with increased business agility, improved customer service, reduced capital and operating expenditures (CapEx/OpEx), and faster return on investment (ROI), all while contributing to growth and profitability. Capacity optimization isn’t getting it done anymore. It’s time to shift our thinking to resource and cost optimization.

Until recently, enterprises relied on capacity planning and optimization to align IT resources with changing business demand and ensure service level agreements (SLAs) for critical business services. However, as organizations adopt new technologies to deliver scalable services faster and more reliably, simply focusing on capacity optimization alone will not deliver the positive business outcomes IT decision makers seek. Why?

The emergence of new technologies such as multi-cloud, hybrid cloud, and legacy on-premises infrastructure, along with the increased deployment of applications based on Kubernetes, micro-services, containers, and Pods, have dramatically increased IT complexity. The result? IT is attempting to manage complex environments with multiple, disconnected tools that make it difficult to:

• View and understand the resources, usage, and costs of supporting applications and business services
• Identify dependencies between resources and the impact of changes to the infrastructure
• Accurately predict capacity and scale IT services to meet business demand
• Manage growing infrastructure complexity—the combination of on-premises and cloud-based capacity and cost management solutions and the transition to modern technologies (Kubernetes, containers, Pods, etc.) from legacy technologies

Having a toolset that’s loaded with disconnected tools is clearly not the answer, and it can also increase costs and degrade business service performance. A better alternative is to shift to comprehensive solutions that deliver deeper, artificial intelligence and machine learning (AI/ML)-enabled insights to help balance risk, efficiency, and cost. Organizations need a way to see resource usage and demand across the entire infrastructure to continuously optimize resources to deliver service and operational excellence that exceeds customer expectations, minimizes risk, and reduces capital and operational spend.

By doing so, they can:

• Achieve greater productivity and efficiency while reducing risk around migrations and strategic company initiatives
• Improve clarity into capital and operational costs and vendor billing
• Make the business more agile
• Plan and position for the future with more accurate IT forecasts

To learn more about the shift from capacity optimization to resource and cost optimization and how it could benefit your organization, download the e-book, Service Assurance and Optimization with AIOps.

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How are IT decision makers balancing risk versus cost using capacity optimization? Honestly, it’s a highwire act that jeopardizes service quality and budgets if not handled properly.

Today’s increasingly complex IT environments are making it more difficult for leaders to continuously optimize IT resources and costs to ensure optimal business service assurance, get a clear view across the entire IT infrastructure, and manage the transition of legacy technologies to modern technologies.

With these challenges, IT is forced to choose between overprovisioning by purchasing infrastructure such as servers and storage to ensure service quality or underprovisioning to save money. This is something BMC product manager Dennis Newberry addressed in a recent IDG white paper, Meeting the Challenges of Optimizing IT Cost and Capacity Management.

“How do you manage that balance? I can increase my costs and lower my risk by overprovisioning my environment, so I’ll never have a performance-related outage,” he said. “Conversely, if I want to reduce costs, I could run the potential of having a performance-related issue. So ultimately you’re trying to find the right balance and then maintain that balance.”

How do you achieve and maintain the correct balance between overprovisioning and underprovisioning? You need a way to accurately see the resource usage and demand across your entire infrastructure to ensure you can support your applications, users, and business strategy with high service quality and responsiveness.

Enterprises using artificial intelligence (AI) and machine learning (ML) tools to increase visibility and support business demand will be able to continuously optimize their resources by rightsizing, maximizing allocation and efficiency, predicting saturation, and matching business initiatives with “what if” simulations and service level agreements based on intelligent analysis of service performance—all without manual intervention.

Increased visibility also helps IT teams:

• Improve IT and end-user productivity and efficiency
• Reduce risk around migrations and strategic company initiatives
• Achieve better clarity into capital and operational costs and vendor billing
• Make the business more agile
• Plan and position for the future with more accurate forecasting

To learn more about effectively balancing cost versus risk with capacity optimization solutions, download the e-book, Service Assurance and Optimization with AIOps.

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IT decision makers (ITDMs) face several challenges managing IT capacity and cost in today’s increasingly complex IT service and operations management (ITSM/ITOM) environments. In fact, 86 percent readily admit in a recent IDG survey that they find it “very challenging” or “extremely challenging” to optimize their IT resources to adequately meet changing business demands. Top challenges include:

• An inability to scale IT services as needed
• Difficulty predicting capacity requirements
• Lack of visibility into resource usage and cost
• Managing the growing infrastructure complexity of on-premises and cloud-based capacity and cost management solutions
• Organizational disruption due to new ways of doing business, i.e., the surge of remote workers due to the pandemic
• Managing the transition to modern technologies—Kubernetes, containers, Pods and so on—from legacy technologies

These difficulties become even more concerning when one considers the continued emphasis on “doing more with less” due to shrinking ITSM/ITOM budgets. Additional complications include managing the exponentially growing volume of data and number of applications, device types, and users—along with user expectations.

So, how are leading IT decision makers finding a balance and meeting those emerging requirements while maximizing the efficiency of expensive resources?

The short answer is they are using software solutions that increase the visibility of resources across the enterprise—physical, virtual, container, Pods, Kubernetes, and cloud infrastructure—to help identify the resources they have and the dependencies and relationships between them. Greater visibility also provides comprehensive views into how changing business requirements impact the IT resources needed to maintain service levels, capacity requirements, budgets, and costs.

With today’s discovery and optimization tools, IT decision makers can gain deeper insight into resource demand and usage. Modern discovery and optimization tools also help them better predict, plan, deploy, and right-size IT resources leveraging artificial intelligence (AI) and machine learning (ML) recommendations to accurately align IT resources with emerging business requirements.

According to the IDG survey, ITDMs can yield a number of benefits, including:

• A reduction in budget overruns by leveraging AI- and ML-driven analytics for resource and cost optimization
• Reduced slowdowns, service outages, and risk, with a deeper understanding of the overall health of business services, through comprehensive views and predictive saturation forecasting
• Increased alignment of resources with business requirements using advanced analytics and forecasts for actionable insights that help ensure service quality
• Improved accuracy when determining the impact of legacy workload migrations to the cloud, and placement of containerized workloads using “what if” simulations

To learn more about efficient resource, capacity, and cost management in today’s complex IT environments, download the e-book, “Service Assurance and Optimization with AIOps.”

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The future of service and operations management is here now and is crucial to control the chaos of hybrid IT. Innovations in service and operations management are emerging as an imperative from the service desk to the boardroom for enterprises to achieve faster time-to-market; increase productivity, efficiency, and quality of service. In a landscape that seems to evolve on a daily basis, successful digital leaders know that aligning IT service and operations management is the key to growing at the scale required to compete and thrive. Industry leading enterprises are embracing this convergence to drive a service experience that delivers service delivery excellence, empowers line-of-business users, and increases business agility.

Instead of treating each as silos, there are immediate benefits realized with a converged end-to-end service and operations management system:

• Faster time-to-market for delivery of quality, differentiating, services
• Faster resolution of service issues and operational events to increase service quality
• Increased IT staff efficiency enabling focus on strategic initiatives
• Automated resolution of routine issues freeing up service desks to focus on issues that impact productivity & efficiency
• Reduced risk of security vulnerabilities
• Increased business agility
• Reduced CapEx

Not only does integration break down silos, it helps you connect the dots across your ecosystem turning your unknowns into knowns. Let’s explore how you can take advantage of these benefits by first understanding best practices and critical capabilities required as you evaluate adopting a converged ITSM / ITOM environment.

Industry leading service and operations management tools should:

• Integrate and automate all key processes including incident, problem, change, release and SLA management to uncover events, alerts and anomalies in real time.
• Apply AI and machine learning across operations management (AIOps), service management and user environments to accelerate resolution of requests and trouble tickets, as well as automated event remediation.
• Provide a flexible and streamlined user experience for self-service and request fulfillment.
• Support non-IT business use cases such as finance and CRM.
• Understand infrastructure trends and adjust automation to match.
• Enable scalability beyond the data center.
• Deliver seamless operational support of enterprise services across multi-cloud environments.
• Increase visibility and control with end-to-end integration of data, management tools and platforms including service and operational dependencies, performance and utilization.
• Reduce risk and cost through intelligent control of services and infrastructure.
• Provide a unified view of cost and performance metrics for all service delivery and IT operations to ensure cost-effective and efficient use of resources.

Learn more about how your enterprise can leverage convergence of service and operations management to increase service efficiency, quality, speed and business agility while reducing costs. The Future of Service and Operations Management: A Buyer’s Guide to learn:

• For IT operations managers, it’s meeting strategic goals for service delivery excellence through automated tools and information that reduce manual workload and use human intervention where it adds the most value rather than responding to alerts and requests.
• For line-of-business users, it’s access to the services and information they need to help themselves, quickly and simply. The right action at the right time, with the least friction, through powerful user portals, intelligent automation and easy-to-use service catalogs.
• For the enterprise as a whole, it’s enhancing the ability to empower users across the organization through digital transformation that’s powerful, efficient and effective.

For today’s enterprises, the time for pursuing digital transformation is now, if not yesterday. As they facilitate digital transformation for their businesses, IT operations teams will either be bolstered by strong IT process automation (ITPA)—or very much hindered by the lack thereof. In this post, we examine why ITPA is so integral to successful digital transformation, and we look at the key requirements that ITPA platforms must meet if they’re to fully support digital transformation initiatives.

Introduction: The Digital Transformation Imperative

For organizations in virtually any industry, digital transformation is a competitive imperative. Today, it falls to IT operations teams to make it happen. In many respects, the IT operations team’s ability to support digital transformation will play an increasingly central role in whether the business achieves its long-term goals and objectives.

However, while pursuing digital transformation is vital, it’s also ramping up the challenges. As digital transformation is pursued, IT teams are being forced to contend with these mounting demands:

• Increasing scale. Within most organizations, teams must support increasing volumes of users, applications, transactions, data volumes, and more.
• Increasing complexity. Compared to just a few years ago, operations teams have to manage far more complex environments, including a broader range of endpoints, a more diverse mix of application architectures, and an increasingly hybrid mix of on-premises environments, private clouds, and public clouds
• Increasing pace of change. To support digital transformation, teams need to accelerate the pace of innovation and new service delivery. At the same time, they have to keep pace with increasingly dynamic modern environments, including software-defined infrastructures, microservices, agile and DevOps approaches, and more—which all serve to dramatically speed the rate of change.

The Challenge: Labor-intensive Workflows a Massive Obstacle on the Digital Transformation Journey

As teams seek to pursue digital transformation and address the associated escalation in demands, they’re finding it tough sledding. That’s because, for too many organizations, automation has been employed in a limited, tactical fashion. As a result, teams continue to be mired in laborious, repetitive, and error-prone workflows. This leaves the organization exposed to spiraling costs, operational inefficiency, and increased risks of outages, breaches, and non-compliance. Ultimately, many organizations aren’t as far along in their digital transformation journeys as they need to be—and the competitive consequences of this reality can be dire.

Automation that Enables Digital Transformation: Key ITPA Platform Requirements

Quite simply, strategically implemented ITPA is a foundational requirement if teams are to meet their digital transformation objectives. As teams embark on their digital transformation journeys, having the right ITPA tools will be essential. To pursue their transformation initiatives, teams should look for platforms that offer the following advanced features:

Rich, Pre-packaged Samples and Templates

Given the urgency of digital transformation, teams need tools that can help them move quickly. Solutions that come pre-packaged with templates, samples, workflows, and more can therefore be invaluable. These resources help teams avoid having to reinvent wheel, which is vital to speeding implementations and time to value.

Broad, Flexible Integration

To deliver the highest strategic value to digital transformation initiatives, organizations need automation that can span technical and organizational silos. The Gartner report, “Market Guide for IT Process Automation,” advises that IT leaders should “Maximize automation investments by selecting ITPA tools that can orchestrate workflow execution across functional requirements, groups and management tools.” To address these requirements, solutions should offer pre-configured, automated integrations with a wide array of technologies and systems—including servers, applications, devices, and operations tools.

Artificial Intelligence and Machine Learning

For automation to deliver maximum support of digital transformation over the long term, teams need to harness ITPA platforms that offer extensive AIOps capabilities, including automation, artificial intelligence, and machine learning. My colleague, Monica Brink recently wrote a post that outlined how this combination yields significant dividends, such as enabling teams to realize up to 75% improvements in mean-time-to-resolution metrics.

It is only by leveraging these powerful capabilities that teams can begin to keep pace with massive volumes of operational data, and establish more complex automation in increasingly dynamic environments.

Conclusion

For some time, IT teams have been hampered by laborious, error-prone manual efforts. Now, these kinds of efforts will seriously jeopardize an organization’s chances at pursuing digital transformation. ITPA is now essential for teams looking to support digital transformation, and the right tools can significantly advance this cause. In addition, please register for our upcoming webinar, “Automated Operations for Proactive Event Remediation.”

Automation and process orchestration can deliver significant benefits, but many organizations are stymied in their efforts to capitalize on these opportunities. Why? First, many teams struggle with the complexity of integrating legacy technologies and cloud-native infrastructures, applications, and services. In addition, Gartner’s “Market Guide for IT Process Automation” outlines a couple additional factors that are limiting the potential gains:

• Limited vision: “Adoption of IT process automation (ITPA) tools continues to be slow because many infrastructure and operations (I&O) organizations continue to opportunistically automate with limited strategic vision.”
• Limited scope: “Organizations that are maturing beyond I&O task automation are focusing on narrow bands of service automation such as cloud management and DevOps, rather than starting with general ITPA and orchestration.”

As a result, it’s all too common for enterprises’ highly skilled workers to be stuck with mundane, time-consuming, and repetitive tasks. Too often, teams have to manually create and track incident tickets. From event triage through to remediation, teams struggle with undocumented, non-standardized processes.

These realities leave organizations exposed to lengthy resolution times, increased risk of errors, high IT support costs, and staff inefficiency. Ultimately, skilled employees spend too much time on administrative tasks and too little time on the strategic projects that generate business value. Further, IT teams increasingly struggle to effectively support the new business models and innovative applications that boost business agility and competitive differentiation.

How can IT teams overcome these obstacles and free skilled employees from mundane, repetitive tasks and processes? By employing event-driven IT process automation, organizations can automate common, frequently occurring IT tasks and workflows. Through this automation, teams can offload labor-intensive efforts and reduce the costs, errors, and risks associated with these efforts.

By harnessing automation and orchestration, enterprises can redeploy their skilled resources and enable teams to focus on pursuing strategic, value-added initiatives that yield such benefits as increased business agility, faster time to market, deeper insights, and enhanced client engagement. Process automation enables IT teams to improve their operational efficiency and respond more quickly to strategic business demands. IT process automation enables teams to gain the following advantages:

• Reduce the time team members spend on recurring, high-volume, low-impact activities, freeing resources to focus on critical business initiatives.
• Automate every stage of incident management, reducing mean time to resolution.
• Establish standardized event resolution processes that increase predictability, consistency, operational efficiency, and speed.
• Minimize the manual efforts needed to resolve incidents, resulting in reduced costs.

Transamerica Life Insurance Company is an example of an enterprise that has embraced IT process automation. Through its automation efforts, the company has improved the utilization of its skilled IT resources and reduced repetitive administrative work.

By leveraging integrated automation and orchestration solutions, IT teams can achieve increased efficiency, responsiveness, and productivity. As a result, they can realize improved business agility, reduced operational costs, and minimized risks of non-compliance. Following are some of the most common, high-value IT process automation and orchestration use cases:

• Event-driven IT automation. IT teams can automate the resolution of recurring events that have standard remediation processes. Organizations have automated the entire process, from incident response to proactive problem management. Enterprises that have adopted orchestration for event-driven IT automation may speed mean time to resolution by up to 90% and reduce operating expenses by up to 50%.
• Closed-loop change and configuration management. This use case enables organizations to reduce labor costs and errors by automating process compliance. Through this approach, enterprises can ensure speed and compliance in their change and configuration processes, bolstering efficiency and security.
• Service desk automation. This use case focuses on automating the fulfillment of common IT requests and processes for end users. Teams can automate such efforts as new hire on-boarding, password resets, and service provisioning. Through orchestration, organizations can realize a number of benefits, including increased efficiency and productivity, enhanced responsiveness, and faster resolution, which can help improve end-user satisfaction.

To learn more about how IT process automation can free your skilled workers from mundane administrative tasks, while enabling improved operational efficiency, reduced costs, and accelerated business innovation, please visit the TrueSight Orchestration page.