Tag: service management

  • DevOps and ITIL Integration: Driving Collaborative Agility in ITSM

    DevOps and ITIL Integration: Driving Collaborative Agility in ITSM

    Businesses face continuous pressure to deliver high-quality IT services efficiently. One emerging integration to meet these goals is between DevOps and IT service management (ITSM), more commonly known as DevOps+.

    DevOps+ is becoming more than a trend and has emerged as a powerful collaborative approach to meet these challenges. By combining the strengths of DevOps’ agile software development practices and ITSM’s structured service management approach, organizations can foster better collaboration, enhance agility and improve overall service delivery efficiency.

    DevOps and ITSM Symbiosis

    DevOps and ITSM traditionally operated as separate frameworks with distinct focuses. DevOps emphasizes rapid software delivery and collaboration between development and operations teams. On the other hand, ITSM-based ITIL (information technology infrastructure library) provides best practices for ensuring service stability, reliability and adherence to governance and compliance.

    Integrating DevOps and ITIL creates a symbiotic relationship, allowing organizations to leverage the best of both worlds. DevOps+ encourages a cultural shift, breaking down silos and promoting cross-functional communication. This collaboration enhances the entire software development lifecycle, leading to faster feedback loops, accelerated innovation, and increased responsiveness to business needs.

    Enhancing Agility and Speed

    DevOps+ integration brings greater agility and speed to IT service management. Organizations can streamline the release process by automating deployment pipelines and implementing continuous integration and continuous delivery (CI/CD) practices, reducing time-to-market for new features and updates. Agile development methodologies enhance the adaptability of ITSM processes to meet evolving business requirements effectively.

    Ensuring Stability and Reliability

    While agility is crucial, it must not compromise service stability and reliability. ITIL’s best practices provide a strong foundation for maintaining service quality. By incorporating ITIL processes such as incident management, change management and problem management, organizations can effectively manage risks, reduce service disruptions and ensure the stability of critical IT services.

    Leveraging Automation and Orchestration

    Automation is central to both DevOps and ITIL. Through integration, organizations can leverage automation and orchestration tools effectively. Automated testing, infrastructure provisioning and configuration management improve efficiency and consistency across the ITSM lifecycle. This enables teams to focus on higher-value tasks, reducing manual errors and operational overhead.

    Emphasizing Customer-Centricity

    DevOps+ puts the end-user experience at the forefront of service delivery. By continuously seeking customer feedback and measuring service performance, organizations can better align their offerings with user expectations. A customer-centric approach fosters higher satisfaction, loyalty, and competitive advantage.

    Breaking Down Barriers to Change

    Change management is vital in ITIL, ensuring that modifications are planned and controlled. In the context of DevOps+, change management becomes more adaptive and responsive, facilitating a culture that embraces change as an integral part of the development process. This promotes experimentation, reduces resistance to change, and accelerates innovation.

    Challenges of DevOps and ITIL Integration

    Despite the numerous benefits of DevOps+ integration, organizations may encounter challenges during implementation:

    Cultural Shift: Merging DevOps and ITIL requires a cultural shift. Overcoming resistance to change and fostering collaboration between traditionally separate teams can be challenging but is crucial for success.

    Process Alignment: DevOps and ITIL have different processes and terminologies. Aligning these methodologies while preserving their individual strengths can be complex.

    Skill Sets: Integrating DevOps and ITIL necessitates upskilling teams in both domains to operate effectively in the integrated environment.

    Tooling and Automation: Adopting suitable tools and technologies that support DevOps+ practices and integration is vital but may require significant investments.

    Metrics and Performance Measurement

    Measuring the success of DevOps+ integration is essential to understand its impact and effectiveness. Key performance indicators (KPIs) can help monitor progress and identify areas for improvement.

    Deployment Frequency: The frequency of software deployments indicates the efficiency of the integrated approach. Higher deployment frequency implies faster and more reliable releases.

    Mean Time to Resolve Incidents (MTTR): MTTR measures how quickly teams can resolve incidents and restore services after disruptions occur. A reduced MTTR demonstrates improved service reliability and faster incident resolution.

    Customer Satisfaction Scores: Measuring customer satisfaction provides insights into how well the integrated approach meets end-users’ needs and expectations.

    Continuous Improvement and Feedback Loops

    Continuous improvement is at the core of DevOps+. Establishing feedback loops and conducting regular retrospectives empowers teams to identify areas for improvement and implement iterative enhancements to processes and practices.

    Implementing DevOps+ integration requires a well-structured roadmap. For example, assessment and planning help leaders evaluate the organization’s current ITSM practices to understand how DevOps and ITIL principles align and define integration vision and goals.

    Additionally, your continuous optimization efforts allow you to continuously monitor performance metrics, gather feedback, and conduct retrospectives to identify improvement areas, leading to better team collaboration and communication. Fostering cross-functional collaboration between development, operations and other relevant teams is easily accomplished. To meet these goals, encourage regular meetings, schedule joint planning sessions and enable shared documentation to ensure everyone is aligned on goals and progress.

    When this happens, leverage automation tools to streamline manual processes and increase efficiency. Implement continuous integration and continuous delivery pipelines to automate software deployment and testing. Automation enhances consistency, reduces the risk of human errors and adds a new layer for measuring and evaluating to continuously measure the performance of the integrated approach using defined KPIs. In this vein, you can regularly review progress against the initial vision and goals to ensure the integration aligns with organizational objectives.

    Next, as the DevOps+ integration proves successful in pilot projects, gradually scale and expand it to other teams and departments. Share the success stories and best practices to encourage broader organizational adoption.

    Conclusion

    In conclusion, the integration of DevOps and ITIL, known as DevOps+, marks a transformative approach to IT service management. By combining the agility and rapid deployment of DevOps with the stability and reliability of ITIL, organizations can drive collaborative agility and achieve efficient service delivery.

    DevOps+ integration requires overcoming cultural barriers, aligning processes and upskilling teams, but the rewards are immense. With clear metrics to measure success, organizations can continually optimize their DevOps+ approach to meet customer needs and adapt to evolving market demands.

    As technology evolves, DevOps+ integration will remain at the forefront of cutting-edge IT service management, empowering organizations to embark on a journey of innovation, efficiency and excellence.

    By embracing DevOps+ as a guiding philosophy, organizations can cultivate a culture of collaboration, continuous improvement and customer-centricity, laying the groundwork for a prosperous future in the dynamic world of IT service management.

  • SolarWinds Adds Service Management Platform to Portfolio

    SolarWinds Adds Service Management Platform to Portfolio

    SolarWinds has added a service management capability to its portfolio as part of an effort to make it simpler for IT teams to align support services with specific functions.

    At the same time, SolarWinds has updated its SQL Sentry observability tool for databases and DataOps workflows to add query-level wait statistics along with a revamped web portal and dashboard for tracking the overall health of a database environment.

    SolarWinds Enterprise Service Management (ESM) makes it possible for IT teams to manage IT services based on the ticketing systems, knowledge bases, service portals and request catalogs available for specific departments such as marketing or human resources.

    Kevin Kline, senior staff technical marketing manager for SolarWinds, said that as IT management continues to evolve, there is a greater need to streamline and optimize workflows based on the insight from observability platforms. As a result, there is now a need to apply observability more broadly to include database platforms alongside DevOps and other IT workflows, he noted.

    The overall goal is to eliminate the blame game that results when IT platforms are managed in a more siloed fashion, added Kline.

    Most IT teams are still relying on monitoring tools to track a set of predefined metrics in the hope that an alert will enable them to proactively address an issue before it leads to a major disruption. However, as IT environments become more complex, there is a growing need for observability platforms so IT teams can launch queries and surface issues that predefined metrics aren’t likely to identify. Initially, observability platforms were embraced by DevOps teams, but it’s rapidly becoming apparent that this capability needs to be applied to every IT process. In effect, organizations are on the cusp of democratizing observability, noted Kline.

    Achieving that goal will also become simpler thanks to the rise of machine learning algorithms capable of predicting issues and generative artificial intelligence (AI) tools that will make it simpler to craft queries.

    In the meantime, there is already no shortage of observability platforms, but the SolarWinds approach is different in that, in addition to DevOps workflows, the company has integrated its platform with multiple database platforms to provide a more comprehensive approach, said Kline.

    It’s not clear just yet how observability platforms might impact the way IT teams are structured, but the need for specialists such as database administrators (DBAs) isn’t likely to go away anytime soon, noted Kline. Instead, the level of collaboration across various IT teams should substantially improve.

    In the meantime, IT teams might be well-advised to define an observability strategy today before multiple teams start implementing approaches that might be optimized for a relatively narrow range of use cases. After all, trying to reconcile insights generated by multiple observability platforms may very well defeat the purpose of investing in observability in the first place.

  • In Service Management, AI Is Still Aspirational

    In Service Management, AI Is Still Aspirational

    Artificial intelligence (AI) has become a matured concept, the excitement of which is bearing results for a number of sectors and it holds a good deal of promise for a bright future. AI is the act of making possible for machines to learn from “experience” while adjusting to new input and stimuli so they can perform human-like tasks, ultimately leading for more complete automation in many traditionally man-powered processes. Computers can be “trained” to accomplish specific tasks, process data and recognize patterns in the data.

    While the use of service management solutions escalates, so do the potential uses for AI approaches in the sector. Because of this, there are advantages to discuss as well as examples of how AI can help to improve the service management operations of your organizations. But AI is a broad and far-reaching concept that’s often misunderstood and difficult for those that don’t work with the technology to understand its full capabilities.

    Is AI All Hype or Is It Actually Helpful?

    Based on the 2018 Interop ITX AI: Hype or Substance report, in a survey of 182 technology professionals, almost two-thirds of these respondents’ organizations are currently working on AI products or evaluating the technology. However, only 12 percent are using AI in production today. For those who responded during 2018, 6 percent of those using the technology said their budgets for it were set to decrease. The outcome, per the report, is that AI interest is high, but the ability to execute is low.

    Are AI Expectations Too High?

    The return on investment of AI is not clear and nearly one-third of organizations say they lack the budget they need to move forward, Information Week reports. Additionally, despite the desire for AI initiatives to reduce manual processes, these tasks must still be carried out by talent in the organization. A lack of expertise is often cited as a barrier to AI initiatives because there is not enough expertise to push the efforts forward. Alternatively, of those surveyed, more than a quarter said they haven’t defined a business case yet and close to half said they “have no idea” what effect AI may have on their businesses.

    Part of the problem with AI is the broad nature of its concept. Much of what we thought we knew AI was is now standard practice. For example, early AI efforts like IBM’s chess computer, Deep Blue, is part of our computing world now. Currently, demand or desire for AI capabilities is still aspirational, but usually is conflated with “machine learning”—where a computer or programming provides examples for how a machine can “learn” how to complete said task. Machine learning has huge potential to help societies automate previously manual systems. Through this, new economies will be developed and work (and workers) will evolve. Certain jobs, eventually, will become minimized and even discontinued in favor of new process and “ways of doing things.”

    We have seen these cycles before. In the United States, from a macro level, there’s been a major shift from a farming/agricultural society to one of more urban-based manufacturing/industry; into the post-industrial; then global-focused; and web-connected economies. These can be drilled down further but the point is made—major variations in our economies and jobs have taken place in a relatively short period of time. Based on these changes, we’ve had to change; jobs and workers have had to change. Machine learning is another disruptor for the new global economy that will force change.

    Hyped Up

    The hype of machine learning—a technology with huge potential—may not actually be overhyped. That said, how will this technology actually impact our everyday lives, and will machine learning change the work we do in service management? Perhaps we’re now starting to get a better idea of what those realities may look like.

    As far back as 2017, Gartner said that machine learning hype peaked, but expectations remain high. For service managers, there’s going to be more than intelligent chatbots to worry about but for now, much of the anticipation likely will continue. Machine learning can be a beneficial tool for identifying trends and changes in trends. In service management, machine learning means quick responses can help recognize when there is an above average number of calls logged, for example, or an unusual number of calls within one category, which can be acted upon.

    For most pressing trends—a specific cloud service that may no longer be available, for example—meaning machine learning-driven technology can recognize this breakdown by sending a signal to a specialized member of the service team, who can then react to this issue. Long-term problems also can be addressed through machine learning technology, spotting urgent disruptions. This may be particularly important during problem management. A labor-intensive process, machine learning has the capability of being able to recognize patterns in these calls, making the discovery of structural problems much easier.

    Misconceptions About Machine Learning

    Misconception surrounding AI and machine learning is rampant from replacing most of our jobs and replacing massive amounts of humans in the workforce to their surpassing our pre-programmed uses for the technology, in which the machines rise up and enslave us all. The more realistic version of things is a bit more benign. The most common current misconception is that chatbots and virtual assistants will make service desk employees redundant in short order. But this won’t likely be the case for the better part of a half decade or more because the technology isn’t sophisticated enough. Most chatbots are pretty expensive and don’t always work well.

    For now, machine learning will likely only help “answer” direct questions more quickly. More complex issues must still be handled by people. The realized benefit here is that because machine learning technology can help solve the easiest questions service desks face, there’s more time for service desk team members to solve the more complex calls.

    Someday Soon …

    Soon, machine learning technology will become better at finding the right information and offering solutions that actually benefit humans. Then, service desk employees will be able to focus more on the overall customer experience in ways that machine learning likely never could.

    While AI is maturing, excitement surrounding this experiment may need to be tempered for a bit. The technology is in the act of making possible for machines to learn from “experience” while adjusting to new input and stimuli so they can perform human-like tasks, but more complete automation in many traditionally man-powered processes is still needed.

    — Nancy Van Elsacker Louisnord

  • How AIOps Helps You Get More Out of DevOps

    How AIOps Helps You Get More Out of DevOps

    DevOps may seem like an overused term. It involves taking an application’s source code and running it in an environment. It can cover the processes, the technology or even the people that maintain the technology that is running those very processes.

    At its heart, though, DevOps is about helping developers to be self-sufficient when it comes to the basic operations around getting their application to a real environment. Once things are running in a test or production environment, there are other IT functions that are required to keep it running and performing well. While there are teams that specialize in these functions, such as site reliability engineers (SREs) and system administration, they are usually overwhelmed by the sheer amount of data their areas of responsibility generate without considering the data that applications going through their DevOps processes are also creating.

    This is what makes AIOps the perfect complement to the DevOps space.

    What AIOps Does

    What AIOps does best is break down silos within IT. Having data from all the functional areas processed and handled by modern machine learning (ML) in a single place allows correlation, which leads to faster problem identification and resolution.

    Before machine learning was introduced, for humans to process data, more or less they operated in three ways:

    • They knew exactly what data to look for, such as when a specific business function isn’t working. There is a typical message in the monolithic application that handles all the core business.
    • They routinely sifted through data only from their area of expertise.
    • When they went outside their area, any logs and other data they had access to often was summarized data, which has time gaps and can miss a lot of detail that proper correlation needs.

    Now with ML, the AIOps data platform can perform trend analysis, look for patterns and exceptions across all the data that is being generated in the environment and highlight what it considers important through web interfaces or using an event management solution for after-hours support.

    Over time, as the AIOps platform continues to learn the environment, it can be given the ability to automatically resolve certain error conditions, as it will be able to identify them faster than human operators and often resolve them before they become service-impacting.

    How This Helps DevOps

    Machine learning aids DevOps processes in three ways when working with logs and data:

    • Knowing exactly what data to look for: In a true polyglot DevOps environment that is leveraging microservices, it is next to impossible for any one person to know the most common error messages that might occur. In this model where a new business function can be conceived, written in one of many languages, and deployed into production without Operations even being notified, ML allows the AIOps platform to quickly identify what “normal” looks like for a new microservice and start looking for anomalies.
    • Only routinely sifting through data from their area of expertise: When working in DevOps, developers need to be able to quickly find data from multiple areas in IT that is related to whatever they are trying to diagnose. Using AIOps, they will be able to quickly pull data from systems directly related to their incident. Whether it is as simple as using timecodes or a correlation GUID (globally unique identifier) that is put in the logs purposefully to aide tracking, AIOps will guide the developer through the other systems’ data.On the flip side, if there is an infrastructure problem, the same AIOps platform can help correlate what downstream services may have been impacted, from failed builds to Kubernetes pods that were restarted.
    • Summarized and incomplete data: The true value of machine learning is that it has the ability to process a higher volume and variety of data at a much higher speed and accuracy than a human, and sort and index it for later use. Not having to summarize the data to one data point every five minutes could result in a problem being discovered that has occurred often but not consistently, as it may have been dropped in the summarization.

    Conclusion

    AIOps is very young in the technology industry, but has great promise as it builds on previous generations of IT operational analytics products, combined with the latest in machine learning capabilities. DevOps is a key field in IT that has more logs than it knows what to do with. Combining the technologies and expertise in these two growth areas will have a huge positive impact on productivity across enterprises with improved service management.

    — Vince Power

  • Agile Service Management in Practice

    Agile Service Management in Practice

    It turns out agile and service management go together quite nicely. But how, and how do you translate the agile philosophy to actual changes in your work? There is much to learn on the topic.

    Agile Service Management: A Checklist

    Here are several practical examples on how to make your service management more agile:

    Make Sure Everything You Do Adds Value for the Customer

    IT departments usually place a good deal work into tasks that have little actual value for their customers. For example, a colleague of mine recently visited an organization where its IT department had written an extensive manual for a new smartphone it offered. While this might sound useful, most of the information was already available to users on the internet. That and next OS update would have made the manual outdated and useless.

    Plainly speaking, this is a waste of time and resources. There’s no need to replicate work already done and content that is readily available anywhere on the web. Taking a focus on agile, a better way to go may have been of documenting information to keep the manual limited to what is strictly necessary, and provide these instructions to a small test group. In doing so, only describe company-specific information, such as how to synchronize your work email with the new smartphone, and respond to the documentation based on the feedback you receive from your test group. Following this feedback, you are able to update the documentation before you officially begin to supply the smartphone, for example.

    Always Work Closely with Your Customers

    As it designs its services and processes, service organizations must make many assumptions about the needs of its customers. For example, for years a facilities organization encouraged its customers to log a call when something was wrong in the office building. Recently, it discovered that customers were annoyed to receive five or six status update emails after they log a call—one reason many customers stop logging calls altogether.

    In agile service management, you always involve your customers as soon as possible with everything you do. Using the example above, come up with a solution together with customers. When customers log a call, they can tick a box saying they want to receive status updates. One question and a single checkbox can spare a great deal of frustration.

    The Right People in the Right Place

    Many IT organizations lean heavily on processes, unfortunately, but their goal is to guarantee consistent quality of services, no matter who supplies the service. While good in theory, in practice it matters who supplies a service. For example, an unmotivated service desk likely probably leaves a less-than-positive impression on your customer than a happy, motivated employee. You simply can’t cover this outcome with a “process.”

    An important part of the agile mindset then is providing enough time and attention for your team members, which only functions well with people who are good at the work they do and when the work they do makes them happy. If a team member is no longer motivated, talk to the employee and see if you can find a role where they’ll be happier, and better able to support the organization as a whole.

    Make Your Processes as Flexible as Possible

    ITIL processes are usually not flexible, to say the least. Change management is a great example. A request for change must go through a set number of predefined steps. The only choice you usually have in the process is approve or decline the change. There’s no room to change plans and if you want to change them, you need to stop the process, make a new plan and get approval. Plan, change, stop with obstacle. Plan change and plan all over again. Not efficient in most cases.

    Your design and planning must remain flexible enough to address ever-changing organizational demands. This, however, doesn’t mean you need to implement every single planned change, and you also must allow your team to deal with new processes as they see fit.

    Design, Implement and Improve Your Services Step by Step

    New software or services implementations can take up months and even years. When the implementation is finally done, you’ve gained new insights and probably want to change many things, but by that time there’s likely little budget left or the project team members have moved on and it’s up to the application manager to process all the feedback on their own.

    Delivering new services in an agile way means you deliver something workable as soon as you are able, collect feedback and use this feedback to improve the product. The process isn’t perfect, but that’s okay. While you continue working on the next process, you can receive feedback to improve your incident management.

    Keep Your Services and Operations Straightforward

    Requests for services often contain a good deal of unnecessary management authorizations. In many cases, IT department leaders assume that department management wants control over every individual request or, alternatively, the IT department doesn’t carry any responsibility. This creates a process unnecessarily full of authorizations and a manager who gets loads of emails with authorization requests.

    Nothing should be this cumbersome. Things will be much smoother when the IT department members ask managers how much control they really want or need. They usually don’t really want to receive a number of emails, but there is an alternative solution: Requests don’t need to be authorized and managers can receive a monthly overview of the costs. This way, the manager still has control over costs, but he or she doesn’t have to process numerous emails. And the employee, the user, is helped much more quickly.

    Making Your Incident Management More Agile

    Where do you need to start when you want to work with agile? The response to this question depends on the organization. The best approach may be starting with taking a look at your current services and compare these with agile principles. For example, where’s the friction? What improvements are easy to implement? That’s where you begin. Then you start by making a small improvement, ask for feedback and move on to the next improvement.

    Incident management is the most important process of a supporting department. It’s also quite straightforward, but how can it be made more agile? Simply start by stripping out everything from the incident management process that has no customer value. Take a critical look at your current processes and evaluate each step by asking yourself if every step of the process adds value for the customer. To answer this question, you first need to know what your customer want, which is probably nothing more than a quick solution.

    Every step in your incident management process must contribute to how quickly an incident is processed. If there is a step along the way that doesn’t contribute to your goal, remove it. Eliminate everything wasteful from your process.

    — Nancy Van Elsacker Louisnord

  • Accelerating DevOps with Service Management (and Vice Versa)

    Accelerating DevOps with Service Management (and Vice Versa)

    One of the great misconceptions of service management is what it means. This also is the reason why so many service management initiatives fail. Consider a call center, for example, with many people answering phones and replying to emails. It’s true that a service desk is one of the functions (and in some organizations, maybe even a cornerstone) of service management. It’s also true that the customer or user is one of the main characters in the story of service management. The very word “service” implies there is a customer at the end of that service.

    However, service management is, at the very core, about designing, delivering and redefining services to the customer base—whether those are internal, external or occasional users of the service. User roles may vary over time and users may become part of the supplier chain, and vice versa. A great example of this is knowledge management, wherein users are typically both consumers and producers of information and, thus, the service.

    When we take this higher-level view of the service management practice, our eyes open to new possibilities. In particular, we can see beyond the service desk. The scope of service management widens to the end-to-end delivery of the services in question, retaining the focus on the customer.

    Finding the Cure: It’s All About the Customer, and Communication

    The happy medium and the much sought-after goal of the harmonization of service management and DevOps can be achieved when stakeholders find common drivers. In both worlds, the respective goals focus on the business, delivering value and doing so quickly.

    The following sections present actionable recommendations that can be implemented incrementally across the entire organization. They offer a bottom-up approach. In conjunction with implementing them, senior management needs to support the culture change that is a vehicle, a catalyst and a byproduct of the improvements. In this way, the full benefits of the changes can be analyzed and achieved.

    Tip 1: Stop playing ping-pong with issues

    We’ve all identified an issue with a system, logged it with IT as a ticket and received updates of the progress while the ticket is handed over from team to team—only to discover weeks later that the development team knew about the bug but had de-prioritized it due to lack of interest.

    Surely, by the time the final bit of information reaches users, they are less than satisfied with the result. What’s more, the organization has wasted everyone’s time, not least the time of network, storage and other team members who had to prove it wasn’t their fault in the first place. Finally, development team members could have prioritized their work correctly if they had known about the customer need in the first place.

    With so many implications in the above scenario, why does this happen? The reason is simple: less than optimum process interfaces and lack of information flow. When you’ve identified the problem, the solution is easy: Include relevant data from the development teams, such as defect information, in your chosen IT service management solution.

    Sometimes, the easiest way is to integrate the defects created in development’s chosen tool set to IT service management’s “problem” records. This way there is no need to change the processes per se, as problem records can be linked to issues (or incidents) easily in the service management tool. The integration simply allows for the information to flow between systems and enables a collaborative approach to issue handling.

    In this scenario, when the development team opens a defect, it creates a problem record in the service management system, which, if feasible, could be displayed automatically to users on a self-service portal. Thus, users can search known errors before logging a ticket, resulting in time savings across the whole organization.

    Tip 2: Communicate bugs and known issues to everyone impacted

    But what happens when a user finds a new issue that has emerged due to a bug that has yet to be discovered by developers and testers? Traditionally, the user might log a ticket, which is then analyzed by the IT service team and forwarded to developers for analysis, coding and testing. That might be last of the ticket the user sees, as the feedback loop often is missing.

    The benefits of forwarding the defect information from the user to developers are realized only when there is a way to easily track the whole life cycle of the issue regardless of where it has been initiated. Instead of batch importing records from one system to another, the most advantageous way is to mirror the record sets in the two systems.

    In this example, the feedback loop between the customer and the service desk to the development team is achieved when synchronizing problems and defects in the two solutions.

    Tip 3: Empower the customer by crowdsourcing bugs and new features

    One key metric that contributes to employee satisfaction and retention is the ability of employees to do their jobs well. To accomplish this, they need resources. When employees have all the resources they need to do their job well, more often they are happy than not.

    We are all dependent on technology; there are few professions that do not require technical resources to perform their jobs. If there is a hiccup in the finance solution, for example, the finance assistant may well be the first to find an issue after a version upgrade. Or, a team-wide brainstorming session may result in some great “if-only-our-analytics-software-could …” ideas of how to improve the efficiency of the team.

    But how best to communicate these issues, and capture the many ideas? Possibly, you might even perform real-time impact analysis on which improvement ideas are important to various business processes, and communicate the urgency of each one to the development organization. The inherent problem in many organizations is that users have only one touchpoint to the “DevOps cycle,” most commonly through the IT service management practice. Meanwhile, the rest of the IT organization may use a number of disparate systems to communicate and assign current work tasks that form a basis of shipping new features and functionalities.

    Again, it may be useful to look at the tools already employed throughout the organization, and understand the existing processes and practices. Understanding team functions is important as well, though many teams are fluid in their roles and tool sets used. Once relevant tools are identified, look for mutually beneficial interfaces between them to ensure that users’ requests for new features are not forgotten but logged and picked up by the development team.

    In this example, you could integrate a tool that supports the back office (such as a defect management tool) and tools that support users (such as requirements management and project management tools). This allows you to effectively crowdsource and track upcoming features and bugs, keeping the whole organization informed.

    Tip 4: Don’t forget suppliers

    Include the entire software supply chain in the equation. After an era of outsourcing, insourcing, and multisourcing, many organizations have a diverse supply and sourcing strategy. One of the main reasons for this is to manage risk and ensure business continuity.

    Thus, the last remark is to ensure that all the above examples work in a multisupplier environment. This typically involves contractual preparation. New frameworks such as service integration and management (SIAM) help identify risk and reward in supplier collaboration. These are useful tools for both IT service management and DevOps practices.

    A great example of supply chain integration is an end user reporting an issue. Once it has been reported, it is then centrally analyzed to find the root cause of the issue and the underlying problem is routed to the correct supplier automatically. By synchronizing the information between supplier and customer, not only is each party kept up to date about current issues, but the pipeline and project customer demand are built by integrating incidents, projects and requirements across the software supply chain.

    One of the core aims of both service management and DevOps initiatives is to respond to customer demand as quickly and effectively as possible. Real-time synchronization between solutions is merely a technical solution, but one that has true potential to elevate the response speed.

    Reflections

    Having examined the above four ways to improve the collaboration of DevOps and service management, there are clear solutions to reforming the partnership to drive quicker customer response and satisfaction. But be forewarned: The four recommendations offered are but advice to improve; an organization’s leadership must truly be committed to a culture change to make change happen.

    About the Author /Tuuli Bell

    tuulibellDr. Tuuli Bell is a Partner Account Manager, EMEA at Tasktop. She is a member of the BCS, the Chartered Institute for IT, and the Institute of Physics. For her, happiness is about discovering opportunities to challenge the status quo and about embracing change, be that organizational change, or professional or personal development. Tuuli’s interests outside work include art, science, and nature. Follow her on Twitter or find her on LinkedIn.