Author: Elizabeth Walsh

Real Life Examples of Successful Atlassian Cloud Migrations

Posted on October 5, 2023 by - Enterprise Architecture, Platform Adoption & Governance

If you rely on your Atlassian stack as mission critical applications for your daily operations—as thousands of companies do—but you’re not yet operating within Atlassian Cloud, you should at least consider it. The Cloud isn’t the best solution for every business, but it definitely is for most. And, if you’re running an on-prem Server instance right now, you’re running out of time to migrate before your Server apps lose all support and quickly become a security risk.

But what makes an Atlassian Cloud migration successful? And what factors do you need to consider when deciding how to approach your migration? We’ll cover the answers to those questions in the context of four real-life examples of Cprime clients who have successfully migrated to the Cloud with excellent results.

This content is drawn, in part, from the recent webinar, Successful Atlassian Cloud Migrations and Optimizations. Watch the webinar on demand for more details.

What makes an Atlassian Cloud migration successful?

Atlassian migrations are no small feat, especially for large enterprises with years of accumulated data, and complex integration infrastructure and automation requirements. It’s easy for a large migration to go very bad very quickly if it’s not handled properly.

After nearly a thousand successful migrations, the experts at Cprime have the process down to a science:

Atlassian Cloud Migration process

Planning and preparation

Following a thorough assessment of the client’s current and optimal future states, the Migrations team will supply a detailed plan to facilitate the most important factor in migration success: adequate organization and preparation.

Here are some factors that need to be considered long before the actual migration takes place:

  • Apps and add-ons – What Atlassian marketplace apps and add-ons are you currently relying on? Are they available on the Cloud? Are the configurations and functionality identical, or will adjustments need to be made?
  • Integrations and APIs – What about non-Atlassian applications that are currently integrated with your Atlassian tools? Are there equivalent connectors available for Cloud, or do you need to consider switching apps, reconfiguring, or having new custom integrations built?
  • User management and administration – Administration of the Cloud environment is quite different from what’s needed for Server or Data Center, so it’s best to determine who is going to be responsible for the limited necessary admin tasks and prepare to adjust permissions accordingly. 

Although the Migrations team from Cprime will do the heavy lifting in terms of setting up the testing environment and running test migrations as needed, you should also plan to invest some time into user acceptance testing (UAT)—letting your power users get into the test environment to poke around and find issues with the data, the functionality, or the user experience. This allows us to resolve those issues before the migration is completed and your teams start actively working with production data in Cloud.

Change management

Change management is another vital piece of the puzzle because moving to Atlassian Cloud may involve some significant changes in process, which can take time. To minimize any disruption to getting your work done day-to-day, you’ll want to partner with our Migration team for:

  • Training and enablement – Moving from Atlassian Server or Data Center to Cloud will involve minimal (but important) changes in the interface for most users; the Admin interface is more different, requiring more extensive training. If you’re moving to Atlassian from a different tool—such as moving from Rally to Jira—the need for training and enablement becomes far greater.
  • Process and configuration optimization – A large part of migration success involves ensuring that your way of working aligns closely with how your new cloud-based tools are set up, and that that configuration takes the best advantage of Atlassian Cloud’s powerful feature set.

This optimization process is different for each company based on their unique data and business goals. So, deciding how to go about it deserves special attention. One of the key decisions you’ll need to make is whether to focus on optimization before or after the production migration. Your migration partner can help you decide which is best. 

Optimizing before or after your Atlassian Cloud migration

At first blush, it could seem that simply moving exactly what you have now into the new system is the easiest and fastest way to complete a Cloud migration. And, to some extent, that’s true. What we call a “lift and shift” migration can usually be done more quickly, and at a lower cost (although that doesn’t count the potentially higher total cost when you factor in slowdowns and missed opportunities caused by working with a dataset that’s not optimized for the Cloud environment.)

Again, we’ve completed nearly a thousand successful migrations, and, although there are rare circumstances where a “lift and shift” is the right play, we almost always recommend that our clients take the time to optimize their data, processes, and configurations before moving to the cloud. Why?

  • Reduces complexity – The more complex the data and configurations you move to the Cloud, the more potential there is for problems in the migration; likewise, the greater complexity generally means you’ll need to dedicate more admin time to navigating the system post-migration. Both issues have real costs and headaches associated with them.
  • Provides standardization – By cleaning up the data, users, and configurations prior to migrating, you enter the new environment with things standardized and organized. This helps you avoid silos, which supports robust governance and reporting; standardization also improves efficiency by streamlining processes and shortening the learning curve.
  • Reduces total cost and effort – Excess users, projects, and add-ons can add to the total cost of your Atlassian Cloud license, and an overly complex environment requires far more time and effort to manage. So, investing the time into cleaning up the data and optimizing everything before the migration will actually save you money overall in the long run.

The importance of governance

Finally, we find over and over again that clients heading into a Cloud migration have either lax, inconsistent governance, or no governance in place at all around their Atlassian data and workflows. 

Resolving this situation is a vital aspect of a successful migration because failing to set up robust governance before heading into the new environment means that all the same problems you faced in your previous environment will eventually be duplicated in the cloud. So, we always include strong governance recommendations in our initial migration plan, and help our clients set that up prior to the move to Atlassian Cloud.

Two real-life examples of successful Atlassian Cloud migrations

Let’s take a quick look at two real-life examples of Cprime clients who went through large Atlassian Cloud migrations that proved very successful. We’ll analyze what was required to make them work, and what benefits they received from doing so.

Client #1 – Fortune 500 financial services organization

Challenge

This global finserv enterprise was a longtime user of Jira. They had several siloed instances across various business units with a total of over one million Jira issues in their combined databases. The data was not standardized, they had no formal governance in place, and they had a lot of stringent security requirements to consider for regulatory compliance.

Their initial plan when they brought us on was to do a “lift and shift” migration to the cloud and focus on optimization later on.

Solution

We recommended they instead focus on optimization, implement a governance protocol, and arrange for training and enablement of their user base ahead of the production migration. Our analysis revealed that doing so would significantly lower the overall cost of the migration while better ensuring a successful migration and lay a stronger foundation for smooth operation and robust security once they were set up in Cloud.

Results

Although it was not initially a popular decision, they agreed to follow our recommendations. In the end, the optimization efforts resulted in cutting the total number of issues in half and dropping the project and user numbers down significantly as well. This combined with standardization efforts to facilitate a smooth consolidation of instances. In total, these efforts cut about 40 percent of the total cost of the migration, so the client was thrilled with the outcome.

Client #2 – Fortune 500 life insurance organization

Challenge

This insurer was at the beginning of a multiyear digital transformation, and part of that initiative involved streamlining their way of working to reduce complexity, create efficiencies, and lower costs in the long run. 

They had some business units using Jira, but many others relying on Rally. Their Rally investment was becoming unsustainable, so they chose Jira Cloud to become their single source of truth for the entire organization’s use. 

Solution

Rally and Jira do the same thing—manage projects and tasks through a ticketing system—but their user interface, configurations, and functionality are very different. There were aspects of Rally’s functionality they wanted to maintain following the move. To facilitate this consolidation and migration to Cloud, we recommended 

  • Extensive preparation and optimization to establish which issues were necessary for ongoing work and which could be archived, and how to map Rally data to Jira via custom fields and other features. 
  • Creating standardized processes and supporting governance so the new consolidated environment could be easily learned and maintained post-migration.
  • A phased approach to the production migration so the users could hit the ground running on Day One with current tickets, and then an archive of past tickets could be brought over for data retention purposes. 
  • Targeted enablement to help existing Jira users get familiar with the new Cloud interface, and to fully train Rally users on Jira.

Results

In the end, the client was very happy with the new Jira Cloud environment. We consolidate over 800,000 issues from both systems and enabled over 5,000 users so they could move smoothly onto Atlassian Cloud with minimal disruption and zero downtime. The company saved money on their licensing fees, and their new Atlassian solution has provided a strong technology foundation for their continued digital transformation.

What’s next?

If you’re in the information-gathering stage of planning a move to Atlassian Cloud, we recommend watching the full webinar this article is based on. You’ll get a lot more detail about the topics we touched on here, plus two additional real-world examples not included in this article.

If you’re ready to move ahead with your migration, we’d like to help. Schedule a Migration Impact Assessment by clicking the link below. 

Optimal ESM: Automation and Integration are Key

Posted on October 4, 2023 by - Service Management

Also check out the first article in this 3-part series, The Customer Journey is Key to ESM Success. 

Enterprise Service Management (ESM) represents an optimized combination of the right software solution, well-thought-out processes and workflows, and customized automation that effectively supports a customer-centric, data-driven approach to each service an internal business unit undertakes.

It’s quickly becoming imperative for organizations to remain competitive and satisfy increasingly demanding customers, both inside and outside the organization.

Yet, many enterprises grapple with its implementation, either hesitating at the onset or stumbling after initial attempts. This article seeks to shed light on the integral roles of automation and integration within ESM, offering a roadmap to mastery. With this foundation laid, let’s delve deeper into the transformative power of automation.

This article is based in part on the webinar, “The Keys to Optimal ESM are Automation and Integration”. Click here to watch the webinar at your convenience.

Delving deeper into the role of automation in ESM

Automation in ESM is not a mere luxury; it’s a necessity. 

Beyond simplifying processes, it plays a pivotal role in data entry, reporting, and establishing continuous feedback loops. By automating repetitive tasks, organizations can free up valuable resources, allowing them to focus on more strategic initiatives. 

A salient concept here is the identification and management of “waste.” Processes that are redundant or inefficient should be targeted. If they cannot be eliminated, they should be automated, ensuring that every step adds value and no effort goes to waste.

Integration: Laying the groundwork for automation

Before the wonders of automation can be fully realized, the groundwork of integration must be laid. 

Integration ensures that various tools, platforms, and processes within an organization communicate seamlessly. This interconnectedness is vital, as it prevents data silos and ensures that information flows smoothly across departments. 

By establishing robust integration, organizations can ensure that their systems are not just talking to each other but are also working in harmony. This sets the stage for subsequent automation, where processes are streamlined, and efficiencies are realized. 

Operationalizing ESM: A phased approach

Implementing ESM demands a phased approach: 

  1. Initiating with individual business functions and addressing their distinct service requests sets the stage. 
  2. Progressively, by dismantling silos, cross-functional value emerges. 
  3. The pinnacle is reached when design thinking is integrated, leading to regular and iterative value delivery across the enterprise. 

Key takeaways for successful ESM implementation

Cross-functional collaboration is paramount for ESM. Every stakeholder has a crucial role to play. Moreover, centering initiatives around the customer ensures that services are not only efficient but also impactful. While the benefits of ESM are manifold, it’s equally important to acknowledge the challenges that lie ahead.

Challenges and hesitations in ESM implementation

Enterprises naturally encounter obstacles. Common apprehensions span from resource allocation to securing stakeholder buy-in. However, with a lucid roadmap and insights into potential pitfalls, these challenges can be adeptly navigated.

Conclusion

ESM is not merely a competitive edge but an organizational imperative. By leveraging automation and integration to align non-IT teams, enterprises can streamline operations and deliver unmatched service to both internal and external customers.

Dive deeper by watching the full webinar on demand: The Keys to Optimal ESM are Automation and Integration.

5 Practical Tips for Technical Product Managers

Posted on September 28, 2023 by - Agile & DevOps

In the world of technical product management, you need to master a diverse set of capabilities. From understanding code to pitching executives, effective PMs have to toggle between technical details and high-level strategy daily.

But aside from core skills like communication and prioritization, what practical tips help PMs deliver technical products in the real world?

In this post, we’ll cover five tactics for navigating common technical PM challenges including:

  • Selling refactoring work
  • Managing engineers without coding expertise
  • Speeding up development velocity
  • Staying in touch with what matters to the customer

Master these practical tricks of the trade to step up your technical product management game.

Tip #1: Sell refactoring by highlighting value

Here’s a familiar scenario: your engineers want to pause feature development for a few months to pay down technical debt. This refactoring work will improve stability and enable long-term velocity. But your executives want to see exciting new capabilities first and foremost.

How do you sell mandatory refactoring in this situation?

First, avoid leading with tech jargon like “technical debt” and “refactoring” in the boardroom. Those terms are meaningless to non-technical leaders. Instead, quantify the business value impact in their language:

  • “By rebuilding our messy legacy code now, we can accelerate releases by 15% next quarter.”
  • “This infrastructure upgrade will reduce service outages by 30%, improving customer retention.”

Second, frame large refactoring projects as enablers of critical business outcomes:

  • “Re-architecting our monolith platform is required to launch our mobile apps with the needed performance.”
  • “Migrating to microservices is essential for entering the Asian market and achieving our growth goals.”

In other words, paint a clear line between refactoring and tangible business results. Technical debt may not be sexy, but investing now enables outcomes they want tomorrow, which is.

Tip #2: Call out B.S. (without being a developer)

Even without a development background, you’ll need to challenge engineering assumptions and call out B.S. occasionally. So how do you effectively push back on technical experts?

First, get smart on the basics of the codebase and architecture. Learn enough to understand the fundamentals and ask intelligent questions. Lean on architects willing to teach.

Next, find your “translator”—an engineer willing to advise you honestly when things sound fishy. Develop trust with them to validate gut feelings that something is off.

Finally, focus on collaboration, not confrontation. Say, “I want to make sure I understand the risks here fully so I can support you.” Rather than accusing them directly, use ignorance to extract the truth politely.

You don’t need to be a coder to push back on engineers. Build foundational knowledge, find internal allies, and lead with curiosity.

Tip #3: Learn enough tech details to manage well

We’ve established you don’t need to be a coder. But how much time should PMs spend digging into the technical details?

As a rule of thumb, strive to understand:

  • The overall architecture and infrastructure
  • How major components and services interact
  • Key quality attributes like scalability, security, and performance

Avoid getting dragged into minor implementation details or trying to micromanage. But major architectural decisions, technical trade-offs, and infrastructure choices should be on your radar.

Knowing the high-level landscape helps you make better product decisions and have meaningful technical discussions. Shooting for the “30,000-foot view” is a good goal.

Tip #3: Fix velocity by improving discovery

Slow project velocity plagues many technical teams. But often, the root cause is poor discovery upfront, not dev team capacity.

Flawed discovery leads to inflated stories that are confusing to estimate and impossible to complete. If your team struggles to meet its sprint commitments, ask yourself:

  • Are large requirements being decomposed into small, testable stories?
  • Do developers understand the user value behind each item?
  • Is the backlog ordered to deliver value incrementally?

Improving your discovery practices, like story mapping and MVP definition, is the fastest way to speed up development. Right-sized, value-centric stories enable accurate estimation and rapid iteration.

Tip #5: Build a feedback loop with customers

This last tip is more mindset than actionable tactic. But savvy PMs continually connect customers back to technical decisions.

Building a tight feedback loop helps in two ways:

  1. Informs architectural choices. If your customers care most about mobile performance, that data point guides infrastructure decisions.
  2. Sells technical improvements internally. If you hear customers complaining about speed, you can sell an optimization sprint.

Constantly gathering feedback is key. Share insights from support tickets, user interviews, and reviews to spotlight technical areas that need attention.

Help engineers deliver value

Technical product management comes with its own unique challenges. But equipping yourself with practical tips and tricks enables you to streamline processes, sell critical work, and collaborate effectively.

Try out these five techniques next time you run into roadblocks on your technical PM journey:

  • Highlight business value to sell refactoring
  • Learn enough tech to call out B.S.
  • Fix underlying discovery before velocity
  • Understand the 30,000-foot view of the architectural landscape
  • Use customer feedback to guide technical decisions

Mastering these practical skills helps you empower engineers to build products that customers love.

Creating a Strong Pipeline of New Product Owners Within Your Organization

Posted on September 26, 2023 by - Agile & DevOps

As companies increasingly see the value of pursuing product agility over project management, the role of a Product Owner has gained significant prominence. A Product Owner serves as the customer’s advocate—the ultimate champion of value delivered—and helps coordinate between the product teams, steering the product’s vision and driving its success. While hiring external candidates with Product Owner expertise is an option, many organizations fail to train or develop their internal employees as new product owners.

We will explore some steps organizations can take to identify existing employees that have the right mindset & institutional knowledge, and equip them with the skills required to become effective Product Owners.

Identifying potential candidates

The first step in developing a strong pipeline of Product Owners is to identify employees who possess the necessary skills and mindset. Look for individuals who demonstrate a deep understanding of the organization’s products, show strong communication and collaboration skills, and possess a customer-centric mindset. 

Where to find potential new product owners

These individuals may come from diverse backgrounds, such as project management, business analysis, or software development. But there are some less obvious choices that are often overlooked: 

Call Center and or Customer Support teams are a great place to find potential new Product Owners. The people in these roles speak with your customers all day every day, and hear firsthand what they love and what they would like to see improved. They should have deep knowledge of your products that can translate well to the Product Owner role. 

Marketing roles are very similar in their product knowledge, with an added view into the market landscape and industry trends. 

Another overlooked role are your QA testers. They review changes to your products to ensure they meet the user needs and are intuitive to use.

Core skills these candidates must possess

Here are some core skills to look for:

  • Strategic Thinking: Product Owners must have a strategic mindset and the ability to think long-term. They should be able to define a clear vision for the product and develop a roadmap to achieve the desired goals.
  • Communication: Strong communication skills are essential for Product Owners to convey their ideas effectively and collaborate with various stakeholders, including engineers, designers, marketers, and executives. They should be able to articulate the product vision, gather requirements, and facilitate cross-functional teamwork.
  • Leadership: Product Owners need to lead without direct authority. They should inspire and motivate their teams, provide clear direction, and make decisions that align with the overall product strategy. Effective leadership helps drive the team towards success.
  • Problem solving: Product Owners encounter complex problems regularly and must be skilled at breaking them down into smaller, manageable parts. They should be proactive in finding solutions and evaluating potential risks and trade-offs.
  • Adaptability: The product management landscape is dynamic, and great Product Owners can adapt to changes quickly. They should be open to feedback, iterate on their approaches, and embrace new methodologies and technologies.

Providing comprehensive training for new Product Owners

Once potential candidates have been identified, it is crucial to provide them with comprehensive training tailored to the role of a Product Owner. The training should cover a range of topics, including agile methodologies, product management principles, user research techniques, and stakeholder management. Interactive workshops, seminars, and online courses can be utilized to impart knowledge and build practical skills.

Focus on enhancing key skills

Here is a list of five skills a good Product Owner should build:

  • Market and user understanding: Understanding the market landscape and the needs of the users is crucial for Product Owners. They should conduct market research, analyze user feedback, and stay up-to-date with industry trends to make informed decisions.
  • Analytical skills: Product Owners must be comfortable working with data and making data-driven decisions to determine value & opportunity. They should be able to analyze metrics, conduct A/B tests, and interpret user behavior to gain insights and drive product improvements.
  • Prioritization & time management: With numerous competing priorities, Product Owners must excel at prioritization. They should identify the most impactful features or initiatives, allocate resources effectively, and manage timelines to ensure timely delivery.
  • Technical understanding: While not always required, having a solid understanding of the underlying technologies and development processes can be advantageous. It helps in effective collaboration with the engineering team and in making informed technical decisions.
  • User experience (UX) knowledge: Product Owners should have a good understanding of UX principles and be able to advocate for a great user experience. They should work closely with UX designers to ensure the product meets user needs and is intuitive to use.

For examples of Product Owner training and certification options available, refer to our training catalog and search for “Product Owner”.

Coaching and mentoring opportunities

To supplement formal training, organizations should provide coaching and mentorship to aspiring Product Owners via coaches that specialize in product development. Product Agility Coaches are an excellent resource that can draw from their real world experience to guide the new Product Owners in their new daily activities.

Another way to help aspiring or new Product Owners is to provide shadowing opportunities. Seasoned Product Owners within the company can serve as mentors, offering guidance, company specific experiences, and providing valuable feedback. Additionally, allowing aspiring Product Owners to shadow experienced professionals during product development cycles can provide hands-on learning experiences and foster a deeper understanding of the role’s responsibilities.

Cross-functional exposure

Product Owners need to collaborate effectively with various departments within an organization. Therefore, it is beneficial to expose aspiring Product Owners to cross-functional teams and diverse projects. Encourage rotations to different departments, such as marketing, design, engineering, and customer support. This exposure will enhance their understanding of different perspectives and enable them to make more informed decisions when defining product roadmaps.

It is important to continue this communication and collaboration with these other departments. It should not only be something that prepares them for the role. Maintaining strong lines of communication with these groups will enhance the Product Owner’s broader understanding of their product’s needs.

Encouraging continuous learning

Learning should not stop after the initial training phase. Organizations should promote a culture of continuous learning and improvement among their Product Owners. Encourage them to attend conferences, participate in industry events, join professional networks, and pursue relevant certifications. Additionally, establishing internal communities of practice or knowledge-sharing platforms can facilitate ongoing learning and collaboration among Product Owners.

Performance evaluation criteria

Regular performance evaluations should be conducted to assess the progress and development of aspiring Product Owners. Objective criteria, such as the ability to deliver successful products, stakeholder satisfaction, and effective collaboration with the development team, can be used to measure their performance. Recognize and reward achievements while providing constructive feedback for improvement. Additionally, organizations should create growth opportunities for Product Owners, such as advancement to senior roles or involvement in strategic initiatives.

Conclusion

Training internal employees to become new Product Owners: 

  • Unlocks the potential of talented individuals within an organization
  • Fosters a culture of innovation and collaboration
  • Nurtures a strong pipeline of skilled Product Owners
  • Ensures a deep understanding of the company’s products
  • Drives innovation
  • Reduces the overhead associated with external recruitment
  • Strengthens employee retention and loyalty 

By providing a clear pathway for career advancement and professional growth, organizations can cultivate a culture of internal talent development and create a competitive advantage in the market.

Debunking the Top Myths in Technical Product Management

Posted on September 21, 2023 by - Agile & DevOps

As a Product Manager in the software industry, you’re likely all too familiar with the unique challenges of managing technical products and working with engineering teams. But despite how often you collaborate with developers and architects to deliver solutions, some persistent product management myths and misconceptions continue to create roadblocks.

These myths impact your ability to build the right product, work efficiently, and communicate effectively. And when a VP or C-suite executive holds one of these common misbeliefs, it can seriously hinder your team’s progress and value delivery.

In this post, we’ll dig into three of the most stubborn myths technical product managers face, the realities you need to know, and how debunking these myths can help you be a better PM.

Myth #1: Non-functional requirements aren’t a priority

If you’ve spent any time in a scrum meeting, you’ve probably heard developers talk about “non-functional requirements” or NFRs. They use this term to refer to aspects of the product like:

  • Usability
  • Scalability
  • Performance
  • Security

These so-called NFRs describe how the product should behave and the quality standards it must meet. But because they don’t seem to map directly to capabilities or features, many engineers view them as lower priority.

Here’s the reality: the “non-functional” label is nonsense. There’s nothing more functional and requirement-like than defining how usable, fast, and secure your product needs to be.

Take performance as an example. If your product takes ten seconds to load a simple search result, that’s clearly not performing to an acceptable level. What good is the front-end UI if the back-end can’t deliver a timely experience?

So, as a PM, don’t accept the “non-functional” misnomer.

Focusing on key user journeys and setting measurable outcomes for these abilities is just as important as delivering specific features. Make sure you incorporate these vital product aspects into planning and prioritization just like any other requirement.

Myth #2: PMs don’t need to understand the technology

Another common and dangerous product management myth is that PMs can manage products successfully without digging into the technical details. As long as you capture requirements, prioritize the roadmap, and interface with customers, you’re doing your core job. Right?

microsoft teams

Wrong. Here’s why this hands-off approach is a myth:

First, you need awareness of how the technology impacts the customer experience. If the architecture is slow and clunky behind-the-scenes, users will encounter lag and friction points that sour their perception of your product. You have to care about that entire iceberg, not just the tip.

Second, you’ll struggle to make informed trade-off decisions during planning if you don’t understand technical constraints and options. Prioritizing technical debt cleanup may not seem valuable through a non-technical lens, but your developers will know it enables future velocity.

Finally, you can’t effectively collaborate with engineers without some fluency in the technology. You need enough technical knowledge to have intelligent conversations, ask good questions, and call BS if someone tries dazzling you with inscrutable jargon.

So, while you don’t have to be a former developer, make sure you invest time to learn the tech stack, architecture, and infrastructure for the products you manage. Doing so helps you make better product decisions and partner with engineering more strategically.

Myth #3: Leadership Doesn’t Care About the Technical Details

The third product management myth relates to communication. Many PMs assume that engineering details are irrelevant to executives focused on business strategy and revenue.

Your job is to translate between these two worlds, but you may hesitate to bring up technical considerations at the leadership table. However, dismissing technical insights as too tactical can backfire:

Technology decisions have business implications that leadership needs to weigh in on. Migrating to microservices could support scale and velocity but requires upfront investment. Great PMs proactively surface these trade-offs.

The trick is to frame technical work so it connects clearly to business value. Help executives understand how improving performance and stability—while less glamorous than new features—translates to revenue by boosting customer satisfaction and lowering support costs.

In other words, get comfortable translating tech speak into business impact and cost/benefit trade-offs. Doing so ensures you get buy-in for important technical investments.

Get ahead by busting these myths

As a PM, you may feel like you’re translating between two different languages and cultures on a daily basis. But embracing the realities behind these common myths puts you in a position to bridge that gap effectively.

Remember that:

  • Managing non-functional abilities is just as important as features
  • You need to understand the technology, not just the requirements
  • Leadership cares about tech decisions that influence business success

Debunking myths helps you make better product decisions, collaborate with engineers, and secure stakeholder support. The result is a product that delights customers by delivering stellar experiences throughout.

The Customer Journey is Key to ESM Success

Posted on September 20, 2023 by - Service Management

Organizations today are constantly seeking ways to streamline operations, enhance customer experiences, and drive value. One such approach that has gained traction in recent years is Enterprise Service Management (ESM). But what exactly is ESM, and why is it becoming a cornerstone for many businesses?

The following content is based on the webinar, ESM Foundations: Do You Understand Your Customer’s Journey. Learn more by watching the 30-minute webinar on demand.

Definition of ESM

You’re likely already familiar with IT Service Management (ITSM). The basic concepts of ITSM are present in ESM as well, but at its core, ESM offers a foundational framework that emphasizes the relevance of service management across an entire organization. It’s about breaking down silos and creating a unified approach to service delivery, ensuring that every department, from Marketing to HR to IT and beyond, operates with a service-oriented mindset.

But why consider ESM at all?

Market trends and data

The shift towards ESM is not without reason. 

Over the past 3-5 years, there’s been a noticeable movement of organizations adopting an ESM approach. This shift is evident in the data, which shows a 50% increase in ESM strategies being implemented. Interestingly, a majority of organizations now consider their ESM strategies to be advanced. However, it’s worth noting that a small fraction (11%) of companies still remain skeptical about its value. 

When we dive deeper into which business units are leading the ESM charge, three stand out: 

  • Customer Support
  • Business Operations
  • HR

Their inherent service-oriented functions make them natural adopters of this approach.

How to approach an ESM program

So, you’re interested in pursuing ESM in your own organization. What should you consider in your approach?

Leveraging a product mindset:

Transitioning to ESM requires more than just a change in tools or processes; it demands a shift in mindset. Adopting a product mindset can be a game-changer. This approach emphasizes iterative value creation, ensuring that businesses, customers, and users all benefit from the services provided.

Product and service roadmapping

To make ESM tangible and actionable, organizations need to invest in product and service roadmapping. This involves taking abstract service management concepts and translating them into concrete actions and strategies.

Core elements of an ESM solution:

For ESM to be effective, there are a few core elements that organizations must have in place:

  1. User Portal: A user-friendly interface where service requests can be raised.
  2. Workflow: A clear and efficient process that tracks a request from initiation to completion.
  3. Service Catalog: A detailed list of services, complete with documentation, service level agreements, and other pertinent details.

Understanding the customer journey

The heart of ESM lies in understanding the customer journey. It’s about being customer-centric, ensuring that every decision, process, and strategy is aligned with delivering the best possible outcomes and value to the customer. This means stepping into the customer’s shoes, understanding their needs, and ensuring that the services provided meet those needs effectively.

ESM design thinking

Design thinking in ESM is about empathy. It’s about understanding the customer experience from their perspective, identifying their goals, and being proactive in meeting those goals. This approach not only enhances the customer experience but also fosters innovation within the organization.

Onboarding experience

A prime example of the importance of the customer journey in ESM is the onboarding experience. A seamless onboarding process, where the end user feels valued and understands every step, can set the tone for their entire journey with the organization. Whether it’s HR providing resources or marketing sending a welcome package, every touchpoint should be orchestrated to make the new employee feel valued and integrated.

What is the future of ESM?

As we look ahead, the future of ESM is promising. It’s about scaling service management across all facets of an organization. By combining the right software with well-designed processes and automation, ESM can support a customer-centric approach in every business unit. The ultimate goal is to foster collaboration and alignment, driving efficiency, quality, and consistency in service delivery.

In conclusion, Enterprise Service Management is not just a trend; it’s a paradigm shift in how organizations view and deliver services. By understanding the customer journey, adopting a product mindset, and implementing the right tools and processes, businesses can elevate their service delivery to new heights. 

For those keen to delve deeper into the intricacies of ESM and its potential benefits, we recommend watching the full webinar on demand: ESM Foundations: Do You Understand Your Customer’s Journey. Your journey to mastering ESM starts there.

And, stay tuned for Part 2 of this blog series, Optimal ESM: Automation and Integration are Key.

Product Owner or Product Manager in SAFe – Which Do We Really Need?

Posted on September 19, 2023 by - Agile & DevOps

Some are confused by the terms “Product Owner” and “Product Manager” What are they, and why do we need them? Must we have both? The answers are directly related to the size and scope of your project, as well as the complexity of your domain.

If you have been working within or with a Scrum team, you are likely very familiar with the role of the Product Owner, who is the person ultimately responsible for the value delivered to the customer. The Product Owner role, which may be played by a variety of people within your organization, focuses on prioritizing the work for your Scrum team and ensuring that the expectations of customers and stakeholders are met consistently.

What is a Product Manager?

As more companies embark on the journey to adopt Scrum and Agile principles into their organizations, the role of the Product Owner has become less clear because of introducing scaling. Many organizations realize that a single Agile/Scrum team is insufficient in building a large, complex solution that the customers demand and expect. Hence, the practice of “scaling agile teams” has quickly become the norm in many organizations that demand sophisticated products and services. As a result, SAFe (Scaled Agile Framework) has quickly risen to become the most popular scaling method in the world.

Within the SAFe approach, the role of the Product Owner remains relatively similar to the original definition outlined by the Scrum Guide. However, the concept of an ART (Agile Release Train) introduces a new role—the Product Manager—which may be challenging to understand for project teams that are new to SAFe. The rise of SAFe, fueled by a need for multiple Agile teams to collaborate on a single solution, requires the Product Manager to provide strategic insights into the customers’ needs.

While most ARTs will likely have a small number of teams, each having a dedicated Product Owner, the Product Manager is an essential role that will ensure the individual teams work together in a synchronized manner towards fulfillment of the greater vision. The Product Manager will help the teams stay aligned in terms of priorities and value delivered to the end customer by focusing at the Release Train level.

Do you need BOTH Product Manager and Product Owner?

One question that I have encountered many times is, “If I can only hire a Product Manager or a team of Product Owners, but not both, which should I choose?”

While launching the team with a Product Manager and no Product Owners is not ideal, it could be managed as an incremental step towards a mature, effective train. Most new ARTs have a tendency to launch without all the roles filled. One strategy is to assemble Agile/Scrum teams that are most critical to the overall solution first, so that they can deliver value as quickly as possible. Even if you have the financial resources to staff up the entire train, more than likely, recruiting and assembling the teams to support the train will require an incremental approach.

So, do you absolutely NEED both roles in order to operate an ART successfully? Yes, especially if your ART comprises five or more teams. Without effective Product Owners to manage the details, the train is at risk of fragmentation. Having skilled Product Owners and Product Managers will provide a cohesive, organized approach that gives your train the best chance for success.

Key Attributes Product Owner Product Manager
Scope Team ART (Agile Release Train)
Focus Area Team Backlog ART Backlog
Key Skills Customer engagement Market strategy, roadmap & vision
Peer Interactions Agile Team, Product Manager Business Owners, System Architect, Release Train Engineer

For help understanding and carrying out the roles of the Product Owner and Product Manager in a scaled Agile environment, reach out to our Agile product coaches.

The Sprint Backlog – An Actionable Plan to Deliver Value

Posted on September 14, 2023 by - Agile & DevOps

The sprint is a container for Scrum events. It contains all the work a Scrum team will do to create an increment (which is formed when it meets the quality measures required for the product as defined by the team’s definition of done). The sprint is the heartbeat of Scrum. 

In her blog, 5 Powerful Things About the Sprint, Stephanie Ockerman covers how the sprint provides:

  • Focus (where ideas are turned into value)
  • Predictability (deliver a ‘done’ increment of work)
  • Control (to inspect an increment and adapt)
  • Freedom (for Scrum team to self-manage, collaborate, and experiment)

The first event of a sprint is sprint planning, which lays out the work to be performed for the sprint. The output of sprint planning is the sprint goal—a concise statement of what the team intends to accomplish during the sprint—and the product backlog items selected for the sprint, also known as the sprint backlog.

Why create a sprint backlog?

The Scrum Guide describes the sprint backlog as a plan by and for the developers. It is a highly visible, real-time picture of the work that the developers plan to accomplish during the sprint in order to achieve the sprint goal. 

The sprint backlog is solely owned by the developers, but the Scrum team collaborates over the work on it. For example, if the developers believe the work in the sprint backlog needs to change to better meet the sprint goal, developers would collaborate with the product Owner when making that decision. The sprint backlog is still owned by the developers.

The sprint backlog contains a commitment—the sprint goal—which provides the ‘why’ for the developers. It enhances transparency and focus against which the team can measure progress.  The sprint goal helps to answer questions like:

  • Why is it worthwhile to run this sprint? 
  • What assumptions/hypotheses do we want to test?
  • What is it we are trying to achieve? 
  • How does it get us closer to our product goal? 

How to create a sprint backlog

During sprint planning, developers collaborate with the Product Owner to craft the sprint backlog, which describes how they intend to deliver the increment. The sprint backlog is an actionable plan for delivery.

The developers decompose work (often expressed as user stories) into smaller items (often expressed as tasks). Tasks are small items of work that can be completed in a short timeframe (typically one or two days). 

Tasks are more precise, in detail and in scope, than user stories. When creating tasks, avoid vague statements such as ‘coding’ or ‘implementation’, thinking that you can just refer to the parent user story for the details. Instead, create meaningful descriptions of the tasks to make the scope of work very clear.

A blog by Victor Dantas offers a very good example of how to break a story down to a task level for a requirement for a web app: 

As a registered user, I want to log in with my username and password so that the system can authenticate me and I can trust it.

And with the following acceptance criteria:

“Given that I am a registered user and logged out… if I go to the login page and enter my username and password and click on Log in, then the data associated with my user should be accessible.“

By getting all the developers together in sprint planning to brainstorm on what is needed, you’re likely to hear things like:

  • “We need a new UI element for Sign-up and Login”
  • “We need to develop encryption functionality for the password”
  • “We need to create a table in the database for user information”

Now, to do things in a more structured way, let’s ask the developers:

How can we break this down into executable, scope-bound tasks? Here, the team may agree on the following tasks for the user story:

computer with code lines

  • Define Sign-up/Login form style and develop new CSS class
  • Develop HTML and Javascript Sign-Up/Login presentation layer code
  • Develop Javascript sign up form validation code 

Now you can see how the sprint backlog gets formed and grows during sprint planning.  However, during sprint planning, you will not create the perfect plan. The sprint backlog is an adaptive plan by and for the developers. It is a highly visible, real-time picture of the work that the developers plan to accomplish during the sprint in order to achieve the sprint goal. 

Consequently, they will update the sprint backlog throughout the sprint as they learn more and, as such, they create, re-order, add more detail, and delete as needed. 

Sprint backlog misconceptions and anti-patterns

Developers cannot change the sprint backlog during the sprint as it is a commitment

The myth is that the sprint backlog is fixed during the sprint and that developers must implement all the work items in the sprint backlog because they have committed to deliver them. If not, the sprint is a failure. Changes to the sprint backlog are not allowed and no work can be added or removed from it, as this creates a lack of focus and there is a risk of ‘goal’ creep. 

That’s not the case. 

The sprint backlog should not be static

The sprint goal is an objective set by the Scrum team during sprint planning. The sprint goal describes what the Scrum team wants to achieve during the sprint (to test an idea, hypothesis or run a test) and how it intends to be closer to the product goal.

Remember, Scrum was created to ‘help people, teams and organizations generate value through adaptive solutions for complex problems. The Scrum team—more particularly the developers who craft the sprint backlog—cannot predict the future and create the perfect plan. Complex work is highly unpredictable, so they cannot set a detailed plan in stone during sprint planning. The developers should refine the work that needs to be done based on what they learn once work begins. 

For example, let’s assume the developers create a new feature and change several existing features during the sprint. All this needs testing, regression testing, and code refactoring, which they expected; they could not anticipate the effort and amount of work required. So, the developers will need to add work items to the sprint backlog. Nevertheless, they remain committed to the sprint goal.

The sprint backlog changes based on ‘inspect and adapt’

The sprint backlog supports empiricism—the idea that knowledge comes from experience and deciding based on what the team observes (The Scrum Guide 2020). The Daily Scrum gives developers an opportunity to inspect and adapt their progress to the sprint goal and make any adjustments to the sprint backlog. 

A metric developers can use in a Daily Scrum to help support empiricism and manage the sprint backlog is Work Item Age. Work Item Age looks at current active work (the amount of elapsed time between when a work item started and the current time). Work Item Age is a leading indicator related to unfinished work items. It is a great metric; it enables transparency to which work items are flowing well and which are stuck in the mud and not progressing as expected. Using Work Item Age in combination with cycle time can help developers to focus on those items of work which are at most risk of missing the teams’ service level expectation, and make the necessary adjustments.

The Product Owner controls the sprint backlog and therefore can pull work items in and out whenever they feel like?

If a Product Owner pulls and adds work items into the sprint backlog at will, and developers just shrug and continue working, the developers are no longer committed to the sprint goal and lack ownership of the sprint backlog that is rightfully theirs. They have just become a feature factory and no longer align with a sprint or product goal, or value creation.

Developers own the sprint backlog and must maintain accountability

The Scrum Guide states that developers are always accountable for:

  • Creating a plan for the sprint—the sprint backlog
  • Instilling quality by adhering to a definition of done
  • Adapting their plan each day toward the sprint goal
  • Holding each other accountable as professionals

The Product Owner owns the product backlog

The Product Owner is accountable for effective product backlog management, which includes:

  • Developing and explicitly communicating the product goal
  • Creating and clearly communicating product backlog items
  • Ordering product backlog items
  • Ensuring that the product backlog is transparent, visible, and understood

To learn more about the sprint backlog and other important aspects of Scrum, check out our popular FAQ, What is Agile and What is Scrum?

Unlock Productivity and Innovation With Our ChatGPT Primer

Posted on September 13, 2023 by - AI-Ready Foundations, Learning

In today’s fast-paced digital landscape, efficiency and innovation are more than goals; they’re necessities. Generative AI, particularly ChatGPT, can empower you in this quest. But it’s not quick and intuitive—you need actionable strategies and best practices to get the most out of this transformative technology. 

As a first step down the road of leveraging generative AI for your business, let’s cover some basics. 

What is generative AI?

Generative AI is a broad category of tools and applications designed to automate and innovate various aspects of business and personal tasks. It has a wide range of applications, from content creation to data analysis. 

Knowing where to apply generative AI, whether in automating customer service or enhancing creative processes, is essential. Interestingly, the rise of generative AI can be likened to the “big data” buzz of 2011, indicating its transformative potential.

A brief ChatGPT primer

ChatGPT has emerged as a particularly accessible and popular form of generative AI. Its ease of use and real-world applicability make it a compelling choice for those looking to explore the world of AI. 

OpenAI’s juggernaut has gained considerable attention for its ability to perform tasks ranging from drafting emails to generating code. Enterprises in every industry are scrambling to figure out how to put this powerful application—and ones like it—to use solving real world business problems.

Leveraging ChatGPT in the enterprise: not just a tool, an assistant

In an enterprise setting, ChatGPT can serve as a valuable assistant, aiding in tasks like content generation and data analysis. Its capabilities extend far beyond simple text generation; it can help kickstart projects, providing a foundation upon which to build.

For instance, if your marketing team is working on a new campaign, ChatGPT can generate initial drafts for email copy, social media posts, or even whitepapers. This not only speeds up the creative process but also allows your team to focus on fine-tuning the content. 

Similarly, in the realm of data analysis, ChatGPT can sift through large datasets to identify key trends or anomalies, serving as a first pass before human analysts dive deeper into the data.

The “second-year intern” analogy

The model’s capabilities can be likened to that of a “second-year intern”—someone who has enough experience to handle a variety of tasks but still requires supervision. This has implications for job roles in the future. 

As ChatGPT takes on more routine tasks, professionals can focus on strategic, creative, and more complex aspects of their work. For example, a data scientist could use ChatGPT to handle initial data cleaning and basic analysis, freeing them to focus on more complex modeling and interpretation.

Technical expertise required

To maximize the utility of ChatGPT, a team with some technical expertise may be required, especially for tasks like scripting or using APIs. 

For example, integrating ChatGPT into your customer relationship management (CRM) system to automate certain customer interactions would likely require knowledge of APIs. Similarly, if you’re looking to use ChatGPT for more advanced data analysis tasks, some familiarity with scripting could be beneficial to customize the model’s queries and interpret its outputs effectively.

Caveats and limitations: know before you go

While generative AI and ChatGPT offer numerous advantages, it’s essential to be aware of their limitations. These limitations can impact everything from the quality of the output to data security, and being aware of them is crucial for responsible and effective use.

Error replication

One of the first things to note is that the model can replicate errors. For example, if you’re using ChatGPT to generate code snippets or automate parts of your software development process, it’s essential to double-check the output. An error in the code could lead to bugs that might be costly to fix later. Therefore, while ChatGPT can accelerate the development process, human oversight is still necessary to ensure accuracy.

The model is also notorious for replicating user errors. Users have reported being able to “trick” the AI with all manner of false information, with sometimes hilarious and sometimes nefarious results. In an effort to learn, ChatGPT has been known to absorb some very ugly ideas.

Outdated training data

Another limitation is the model’s training data, which cuts off in 2021. This makes it less reliable for tasks requiring real-time updates or current information. 

For instance, if you’re in finance and looking to get the latest insights on emerging markets or investment trends, ChatGPT out-of-the-box might not be the best tool for the job. Its data is not up-to-date, and therefore, it can’t provide real-time market insights.

Some other generative AI applications offer limited access to current online content, but this can be problematic in its own way. ChatGPT experimented briefly with a real-time browser plugin in beta, but shut it down fairly quickly when it found that the AI was bypassing security protocols and absorbing tremendous amounts of false or inappropriate data from the internet. Eventually, those problems will be solved. But until then, ChatGPT’s knowledge of the world ends in 2021.

Data security concerns

Data security is a significant concern, especially for enterprises dealing with sensitive or confidential information. Some companies are cautious about using models like ChatGPT due to potential data security risks. For example, if you’re in healthcare and considering using ChatGPT for automating patient interactions, you’ll need to be extremely cautious due to the sensitive nature of medical data—using the public ChatGPT application means accepting that every bit of data passing through it can be stored and reviewed to train the model going forward.

To address data security concerns, solutions like private instances of these models are being developed. These private instances would reside within a company’s own infrastructure, providing an additional layer of security. 

This is particularly useful for companies that need to adhere to strict compliance regulations, such as those in the financial or healthcare sectors. But really, every organization that wants to fully leverage generative AI would be well served to consider establishing a private instance to ensure proprietary and protected data remains safe.

Effective communication with ChatGPT: more than just commands

Interacting with ChatGPT or any other Language Learning Model (LLM) is not a dialogue to be taken lightly, especially in a corporate environment. The importance of iterative conversations and feedback loops is paramount for achieving precise and useful outcomes.

Clear and specific prompts

You might be looking to generate marketing copy for a new product launch. Instead of asking the model to “write some marketing content,” you could specify, “Please draft a compelling product description for our new line of ergonomic office chairs.” 

The more detailed your prompt, the more aligned the output will be with your marketing objectives. You can mold the AI’s responses by requesting specific tone, telling it who your target audience is, and describing the way the finished content will be used.

Being specific is crucial when you’re dealing with business data analysis. For instance, if you’re looking to understand quarterly sales data, asking “Provide insights into Q2 2023 sales data for our software products” will yield a more focused and actionable analysis than a vague query like “Tell me about our sales.”

The deeper you drill down into details, the more insights ChatGPT can provide, as long as the broader context is available to work from.

Iterative process and feedback

ChatGPT learns from the feedback you provide, which is invaluable when you’re iterating on complex projects like a business proposal. If the initial draft isn’t aligned with the client’s needs, you can refine your prompt or provide additional context. 

For example, if the first draft is too technical, you could say, “Revise the proposal to focus more on business outcomes and ROI.” Or, you could reference a particular sentence, paragraph, or section and say, “Expand on this statement by providing two examples of how it can be applied by HR professionals.”

Chain prompts for contextual outputs

Chain prompts allow you to build upon previous queries for more nuanced and contextual outputs. 

For instance, after generating a list of potential leads, you could ask, “What would be an effective email subject line to engage these leads?” The model, remembering your previous query, can suggest a subject line that aligns with the type of leads you’re targeting. 

Used in conjunction with iterative feedback, chain prompts can produce exceptional results with a little time and effort.

Identifying opportunities for generative AI: a framework for success

Understanding what machines excel at versus human capabilities is crucial when considering the implementation of generative AI. When evaluating tasks for automation, three key factors come into play: repeatability, scalability, and data orientation.

Repeatability

Tasks that are repetitive and follow a set pattern are prime candidates for automation. Generative AI excels in these areas because it can execute the same task consistently without fatigue or error, provided the task is well-defined. 

For example, if you’re looking to automate the generation of monthly reports, generative AI can be programmed to pull the same types of data and format them in a consistent manner, saving valuable human hours.

Scalability

Another factor to consider is scalability. If a task needs to be performed on a larger scale, generative AI can easily handle the increased workload without requiring a proportional increase in resources. 

For instance, customer service chatbots powered by generative AI can handle hundreds or even thousands of queries simultaneously, providing quick and consistent responses. This is something that would be incredibly resource-intensive if done by human agents.

Data Orientation

Generative AI shines in tasks that are data-oriented. These are tasks that require the analysis or interpretation of large sets of data. 

For example, generative AI can sift through vast amounts of market research data to identify trends or patterns, tasks that would take a human analyst a significant amount of time. The AI can then generate summaries or even predictive models based on this data, aiding in decision-making processes.

The transformative potential  

Generative AI and ChatGPT are not just technological novelties; they are tools that are already significantly impacting how we work and innovate. To truly grasp the transformative power of these technologies, we invite you to dig deeper by watching a comprehensive webinar that covers these topics and includes live demonstrations: How to Unlock Productivity and Innovation With Generative AI and ChatGPT.

By embracing these advancements, you’re not just staying ahead of the curve; you’re shaping it. Welcome to the future.

Former Senior Cognizant Executive to join Cprime as President and Member of the Board of Directors

Posted on September 13, 2023 by - Company News

Srinivasan Veeraraghavachary named Cprime’s President, bringing tech leadership experience to accelerate growth

 

CARY, NC, September 13, 2023 — Cprime, a leading provider of agile ways of working and technology consulting services, today announced the appointment of Srinivasan Veeraraghavachary as the company’s President and member of its Board of Directors.

Srinivasan Veeraraghavachary, a seasoned leader in the technology consulting sector, has joined Cprime as our new President and a member of our Board of Directors. This appointment comes at a time when we are actively expanding our services and entering new markets.

Mr. Veeraraghavachary previously spent more than two decades with Cognizant (Nasdaq: CTSH), holding several leadership positions, including most recently as Chief Operating Officer and Executive Vice President. During his tenure at Cognizant, he played a key role in driving strong and sustainable growth by defining go-to-market strategies, initiating and deepening relationships with customers, and driving best-in-class execution. Prior to assuming his role as Chief Operating Officer, Mr. Veeraraghavachary was responsible for several scaled business units within the organization and managed several strategic client relationships.

He joins Cprime on a full-time basis during a new chapter of growth for the company. In January, Cprime announced a majority investment by Goldman Sachs Asset Management and Everstone Capital, and the company is currently expanding its footprint into new technology services and global markets.

“We are thrilled about Mr. Veeraraghavachary joining Cprime’s Board,” commented Harsh Nanda, Partner and Head of Technology for Private Equity within Goldman Sachs Asset Management. “As a highly respected technology executive with decades of experience, he brings a blend of strategic vision, significant experience in scaling businesses, and focus on operational excellence to Cprime. With his successful track record of growing technology consulting businesses and driving organizational and operational execution he will be an important addition to Cprime’s leadership team.”

“We are excited to welcome Mr. Veeraraghavachary to Cprime,” said Zubin Irani, CEO of Cprime, and Gerald Attia, Chairman of the Board of Directors. “His extensive background, strong leadership skills, and client-centric focus align perfectly to Cprime’s mission to provide clients a more productive future where process and technology converge for better results and increased speed to market. We are confident that he will play a key role in driving our company’s growth and delivering exceptional value to our clients.”

“I am honored to join Cprime,” said Mr. Veeraraghavachary. “Cprime is a highly respected company and a leader in driving digital transformation via the implementation of Agile and DevOps frameworks for its clients. I am excited about the opportunity to join Cprime’s talented management team and use my experience to contribute to the next chapter of Cprime’s expansion.”

About Cprime

Cprime is a full-service global consulting leader helping clients modernize ways of working and gain the best out of their processes, people, and technology to innovate and thrive. Cprime’s team of experienced practitioners help businesses achieve agility, improve visibility and alignment, speed time to market, and realize significant operational and cost saving improvements. With over 20 years’ experience, Cprime is trusted around the globe to provide strategic, agile, and technical consulting, coaching, and training to businesses leading their industry in digital transformation.

To learn more visit http://www.cprime.com and LinkedIn.

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Media Contact
Lisa Flattery, Cprime, lisa.flattery@cprime.com