Tag: leadership

  • The Practicalities of Open Sourcing

    The Practicalities of Open Sourcing

    I’ve been deeply immersed in the world of developer products for the past decade, and let me tell you, I’ve been quite the open source enthusiast. Over the years, I’ve had the pleasure (and occasional pain) of shepherding open source projects of all shapes and sizes. It’s almost become a rite of passage in some teams – the moment when your APIs and libraries step into the spotlight. After all, customers want to know what kind of software is going into their code concoctions. But, let’s be real, I’ve also witnessed open source used as a bit of a smoke-and-mirrors exercise. So, if you’re contemplating the daring act of open sourcing your projects, here are some things to know before you set out.

    Manage Your Expectations of External Contributions

    If I had a penny for every open source manager disappointed by unrealistically high hopes of a flood of external contributions, I’d have enough pennies to… well, still not meet those expectations. The truth is that the majority of open source projects never witness a bustling community of external code contributors. Just because your software is popular doesn’t guarantee open source success. Open source is like nurturing a garden; it takes time and effort to grow. Building a community involves shaping your APIs, fine-tuning functionality, defining boundaries and managing expectations. Expecting an avalanche of external contributions in the early days is a recipe for disappointment.

    OSS can be Intimidating

    While developers generally relish the idea of sharing their work with the world, I’ve stumbled upon situations where junior engineers were a tad shy about coding in the public eye. In some cases, we’ve had to delay open sourcing because engineers wanted to tidy up their work before unveiling it to the world. Especially if your team is a mix of early-career engineers, it might be easier for senior team members to offer coaching and conduct code reviews in a more private setting without the intimidating public glare.

    Issue Triage and the Support Price Tag

    In theory, maintaining a public issue tracker is distinct from open sourcing the code itself. In practice, these two are closely linked. Opening up your product’s priorities to the public means putting them on display alongside real interactions and feedback from customers. This doubles the importance of being responsive to customer issues, efficiently triaging them, and setting the right external expectations. For successful open source projects, this is a genuine labor of love.

    The Need for a Private Mirror

    There comes a time when you need to work on something in private, perhaps in preparation for a grand launch event. Unfortunately, last time I checked, GitHub doesn’t offer private branches. You might find yourself wrestling with the challenge of setting up a private mirror. What happens when you’re juggling a significant launch on an internal mirror while simultaneously managing customer bug fixes on the open source repository? Mirrors are like trying to keep two squirrels synchronized – challenging.

    Saying Goodbye to Obscurity

    Some software on the internet relies on obscurity for its security. Open sourcing it would be like sending hackers an engraved invitation to a party they don’t need directions to.

    Unfriendly Dependencies

    If your project is tangled up with third-party libraries sporting licenses that are less open source-friendly than a cactus in a desert, you’re in for a headache. I sincerely hope you don’t run into this, as unfriendly licenses often come hand in hand with unfriendly people.

    Navigating the Ecosystem: Dealing With Dependency Upgrades

    Open source codebases often face a common challenge – the relentless pressure to keep dependencies up to date. This is especially true for libraries and APIs embedded in customer applications, where managing transitive dependencies and supporting older versions can be a delicate balancing act.

    Teams typically adopt one of two approaches. Some isolate these dependencies in a separate namespace to avoid conflicts, while others enforce a policy to always use the latest versions. Regardless of the chosen method, open source projects frequently encounter external contributions aimed at upgrading dependencies. Handling such contributions publicly, and sometimes declining them, can be a tricky task.

    Maintainers must navigate this terrain diplomatically, explaining that the proposed change might not be suitable for all users by paraphrasing, “You’re not our only customer, and this could affect many others.” This balancing act showcases the challenges of maintaining open source projects in a dynamic ecosystem.

    Unexpected Benefits

    Now, let’s not forget the unexpected perks I’ve stumbled upon during my open source adventures. After all, I’ve done enough complaining.

    ● Modernization: Open sourcing often nudges you to modernize your build and deployment pipelines because, frankly, it’s easier to get them right than to get them wrong.

    ● Privacy and security: Open sourcing can make addressing questions about privacy and security a breeze. In an era of regulatory crescendo, it’s your golden ticket to showcasing your data-handling ballet. It’s like saying, “Hey, world, check out our moves!”

    ● Building trust with customers: I’ve found some outstanding team members through successful open source projects.

    ● Trust in open standards and code: Organizations are increasingly placing their trust in open source software. Your larger customers might care about this more than you’d imagine.

    And that’s a wrap, folks. Best of luck with your open source journey!

  • Leading DevOps Transformations With AI

    Leading DevOps Transformations With AI

    In my recent article Revolutionizing the Nine Pillars of DevOps with AI-Engineered Tools, I explained that AI-engineered tools can help with automating repetitive tasks, improving decision-making with predictive insights and facilitating proactive issue resolution. AI can drive a higher level of quality, security and performance in the software life cycle. Leadership, the first of the nine pillars of DevOps, is the catalyst for a successful DevOps transformation using AI-engineered tools. It’s the guiding force that brings about the alignment of people, processes and technology in the pursuit of continuous delivery and operational excellence.

    How AI-Engineered Tools Assist DevOps Leaders

    Vision and Direction: Leaders define the vision and strategic direction for a DevOps transformation. They set expectations, define goals and align all stakeholders around a common purpose. By clearly articulating the benefits and objectives of the transformation, leaders can secure buy-in from the whole organization and guide their teams toward success. AI can provide data-driven insights to assist in strategic planning and decision-making. By analyzing historical data and current trends, AI can help leaders make informed predictions about the future and set the direction accordingly.

    Cultural Change: DevOps is not just about technology, it’s about changing organizational culture. Leaders are instrumental in driving this change. They model the collaborative, open and learning-focused culture that DevOps requires. They facilitate communication and collaboration across traditionally siloed teams and encourage a mindset of shared responsibility for product quality and customer satisfaction. AI tools can facilitate collaboration and knowledge sharing, helping to break down silos. These tools can enhance communication, support shared workspaces, and even analyze team dynamics and communication patterns to provide suggestions for improvement.

    Resource Allocation: Effective leaders ensure teams have the necessary resources, including tools, training and time to successfully adopt DevOps practices. They advocate for their teams and prioritize investments in areas that will maximize the benefits of DevOps, such as automation tools or cloud services. AI can assist in optimizing resource management. Predictive analytics can help leaders identify where investments will yield the greatest return, and automation can free up team members’ time to focus on high-value tasks.

    Risk Management: Leaders play a key role in managing the risks associated with a DevOps transformation. They set the pace of change, balancing the need for speed with the need to maintain stability and security. They make tough decisions about when and how to deploy new practices or tools and they are prepared to deal with setbacks or failures as opportunities for learning and improvement. AI can play a crucial role in identifying and mitigating risks. By predicting potential issues in the development and operations pipelines, leaders can take preventative action. AI can also improve incident management, speeding up the detection and resolution of issues.

    Continuous Improvement: The nature of DevOps is iterative and based on continuous feedback and improvement. Leaders need to instill this principle within their teams, emphasizing the importance of regular reflection, learning, and adaptation. Leaders can drive ongoing improvement and innovation in their DevOps practices by fostering an environment where experimentation is encouraged and failure is seen as a learning opportunity. AI can support continuous improvement by analyzing performance data and identifying bottlenecks or areas for improvement. AI-powered analytics can turn raw data into actionable insights, helping leaders understand the impact of their actions and make informed decisions about future changes.

    Risks of Not Leading With AI-Engineered Tools

    In an increasingly digital world, the use of AI-engineered tools is becoming standard practice in DevOps. While every organization must assess its own readiness and capacity to adopt AI, the risks of not doing so are significant and could impact competitiveness and operational efficiency.

    • Missed Efficiency Gains: AI offers substantial efficiency improvements through automation, prediction and analytics. Organizations not leveraging these benefits could find themselves outpaced by competitors that do.
    • Decreased Competitiveness: AI can enable faster and more reliable software delivery, quicker response to market changes and more efficient problem-solving. Without AI, organizations might struggle to keep up with competitors in terms of innovation and speed to market.
    • Inferior Decision Making: AI enhances decision-making by providing leaders with data-driven insights. Without these insights, leaders might make less informed decisions, potentially resulting in suboptimal outcomes.
    • Reduced Agility: AI can help organizations anticipate and quickly respond to changes. Not using AI may limit an organization’s ability to adapt quickly to new market trends or customer demands.
    • Increased Operational Costs: AI can significantly reduce operational costs by automating repetitive tasks, predicting system failures and optimizing resource usage. Without AI, organizations may face higher operational costs.

    Transformation Roadmap With AI-Engineered DevOps

    The successful integration of AI-engineered tools into DevOps is not a one-time project but a continuous journey of learning, experimenting and adapting. Leaders play a crucial role in guiding their organizations on this journey, and developing their own AI competencies is a key part of that.

    1. Education and Awareness: Begin with enhancing your understanding of AI fundamentals, its capabilities, limitations and implications. This can be done through formal training, online courses, seminars, workshops or self-study.
    2. Identify AI Opportunities: Leaders need to identify areas in their DevOps practices where AI can provide the most benefit. This might be where automation could save time, where predictive analytics could provide valuable insights or where machine learning could improve system performance.
    3. Start Small and Experiment: Begin by piloting AI tools in one or two areas. This provides an opportunity to learn about AI’s capabilities and challenges in a controlled, low-risk environment.
    4. Gather and Analyze Data: Data is crucial for AI. Leaders must ensure their organizations have systems in place to collect, clean and manage data. They also need to learn how to interpret the data and insights provided by AI tools.
    5. Build a Multidisciplinary Team: AI requires various skills, including data science, software engineering and domain expertise. Leaders should aim to build diverse teams and foster a culture of collaboration between these different skill sets.
    6. Scale and Integrate: Once they have seen success with initial pilot projects, leaders can start to scale their use of AI tools and integrate them more deeply into their DevOps practices.
    7. Continuously Learn and Adapt: As with any technology, the AI landscape is constantly evolving. Leaders need to commit to continuous learning and stay updated with the latest trends, tools and best practices.
    8. Develop Ethical and Responsible AI Practices: Leaders should ensure AI is used responsibly within their organization, considering aspects like data privacy, transparency and bias. They should create guidelines and practices for ethical AI use.

    Pitfalls and Challenges

    By being aware of potential pitfalls and planning for them in advance, leaders can increase the odds of a successful implementation of AI-engineered tools in their DevOps practices.

    Resistance to Change: Implementing AI tools often requires significant changes to workflows and practices. This can be met with resistance from team members. Effective change management practices can help overcome this resistance. Communicate the benefits of the change, provide ample training and support and involve team members in the process.

    Data Privacy and Security Concerns: AI tools often rely on access to sensitive data, which can raise privacy and security concerns. Develop and adhere to strict data management policies, ensuring compliance with all relevant privacy and security regulations. Use secure AI tools that offer robust data protection features.

    Skills Gaps: Implementing AI tools often requires skills that existing team members may not have. Invest in training for your team, hire new staff with the necessary skills or bring in consultants or external experts to help.

    High Expectations: AI is often perceived as a magic bullet that will solve all problems. This can lead to unrealistic expectations and eventual disappointment. Set realistic expectations about what AI can and cannot do. Communicate clearly that AI is a tool that can enhance efficiency and effectiveness, but it requires human oversight and cannot replace all human tasks.

    Choosing the Wrong Tools: With so many AI tools available, it’s easy to choose ones that aren’t a good fit for your organization’s needs. Carefully evaluate potential tools based on your specific needs and constraints. Look at factors like compatibility with existing systems, ease of use, scalability and vendor support.

    Lack of a Clear Strategy: Implementing AI tools without a clear strategy can lead to disjointed efforts and wasted resources. Develop a clear strategy and roadmap for your AI implementation. This should outline your goals, the steps to achieve them and how you will measure success.

    Summary

    Leadership plays a crucial role in the successful transformation and adoption of AI-engineered tools in DevOps practices. The journey involves educating themselves about AI, identifying suitable opportunities, experimenting with AI tools, gathering and analyzing data, building multidisciplinary teams, scaling AI usage and promoting ethical AI practices. However, challenges like resistance to change, data privacy and security concerns, skill gaps, high expectations and selecting the right tools can be encountered. These can be mitigated with effective change management, strict data policies, training and hiring strategies, setting realistic expectations, careful tool evaluation and a clear AI implementation strategy.

  • How to Supercharge Your Engineering Teams

    How to Supercharge Your Engineering Teams

    With the economy still bleak, data and engineering teams that were already struggling to keep pace with business needs are now facing a potential hiring freeze or worse in 2023. That’s why there’s never been a more important time to maximize the productivity and impact of your teams, but the question is how to identify the big changes that move the needle in performance. Incremental adjustments that save a sliver of time here and there are not hard to come by, but what teams need are the breakthroughs that yield giant leaps in productivity and efficiency. Rather than a 10% improvement, it’s the 10x improvements that drive lasting gains.

    As an engineer and CEO of a software company, I’m constantly looking for ways to boost the productivity of our teams. Our guiding principle is simple: Maximize the impact per hour invested for every individual. To do that, we must ensure that individuals maximize the time spent flexing their superpowers, minimize busy work and reduce dependencies on others that delay work or tie them up in meetings. While counterintuitive at first, we consistently find that collections of well-aligned, independently executing individuals produce a far greater impact than a large team swarming on a project. Put another way; the individual impact goes up when the number of people you depend on to deliver the result goes down.

    I’ve developed an approach over the years that has allowed me to identify several opportunities for step-change advancements in productivity and efficiency, and I’d like to share it here, along with two concrete examples. I will also share an exercise we run with our teams to help identify and execute these opportunities.

    First, here are my two main criteria for identifying the projects and tasks where we can effect changes that will have an outsized impact on the company:

    ● Big resource-consumers: Work that’s essential to the business but consumes a large amount of engineering and other resources is a top candidate for optimization.
    ● Big impact, easy win: Areas that will have a significant impact on company performance if we can do them faster and with higher frequency are also great candidates—even if they’re not consuming a ton of resources.

    Here are two examples that illustrate each of those criteria and where we were able to see massive gains in productivity, quality of service, or both.

    Tackling Big Resource-Consumers

    At Ascend.io, we provide a platform for building and automating data pipelines, which requires us to build connectors into a huge variety of data sources. At one time, building a new connector required multiple engineers to spend two to three weeks writing more than 5,000 lines of code that spanned four microservices in three different languages. As we added more customers and needed to support more data sources, this quickly became unsustainable.

    When we looked at this process, we saw two issues: Engineers were writing custom code for each connector in a way that would be better served by a common framework. Moreover, the process required engineers from multiple teams and disciplines to work together and coordinate their priorities. As soon as you get dependencies that require engineers to coordinate with others and wait on the outcomes of other people’s work, you’re wasting time.

    We addressed this by designing a new development framework that exploits commonalities across the connectors we build. This now requires far less unique code and removes the need for multiple engineers to work together. In most cases, one person can build a new connector in days with 100 lines of code. This made us far more nimble and freed up engineering time to do other valuable work.

    Achieving High Impact

    Like most companies building software, we need to convey the capabilities of our product to new and existing users to ensure they receive maximum benefit from their use of Ascend. With new features and enhancements being released on a weekly basis, there is a lot to keep up with. This is high-impact work, however, and if we can do it in a vastly better way, it drives an outsized impact for Ascend and our customers.

    For us, building these automated product tours typically required a product marketer or product manager to design the customer journey, and one or more engineers on a sustained basis to build the actions into the product. This again creates dependencies that slow progress and require significant manual coding.

    The breakthrough for us was a tool called Intercom, which allows you to build sophisticated product tours without needing to write code. Our product team can now build more interesting and complex product tours for customers, and our engineers can stay focused on building new features instead of the code needed to showcase them. What’s more, they are able to design, test and deploy these tours independent of our product and code deployment cycle, further freeing them to iterate as fast as possible.

    A Thought Experiment

    So how do you actually find these opportunities for 10x improvement? I run the following thought experiment with our teams several times a year to uncover these opportunities:

    Imagine your workload scales 10x overnight and you absolutely must meet this increased need, but without hiring more engineers or working more hours. How do you do it?

    It’s amazing what this exercise can uncover—but there are ground rules and it can take time to see results. Coming up with these big ideas is a skill like any other, and most people are not great at it the first time they try it. Your first iteration may produce no options to pursue—some may have high-impact ideas but with even higher investment requirements, while others may reject the premise outright. That’s normal. So, don’t insist they sit in a room until they dream up that 10x breakthrough, because it will be demoralizing. Instead, plant the seeds by establishing the above framework and then let the ideas start to grow.

    More likely, a few days later, they’ll be out for a hike or chatting with an old co-worker and they’ll suddenly have the germ of an idea. That may still not be the winning solution, but someone else will build on it, and then someone else and, finally, you iterate your way to a breakthrough. Pulling the team back together and embracing the “yes, and” approach can be both energizing and highly productive.

    Brainstorming like this is fast and free, and you only need one great idea to have a material impact. We run this exercise a few times a year and have come up with several big ideas that were game-changers for the company. Besides the examples above, we also moved key parts of our software development from Scala and Go to Python a few years ago, which is a much more efficient language (as measured by developer time) and allows our engineers to build things much faster.

    Software engineering is a complex beast that often spans many teams working on multiple processes in parallel. But that complexity is also your opportunity: Every complex system has room for optimization, especially at companies that moved fast in the beginning to build a product and find market fit. Now is the time to lift your gaze, look around and ask where significant gains can be made. They almost certainly exist, and a 10x improvement could be what allows you to not only survive the turbulent year ahead but emerge with a thriving team and business on the other side.

  • Day in the Life of a Chief Developer Experience Officer (CDXO)

    Day in the Life of a Chief Developer Experience Officer (CDXO)

    Developer experience (DX) has become essential to modern enterprise software development. As more companies become software companies, more are opening up their software both for internal reuse and externalized consumption. As part of this process, making developer-facing tools consumable and friction-free becomes more necessary to both perform well and stand out in the market.

    To oversee developer experience quality within an organization, an entire new role is beginning to emerge — the chief developer experience officer (CDXO). A CDXO is in charge of ensuring the intuitiveness of developer-facing toolsets and being an advocate for engineering needs. Such a focus could improve internal platform usability, like within platform engineering initiatives. Or, it may involve improving the developer experience for public or partner APIs through quality documentation, SDKs, libraries, forums, tutorials and more. A CDXO might interface with many departments to monitor and improve DX across the organization.

    Since the role is in its very early stages, few CDXOs exist. But I tracked down a few to gather insights on the emerging position—I had the unique opportunity to sync with Alessandro Cauduro, chief developer experience officer at Azion and Ivan Burazin, chief developer experience officer at Infobip. They both shared some fantastic insights on why DX is so important these days and what qualities make a good developer experience leader. Below, I’ll distill their wisdom and take a peek into the life of a CDXO.

    Why DX is Important

    First, it’s good to reiterate that developer experience is increasingly important for several reasons. Organizations want to build and ship applications faster and more securely. Yet, it can be difficult for programmers to keep up with new technology trends. “Technology is always changing, and developers are always having to try new things,” said Cauduro. “As a result, you rarely become an expert on a single platform.”

    Developer experience helps you get up and running quickly with new tools. The mindset is similar to user experience (UX) but more applicable to different interaction points like APIs, CLIs, SDKs, VSCode plugins, libraries or other developer-facing technologies. Improving usability for these packages helps ease the daily grind, increases productivity and can be a competitive advantage, said Cauduro. He added that a benchmark of great developer experience is when you don’t even have to read the documentation to understand what you have to do.

    “I think that developers are the lifeblood of innovation,” said Burazin. “They are the ones creating solutions and implementing transformative technologies. Yet, they are often let down when it comes to the tools they use to achieve this innovation, so providing a great developer experience is paramount if we want to foster that innovation as much as possible.”

    CDXO Roles and Activities

    So, what does a day in the life of a CDXO officer look like? What are some of their roles and responsibilities? According to Cauduro, the overarching goal is to put himself in the developer’s shoes—he constantly thinks about common developer workflows and considers how to create a seamless experience throughout the entire development life cycle.

    Next is spreading awareness throughout the company about DX principles and how to increase DX within their offerings. A CDXO will likely answer directly to executive leadership but might interface with many departments. A CDXO may direct teams to construct developer-specific tools, like libraries, documentation, SDKs and self-service environments. “DX is a mindset,” said Cauduro. “The whole company needs to be engaged in it.”

    “As with any C-level position, your job is on the one hand to make your team’s life easier in any way you can,” said Burazin. “And on the other to convey the developers’ issues or ideas to the company in hopes of nudging the company in the correct direction.”

    A CDXO may also oversee developer relations efforts, which focus on fostering a developer community. There are many ways to interface with partners and clients to exchange ideas on how to build against the platform, Cauduro explained. This includes promoting open source projects, encouraging user meetings or interacting on Discord and forums to provide answers to community questions.

    Qualities That Make a Good CDXO

    The CDXO position isn’t for everyone. So, what personality traits make a good candidate for the role? Here are some of the necessary qualifications for the type of work:

    • Experience as a programmer. A CDXO should have past experience as a professional developer. Engineering knowledge will help them understand the persona and empathize with their needs.
    • Leadership qualities. The role also requires leadership expertise, as a CDXO must have the ability to coordinate and influence many different areas of the company.
    • Creativity. Since the role is pretty nascent without a written path, it will require creativity. Having the ability to experiment, accept feedback and reiterate is also important, said Cauduro.
    • Empathy. Communication skills and empathy also go a long way. “Deep engineering knowledge crossed with great people skills is the mix you would need for such a task,” said Burazin.

    Developer Experience in Practice

    At Azion, Cauduro is interested in how its tools can help developers move solutions from the cloud to the edge more seamlessly. To that end, they’ve found that Jamstack fits well with the needs of edge computing. Thus, some of his efforts focus on making the process of deploying a Jamstack app to the edge as seamless as possible for engineers.

    While DX efforts have helped address development bottlenecks at Azion, the role of CDXO may not be necessary within all companies, admitted Cauduro. It’s more of a fit for API-first or SaaS companies that target developers as a primary consumer base. That being said, other companies can still benefit from a developer experience focus to enhance their internal IT platforms.

    At InfoBip, Burazin explained that developer experience efforts center around helping external developers consume the InfoBip API, an API for all communication channels, such as SMS, voice, WebRTC and more. Sitting under the CTO, Burazin helps run three teams and DX has its own department. Impressively, he reports revenue on self-service APIs has increased fivefold in the past two years.

    Burazin, also the co-founder of Codeanywhere, explained that his role is to “convey the worries or needs of the developer customers to management and help steer the ship in the right direction.” To discover those needs, he recommends ‘dogfooding’ what the customer is experiencing and streamlining the onboarding process to be as self-service as possible. He also recommends having measurable insights on metrics you can directly impact, like decreasing time from discovery to ‘hello world.’

    Final Thoughts

    Developer experience is becoming a unique selling point for technology companies—so much so that it’s entered the C-suite. “Whoever has the better DX will have the leading edge,” said Cauduro. For him, it’s about finding small things to optimize that remove pain points from the developer’s process.

    To summarize, the role of CDXO is still evolving and not set in stone. And, granted, many different labels are being applied to describe similar objectives. But to get an idea of what the CDXO role entails, some common activities include:

    • Considering the perspective of the developer.
    • Engaging the entire company to prioritize DX.
    • Overseeing the construction of DX-related assets and resources such as tutorials, documentation and guides.
    • Collecting feedback and reiterating platforms.
    • Overseeing developer relations and advocacy teams.

    Looking to the future, developer experience will likely become more of a necessity as developer-driven purchasing habits become a real revenue driver. “This bottom-up go-to-market motion will help awareness and increase sales,” said Burazin. And, to helm this movement, more companies may adopt DX within a C-suite title. But of course, the role may look different from company to company as DX is applied in different ways.

    “If we look at the largest technology companies, almost all of them have a developer experience department in their organization. And this is due to the fact that so much of a developer’s productivity is directly linked to their experience while working,” said Burazin. Things like internal developer portals and standard cloud deployments will help improve developer experience and help them focus on what they do best, which is coding, he said.

  • Break Open the Black Box of Software Development

    Break Open the Black Box of Software Development

    If you asked an airline executive what their biggest expense was just a few decades ago, they would’ve easily answered, “Jet fuel.” These days, you’d be hard-pressed to find an executive in any industry that wouldn’t answer with, “Software.” But here’s the difference: With jet fuel, that executive would have told you that they can fly x number of seat miles per gallon/liter of fuel (or pounds of fuel, if we’re being technical). With software development, the expense is becoming more material–and far more variable–but the return on that investment is rarely clear. Over the past decade or more, software development has readily assumed its position as the fastest-growing (and often largest) expense line item in virtually every industry. All companies are adding software experiences to or around their products, and they need the people and tools to build, support and continuously optimize those experiences. And that costs money–a lot of money.

    The problem is that the language, the metrics and the world in which software development exists do not translate into operational or financial terms that business leaders can readily understand.

    “We invested X million dollars into software development last year,” a CFO might say. “And what do we have to show for it?”

    Meanwhile, a technology leader might respond with, “We’re doing X deploys a day!” or, “We wrote X thousand lines of code!”

    They might as well be speaking different languages because, in practical terms, they are.

    And the problem is, that you can’t manage what you can’t measure. To continue our airline theme, software development continues to be a ‘black box’—this hidden-in-plain-sight source of information—that financial executives can’t seem to peek into.

    Why the Black Box?

    It’s not likely that technology leaders are being purposefully elusive toward business leaders–it’s more likely that they simply are not aligned on what, fundamentally, they need to do to speak the same language.

    The question at hand is, actually, “Are these investments we’re making turning into our desired business outcomes?” But the question technology leaders feel compelled to answer is, “What do your people do all day?”

    These are questions that Agile and DevOps don’t solve–translating Agile or DevOps metrics (also known as DORA metrics) into actual, actionable metrics for business leaders to understand. Although these metrics are tremendously useful for teams, using them to steer the business is a mistake.

    Misaligned in purpose and using different language, business leaders and technology leaders talk past each other as software development costs continue to rise.

    But the cost of software development is too high for business leaders to continue to tolerate this ‘black box’ of ever-rising costs. It’s the fiduciary responsibility of financial leaders to understand the value of software investments and figure out how they are affecting business outcomes–or their jobs could be on the line.

    In case this seems like a distant threat, it isn’t: I saw a headline recently about a prominent automobile executive who lost their job because they weren’t able to gain the necessary insight into, and business outcomes out of, their significant software development costs and that was affecting the competitiveness of their entire company.

    It’s happening. And it’s on both business and technology leaders to break that black box open and start speaking the same language.

    The next question, of course, is, “How?”

    How to Bridge the Communication Gap Between Technology and Business Leaders

    For far too long, business leaders have made do with the activity metrics provided by technology leaders–they’ve tolerated this lack of visibility and found other ‘strategic’ ways to justify the rising software development costs. Perhaps they’ve been questioning how A leads to B–how an increase in funding for software development might result in greater customer retention or app usage, for example–but they have not had a tangible way to prove to themselves, much less to investors, whether this is actually happening.

    In order to understand and quantify software development costs, we have to start demanding more from our technology leaders: Working with them to establish realistic objectives and key results (OKRs), and holding them accountable to business metrics that actually relate to outcomes. That means insisting on business results–and not accepting activity metrics in their stead.

    Stable-Fund Products, Not Projects

    Here’s a hard pill for finance to swallow: When it comes to delivering software-enabled customer experiences, it’s not about optimizing costs. It’s much more nuanced than X dollars in equals X dollars out. Funding by projects might help make the numbers neat, but it doesn’t reflect the reality of the business.

    Project-based funding also tends to keep project leaders in a cost-center mentality: It makes it seem as though all resources are fungible; as if the work and the people performing it are interchangeable.

    One of the goals of Agile is to maximize value for the customer. But when we fund by project, we often stop funding a piece of work–declaring it done–before it actually starts generating value. We have this false end date that doesn’t reflect the actual ending of the value that we funded to create.

    Instead, finance organizations should move to the stable funding of products: Funding an outcome and giving teams the ability to stop, change or extend their work to achieve the business outcomes of the product.

    This is a shift that one prominent UK bank has been going through in recent years–from traditional portfolio management to lean portfolio management, including the shift to stable-funding projects. You can learn more about how NatWest Group (formerly Royal Bank of Scotland) has made this shift in this webinar.

    Visualize the Flow of Value with Flow Metrics

    Finally, we have to stop treating the collection of technology metrics and business metrics as two separate, unrelated efforts. Agile and DevOps are great at accelerating the throughput of your software development … but vanity metrics around how quickly teams are delivering are not enough to justify the growing and material investment in software development.

    Finance leaders have the opportunity to be the Babelfish between technology leaders and business leaders. As mentioned above, one way to encourage clearer communication between teams is to use OKRs to naturally tie software development objectives to tangible business results. The more we practice drawing connections between technology and business metrics–the closer we get to finally breaking open that elusive black box.

    A key part of this is communicating operational metrics differently: Developing a core set of metrics for tracking the flow of business value in software delivery, and providing a mechanism that correlates the investment in flow for each product’s value stream with the business results for that value stream.

    Visualizing the flow of value in a software development process may not be as easy as watching value flow on a manufacturing floor–but that doesn’t mean it’s impossible. Thanks to the vast number of data and visualization tools at our disposal, it is possible to make software products and their value streams just as visible as production lines.

    The Flow Framework, created by Dr. Mik Kersten, addresses the pivotal challenge of breaking open the black box of software development and bridging the gap between business and technology to optimize the flow of business value to customers.

    Break Open the Black Box with Value Stream Management

    The black box of software development is, at its core, a communication issue. It’s on both business and technology leaders to bridge this communication gap. Business leaders need to demand more from technology leaders and insist on translating activity into business metrics. Technology leaders need to practice tying their efforts to tangible business outcomes to help justify their growing expenses.

    Of course, it’s helpful to have tools purpose-built to facilitate this visibility and communication.

  • Why Your Next CIO Will Be a CPO

    Why Your Next CIO Will Be a CPO

    Here’s what the transition to CPO means for everyone in IT

    Over the last 20 or so years, the evolving role of the CIO, or chief information officer, has been a hot topic of conversation in most large enterprises. It’s a topic that doesn’t just affect those breathing the rarefied air of the C-suite but has concrete implications for everyone in the IT organizations these CIOs lead.

    For these last two decades, most larger companies in traditional industries have vacillated between periods of enthusiasm for technology and so-called “digital transformation”—in which CIOs are viewed as wizards bringing new wonders, changing their entire business models and growth trajectories for the better—and periods of disillusionment, with late projects, missed requirements, user and customer dissatisfaction and cost overruns—in which the CIOs become scapegoats. In these latter times, they often are replaced by CIOs of a different stripe, often moved laterally from finance or general management roles and charged with cost-cutting and predictability as top priorities. Even if the existing CIO keeps their job, they’re often pushed to change the way they operate and lead. When this happens, the entire IT organization finds it needs to change its pitch and priorities to sustain funding for every project and every function, resulting in whiplash. That itself contributes to the perception, and often reality, of late and unfinished projects and unpredictable IT outcomes. It is usually at that point someone realizes the newly efficiency-focused organization is losing market share, brand perception or customers to competitors that are more technically innovative (often digital-first upstarts challenging incumbents in a given industry), and the organization pivots back to “techthusiasm” and a different kind of CIO again. And more whiplash. And so it goes.

    During the periods of techthusiasm, some organizations replace or supplement the CIO title with newly coined titles such as CDO (chief digital officer), CAO (chief analytics officer, an uncomfortable namespace collision with the established corporate title of chief accounting officer), or chief experience officer (no one dares make that into a redundant CEO three-letter acronym).

    In the disillusioned periods, the CIOs stay CIOs as long as they can hang onto their jobs. Title creativity is as suspect as any other kind of creativity.

    Meanwhile the vicious cycle continues: techthusiam -> disillusionment -> retrenchment -> falling behind -> renewed techthusiam.

    As a longtime CPO (chief product officer) for enterprise software companies whose customers predominantly have been these seesawing IT organizations, I’ve been seeing of late the start of a powerful conceptual shift that is the escape route from this vicious cycle.

    So what’s the magic shift in thinking?

    If you’re in a traditional business in which the technology your IT organization delivers merely facilitates people doing their jobs and interfacing with each other and customers, your primary threat in the 2020s—especially with a pandemic interrupting face-to-face interactions—is digital-first, new entrants that conceive of their product as the software and the people as the behind-the-scenes back office and failover when the software doesn’t work. Every business is now a software business, and the software is now the product; some companies in a given industry just happen to be better software companies than others. Such digital-first entrants range from Amazon to Netflix to Workday to Sofi to Wealthfront.

    However, you don’t leap from being ADP to Workday simply through what so far has passed for “digital transformation” led by a CIO, CDO, CAO or whatever another newfangled c-level tech title, as a peer to product leaders whose organizations came from the pre-digital business and look to the CIO, CDO, CAO, etc., to simply execute the technology support.

    What do true software companies in traditional industries have in common? They have CPOs! (Chief product officers, not chief procurement officers or even chief pandemic officers.) Analytics and digital are not in their titles because these are assumed means at their disposal. (I’m thinking of taking on the excesses of our fetish for data in IT and software today in a future column. Send me thoughts if you have them.)

    The role of the CIO was to deploy technology efficiently to support the company’s strategies and plans. The role of the CPO, as inherited from pure technology companies, is to develop and maintain a deep understanding of the customer and market and guide the delivery of products to best meet and monetize their needs, and do so ahead of any and all competition. The traditional CIO derives the why and what from other parts of the organization and supplies the how. Transitional versions of the CIO and the CDO and other neologisms may start to encroach on the what. But the true CPO drives the why and what—and the how if they also have engineering, or collaborates on the how with a CTO or head of development if not. (My friend Kaj van de Loo has an excellent discussion of CPO vs CTO and the trend toward combining the roles here, implicitly focused on digital-first companies, here.)

    Does this sound broad, even encroaching on CEO territory? Well, yes. It’s no accident that former product chiefs are the new CEOs of Google and Microsoft.

    So what does that mean for you if you are in an IT organization?

    Well, first, while your organization may or may not change the actual title to CPO from CIO, it’s important for your career to recognize when the definition of their job becomes that of what a CPO would do in a “pure” software company. If you see the signs that the CPO is guiding the IT organization to become the experts on the market and customers and invent new digital-first products, that shift is underway. It’s good news for those in IT because it means you no longer are simply a cost center to be minimized and even offshored but a driver of the business and value.

    Once you realize you are now in a product organization and not an IT organization, you need to start thinking about what a (software) product actually is and how that differs from what IT delivered before.

    IT traditionally operates on a project and service maintenance basis. Projects have a defined scope and concrete, finite objectives to be considered complete. They have beginnings and ends. Projects either result in the existence of a service that is operated and maintained on an ongoing basis or deliver a discrete set of changes to a service that already existed. Project teams form, deliver the project, and then break up and are reassigned to the next project. Much smaller maintenance teams (usually as low-cost and low-skill as the organization can get away with) make sure that the resulting services stay alive and maintain agreed service levels and consistent, fixed functionality (until the next project to evolve the service is funded).

    True products are quite different. Products have many yearslong life cycles, from inception through launch, constant active enhancements and growth and then eventual end of life. During these life cycles, customers reasonably expect new capabilities to increase and existing capabilities to evolve for better usability and effectiveness.

    Products are not defined by a particular architecture or features but their mission on behalf of the market, users and customers. During a product’s life cycle, the product team may discover new feature ideas or develop new architectural implementations to replace or enhance old ones, all within the umbrella of the same product and mission.

    Product teams maintain staffing levels throughout a product’s life cycle to continue delivering new capabilities and technical enhancements, not just keep the lights on. Every member of a high-performing product team takes the team’s mission as its own and strives to build holistic knowledge of the mission and the product, and contribute new ideas and challenge existing ones—not just a defined role of a product manager or product owner or architect.

    Product teams are acutely aware of competitive and substitute products and strive to become and stay their target customer’s first choice in the face of competitive product teams doing the same. Product teams regard selling, evangelizing and making their products available to their market as being as much a part of delivery as software development and integration. Product teams see opportunities to interact with target users and customers as invaluable two-way dialogue during which they get to show and get reactions to the shiny features they’ve built, as well as discover latent needs that drive ideas for new features and maybe even entirely different conceptions of the overall product.

    In an IT organization that is transforming itself into a product organization, these ideas and this approach apply not just to teams working on “external” products for paying customers outside the organization but also in equal measure to internal products that either serve internal end users, such as a finance or payroll system, or become services that developers on other teams incorporate into their products or platforms on which other developers build, such as a common identity service, customer data pipeline or private cloud. In today’s world, every such official internal service resides in an environment with competitive third-party services and possibly competing internal approaches, and in which what was state of the art yesterday is not viable today.

    Conversely, a well-conceived, designed and managed internal product may turn out to be the basis of a massive external business. Witness AWS and countless DevOps startups that began with the old story, “We built this thing to support our social media/dating/gaming/whatever B2C startup and it turned out to be something other companies wanted to buy more than people wanted what our startup was doing.” Managing internal services and platforms as products is the way to both ensure that the original mission is fulfilled and new opportunities are discovered, too.

    I’ll come back to some of these themes in future columns, but for now, I’ll leave you with this link to a podcast featuring a small Brazilian fintech startup that I believe is one of the best recent examples of a true product team’s approach: Their level of customer intimacy enabled them to identify a new product that solved problems within the scope of their mission and on behalf of their target users that a lesser product team would not have done. How would this kind of product thinking apply to the products in your IT organization?

    Until next time,

    Christina