The Future of VSM with AI - Finding the Human Touch in an Automated Age

Authors: Ravi Sawant, Sharat Kunduru

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Overview

The world of Value Stream Management (VSM) is constantly evolving, with technology playing a major role in shaping its future. In this article, we'll explore some exciting emerging technologies, like AI and automation, that are transforming VSM capabilities. We'll also discuss the importance of striking a balance to ensure the human experience remains an essential part of the value creation process.

VSM in the Digital Age?

We've seen in our earlier articles that value streams exist in every organization, regardless of whether they consciously leverage the power of VSM. However, the complexities of these value streams are growing exponentially across organizations of all sizes and industries in the digital era. Managing this complexity is highlighted in reports from leading consultancies like McKinsey & Company.?These reports emphasize the challenges posed by the proliferation of digital channels, diverse partnerships, and the abundance of data sources involved in delivering value. Such dynamics contribute directly to the increasing number of touchpoints within value streams, underscoring the critical need for effective management and optimization strategies.?

Even a simple development value stream these days could have multiple agile teams, at least a handful of work planning systems, a plethora of development and QA platforms across public and private clouds, security tools, multiple CI/CD pipelines, and tens of environments — all of which generate vast amounts of data. This data needs to be integrated seamlessly to make sense of it and ensure a consistent flow of value.

To address this growing complexity, organizations adopting VSM are increasingly focusing on more advanced VSM tools and platforms. These tools promise niche capabilities to make data collection and analysis, integration, and visualization more efficient and insightful than ever before. AI plays a major role in enabling these niche capabilities in most of the VSM platforms we have today.

In the next section, we'll explore how AI is transforming VSM in the digital age.

The Rise of AI

AI today is revolutionizing every facet of business and consumer life. Integrating AI into VSM solutions can provide significant benefits. AI's ability to analyze vast amounts of data to identify patterns, predict trends, automate repetitive tasks, detect bottlenecks, recommend process improvements, and even simulate scenarios can exponentially improve the adoption of VSM solutions and optimize value streams.

Leveraging AI is transformative not just for building AI-enabled VSM products and solutions, but also for channeling these products and solutions to unlock new efficiencies and capabilities in various personas and roles involved in a value stream. This is what we call enhancing the human experience — helping people do more productive and satisfying work, enhancing their critical thinking abilities, and increasing collaboration, while letting AI augment and complement the human experience.?

AI Augmenting Human Intelligence

We've already spoken at length about how AI can bring modern capabilities to VSM solutions in our previous VSM platforms article. Here, we'll focus on how such AI-enabled VSM solutions transform the human experience in a value stream by augmenting and complementing the capabilities of various personas. We will discuss this by taking examples of three very important personas in a value stream, though AI can positively influence nearly every persona involved.

Portfolio Leaders:

In a value stream, business portfolio leaders are responsible for overseeing and optimizing multiple initiatives to maximize value delivery. They often face challenges with prioritizing and balancing a portfolio, optimally allocating scarce internal resources, aligning the portfolio with business strategy, and managing portfolio risks. With the increasing complexity of organizational processes, systems, and the ever-changing market landscape, portfolio leaders today are presented with tons of data points from their teams.

Analyzing all that data and making effective decisions becomes humanly impossible, especially when data from multiple teams or departments is siloed and doesn’t tell the same story.

That’s where AI can play a crucial role. For example, given the right inputs, AI can prioritize initiatives based on value, risk, and strategic alignment, facilitating more effective portfolio balancing. It can also optimize resource allocation across the portfolio by analyzing historical data and current needs, ensuring optimal use of resources. AI algorithms can assess and predict potential risks across the portfolio, enabling proactive risk mitigation strategies. Additionally, AI can integrate siloed data from multiple teams, creating a single source of truth.?

Another significant outcome of leveraging AI is its potential to eliminate human biases in decision-making. We've all encountered situations where teams present business cases with inflated ROI numbers or exaggerated risks, influencing portfolio leaders to act in their favor. Moreover, there are often instances where project statuses are inaccurately reported as green, masking underlying issues that could jeopardize success. These discrepancies may seem trivial, but they can perpetuate a culture of misguided priorities within an organization.

AI addresses these challenges by validating the accuracy of data points, ensuring decisions are grounded in precise and objective information. By doing so, AI empowers portfolio leaders to make informed decisions that align with strategic objectives and bypass the pitfalls of biased reporting. This capability is crucial in steering the organization towards sustainable growth and operational excellence.

With such rich insights available, portfolio leaders can make higher-quality, more reliable business decisions, thereby improving overall portfolio performance. With AI doing most of the data groundwork, they can spend more time in customer conversations, building new partnerships, and analyzing market trends to proactively identify future opportunities for the organization. They can also spend more time coaching and mentoring teams and improving collaboration and communication between them. This is how AI can elevate the experience and productivity of portfolio leaders.

PMO, EPMOs & Agile Structures:

PMOs, EPMOs, and Agile frameworks all play pivotal roles in value streams, encompassing strategic oversight, governance, process optimization, delivery, and compliance. However, roles in these structures face significant challenges in keeping pace with the rapid changes within organizations today. Projects must continually adapt to shifting market demands, placing increased pressure on these entities to maintain adaptability while upholding essential governance and controls for data security. There is also a growing demand for real-time data, leading to these structures spending excessive time on data collection and analysis.

Enterprise Project Portfolio Management (EPPM) and Strategic Portfolio Management (SPM) tools have significantly aided these structures recently with advancements in their capabilities. However, AI presents an opportunity to exponentially enhance their efficiency. With advancements in big data and machine learning (ML), data collection and analysis have become more streamlined. AI-powered automation can now handle routine tasks such as status updates, forecasting, progress tracking, and report generation. Predictive and prescriptive analytics can proactively identify risks and even recommend mitigation strategies. Additionally, virtual assistants fueled by generative AI offer conversational interfaces for comprehensive project management.

For example, my team recently assisted an IT division in a large manufacturing organization to simplify and optimize their complex value streams. Previously, approximately 10,000 project status slides were manually generated each month to report on nearly 2,000 active projects across multiple value streams — a time-consuming and subjective process that yielded outdated insights. By adopting an AI-enabled VSM platform, we automated data collection, aggregation, analysis, and visualization of status reports. This transformation significantly boosted productivity, freeing teams from laborious tasks to focus on strategic initiatives. It also enhanced the quality of insights, improving decision-making capabilities.

This shift — from report generation to strategic oversight — fostered a more positive work environment, promoting innovation and ensuring project success within the organization. 'Automate to liberate' became the guiding principle in this transformation.?

AI has the potential to alleviate these structures from operational and administrative burdens, which understandably raises concerns about roles redundancy. However, this transformation fosters increased collaboration, critical thinking, and innovation as these roles shift focus from routine administrative tasks to their original intended strategic endeavors – high value and innovative work. Teams can now dedicate themselves to project leadership, stakeholder engagement, gaining deeper insights into customer needs, team coaching, and customer relations — core responsibilities that are often overshadowed by administrative demands. Similarly, these structures can embrace servant-leader roles, empowering teams, fostering collaboration, and championing best practices. This approach enhances organizational efficiency and nurtures a culture of success and innovation.

Software Development Teams:

The benefits of AI-enabled value streams also extend to the work execution stage, where software development teams are increasingly leveraging no-code/low-code AI platforms, advanced test automation tools, automated deployment processes, and autonomous software maintenance capabilities that detect and resolve issues autonomously.

Similar to earlier personas in the value stream, AI can profoundly impact the overall experience of software development teams. It automates tedious and repetitive tasks such as code reviews, testing, and debugging, significantly reducing the time teams spend on these activities. This automation allows them to redirect their efforts towards solving complex problems and innovating to create superior software solutions.

The Efficiency vs. Experience Trade-off

As demonstrated in the examples above, leveraging AI can exponentially enhance productivity for various personas in VSM. AI automates routine, mundane, operational, and administrative tasks while providing deep insights through the analysis of vast amounts of structured and unstructured data — tasks that would be impossible for humans to handle alone.

However, it's crucial to remember that AI should always complement and augment human capabilities, not replace them. There's a significant risk in organizations becoming overly reliant on AI to eliminate human intervention in pursuit of short-term efficiency. In this race for higher efficiency, we must prioritize maintaining a focus on human experience.

All these technological innovations, from AI to the development of new products and services, are ultimately crafted for human consumption and for the betterment of humanity. At the heart of it all, humans are the end users and beneficiaries of these advancements. You can't remove humans from the equation of serving humanity — it's essential to prioritize the human element in every technological stride forward.

AI and humans possess unique qualities that, when integrated, can achieve remarkable results. AI excels in accuracy, reliability, and speed compared to humans, yet it lacks the emotional, moral, ethical, social, and cultural sensitivity crucial for navigating diverse and nuanced situations. Human experience, on the other hand, thrives on collaborative efforts and the ability to navigate the complexities of workplaces with empathy and intuition. Moreover, while AI systems rely on the data they are provided, human experience empowers individuals to dynamically anticipate and adapt to evolving circumstances, enabling thoughtful and informed decision-making when supported by AI.

This synergy between AI and human capabilities not only enhances efficiency but also enriches the overall human experience within organizations, fostering a balanced approach that values both technological advancement and human ingenuity.

The Seinfeld Connection

Recently, I had the opportunity to attend Duke's commencement ceremony, where Jerry Seinfeld delivered the commencement speech. He poignantly captured this sentiment when he said,

"Making work easier. This is the problem. We are so obsessed with getting to the answer, completing the project, producing a result — these are all valid pursuits, but they do not encompass the richness of the human experience."

This idea deeply resonated with me. It made me reflect on how everything we learn and the wisdom we accumulate stem from our personal journeys of attempting, failing, succeeding, and evolving along the way. I often contemplate the motivations and passions that drive me, the small victories that bring happiness and purpose to my work. These elements form the essence of our growth and fulfillment, often unnoticed in their daily impact. If AI can expedite these essential aspects of human experience and learning, will it diminish the joy and sense of purpose that these experiences bring?

Over-relying on AI could prove detrimental to humanity. Without nurturing the human experience, we risk becoming excessively dependent on AI even for basic tasks, gradually diminishing our collective knowledge and wisdom. This challenge is critical and demands a concerted effort to strike a perfect balance. We cannot afford to falter, as the future of generations and the essence of the human race are at stake.

Beyond the Answer: The Value of the Journey

Seinfeld argues that the true value lies in the "expenditure of energy" the process of working through challenges, collaborating with colleagues, and navigating the complexities of work. While AI can streamline routine tasks and provide valuable insights, it shouldn't eliminate these human experiences entirely. VSM should embrace AI technology to free up human resources to focus on the creative problem-solving, critical thinking, and team collaboration that are essential for continuous improvement in the long run.

This idea can be better illustrated through practical examples involving the VSM personas we discussed earlier. Consider the Portfolio Leader persona leveraging AI to analyze the performance of portfolio initiatives within the value stream. The AI-powered VSM platform aggregates data from various sources, providing rich insights on the current status of each initiative and predictive analytics on potential risks. The Portfolio Leader can use this data to collaborate with the teams leading the initiatives, understand root causes, explore solution options, plan future interventions to prevent issues, create action plans, and offer necessary assistance. All these activities rely on collaboration, judgment, leadership skills, and managing complex human factors — enhanced by AI insights but fundamentally human-driven.

In another example, consider the PMO from the same value stream, tasked with optimizing people allocation to increase overall efficiency. The PMO utilizes AI-powered VSM platform capabilities to determine current allocations, forecast future demand and capacity by skills and region, and receive recommendations for optimal allocations. While AI can suggest ways to improve efficiency, the PMO must still consider team dynamics before making staffing decisions. After all, people are social beings whose emotions and perceptions greatly influence team outcomes—something AI cannot drive, only humans can.?

The bottom line is that relying entirely on AI for decision-making can lead to a loss of human intuition and judgment honed over years of experience. AI operates purely on data and algorithms and cannot replicate this human ingenuity.

So, what’s the recommended way forward?

Finding the Balance

The future of VSM lies in finding the right balance between leveraging technology's efficiency and embracing the richness of the human experience to drive continuous improvement. Imagine a scenario where AI analyzes vast amounts of data to identify a potential bottleneck in the value stream. Human expertise then comes into play to delve deeper, understand the root cause of the issue, and brainstorm creative solutions within the context of our constraints and challenges, including emotions, societal factors, fairness, and ethical and moral considerations.

VSM shouldn't treat bottlenecks solely as digital problems. Human understanding is crucial to consider the broader impact on people and processes. The goal is to develop solutions that address not just the immediate problem but also contribute to long-term improvements in the overall process, accounting for the human element and its various complexities. By doing so, we ensure that our approach to VSM remains holistic, integrating the strengths of both AI and human insight to foster a more effective and empathetic workflow.

Preparing for the Future?

The future doesn't belong to AI alone; it belongs to enhancing the human experience by augmenting our capabilities with AI. As the famous saying goes, "AI will not replace humans, but humans who leverage AI will replace humans who don't." This highlights the importance of embracing AI while keeping the human element at the forefront.

One approach to ensure a people-focused VSM platform is to leverage Human-Centered AI (HCAI) principles. Frameworks like Google's Design HCAI, Ethics Guidelines for Trustworthy AI by the European Commission, and The Human-Centered AI by Stanford provide guidance for designing AI systems that prioritize human needs and values. These frameworks emphasize aspects like fairness, transparency, user-centered design, and ensuring that AI benefits society as a whole.

By following these HCAI principles, VSM solutions can be designed to complement and augment human abilities rather than replace them.

Another key factor for building trust in AI-powered VSM solutions is explainability. Imagine VSM platforms where we don't just see the outputs generated by AI (e.g., recommendations related to funding a portfolio), but we also understand the reasoning behind them. This transparency will increase human confidence in AI platforms and allow for further fine-tuning for better results.

Start by fostering a culture of continuous learning within your organization. Encourage everyone to stay updated on advancements in VSM and AI. This growth mindset will empower your teams to leverage AI effectively and adapt to the ever-changing business landscape.

Let's conclude with another insightful quote from Seinfeld:

"We're smart enough to invent AI, dumb enough to need it, and still so stupid we're not sure if we did the right thing!"

Let's ensure AI empowers us and enriches the human experience, rather than replacing it!

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