Voices on Project Management

By

Peter Tarhanidis, Ph.D.

Project management methodologies have evolved significantly over the years, with waterfall and agile emerging as two of the most prominent approaches. Each has its strengths and weaknesses, making them suitable for different types of projects and organizational needs.

• Waterfall is a linear, sequential approach to project management. It is characterized by distinct phases; each phase must be completed before the next begins with limited ability to revisit or revise previous stages. Waterfall is effective for projects with well-defined requirements and a clear path to completion, such as construction or manufacturing projects.
• Agile is an iterative, incremental approach designed to accommodate change and foster continuous improvement. It emphasizes collaboration, customer feedback, and small, manageable units of work called sprints. Agile is well-suited for projects where requirements are expected to evolve, such as software development or other innovative fields.

Surveys indicate:

• 51% of companies implement waterfall and 71% of companies utilize agile.
• PMI’s 2020 Pulse of the Profession® report Ahead of the Curve: Forging a Future-Focused Culture indicated that 11.4% of investment is wasted due to poor project performance.
• The Standish Group’s CHAOS report showed only a 31% project success rate.
• Harvard Business Review estimated a $3 trillion annual global financial loss, wasted resources, missed opportunities, and negative societal impacts due to project failures.

Given these statistics, you may ask which method is best for a given project. Many organizations find value in blending these methodologies to create a hybrid approach, leveraging the structured planning of waterfall and the flexibility of agile. This hybrid model can offer a balanced framework that enhances efficiency, adaptability, and customer satisfaction.

While waterfall's structured approach provides clear milestones and accountability, its rigidity can be a drawback in dynamic environments. Agile's flexibility and responsiveness to change make it ideal for such settings, but it can struggle with scope creep and lacks the clear, long-term planning of waterfall.

The hybrid approach seeks to combine the best of both worlds, providing a structured framework that remains flexible and adaptable. By relying on a competency and development framework, management can highlight the key components of hybrid—consistently applying best practices to mature success and project outcomes.

Key components of hybrid project management include:

1. Phase-based structure with iterative execution: Projects are divided into phases similar to waterfall, but within each phase, agile sprints are used to execute tasks. This allows for detailed planning and requirements gathering upfront, followed by iterative development and testing.
2. Defined milestones with flexible deliverables: Hybrid project management sets clear milestones to track progress and ensure alignment with overall goals. However, the deliverables within each milestone can be adjusted based on iterative feedback and changing requirements.
3. Customer collaboration and feedback loops: Regular interactions with customers and stakeholders are maintained to gather feedback and make necessary adjustments. This aligns with agile’s emphasis on customer collaboration and helps ensure the project remains on track to meet user needs.
4. Comprehensive documentation with adaptive planning: Initial project documentation and planning follow a waterfall approach to establish a clear roadmap. Throughout the project, adaptive planning is used to refine and update this documentation based on iterative insights and changes in scope.

Steps for implementing a hybrid model:

1. Assess project requirements and environment: Evaluate the project's nature and complexity, and the environment in which it will be executed. Projects with stable requirements and clear end goals may lean more toward waterfall, while those with uncertain or evolving requirements may benefit more from agile practices.
2. Define phases and iterations: Establish major project phases with clear objectives and timelines. Within these phases, implement agile sprints or iterations to manage work increments, allowing for continuous assessment and adjustment.
3. Foster collaboration and communication: Create a culture of open communication and collaboration among team members, stakeholders, and customers. Regular meetings, such as daily stand-ups and sprint reviews, can help maintain alignment and address issues promptly.
4. Balance documentation and flexibility: Ensure that initial project plans and requirements are well-documented but remain open to revising them as the project progresses. Use documentation as a living document that evolves with the project.
5. Monitor progress and adapt: Use waterfall’s milestone tracking to monitor overall progress, and agile’s sprint reviews to assess interim deliverables. Be prepared to adapt plans and strategies based on feedback and performance metrics.

The leadership required in hybrid project management has a blend of strategic oversight and adaptive facilitation to balance the structured rigor of waterfall with the dynamic responsiveness of agile. Effective leaders in this context must embody several key traits and skills to ensure project success:

1. Visionary thinking: Leaders must articulate to the team a clear vision of the project’s goals. They need to establish long-term objectives while accommodating short-term adjustments, maintaining alignment with overall project aims.
2. Flexibility and adaptability: Leaders must pivot between structured planning and iterative development. They must be comfortable with change and capable of guiding their team through unexpected challenges and shifts in project scope.
3. Strong communication skills: Open, transparent communication is essential. Leaders must facilitate continuous dialogue among team members, stakeholders and customers. Regular updates and feedback loops are crucial for maintaining alignment and addressing issues.
4. Collaborative mindset: Encouraging a culture of collaboration is vital. Leaders should promote teamwork, ensuring that all voices are heard and valued. This involves fostering an environment where team members feel empowered to contribute ideas and solutions.
5. Strategic decision-making: Effective hybrid project leaders must be adept at making informed decisions quickly, balancing the need for detailed planning with the flexibility to adapt plans based on real-time insights and feedback.
6. Risk management: Proactively identifying and mitigating risks through both structured risk assessment and iterative reviews is crucial. Leaders must be vigilant and responsive, adjusting strategies as necessary to keep the project on track.

By embodying these qualities, leaders can successfully navigate the complexities of hybrid project management, ensuring that projects are both well-organized and adaptable to change. The overall benefits of hybrid project management provide for:

1. Enhanced flexibility: Combining structured phases with iterative sprints allows for greater adaptability to changes in project scope, requirements and market conditions.
2. Improved stakeholder engagement: Regular feedback loops and collaborative practices ensure stakeholders are consistently involved and satisfied with the project’s direction.
3. Risk mitigation: The hybrid approach can identify and address risks earlier in the process through iterative reviews, reducing the likelihood of major issues arising late in the project.
4. Balanced planning and execution: It provides a comprehensive planning framework while maintaining the flexibility needed for creative problem-solving and innovation.

In conclusion, hybrid project management offers a robust framework that leverages the strengths of both waterfall and agile methodologies. By blending structured planning with iterative execution, organizations can achieve greater efficiency, adaptability, and customer satisfaction, making it a versatile approach for a wide range of projects.

Please share in the comments how your organization defined hybrid project approaches and any case studies that you would like to share.

References

1. PMI Pulse of the Profession®: Ahead of the Curve: Forging a Future-Focused Culture
2. The Standish Group: Benchmarks and Assessments
3. It’s Time to End the Battle Between Waterfall and Agile
4. Agile vs Waterfall: Which Approach Should You Choose for Your Project
5. Waterfall vs Agile Methodology: What’s Better for Your Project?

By Peter Tarhanidis, PhD

Technology has demonstrated tremendous benefits and efficiencies (many of them unstated) over time. The technology lifecyle enhancements that started with our initial computers, software programs and the internet of the past have given way to the modern-day cloud, Big Data and artificial intelligence.

Throughout this maturing landscape, technology has affected all industries—especially how we collaborate. According to Peng (2021), here are some key impacts to consider:

• Digital transformations spending will exceed an estimated $2.39 trillion by 2024.
• Collaborative tools and technologies increased operational efficiency by 131%.
• Technology will displace an estimated 85 million jobs globally by 2025.
• AI augmentation will increase global worker productivity hours to an estimated 6.2 billion hours.

Project management has benefitted from the overall technology lifecycle, either by implementing aspects of it or by being a user of its collaboration outputs. Yet project managers are at the doorstep of being part of the next wave of AI disruption.

What a PM organization must consider is the methods and concepts used in managing past programs and become proactive in shifting to an AI-enabled PM organization. There is no doubt that the role of PMs and our methodology will be augmented with AI-enabled assistance.

PwC identified five areas of AI disruption and decision making in project management:

1. Business insights: Filter data to gain actionable perceptions
2. Risk management: Develop the ability to run multiple risk scenarios and outcomes
3. Human capital: Optimize teams and leverage staff skills or new areas of training
4. Action-taker: Provide analysis and optimization of schedules and staffing needs
5. Active assistant: Augment the collection process of information to generate progress reports

To prepare for these changes, project managers should:

• Invest in data sciences and digital skill sets
• Create a culture that adopts digital disruption
• Enable the use of digital tools and approaches to limit manual efforts and drive value-added work.

In order for these changes to emerge, there are a few considerations that may hold one back from the changes—such as organizational readiness, employee skills assessments, and the state of technical tools.

PwC outlines a change approach to assist in the transition that relies on updating project management strategy, leveraging technology investments, integrating digital and AI, and a comprehensive communication plan to generate awareness through adoption by the future project management workforce.

What other approaches have you used—or should be considered—to manage AI disruption in project management?

Reference:

1. https://www.pwc.com/m1/en/publications/documents/virtual-partnership-artificial-ntelligence-disrupt-project-management-change-role-project-managers-final.pdf
2. https://writersblocklive.com/blog/technology-in-the-workplace-statistics/

As part of starting my technology career, I augmented my undergraduate degree in computer science with a minor in economics. Over the years, I began to appreciate more the inherent wisdom of the demand and supply relationships as it pertains to labor forces. In particular, the laws of economic supply and demand are playing themselves to new heights in these uncertain times.

We see it every day in the news: Jobs by the thousands of all types are going unfilled with nobody stepping forward to fill them. In our industry, we are seeing multiple factors converging to create difficult times for project and product managers. The exponential growth in technology, changing demographics in work forces as well as COVID-19 have all greatly impacted what we do on a day-to-day basis.

For project and product delivery, I am observing that labor shortages that impact our delivery efforts take on two different forms:

1. For new projects and products, the ability to find new resources is extremely difficult. Staffing durations are taking longer and it’s ever more challenging to find skilled, experienced team members.
2. In addition, existing project and product resources are being consistently overcommitted, which leads to multiple negative outcomes—including their potential loss as they explore other options due to burnout.

As a project and product manager, these market conditions create a confounding set of risks that need some refreshed thinking in order to mitigate their impacts. Here are a few of my thoughts on ways we can manage around these challenging times:                                                           

1. Up Your Game on Scope, Schedule and Resource Management
One of the hallmarks of a great project manager is their ability to synthesize threats to scope, schedule and resources. They rigorously examine and take action to curtail creeping scope, aggressively monitor planned versus actual schedule progress, as well as frequently check resource utilization.

In addition to giving more emphasis to these areas than ever before, project managers need to look beyond their project for external threats. By taking more of a portfolio manager mindset and looking for external threats including other projects, they can better anticipate and address challenges to their own delivery commitments.

For high-speed, iterative agile product delivery, labor shortages make for even more challenging times. One of the benefits of a dedicated set of resources for an agile product team is that over time they reduce the learning curve and improve decision-making efficiency. Swapping resources in and out of agile product delivery due to labor shortages creates damaging disruption to both schedule and quality. This environment compels agile product managers to be even more vigilant when it comes to managing scope, schedule and resources.  

2. Get Back to Basics
As the complexity of project and product delivery grew over the years, the amount of supporting reporting, analysis and review meetings grew in lockstep. In addition, the complexity of indicators, metrics, narratives and other project metadata increased as well—the intent being to quantitatively identify delivery volatility before it becomes an issue.

While the increased frequency and depth of examination improves stewardship and has helped with early detection of delivery volatility, in these times there may not be enough capacity to warrant this level of detail.

To help mitigate impacts of labor shortages while not adversely impacting delivery, take a good hard look at the project and product metadata that is currently being produced. For the level of uncertainty and risk on your project or product, can the frequency of reporting, analysis and review meetings be reduced in order to spend more time on activities that directly impact delivery?

For the depth of metadata, explore simplified methods for conveying progress against a plan. For example, the use of additional done/not done milestones to measure progress would take less effort than gathering timesheets to calculate total effort. Rationalizing where it makes sense, the frequency and breadth of supporting metadata creates more capacity for direct project and product activities.

3. Restore Real-Time Individual Engagement as a Norm
People are both the most valuable and the most fragile when it comes to project and product delivery. One of my post-graduate professors in an organizational design class once shared, “The greater the level of uncertainty, the closer the level of interaction is required between people.” Loosely translated for modern times, this means: Don’t try to solve complex problems by email.

Pre-pandemic, there was a lot of personal interaction in an office or site; these days, we rely on online collaboration tools as a primary means of connection and communication. Despite the ability as a group to remotely connect audibly and visually through the use of these tools, difficulties remain in terms of the effectiveness and efficiency of personal engagement, especially at an individual level. Individual connection has always been a means of identifying both new ideas as well revealing challenges that may not arise in a group setting; all the more reason to make it an increasingly frequent activity when managing projects and products.

While modern times present new challenges, it’s still possible to connect on a person-to-person level. Outside of the normal cadence of group meetings, set up recurring individual connection sessions with team members. These can still be done with collaboration tools—but they have all the advantages of what private conversation can provide. I’m finding these individual meetings have a great propensity to really help us understand the underlying dynamics of project and product delivery. (If you happen to live in reasonably close proximity and abide by any local regulations, that doesn’t mean an espresso in person to stimulate conversation would be out of the question!)

These are indeed challenging times, the likes of which I have never before seen in my project and product management career. Labor shortages as well as volatility from resource overcommitments are all causing us to rethink our day-to-day activities on how we interact with people. While we can long for the days when walking down the hall in an office to connect with a team member was the norm, we as project and product delivery managers still need to take steps to overcome these challenges in our drive for successful delivery outcomes.

I welcome any comments on what others are doing to help reduce the impact of labor shortages with creative project and product management techniques. Share your insights below!

By Peter Tarhanidis

Artificial intelligence is no longer a tool we’ll use on projects in the future. Right now, many organizations are formalizing the use of advanced data analytics from innovative technologies, algorithms and AI visualization techniques into strategic projects.

The maturity of advanced data analytics is creating an opportunity for organizations to unlock value. The McKinsey Global Institute estimates AI’s global economic impact could climb to US$13 trillion by 2030.

As an example, in the healthcare industry, Allied Market Research reports rising demand for data analytics solutions due to the growth in data from electronic health records, among other factors. The global healthcare analytics market was valued at US$16.9 billion in 2017, and the report forecasts it to reach US$67.8 billion by 2025.

The Evolution of AI Maturity
Gartner describes four growth stages of analytics and value activities. The first is descriptive analytics, which gains insight from historical data on what occurred in the firm or a project. This includes key performance measure reports and dashboards. Second, diagnostics analytics allow you to learn why something happened and the relationship between events. Third, is the use of predictive analytics to develop viewpoints into potential future outcomes. Finally, prescriptive analytics allow you to provide users with advice on what actions to take.

Everyday examples of these solutions range from simple automated dashboards, remote check deposit, Siri-like assistants, ride-sharing apps, Facebook, Instagram, autopilot and autonomous cars.  

Tips on Successful Transformation
Leaders must consider advanced data analytics as a transformational journey—not a complex project. Without thoughtful consideration of the implications of managing AI projects, one may create chaos in adopting these new services.

As a project leader, take these steps to avoid key pitfalls:

1. Develop your understanding of data science tool kits and technologies and identify any centers of excellence. Start with basics such as descriptive statistics, regression and optimization techniques. You’ll also want to familiarize yourself with technology such as machine learning and natural language processing.
2. Determine how these AI initiatives integrate into the organization’s mission and vision. This may require a new strategic business plan, optimizing an organization, culture change and change management.
3. Establish a data governance body and framework to ensure accountability, roles, security, legislative and ethical management of consumer, patient, customer and government data.
4. Develop strong multiyear business cases that clearly indicate cost versus revenue or savings.
5. Maintain an agile mindset and leverage design thinking methods to co-create the pilots into products alongside stakeholders.

Please comment below on what approaches you have taken to enable advanced data analytics in your role or in your organization.

By Peter Tarhanidis, Ph.D., M.B.A.

Program teams should collaborate like a world-class orchestra.

This ideal state of team engagement and performance requires the presence of several key elements, including an engaged sponsor, a governance committee, a project manager and a status dashboard to communicate performance.

However, maximizing this level of performance is especially challenging when working with cross-functional groups, external stakeholders and shareholders. This increases the complexity of the human performance aspects of team management.

I recall one assignment I worked on that required the team to design and build a new centralized model to bring together three different operations. The team was given two additional challenges. The first challenge was to consolidate disparate teams into two geographic centers. They also had to reduce the overall timeline from 18 months to 10 months.

These challenges exacerbated how teams were not working well with their counterparts. They quickly became dysfunctional and lost their purpose. The project was crashing.

Stepping into this situation I decided to conduct a stakeholder analysis. I used this approach as an intervention method to understand the underlying themes. The analysis revealed the team:

1. Lacked shared values: Members did not have a sense of purpose on the intent of the program.
2. Were not being heard: Members felt they had no control over the program’s major activities or tasks.
3. Lacked trust: Members felt they could not rely or confide in their fellow team members, sponsors or peers to accomplish tasks on the program.

After reflecting on the team’s feedback, I realized that most members wanted to find meaning in their work. It seemed no one was developing their sense of shared purpose and putting their strengths to work toward this program.

I decided I needed to re-invest them as members of the team. To get the team back to performing well, I:

1. Built rapport with various team members
2. Gained their trust by delivering on my commitments
3. Integrated their perspectives into decision making
4. Recruited new members to build up gaps in team capabilities
5. Focused the conversation on our individual purposes and aligned them to a shared value

This approach strengthened the program and delivered on the challenges.  

The lesson learned is, do not simply apply methods and approaches in complex program delivery. Manage the team’s purpose and establish shared values as an important driver of overall delivery.

How do you manage that purpose and invest in high-performing teams?