AI To Disrupt Project Management
Education and Training,
Human Aspects of PM,
Nontraditional Project Management,
Categories: Career Help, Change Management, Cloud Computing, Complexity, digital transformation, Education and Training, Ethics, Facilitation, Generational PM, Human Aspects of PM, Human Resources, Innovation, IT, Leadership, Leadership, Nontraditional Project Management, PMOs, Portfolio Management, Program Management, Stakeholder, Strategy, Talent Management, Teams, Tools
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:
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:
To prepare for these changes, project managers should:
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?
Plan for the Velocity of Change to Keep Increasing!
Human Aspects of PM,
Categories: Agile, Best Practices, Career Help, Change Management, Complexity, Facilitation, Generational PM, Human Aspects of PM, Human Resources, Innovation, Innovation, IT, Leadership, Leadership, Lessons Learned, Portfolio Management, Program Management, Project Planning, ROI, Stakeholder, Strategy, Talent Management, Teams
By Peter Tarhanidis, Ph.D., M.B.A.
Today, developments in emerging technology, business processes and digital experiences are accelerating larger transformation initiatives. Moore’s Law means that we have access to exponentially better computing capabilities. Growth is further fueled by technologies such as supercomputers, artificial intelligence, natural language processing, Internet of Things (IoT) and more across industries.
Business Process Maturity
According to market research group IMARC, automation and the IoT are driving growth in business process management (BPM); the BPM market is expected to grow at a 10 percent compound annual growth rate between 2020 and 2025.
Customer experience is redefining business processes and digitizing the consumption model to increase brand equity. Gartner reports that among marketing leaders who are responsible for customer experience, 81 percent say their companies will largely compete on customer experience in two years. However, only 22 percent have developed experiences that exceed customer expectations.
The Way Forward
I’ve developed a few guidelines to help navigate this change:
Change is now inherent and pervasive in the annual planning process for organizations. Given that, I like to ask: What is the plan to prepare staff and colleagues to compete in this hyper-transformation age?
What observations have you made to keep up with this new era’s velocity of change?
By Christian Bisson, PMP
Machine learning is one of today’s hottest tech topics.
It’s essentially a type of artificial intelligence (AI) in which you give your software the ability to “learn” based on data. For example, you probably notice how YouTube, Netflix, Amazon and many other companies suggests videos or products you should check out. These suggestions are based on your previous online actions, or those of other people deemed “similar” to you.
For some time now I’ve been working on projects that involve this technology. We often have clients who want machine learning even though they do not know if it’s even relevant to them. Since “everyone is doing it,” they want to do it too.
Calibrating a project sponsor’s expectations is often a good idea. While the automated services generated through machine learning may seem magical, getting to that point involves challenges—and a lot of work.
The machine will learn using the data it has being given—that data is the crucial starting point. The data that’s available is what drives how the machine will evolve and what added value machine learning can bring to your project/product. For example, if you are trying to teach the machine to recognize vehicles on images it scans, and all you can teach it with are images of small cars, you are not set up for success. You need a better variety of images.
The machine’s ability to learn is directly tied to the quality of the data it encounters.
Once you have quality data, you need it in high quantities. If you can only provide the machine with the website behaviors of, say, hundreds of users per month, don’t expect it to have enough information to be able to recommend the best products based on user trends. Its sample will be too little to be able to be accurate.
Once you have the necessary data, the journey is not over. The machine may learn on its own, but it’s learning based on how it was built and with the data it’s being fed. There is always room for improvement.
As amazing as machine learning is, it is not cheap. So keep an eye on your project’s budget. Machine learning experts can command high salaries, and there is a lot of effort involved with researching the best approach—creating the models, training them, testing them, etc. Make sure the ROI is worth it.
Have you had a chance to work on a project involving machine learning? What challenges have you faced?
by Christian Bisson, PMP
Several years ago, I decided to put my web developer hat behind me and become a project manager (and eventually product owner). At first I wasn’t sure if I would be up to the challenge given that most project managers have different backgrounds.
But several years later, I don’t regret my decision.
Technical project managers are more present — and required — in the digital world, and I have no doubt that will keep rising. Here’s why.
The Rising Digital World
The digital world is taking up more space in our lives. And it doesn’t stop at what people see, there is also a vast world of data happening behind the scenes.
A project manager that can’t comprehend the technical relationship between every piece of a client’s ecosystem will fail to manage it properly. As ecosystems grow, it will become more of a challenge to ensure teams have the right people at the right time so that everything comes together as planned.
Still, many project managers are not even aware of what a development environment (development, staging, user acceptance testing, production) or even deployments are. Project managers today should know about synchronizing websites, apps and other tools together. If one can’t deploy a site, then there is simply no hope.
A website used to consist of images and text, so not understanding how it worked didn’t matter much if you had the team to compensate.
Today, however, a lot of websites use advanced technologies to provide users with what they want, like powerful search engines or features using machine learning.
Machine learning in particular is becoming the toy every kid wants. It’s also within everyone’s grasp—whether it’s with advanced machine learning expertise or with tools made available by Google, for example. Project managers need to understand this technology in order to bring out its full potential within the projects they manage, otherwise it becomes a trend word that brings nothing to the table.
Everyone knows that communication is key to running any team smoothly. If a project manager can’t understand what the team is communicating, then he or she can’t properly manage the project.
Furthermore, clients are becoming more techy and often have a better understanding of how things work. So if project managers don’t understand the tech behind the project, they can’t have proper conversations with the client. It helps in key project decisions to actually understand what is going on.
What are your thoughts on technical project managers? As the world becomes more digital, are they becoming essential?
By Marian Haus, PMP
Welcome to the age of digital transformation.
New technologies such as 3-D printing, augmented and virtual reality, and digital currencies are becoming commonplace. Connected and autonomous cars, and holographic displays are on the horizon. This is all on top of the various mobile devices—smartphones, tablets, laptops—that we can’t let go of.
All this has changed consumer expectations and behaviors for good. Services must be fast and easy-to-use (RIP user-manual/guide), fully transparent (in terms of product offering, quality, price), always available (24/7) and multi-device accessible (via desktop, mobile, wearables, etc.).
Fearful of being left behind, businesses look to understand and predict consumer needs through deep and semantic web search, machine learning and big data customer analytics.
The Upshot for Projects
But digital transformation is not only changing our lives and disrupting businesses. It’s also reshaping and speeding up project delivery models. The planning and execution of innovative projects in today’s digital era can no longer be done at the same pace, with the same methodologies and tools. To attain increased time-to-market results, speed and flexibility are key—so project managers must adapt their approaches.
So what’s a project manager to do? Here some thoughts.
1) Remain calm and confident! Remember when agile disrupted the well-established waterfall world? Project managers had to adapt their approach, toolsets and methodologies. We can adapt again.
2) Enable organizational and structural simplicity and dynamism. Foster flexible structures, smaller project teams and increasing collaboration within the project team. (Here are some tips on how to set up your team and organization.)
3) Improve execution speed by tailoring and simplifying your approach and methods. For instance, embark on some rapid prototyping as a proof of concept before implementing the final product. Or breakdown the project into several smaller projects that can move independently faster as together.
4) Foster new and innovative ideas. Encourage open-mindedness and increasing failure tolerance.
5) Focus on results, not process. Plans, Gantt-charts, budgets, forecasts, risk plans and stakeholder lists are important. But while prototyping or going through trial-and-error iterations during product development, don’t let methodology and specific techniques get in the way of the needed results.
6) Adapt your communication approach by providing stakeholders with rapid access to real-time project information. For example, establish an online project community that can easily be updated with the latest information. (Here are more ideas on how to improve communication.)
Finally, enjoy the exciting and intense times we leave in, driven by dynamism, innovation and more networking and collaboration than ever.
I’d like to hear from you on how you are managing projects and embracing change in the modern digital age.