This question is so common that it seems to be taken from a predefined list of questions from the audience, and it comes up in every course, webinar, workshop and conference I participate in. The need to identify whether being agile, predictive or hybrid represents the solution to all management challenges is always evident.
But behind the question there is a valid concern that all project managers have: How should I manage my project? Is agility the future and will it replace the traditional management model? Is agility the only valid management model in our time? Here I present in detail the different management paradigms, where they come from and the advantages and disadvantages of each one.
Why look for the best project management methodology? Agile, predictive or hybrid
Although the article talks about paradigms, the truth is that methodologies and frameworks assume a context of application - which we formally call paradigm. These contexts can be classified in multiple ways, however, in this article I present the most popular classification model.
Our brain is not designed to make objective value judgments. It is always tempted by the power of comparison - and comparison is something we humans are exceptional at. That simplicity of looking for the best, the prettiest, the cheapest, the fastest and of course the most effective methodological approach is in our DNA. We find it hard to quantify the intrinsic value of things, so we always make a comparison between X or Y according to a certain quality.
I can't claim to be a "pure agilist" or "radical", nor have I been an exemplary traditional project manager who relies on documents, minutes and all kinds of written evidence. Therefore, in this article I invite you to abandon the task of looking for the best or most efficient way to manage a project, and reflect on the meaning and implications of each paradigm, the value and benefits of the practices and procedures we use in each one.
Project manager's toolbox: The Batbelt.
I am a lover of examples and similes. This is one of my favorites. All of us who have ever followed Batman - the fictional character created by Bob Kane in the late 1930s - we know of the existence of the Belt Belt. This belt, which is nothing more than the careful selection of tools and gadgets for a superhero with no powers other than his own conviction, is a great example of what in English we know as ".toolbox"or toolbox.
A good project manager is like Batman, without superpowers, but with the conviction and desire to complete a project successfully. The best project managers I've had the good fortune to share with have at their disposal a toolbox enviable. Likewise, these directors don't waste time choosing one over the other, or the newest, they are simply pragmatic in their choice of tools within a given context.
What are the best tools to manage an agile, predictive or hybrid project?
I should say first that the manager who assumes that one practice replaces another just because it is new or "trendy" is unaware of the value that each tool offers. Each practice, tool or technique has been designed for a specific problem, challenge or opportunity, within a specific context or paradigm.
What we know today as best practices are the result of the work and experience of one or several project managers over several years. So here are 5 tips to consolidate the best tools for your toolbox:
- Don't dismiss a practice without understanding its application paradigm, whether it's agile, predictive, or even hybrid.
- It's no use having the best screwdriver - or screwdriver in my country - if you are unable to identify a screw. Even for those practices that you do not appreciate, consolidate the criteria to define where and when to use it.
- It is worth noting that leading project management institutions such as the Project Management Institute (PMI), the International Project Management Association (IPMA), Scaled Agile (with its framework SAFe) and Advanced Development Methods, Inc. (the company behind Scrum.ORG). A final place of reference could be Management 3.0 which, although it is several years old, still represents an excellent point of reference.
- A good manager knows his or her strengths and feels comfortable in certain contexts. Identify which projects or challenges you like to manage, under which conditions and in which role (director, manager, facilitator or coach). Identify good practices in that context. Specialisation can be a differentiating factor in your professional career.
- Always stay current. Practices evolve, in all paradigms - agile, predictive or hybrid. Join professional associations, interest groups and forums. This is not only useful for the performance of your profession, it is key to job survival (staying current).
Stacey Matrix and Decision Making
I have talked about the importance of the context - paradigm - where project decision making is planned or happens. This is key in finding the right answer to the question agile, predictive or hybrid? So let's get into it.
Ralph D. Staceya former lecturer at Hertfordshire Business School, has worked for years on the study of human organizations and their management models. Within his work more "popular"we found Stacey's Matrix - I clarify that I haven't read all of Stacey's work, so I refer you to the most popular of his publications according to Google.
Stacey's matrix is a graphical representation - derived from his work - that has been adapted over the years to represent the different paradigms associated with strategic decision making - including, for example, deciding how to plan and manage projects. This "matrix" sets out two dimensions to consider, the first dimension "agreementrefers to "how much agreement or clarity we have on what we want to achieve or decide", and the second, "how much agreement or clarity we have on what we want to achieve or decide".certainty"represents the level of "certainty" we have about what the outcome will look like or be achieved.
Consensus and Certainty
Stacey may have a fit reading how I have oversimplified the work of years and how I apply it to the agile, predictive or hybrid paradigm, but the important thing for this article is to identify the impact that these two dimensions have on our decision making: Consensus and Certainty.
- ConsensusWhat do we want to achieve?
- CertaintyHow are we going to achieve this and what can we expect from such a process?
So here I present my personal version of the matrix - you could say it's a derivative work.
In summary, we can see:
- Simple Domain: we have a clear objective and high certainty in the results that our actions will have (in pursuit of that objective) we are in the domain of the simple.
- Complicated Environment: When certainty diminishes or consensus about what we hope to achieve, or both (to some extent), we enter the domain of complicated decisions.
- Complex Environment: When one or both of the variables are outside of what I would call the "zone of apparent control" then we enter the domain of complex decisions.
- Chaos: If we go too far away, we lose the very meaning of the work.
For each of these regions or domains a paradigm for decision making is proposed. These decisions are:
- Rationalwhere there is agreement between what we want to achieve and certainty in the way to achieve it.
- Negotiatedwhere, having certainty in the ways to achieve the objectives, the debate requires negotiation and agreement between the parties.
- Based on the evidencewhere, rather than agreement, we must discover or create ways to solve problems or achieve goals. This context requires experimentation and, consequently, relies on data and evidence to make judgments.
- Complexwhere we apply both learning and creativity to decision making and it is, in essence, a combination that requires adaptation.
Although project management is not a direct part of Stacey's work, it is possible to extrapolate the concepts to decision making within the project, and in particular, to decision making associated with project planning.
Adaptive, predictive or hybrid planning
For each of the paradigms or frameworks for decision making proposed by Ralph Stacey it is possible to propose a "best" way to conduct the management of this process. In the context of projects we speak of the "project management paradigm".
For each of the paradigms there is a recommendation to govern the planning and management processes during implementation. I want to clarify that I speak of management and not execution because execution can only occur (academically speaking) if there is a plan. So, decisions are made when planning the work or managing it (corrective and preventive actions) and not in the process of executing the tasks - as if we were automatons.
This is how the so called management paradigms (agile, predictive or hybrid) in projects. These paradigms are:
- Predictive planning - where based on experience and knowledge we make rational decisions and can define a plan in advance. This management model is sometimes referred to as "traditional".
- Incremental management involves the definition of stages or "intermediate points" where the result is validated according to the expectations and interests of those involved. stakeholders. These intermediate points must be verifiable results, and are commonly called "increments".
- Decisions that require evidence use experiment-oriented models. Each experiment must have controlled variables - since we cannot anticipate the outcome, we try to contain other dimensions such as the duration of the experiment or the budget. These periods of experimentation are known as iterations.
- For complex decisions we need to define a sort of combination between validating expectations and needs, and discovering the path to achieve the expected outcome. This model is known as adaptive or agile (I'm not entirely convinced by that association) and is where complex adaptive systems come into the picture. This paradigm requires a balance between creativity and learning, with increments to validate the "what" and experiments to validate the "how".
Example projects for different project management paradigms
It is possible that during the next paragraphs we will touch sensitive fibers in the philosophical discussions of project management and, surely, one or the other professional. Please understand the educational purpose of this article as the reason for simplifying the concepts (sometimes too much). Always remember the metaphor of the "perfectly spherical cow".
Example of a predictive project: The bridge
Problems within the context of the simple involve the ability to anticipate the results of our decisions and actions. This is how predictive planning conceives management.
A problem or challenge that we can solve predictively is the construction of a vehicular bridge. Suppose the governor of a region wants to build a bridge between two cities separated by a river, and your company has been selected for its experience and track record in building similar bridges for other regions and even over the same river.
Although building a bridge is not a simple task and requires calculations of structure and construction quality, often executed by tens or hundreds of people that require great coordination, we can say that the problem to be solved is part of the domain of predictable or simple problems or decisions. That is, our knowledge and the technology we have allows us to anticipate the risks and difficulties we will face, as well as to identify proven solutions.
You are not going to start building a bridge by doing experiments, you are going to define a work plan and focus on completing it - the plan represents thousands of years of mankind's experience in civil works and constructions. That's why it's called a predictive model or paradigm.
Example of an Incremental Project: The Campaign for President
The imaginary scenario of this example is that you are part of the campaign team of a candidate for the presidency of your nation. You, as a serious and responsible professional, develop with the team a campaign plan on the thematic axes that have historically proven to be key to changing the voting intentions of citizens.
So far, it all seems like a predictive project, but as soon as the campaign begins, you face your audience: the voters. They are the ones who ultimately choose, often guided by the most unlikely scenarios, the issues they expect to hear from the candidates. They are the ones who dictate the priority of the campaign team's work. One day it may be a predictable situation and the next day a video goes viral on social networks showing the profound disconnection of the citizenry with their electoral process and shifts the balance in an unsuspected way just days before Election Day.
You know you can't see the future, you have a plan, but you must adapt it to the needs and expectations of your stakeholders. You have the tools, the technology and you know how to respond. Success will be how sharp your increments are.
Example of an iterative project: The Vaccine
Well, iterations may look like iterations to you, but they are not. Here's why increments are not like iterations.
Iterations vs. Increments
Increments can be "planned", we know what actions to take to develop one outcome or another. What we cannot anticipate is whether our assumptions about the value of the product or service we develop are correct or whether, on the contrary, our stakeholders will change their minds when they see it.
For iterations, we can't anticipate the outcome, we don't know if we are going to achieve or not to build something, we may still doubt if it makes technical sense what we propose. And that's why we decide to modify other variables, such as the duration of the iteration and the resources allocated.
So, we come to our example. The development of a vaccine for a disease that has the world in the grip of a pandemic. Who can anticipate when the vaccine will be developed? Who can anticipate whether we will find the vaccine on the first try, or whether it will take 5, 10, 20 or 1000? The answer is that no one can.
Remember the movie where the protagonist was the "sole human survivor of a pandemic in New York City" and performed experiments on test subjects over and over again waiting for the result. Such projects of a complex nature cannot be anticipated and only involve the indefinite attempt to find a solution to a problem.
To prevent these types of projects from bleeding organisations or nations dry, the resources invested (time and money in particular) are limited and managed in cycles - which we call iterations, or are known in Scrum such as Sprints - where we perform evaluations of the results to adjust our plans.
To bring this example closer to the corporate world, imagine you are the director of an innovation area. I assure you that more than one director would like to be able to promise to develop 3 or 5 or 10 new and successful products by the end of the year, but the reality is that it's impossible, so we allocate a specific budget for innovation and we manage to optimize that investment and its impact - even if it's just one very successful product.
Example of adaptive or agile management: The development of software products.
Well, this is perhaps the model you've heard the most about in recent years and, although it's been around for more than three decades, it's new to many organizations that are now evaluating specific methods in their organizations.
The adaptive management Agile design requires a delicate combination of increments and iterations. Several models have emerged in this effort - very close to the software industry. The reason, I can bet, is because of the unique combination that exists between the development of intangible products - such as SW code - and the accelerated evolution of the technologies for which we develop SW products.
Naturally to SW development and technological evolution, we see an explosion of new opportunities, this makes the process itself a continuous search between the perfect product and features - or more timely and effective in the context - and the best way to use the available resources - new programming languages, new frameworks, new architecture models (such as serverless, to give an example).
Adaptation is almost natural to intangible products, to their abstract nature that depends a little on the criteria of the builder or "producer" of the result. However, it is not exclusive to this type of product. A book, a document or contract developed by lawyers, the source code of an application, and in general those results that arise from very personal processes and are then confronted in the light of other people, will be subject to questions of form and substance.
And finally what, agile, predictive or hybrid?
Well, I think you can already anticipate the answer: "it depends". Then I close this article with a reflection and a tool to define the management framework or context for managing a project, whether it is agile, predictive or hybrid.
When to use forward planning and predictive management modeling?
Whenever you can. Without a doubt, predictive planning is the best way to anticipate an outcome. If you and your team agree that it is possible to anticipate the outcome of your actions and that both external and internal factors will not alter the substance of the product or service under development, then you have a predictive project.
What are the advantages of advance planning?
- Brings clarity to the work team and stakeholders by reducing speculation.
- It allows for more detailed and, in many cases, accurate estimates.
- Greater control over implementation and measurement of progress - based on indicators.
- Reduces the risk - in theory - of fixed-cost, fixed-duration projects.
When to use adaptive planning and the agile management model?
Whenever you can - how awful, isn't it? However adaptive planning has a different goal, to maximize profit. Predictive planning talks about compliance (versus plan) and adaptive planning talks about effectiveness. If your project needs to adjust over time in order to maximize profit, then adaptive is your thing.
What are the advantages of adaptive planning?
- Greater manoeuvrability to adjust the plan.
- Promotes innovation, both in products and in processes and practices.
- Maximize the return and reduce the risk of early cancellation.
- Greater visibility on overall progress - evidence-based
What is a hybrid management model?
In my opinion, the term "hybrid" is valid during this profound transformation that project management as a profession is undergoing. This is happening because "traditional" management had a deep focus on processes, their inputs and outputs, and had diverted the focus of the manager to a kind of process auditor. Today, the profession speaks of values, principles and in general a paradigm oriented to results and generated value. In this context, the hybrid concept implies a particular mix in some projects where different approaches are needed in different components or stages.
Example of a hybrid management model: Designing and building a dream home
Well, this one is easy, we know that the construction process of a house is, almost always, predictive. Not so, the design. The design process is more incremental, and if the design is extreme, even experimental.
Therefore, in the same project we can have incremental or adaptive phases (such as property design) and predictive phases (such as construction).
Conclusion: agile, predictive, and hybrid
It is not a disjunction, it is a conjunction. A true toolbox includes all kinds of practices, applicable to one or more contexts, whether agile, predictive or adaptive.
It's not about filtering, it's about adding and building criteria. Our toolbox has no weight, only value to contribute.