Strategy evolution, talent alignment, embracing uncertainty, and AI driving leadership autonomy | Aleix Morgadas, Engineering Strategy Consultant
Yassine Kachchani
I publish Exec Engineering, a weekly digest on Engineering + Talent | Co-founder & CEO at Gemography
Aleix Morgadas is an Engineering Strategy Consultant, he helps organizations optimize their engineering practices and achieve scalable success.
With over a decade of experience in the software industry, Aleix brings a wealth of knowledge from roles spanning senior developer consultant, tech lead, engineering manager, and head of engineering.
His expertise encompasses diverse sectors such as fintech, e-commerce, and developer tools, working with startups, scale-ups, and large enterprises to shape effective engineering strategies.
Highlights
Yassine: You've written extensively about engineering strategy. What are the key elements that distinguish a robust engineering strategy from a collection of technical decisions?
Aleix: The key elements I look for in any engineering strategy are:
Therefore, when we look at a collection of technical decisions, we can ask questions such as; how does it address the business challenge? Are those decisions coherent with each other? How do those decisions put us closer to our vision?
When answering those questions, we can detect if the engineering strategy is robust, or if it is just a set of desires or buzzwords that do not sustain the strategy.
Y: At what stage of growth does engineering strategy become critical for a company?
Aleix: Even though an engineering strategy is needed at any stage of a company, it is true that it provides the right clarity and alignment when a company reaches a certain number of employees, in my experience more than 50 employees.
Two types of engineering strategies coexist:
When you are a small team, looking for product-market fit for example, with high cohesion between all the team members, you are probably operating under an emergent strategy.
As the company grows, the leadership cannot be as close as before, and you start forming teams, and the first management positions appear. It is at this right moment that you can start sensing a team requires more autonomy to make decisions that are coherent with the bigger picture.
That’s why a deliberate engineering strategy becomes critical to keep the company as fast and flexible without adding unnecessary processes, and bureaucracy.
Y: How does having a clear engineering strategy impact team structure and technical hiring decisions?
Aleix: An engineering strategy brings focus, and makes it explicit what we want, but more importantly, what we don’t want. By defining those sets of directions, or constraints, we can point out decisions that aren’t aligned, or even worse, they are competing with each other.
Decisions such as Modular Monolith or Microservices, Product Developers, or technology-specific developers, like <technology> backend developer, will determine which team structure will emerge over time.
If we need a fast feedback loop per business domain, but the hiring process is based on technology selling that we do X architecture, and having hard technical problems. The people we hire will look for technical problems instead of business problems.
Even though it is quite obvious, I found many organizations adopting a vague hiring process, creating unaligned expectations when onboarding people, and losing talent along the way, or even worse, focusing on the wrong thing, technology over business and customer needs.
Y: As with all strategies, the engineering strategy might need to evolve or pivot. What traits in tech talent allow leaders to stay flexible with their engineering strategy?
Aleix: Any engineering strategy is as valid as the business/product strategy. When a business evolves, the engineering strategy needs to evolve as well, and so does your talent.
It’s crucial that you create a culture of embracing uncertainty and change to be ready when your organization requires a strategy evolution or a pivot.
In order to stay flexible from a talent point of view and create a culture that embraces uncertainty, you need to look for the right attitude. Even though hiring is key, it is important that you align those expectations with people leadership, the ones that create the job expectations, and career leadership.
Hiring the right people with the right mindset, but then having company incentives and behaviors that discourage that, is a recipe for bureaucracy, inertia to change, and status quo.
Be sure that you promote experimentation, and a non-blame culture, where failure, as any strategy, is part of the journey. The celebration grid summarizes this mindset quite well.
Y: How have you seen organizations leverage flexible talent models like staff augmentation in enabling engineering strategies to scale or pivot quickly?
Aleix: I have seen organizations leveraging flexible talents with much success when there’s a clear engineering strategy that helps engineering leaders be aligned to the expectations within the company plus the external company, like a consultancy firm.
It is crucial to understand how and why flexible talent models, like consultancy, can help us accomplish our goal, and not use that model to do the job we don’t want to do in the first place. Their impact has to be seen as a necessary gear within a bigger engine to accomplish our goals.
When we lack that alignment, we can find that the work isn’t adding up but creating more noise and waste along the way. And even becoming a company risk by creating a huge dependency on external talent because we didn’t identify the need to transfer the knowledge to our internal employees.
Y: What practical applications of AI have you seen make a meaningful impact on engineering leadership and strategy execution recently?
Aleix: The main meaningful impact I have seen of using AI for engineering strategy is supporting the engineer leaders to be more autonomous in the diagnosis phase when we aim to understand the high-stake business problem and the execution phase when we want to understand how well are we doing.
During the diagnosis phase, it helps by creating complex SQL queries and reports, reducing our previous dependency on the data team. This helps avoid delays in decision-making caused by the time needed to extract data, while also enabling exploration of key business areas such as sales and finance, and producing clear strategic documents for different stakeholders.
While in the execution phase, AI assists in building an effective reporting structure by collecting data from our systems and visualizing progress. Previously, we relied on manually updated Excel files, but now we can create no-code mini-tools that automate the process, eliminating the need for extensive internal development and allowing us to stay focused on high-priority business challenges.
AI is helping engineering leaders be more efficient during the whole strategy journey by removing human dependencies on low-value activities, helping them collaborate on high-value meetings, and workshops, and be more prepared. Plus reducing the cost of supporting tools required to reduce the strategy feedback loop.
Thank you Aleix for your time and insights!
This interview is part of the “Exec Engineering Dialog” series where I interview seasoned tech leaders on the topics of talent, product, management and culture.
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Yassine.
Business and Technology Strategist | 20+ years of experience in Consulting & Operations | Expert in Wardley Maps | Emergent Strategy | Values Chain Discovery | Speaker & Author
1 个月probably it was part of the conversation, because I know Aleix is aware of this. To experiment, you have 3 outcomes: you succeed, you fail, and an unexpected outcome emerges. This third one is not possible if a great culture on failure is present in the organizations. :-)