McKinsey summarised the typical tech-talents a company would need during digitalization. While there is a broad range of skills needed, this set should be part of any company’s tech-talent list:
- Experience designers and engineers.
They are crucial in delivering excellent customer experience. Experience designers tend to wear multiple hats, from driving insights through customer research to running rapid test-and-learn programs in the field. They should have considerable experience creating and iterating products or services based on real customer interactions (i.e., not just data) and translating customer research, insights and ideas into solutions using design tools.
- Scrum masters and agility coaches.
They are crucial in building and maintaining a team’s “agile development”—where software is rapidly developed in iterative cycles. While it’s desirable for scrum masters to be certified, it’s more important that they understand the values and principles of agile (e.g., value-focused delivery, adapting to change, continuous improvement, et cetera) and have at least two to three years’ experience training, coaching and working to build high-performing agile teams. They are people leaders with the ability to deal with conflict, influence ideas, and have empathy. It is helpful for them to have a baseline knowledge of software engineering best practices to appreciate what goes into building high-quality software.
- Product owners.
This role is often referred to as the mini-CEO of a digital product. Product owners clearly define the vision of a product or service, are fully empowered to make decisions that deliver high business value, and are laser focused on KPIs to track progress. Being a successful product owner typically requires four key skills: Vision, Value focus, Decisiveness, Product management. They typically have three to five years of strong product-management experience and a good sense for the intersection of business, user-experience design, and technology.
- Full-stack architects.
These roles are particularly important in a more complex and rapidly changing technology landscape. They are generally hands-on developers with at least eight to ten years of software engineering experience and deep expertise with one to two core programming languages (e.g., Java, .NET, Node.js, et cetera). They also need to be knowledgeable and fluent across the different “stacks” of a large-scale software system (e.g., front-end user interface, middleware integration services, databases, et cetera). They are effective at building solutions that focus on business value, not just technical excellence. They have a deep understanding of how an architecture will need to evolve to meet changing business goals and like to produce working software as one of the best ways to illustrate a concept.
- Next-gen machine-learning engineers.
They are crucial as companies move toward machine learning. They are fluent in distributed computing techniques, have experience using different machine-learning algorithms and applying them effectively and understanding the trade-offs with different approaches. They work closely with customer data managers in particular, who use machine learning to collect and rationalize the massive amounts of data. They have a strong computer science foundation to understand how to structure data and make efficient use of computing resources (e.g., memory, CPU, et cetera) when designing and implementing machine-learning algorithms. They also have a baseline knowledge of probability and statistics (e.g., regression, probability theory, et cetera) techniques as well as experience in data modelling and evaluating data sets for patterns, trends, and predictability. This capability is important since machine-learning algorithms rely on these data sets to learn and iterate.
- “DevOps” engineers.
Organisations need DevOps (the integration of development and operations) engineers who have the experience to navigate a rapidly changing development and cloud infrastructure computing ecosystem. They are generally software engineers with typically five to eight years of software-engineering experience and have now ventured into infrastructure-automation technologies (e.g., Chef, Puppet, et cetera), cloud platforms (e.g., AWS, Azure, et cetera), and more advanced containerization technologies (e.g., Docker). Besides technical excellence, DevOps engineers understand how technology serves business goals and are flexible in adapting approaches to changing business needs.
Author: Selina Gao, Plusser Marketeer based in Manchester