Home >ai >artificial-intelligence >Eight skill sets needed to set up your dream digital team

With every company jumping on to the digital bandwagon, demand for technology talent is unprecedented. However, given the novelty of the profession, the supply of talent is short. Here are the specific skill sets that these employees should have and some ways to make them work effectively.

There are eight specific skill sets required (in a mix that depends on the use case):

Product manager: These employees combine an understanding of business opportunity, technical enablers and existing digital products, to develop innovative, best-in-class solutions. They manage end-to-end design, development, maintenance and upgrade of the digital solution. They also understand how to test solutions, drive adoption, set up partnerships and measure impact. The best product managers have the ability to create disruptive offerings and an instinctive sense of what trade-offs in design will lead to the greatest business impact.

User experience (UX) designer: Create digital products that users will love. They know techniques of ethnographic research to go very deep in surfacing pain points and needs of users. They use this insight to re-imagine user journeys and create product concepts that enable the same. They understand how to test concepts with users.

Visual Designer: Design simple and intuitive interfaces for users to interact with. They create “development-ready" design assets, working closely with UX designers, and then work with developers to ensure that the visual design is accurately implemented.

Scrum Master: Run agile software development process and coach technology vendors. They manage the end-to-end development, testing, deployment and maintenance of the digital solution, working with multiple vendors and systems integrators.This role is crucial for high quality delivery in a short period of time.

Solution Architect: Design how the various modules of the digital solution will interact with one another and with existing systems. They define and own the solution architecture, including all components, middleware, interfaces and application programming interfaces (APIs) required. They also define the testing and scalability requirements. The best architects can quickly understand an enterprise’s core systems, are conversant with middleware and cloud platforms as well as third-party digital products, and can put all these together into a system design.

Data Scientist: Develop the advanced analytics models and algorithms required to bring “intelligence" to digital products. They can crunch large amounts of data using machine learning tools to derive insights and develop algorithms. The best data scientists are familiar with all major tools and techniques and bring clarity on the best ones to use in different situations. They can also combine business rules with predictive models to develop pragmatic solutions.

Data Engineer: Gather data from multiple sources and capture it in a form that can be read by analytics platforms. They use tools to extract data from wherever it’s generated, translate it into a form usable by analytics platforms and load into databases ready for integration and ingestion. They also do the data clean-up wherever required.

Digital Marketer: Design and execute internal or external campaigns using digital channels to drive adoption and usage of digital solutions. The best digital marketers can use analytics to significantly enhance effectiveness and also find creative ways to use free marketing via influencers.

The specialist talent described above works closely with three other sets of people—one, subject matter experts from within the company who understand current processes, user behaviour and economics of the business; two, technology vendors or systems integrators who write, test and maintain the code; and three, programme managers who help de-bottleneck other parts of the organisation that often struggle to keep pace with the digital team. The magic happens when they are housed together—full time in a digital “garage"—a single physical space. We advise against breaking the rules of full-time staffing, co-location and specialists playing the respective specialist roles. Garages also provide a modular organisational unit that can be plugged in wherever appropriate given their focus area and the context of the organisation. These employees may report to a chief digital officer, chief transformation officer, functional leader or an independent business head.

There are three specific lessons that are relevant here:

Ignore compensation bands: Specialist talent, especially the best people, are scarce and highly valued. Many come from start-up environments where stock is an important element of compensation. Traditional company compensation bands are created for constructs where growth in career largely happens through managing larger numbers of people, whereas specialists may never manage more than a small group. It’s best not to try and force-fit specialists into traditional bands.

Plan career paths around growth in individual expertise: For specialists, the career goal is often around taking on more complex digital challenges and gaining acknowledgement for their work. They care less about managing “empires" of people. Training programmes overseas; allowing space for personal pet projects; speaking, writing, and teaching opportunities; participation in hackathons; and creating digital “labs" are some ways to motivate them.

Actively create a nurturing culture: There is nothing more discouraging for a garage team than senior executives exhibiting “traditional" behaviours that are not user-centric, not agile or not supportive of disruption. For specialist talent, this presents a stark contrast to the environments they come from, confirming their worst fears about large companies. We recommend systematic “immersion" programmes that sensitise senior executives to the right behaviours as well as training programmes to explain the new approaches to a broader set of executives.

Kushe Bahl is partner and lead, digital and analytics, McKinsey & Company.

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