Coding Isn’t a Necessary Leadership Skill — But Digital Literacy Is

When former Microsoft US chief technology officer Jennifer Byrne was offered her role, she worried that she didn’t know enough about technology. After all, Microsoft’s suite of tech products is just so vast.

If even one of the world’s top technologists worries about not having enough tech knowledge, what hope is there for those of us who have never written a line of code?

Digital transformation is everywhere — even your local coffee shop has an app. When done right, it brings impressive business outcomes. But sadly, success is not a likely outcome: according to McKinsey 70% of all digital transformation initiatives do not reach their goals.

While most leaders now know that tech is a vital part of business, many are wondering what they really need to know about technology to succeed in the digital age. Coding bootcamps may appeal to some, but for many leaders, learning to code is simply not the best investment. It takes a long time to become a proficient coder, and it still doesn’t give you a holistic overview of how digital technologies get made — even if you learn Python, you still won’t understand how product goals relate to business goals, why user experience research matters, or how to assess your product’s success.

The good news is that most leaders don’t need to learn to code. Instead, they need to learn how to work with people who code. This means becoming a digital collaborator and learning how to work with developers, data scientists, user experience designers, and product managers — not completely retraining.

For example, when non-technical, customer-facing teams in the planning and development department at Santa Clara County collaborated with external technology consultants, they created a process to improve efficiency by 33%. The software specialists were experts in their fields, but only by combining forces with non-technical professionals who could make useful products.

Most ambitious leaders are working under severe time constraints, so the time they do have to be used effectively. What’s the best return on your time investment, given your opportunity costs? The best and most efficient use of a leader’s time is to become a digital collaborator by learning how to get a holistic view of how a software product gets made and who does what on a tech team. Here are four ways to do it.

Remove choice.

The best way to learn anything quickly is to put yourself in a situation where not doing it isn’t an option.

Set up a weekly meeting with technical specialists and your team to discuss what they’re working on and how it impacts scale, efficiency, and customer satisfaction. This public commitment to collaboration removes your choice to delay.

Catherine Breslin, a machine learning scientist with a PhD in automatic speech recognition from the University of Cambridge, told me that, while she is a technical specialist, she needs the insights of domain experts to do impactful work. She notes that non-digital professionals often don’t know that some problems can be solved easily by technology because they’ve never discussed them with a technologist. This is why regular communication is vital.

For example, if you work in marketing, understanding consumer behavior is your top priority. This is where a regular meeting of the marketing team and data scientists can help both become more productive.

This weekly event doesn’t have to be longer than 30 minutes. In the first meeting, begin by outlining your goals for the year and where you see the biggest bottlenecks. Is there something you wish you knew about your customers? Are there sales spikes or sudden drops that mystify you? What concerns you about your next advertising campaign?

While the data science team might not have solutions right away, this conversation will lay the foundation for effective collaboration. In turn, ask the technical team to tell you what problems they’re working on, how they measure success, and who is involved. Seeing how engineers and data scientists solve problems will educate you on what’s possible for you.

Remember that while your team may be concerned that they don’t “speak tech,” technical teams are often concerned that they don’t understand the business side. See these meetings as a coming together of two equal partners sharing knowledge, not one Luddite seeking the wisdom of an oracle.

Learn how other people did it.

The myth of coders in a garage creating a billion-dollar company is persistent. The story of non-technical professionals driving technological change is not often told, but that doesn’t mean it doesn’t exist.

For example, non-technical founders like Katrina Lake of Stitch Fix and Brian Chesky of Airbnb have created innovations and massive shareholder value driven by technology. Colin Beirne, a liberal arts graduate, has had more impact on deep tech than many computer scientists, because he founded Two Sigma Ventures, a deep tech investor that has funded 100 startups, 10 of which are now valued at over $1 billion. Bruce Daisley, who started his career selling radio advertising, had more influence on social media than most developers when he helped take Twitter global as its vice president for Europe, Middle East, and Africa.

Each of these people had to learn how to collaborate with technology teams, make the right investments, and lead people who did jobs they themselves could not do. Learning how they did it — and what they had to learn about technology on their path — will give you the knowledge and confidence to apply their lessons to your career.

However, the current cultural zeitgeist focuses on the story of engineers-turned-developers, and if you passively consume most technology-focused media, you’ll mostly hear the stories of the likes of Mark Zuckerberg, Bill Gates, and Elon Musk. Seeking out the stories of non-technical professionals who have succeeded in tech is an effort, but well worth it.

Understand different working styles.

The biggest difference between how technical and non-technical teams work is that the former iterates and learns, while the latter focuses on perfection. This difference can create tension and misunderstanding if not addressed head-on.

One of the core concepts of software development is releasing new features, seeing how people use them, and then iterating based on results. Thus, the aim of releasing something new is to test a hypothesis, rather than to create a perfect end product for a customer. On the other hand, non-technical teams usually focus on creating a perfect end product for a customer. This difference makes sense: Digital products can be quickly changed when customers already have them, while traditional products cannot. For example, developers can release a new feature once an app is already on your phone, but a chocolate bar can’t become less sweet or more nutty after you buy it.

Thus, traditional products require more planning and forecasting before release than digital products. Tension often arises when non-technical teams want to discuss and plan every feature for every possible outcome, which frustrates technical teams, who want to “move fast and break things.” Both approaches are right for their own specialty; the key is not to mix them up.

If you’re working on a digital product for the first time, understand that apps, sites, and algorithms are built using an experimental “build — measure — learn” cycle. The product team simply cannot tell you what features are going to be released in a year because they don’t know yet.

This can cause frustration, especially in the finance department, which understandably wants to forecast spend and revenues. This is where it helps to learn from startups. Early-stage technology companies are by nature experimental, but they have a very clear deadline: the amount of cash left in the bank. The question they’re answering is: What can we learn given the amount of funding we have? Given our runway, what experiments can we do to get closer to our goal?

Thinking in terms of experimentation within a certain budget or time frame helps bring business realities to the scientific method used in digital innovation.

Learn concepts rather than skills.

While you don’t need to learn to code a product with your bare hands, you do need to learn core tech terminology. As Jennifer Byrne told me: “You have to understand the difference between acquiring digital context versus digital fluency. Context means seeing the bigger picture of how things connect together, but not necessarily understanding the detail.”

Concepts such as user-centric design, APIs, and cloud computing are pervasive, but many non-technical leaders don’t fully understand them. Taking a course on technology for non-technical professionals or creating a learning program at your organization is a great way to invest in your leadership capital.

For example, according to Tsedal Neeley and Paul Leonardi, the Digital Transformation Factory program at French IT company Atos trained both technical and non-technical employees in digital technologies and artificial intelligence. Within three years, more than 70,000 Atos employees completed their digital certification and helped contribute to revenue reaching close to $13 billion.

Neeley and Leonardi argue that most people can become digitally savvy if they follow the “30% rule”: “You only need about 30% fluency in a handful of technical topics to develop your digital mindset.” In other words, that’s the minimum threshold that gives you enough digital literacy to be an active participant in digital transformation.

When many of today’s leaders graduated from college, the technology sector simply wasn’t what it is today. The typical jobs that the smartest graduates considered were in investment banking, consultancy, or advertising. The world has since changed, and the skills we learned are no longer enough. Today, Amazon (founded 1994) and Google (1998) are in the top five recruiters of MBAs, while they weren’t even in the top 10 in 2002.

. . .

To succeed in this new tech-enabled world, learning how to work with people who make tech products is simply a core leadership skill.

For example, Starbucks is a coffee chain. Its core focus is selling coffee and snacks and running coffee shops. But its app-based rewards program represents 53% of the spend in their stores, and AI-based personalization drives customer loyalty. Thus, how understanding digital technology works and how to embed it into business strategy has had to become a core leadership skill for people running a coffee company.

Making the best use of digital technologies is what propels organizations into the future. To lead successfully in the digital age, leaders have to go beyond their usual training and learn to become digital collaborators.

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