Programming is not a necessary leadership skill, but Digital skills are.

Programming is not a necessary leadership skill, but Digital skills are.

While most executives today know that technology is an integral part of business, many wonder what they really need to know about technology to thrive in the digital age. Coding bootcamps may be appealing to some, but for many executives, learning to code isn’t the best investment. It takes a long time to become a proficient programmer and it still doesn’t give you a complete insight into how to make digital technologies. The good news is that most executives don’t need to learn to code. Instead, they have to learn 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, without completely retraining. The author presents four ways for non-technical leaders to become digital workers.

 

When Jennifer Byrne, former CTO of Microsoft in the US, was offered her job, she feared she didn’t know enough about technology. After all, Microsoft’s line of technical products is vast.

If even one of the best technologists in the world is concerned that they don’t have enough technical 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 produces impressive business results. Unfortunately, success is unlikely: According to McKinsey, 70% of all digital transformation initiatives fail to meet their goals.

While most executives today know that technology is an integral part of business, many wonder what they really need to know about technology to thrive in the digital age. Coding bootcamps may be appealing to some, but for many executives, learning to code isn’t the best investment. It takes a long time to become a proficient programmer and it still doesn’t give you a holistic view of digital technology manufacturing; even if you learn python, you still won’t understand how product goals relate to business goals, why user experience research. questions or how to measure the success of your product.

The good news is that most executives don’t need to learn to code. Instead, they have to learn 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, without completely retraining.

For example, when non-technical customer service teams at Santa Clara County Planning and Development worked with outside technology consultants, they created a process that increased efficiency by 33%. Software specialists were experts in their field, but only by working with non-technical specialists could they produce useful products.

Most ambitious leaders work under intense time pressure, so the time they have must be used effectively. What is the best return on your time investment given your opportunity cost? The best and most efficient use of a leader’s time is to become a digital employee, learning to see the big picture of how a software product is made and who does what in a technology team. Here are four ways to do it.

Remove selection.

The best way to learn something fast is to put yourself in a situation where not doing it is not an option.

Host a weekly meeting with technical specialists and your team to discuss what they’re working on and how it affects reach, efficiency, and customer satisfaction. This public commitment to cooperate takes away the ability to delay.

Catherine Breslin, a machine learning scientist with a Ph.D. in automatic speech recognition from the University of Cambridge, told me that although she is a technical specialist, she needs expert knowledge of the subject to do an efficient job. She points out that non-digital professionals often don’t know that some problems can be solved simply with technology because they’ve never discussed them with a technologist. For this reason, regular communication is essential.

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 of you be more productive.

This weekly event should not last more than 30 minutes. During the first interview, start by outlining your goals for the year and where you see the biggest bottlenecks. Is there something you would like to know about your customers? Are there any sudden spikes or drops in sales that intrigue you? What do you think of your next ad campaign?

Although the data science team doesn’t have immediate solutions, this conversation lays the groundwork for effective collaboration. In turn, ask the technical team to let you know what issues they’re working on, how they measure success, and who’s involved. When you see engineers and data scientists solving problems, you learn what’s possible for you.

Keep in mind that while your team may be worried about not being “technical,” technical teams are often worried about not understanding the business side of things. Think of these meetings as a meeting of two equal partners sharing knowledge, not like Luddite seeking wisdom from an oracle.

Find out how others have done it.

The myth of programmers in a garage building multi-million dollar companies persists. The story of non-technical people driving technological change often goes untold, but that doesn’t mean it doesn’t exist.

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

Each of these employees had to learn to work with technology teams, make the right investments, and lead people who were doing things they couldn’t do themselves. Learning how they did it, and what they had to learn about the technology along the way, will give you the knowledge and confidence to apply their lessons to your career.

However, the current cultural zeitgeist focuses on the engineer-turned-developer story, and if you passively consume most tech-focused media, you’ll mostly hear the stories of Mark Zuckerberg, Bill Gates, and Elon Musk. Finding the stories of non-technical professionals who have succeeded in technology is hard work, but it’s worth it.

Understand the different work 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 directly.

One of the fundamental concepts of software development is to release new features, see how users use them and then iterate based on the results. Therefore, the point of launching something new is to test a hypothesis rather than create a perfect end product for a customer. On the other hand, non-technical teams are usually focused on creating a perfect end product for a client. This difference makes sense: digital products can be changed quickly if customers already have them, while traditional products cannot. For example, developers can release a new feature as soon as an app is already on your phone, but a candy bar can’t get any less sweet or crazier after you buy it.

Therefore, traditional products require more planning and foresight before launching 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 correct for their own specialty; the key is not to confuse them.

If you’re working on a digital product for the first time, keep in mind that apps, websites, and algorithms are built using an experiential cycle of build, measure, and learn. The product team simply can’t tell you what features will be released in a year, because they don’t know yet.

This can be particularly frustrating for the finance department, which naturally wants to forecast expenses and revenues. Here it is useful to learn from startups. Tech startups are inherently experimental, but they have a very clear deadline: the amount of money left in the bank. The question they answer is: given the amount of resources we have, what can we learn? Given our trajectory, what experiences can we carry out to get closer to our goal?

Thinking in terms of experiments within a specific budget or time frame allows business realities to be incorporated into the scientific method used in digital innovation.

Learn concepts instead of skills.

Although you don’t need to learn to code a product on your own, you do need to be familiar with basic engineering terminology. As Jennifer Byrne told me, “You have to understand the difference between acquiring digital context and acquiring digital fluency. Context means seeing the big picture, but not necessarily understanding the details. »

Concepts like user-centered design, APIs, and cloud computing are ubiquitous, but many non-technical executives don’t fully understand them. Taking a technology course for non-tech professionals or creating an apprenticeship program at your company is a great way to invest in your leadership capital.

For example in Tsedal Neeley and Paul Leonardi, the Digital Transformation Factory program at the French IT company Atos has trained technical and non-technical staff in digital technologies and artificial intelligence. In three years, more than 70,000 Atos employees have obtained their digital certification, which has allowed sales to reach almost 13,000 million dollars.

Neeley and Leonardi say that most people can become digitally literate by following the “30% rule”: “You only need 30% fluency in a handful of technical subjects to develop your digital mindset.” In other words, it is the minimum. threshold that gives you enough digital skills to actively participate in digital transformation.

When many of today’s leaders graduated from college, the tech industry just wasn’t what it is today. Typical jobs considered by the brightest graduates were investment banking, consulting, or advertising. Since then, the world has changed and the skills we have acquired are no longer enough. Today, Amazon (founded in 1994) and Google (1998) are among the top 5 MBA recruiters, while in 2002 they weren’t even in the top 10.

. . .

To thrive in this new technology-driven world, simply learning to work with people who make engineered products is a critical leadership skill.

For example, Starbucks is a chain of coffee shops. Its main objective is the sale of coffee and snacks and the management of cafeterias. But its app-based rewards program accounts for 53% of spending in its stores, and AI-powered personalization keeps customers coming back. Therefore, understanding how digital technology works and how to integrate it into business strategy became a core leadership skill for people running a coffee business.

The optimal use of digital technologies propels companies into the future. To lead successfully in the digital age, leaders must go beyond their regular training and learn to become digital collaborators.

Editor’s Note, Jul 27: This article has been updated from its original version to clarify the formation of Two Sigma Ventures.

Source: hbr.org

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