Part 1: Understanding the Responsibilities of a Successful Data and AI Leader

By:   |   Updated: 2022-04-19   |   Comments   |   Related: 1 | 2 | More > Professional Development Career


Problem

If your actions inspire others to learn more, dream more, and do more, then you are a leader. These wise words of wisdom from John Quincy Adams, the 6th US President, which has also been reiterated in motivational speaker Simon Sinek's book 'Leaders Eat Last', both challenges and inspires us to be exceptional leaders in an age where leadership is most needed.

Much like any other industries, leaders in the Data and AI community have a day-to-day responsibility and calling to empower, challenge, grow and protect those in their care. To thrive, these leaders need to embrace a growth mindset, coupled with humility, an attitude of servitude, and a charismatic management style aimed at peaking intellectual curiosity, which leads to transformative innovation. Leaders with limited success might possess a fixed mindset, driven by self-interest. They might be highly capable and even charismatic individuals that lack the function of discipline, or are subject to bureaucracies that they believed were out of their control to contribute positive and impactful change towards.

The 'Great Resignation', a term coined by Anthony Klotz, professor of management at Mays Business School at Texas A&M University, is a trend beginning in early 2021 where employees resign from their jobs in masses due to a number of factors including but not limited to poor leadership. With the right mindset and guidance, all leaders can become great and in return empower others to strive for success. Aspiring leaders are on a constant quest for growth, positive impact, and success.

What are some of the day-to-day responsibilities of these leaders in the field of Data and AI and how can they fulfill their leadership commitments to be successful?

Solution

Throughout history, it is evident that the topic of leadership has prevailed across books and teachings. Dating back to the 5th Century B.C., Laos Tzu has chronicled his understanding of leadership tactics which was later translated in the book 'The Art of War'. As you read more books and articles about leadership, you'll notice commonalities across the various domains and industries that these works focus on. For example, Laos Tzu's grounds for battle and comparisons to Generals at war can be applied to peaceful navigation within the corporate sector. Such leadership comparisons have been prevalent in Marine Corps. Training, numerous battlefields, and the modern workplace.

Among the various common lessons across these books, they teach us to resolve conflict among people peacefully and strategically. Many of these books describe leadership as a combination of Intelligence, trustworthiness, humaneness, courage, and sternness to establish discipline. Among the many responsibilities, a successful leader needs to hire the right people and begin executing of their strategic plans for growth and success. Successful leaders are capable of channeling innovation and re-thinking among their employees and teams. By being mindful, authentic, and emotionally intelligent these successful leaders possess the soft skills to understand and empower their employees and successors. A growth mindset allows these leaders to embrace their calling from servitude by staying patient, persistent, and constantly striving for excellence.

In this two-part series, you will learn more about leadership in the context of the Data and AI domain. Specifically, you will learn about the day-to-day responsibilities of a successful Data and AI Leader.

Plan your Strategy

Strategic leaders are often successful because they hire the right people and then build a disciplined culture for success. They are capable of committing to a strategic vision that is challenging enough yet not impossible to pursue. In his book 'Good to Great', Jim Collins discusses how important it is to embrace a culture of discipline which leads to disciplined people, actions, and thoughts. Collins emphasizes just how important it is to have the right leaders in place that can then help and guide the organization and teams in setting the right strategic vision. The right people will be self-motivated and ambitious for the cause and will not need to be micro-managed to yield positive results.

Once the right leaders are in place, it is crucial to begin thinking about successors that will both support the execution of the vision and carry on the legacy of the leader's vision. As we visualize the next level of the leadership hierarchy, it is important to hire the right employees that are passionate and have a hunger for success, and to then put the best people on the best opportunities rather than on the biggest problems. This will prevent people from becoming de-motivated.

Data and AI Leaders may need to formulate strategic plans related to Pre-Sales, Delivery Excellence, Team management, Solution Offerings, Centers of Excellence and more. A strategy which includes a disciplined culture leads to overall success through well-organized iterative steps along the way. For example, in the field of Data and AI, leaders often refer to the maturity curve which ranges from foundational migration to advanced analytics journeys. They often propose a foundational Minimum Viable Product (MVP) build out of a Modern Cloud Data Platform as the basis of this journey. Once the value of this MVP product is realized by early adopters including customers and stakeholders, they are empowered to continue the upward journey towards the more advanced capabilities of cloud offerings which may include advanced analytics, DevOps for numerous disciplines, and cognitive services. Spending the time to work closely with organizational leadership to devise these strategies for growth and success is key.

Channel Innovation

Innovation is prevalent across a variety of industries. With Data being one of the most valuable assets within organizations, coupled with AI and Advanced Analytics capabilities, it fuels digital innovation and transformation in the modern workplace. Leaders within the field of Data and AI have an intrinsic responsibility to inspire others to channel innovation by thinking outside the box. Great discoveries and innovation can be achieved by embracing open-mindedness, creativity, and intellectual curiosity. Empowering employees to pursue relevant industry certifications and providing access to a variety of learning materials leads to intellectual curiosity, which in turn channels innovation. Providing employees with the right opportunities driven by investments in Innovation Labs, Centers of Excellence, Hackathons, and more yield innovative returns. Providing the right channels for innovation leads to new ideas and perspectives which in turn leads to digital innovation and transformation.

For example, a leader who is leading a Microsoft Azure Data and AI practice might support investments in Labs where employees could spin-up resources within the Azure Portal for experimentation purposes. Additionally, there are a variety of Azure certifications and readily available Cloud learning resources which channel innovation and empower learning and growth. There are numerous innovative data solutions built for processing and optimizing a variety of big data streams from social media, transactions, and log data sources. For example, real-time streaming data analytics on transactional data leads to quicker time to insights and reduced ELT development and processing times, coupled with optimizations for higher performance and lower costs are a result of decades of innovation channeled by the need for improvements to existing processes. Additionally, disruptive innovation addresses customers future needs through advanced predictive analytics, machine learning, and cognitive services.

Challenge Re-Thinking

In his book 'Think Again', Adam Grant challenges readers to re-think often because it is the re-thinking process which provides a fresh perspective on our traditional thoughts and ideas and ultimately leads to new discoveries when the process is approached with an open mind. There are numerous methods and avenues for challenging this re-thinking within team and organizations as a Data and AI Leader. In 'Think Again', Grant introduces the concept of a 'Challenge Network'. This is prevalent in technical code review sessions, which often times bring with it the pressure of a war-room. At first glance it may appear that the environment is filled with challengers, difficult people, and constant conflicting opinions. However, when approached with an open mind and view that conflict is not always depraved, we quickly uncover the value of such challenging interactions because it leads to rethinking which leads to more solidified and scalable code and architectures.

Since there is so much value in this 'Challenger Mindset', there are numerous training programs and learning material offered by industry leading organizations. For example, Microsoft's Challenger Program which is 7 weeks in duration provides content and practical applications through training videos, reading materials, and assignments to empower a Challenger Mindset for delivering a differentiated experience for customers by focusing on teaching customers something about their business, tailoring the conversation, and guiding customers through the buying process. The program empowers us to understand the business needs and lead to a solution by building constructive tension to compel a customer or employee to act. This 'Challenger Mindset' methodology can be applied by leaders in Data and AI as they work closely with their teams and employees to strategically challenge the critical re-thinking process.

Empower a Growth Mindset

In her book 'Mindset', Carol Dweck discusses the differences between fixed and growth mindsets. Those who are empowered towards a growth mindset often challenge themselves to do more and have a keen interest in learning and growing over time. These challenges could possibly lead to failure, however the lessons learned lead to elevated skills improved confidence, and greater success. Greater success can be achieved by investing time into altering our mindset. Those with a predominantly growth mindset view failure as a lesson and opportunity to improve.

As Data and AI leaders, it is important to empower a growth mindset by providing our teams with the right tools and technologies for upskilling their tech stack capabilities. Supporting growth in light of failure can lead to excellence over multiple iterations to perfect a process or skill. Failure can manifest itself in the form of a project or sprint iteration that didn't go so well. As part of the Agile Scrum methodology, the Sprint review and retrospective ceremonies provide leaders with the opportunities to gain deeper insights into what went well along with what did not go well. It is the retrospective feedback and brainstorming sessions that occur within these ceremonies which empowers the team to channel a growth mindset which results in thinking through improvements for the next sprint iterations. It is this devotion to growth coupled with the understanding that we are imperfect, which keeps egos in check and humanizes us all as we learn and grow a little more each day.

Embrace Servitude

Great leaders have a responsibility to protect those in need and under their care. With humility and ambition, they are willing to go beyond themselves to do the right thing regardless of the impact on themselves. Abraham Lincoln echoed this principle when he stated that the nation must prevail at all costs. In his book 'Leaders Eat Last' Simon Sinek details the intrinsic responsibility for servant leadership through numerous examples based on his research. He talks about our need to feel safe and for leaders to provide protection from above because this will lead to stronger loyalty and the wholistic advancement of the organization.

Sharing is another way of serving as a leader because it empowers growth, breaks secretive information silos and leads to a more inclusive environment which fosters collaboration and innovation. As a Data and AI leader, this concept of sharing can manifest itself in the form of contributing articles for global publications, giving demos and presentations to a variety of audiences, or simply helping a teammate with unblocking or reviewing their code. As leaders, we must embody the characteristic of 'trust' by possessing the responsibility to do what is right and telling people what they need to hear rather that what they want to hear. Since time is finite, employees greatly value a leader's time, therefore it is important to spend 1:1 time with employees to listen, understand, socialize, and humanize which in turn will lead to cooperation, loyalty, and greater job satisfaction. This will in turn lead to a culture with lowered turnover rates and greater growth opportunities from within the organization.

Next Steps

In Part two of this series, you will continue to learn more about the responsibilities of a Data and AI Leader. The following books have been referenced in this tip and provide a wealth of information and insights into successful leadership traits, tactics, and responsibilities:






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About the author
MSSQLTips author Ron L'Esteve Ron L'Esteve is a seasoned Data Architect who holds an MBA and MSF. Ron has over 15 years of consulting experience with Microsoft Business Intelligence, data engineering, emerging cloud and big data technologies.

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Article Last Updated: 2022-04-19

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