Leadership for Analytics Teams

Show up early, it pays off.

—Edward Tufte

What are we talking about when we use the term leadership? What makes leading an advanced analytics and artificial intelligence (AI) team different than any other high-performing team? In what ways are the team dynamics different in an analytics team compared to software development teams and other project teams in general?

Leadership is a well-worn term used in a highly varied and diverse set of contexts. In this chapter, we will use the term to describe and discuss the people who attract, evaluate, hire, manage, fire, lead, and otherwise direct and encourage all the aspects of the daily operation of an advanced analytics and AI team.

The people in the leadership positions who will be the subjects of our discussion and examination undertake activities related to defining the vision, direction, application, implementation, maintenance, revision, and continuation of analytics...

Artificial intelligence and leadership

Given that we are engaged in a discussion about advanced analytics and AI teams, and we are in the midst of examining the topic of leadership, we need to ask the question, "Will AI take over the leadership of corporations and the leadership of AI teams?"

The management consulting firm McKinsey has remarked that:

…the role of the senior leader will evolve. We'd suggest that, ironically enough, executives in the era of brilliant machines will be able to make the biggest difference through the human touch.

By this, we mean the questions they frame, their vigor in attacking exceptional circumstances highlighted by increasingly intelligent algorithms, and their ability to do things machines can't. That includes tolerating ambiguity and focusing on the "softer" side of management to engage the organization and build its capacity for self-renewal. [1]

There is no question that computers...

Traits of successful analytics leaders

Being a leader of an analytics team and function is in some ways like leading any other function in an organization, but it is also unique in several ways. Let's outline the traits that make an analytics leader stand out in the minds of subordinates, peers, and superiors.

Consistency

Consistency is an element of work or an approach to interacting with a wide range of people that has been valued and respected in all the roles that I have held and all those that I have worked with around the world. In Chicago, London, Stockholm, Tokyo, Sao Paulo, Melbourne, and all the other cities that I have worked in, being consistent is reassuring to people, whether those people work for you, or you work for them, or whether you are collaborating across functions, across organizations, or across continents.

Consistency is not only globally applicable, but it is also a relevant personal trait in organizations of all sizes. From start-ups to...

Building a supportive and engaged team

What do analytics professionals want their working days to look like? What do professionals who are engaged in advanced analytics want from their projects, teams, and leaders? Multi-faceted and meaningful questions, those are. A bit of Yoda there for you, Star Wars fans…

Let's start with where we just arrived in the previous section. Let's begin with assessing and understanding how to lead the team that you have. You must be aware that not all analytics teams are the same. The mix of skills and abilities of team members will, to some extent, dictate the projects you can undertake, how quickly you can move, and the level of impact you and your team can have on the firm. You need to understand the current technical, professional, and soft skills of the team and the teams that are ancillary to the core analytics team.

Traditionally, analytics teams were comprised of a significant number of highly autonomous individual contributors...

Managing team cohesion

In Chapter 3, Managing and Growing an Analytics Team, we discussed managing talented jerks and the need to hire the best possible people. The previous points were made, and the discussion remains valid. It is worth reiterating that a bad hire will dampen and diminish the cohesion of the team and the team's ability to collaborate. Once you realize that a person is a poor fit with the group, move to collaborate with the human resources department quickly to manage them out of the company or, to put it more plainly, to fire them.

It is important that you do not equivocate or waiver. You may think that it will take time away from other tasks, and it will, but acting quickly and decisively will be better for you, the team, and, in the end, the employee who is not working out.

The most dangerous element of this situation is that if you attempt to help this person in fitting in, you will waste your time, the team will see that you have made a poor decision...

Being the smartest person in the room

Let's be clear about one thing. If you need to be the smartest person in the room, then you will need to find a very special company, start a company of your own, or get over the feeling that you need to be smartest person in the room. The last approach is the one I would recommend.

I hope for your probability of success in leading an advanced analytic and AI team that you are not the smartest person in the room. If you are, then you are either an incredible person, or you have hired poorly, or maybe a bit of both.

I am certain that at one point in my career, I needed to be the smartest person in the room and I am certain that I embodied all the less-than-desirable personal traits of such a worldview. With these beliefs and views, you will not be seen as a leader and you will not be able to lead a team to sustained success.

Competing with your team to be crowned the best and brightest is one of the fastest paths to team discord...

Good (and bad) ideas can come from anywhere

If you are lucky, you will have a team of highly skilled, highly trained professionals who have technical acumen in varied areas that include math, technology, data management, process design, user interaction design, and more. For your success and your team's well-being, you need to celebrate their expertise. Also, you need to bring value in several ways.

One way that you can bring value is by bringing the perspective of a novice to the discussion.

About 15 years ago, I was on the executive team of a start-up. My role was marketing and corporate development. The development team was trying to solve a problem related to fraud in credit card use. The technical team had camped out in the conference room and they were furiously debating how best to draw a curve through the data space that described all the possible uses of a credit card. The line illustrated the risk frontier for the credit card issuer. The team had the data space...

Emerging leadership roles – Chief Data Officer and Chief Analytics Officer

Leading organizations are beginning to create C-level positions to direct, grow, and manage the emerging and evolving functions related to data and analytics. Some organizations are focused on the data side of the function and hence they start their efforts by creating the Chief Data Officer role, while others begin with the Chief Analytics Officer role. Either starting point is valid and useful.

The creation of these roles and opportunities for the people assuming these roles illustrates the importance of these functions and the corporate recognition that these roles are strategic and are crucial to drive the company in a defined direction. These roles will grow in number and sophistication. The creation of these roles signals a tipping point in corporate history and illustrates that the data and analytics function is a core strategic capability for leading corporations.

On or around November...

Hiring the Chief Data Officer or Chief Analytics Officer – where to start?

Building an analytics team can start at any number of points: bottom-up, top-down – either approach can work. Let's assume that the organization is just beginning to build the data and analytics capability; they can start by hiring the Chief Analytics Officer or the Chief Data Officer. As supported by the dialog above, and my decades of experience, and if we are using probabilities to make a choice of where most organizations will start, the majority will start by hiring the Chief Data Officer.

The Chief Data Officer

Hiring a Chief Data Officer is seen by most as a choice that is safer, easier to understand, and easier to gain consensus around. This is a valid starting point, but as called out above, it is a decision and starting point that will begin the organizational journey by looking inward – inward at the data, technology, and processes that the company currently has...

Summary

Leadership is the topic of many books, thousands of lectures, and much discussion and conjecture. Leadership is an industry unto itself. It is funny how many leadership gurus have never been leaders in the fields that they profess to hold the pinnacle of knowledge in. Nonetheless, they have followers and people who believe in their teachings. That is good for all involved.

Analytics leadership is a subject that has not been discussed much and has been written about even less. This is not surprising given the state of evolution of analytics leadership. Analytics leadership is emerging as an area of study and practice.

In this chapter, we have examined why analytics leadership is different from leadership in information technology, software development, or general leadership. We have enumerated the traits that make a good analytics leader and we have examined the point of evolution in the current market for new analytics leadership roles in corporations.

In this...

Chapter 4 footnotes

1. Manager and machine: The new leadership equation, McKinsey Quarterly, September 2014, By Martin Dewhurst and Paul Willmott https://www.mckinsey.com/featured-insights/leadership/manager-and-machine?cid=other-eml-cls-mip-mck&hlkid=0b00d5ae4c264dd0821632a30c90eb75&hctky=2020931&hdpid=5de210fe-6adc-4201-9d10-1e5f9c04e8ef
2. Peter Drucker, The manager and the moron, McKinsey Quarterly, 1967
3. Augmented Intelligence: The Business Power of Human–Machine Collaboration First Edition, by Judith Hurwitz, Henry Morris, Candace Sidner, and Daniel Kirsch, https://www.amazon.com/Augmented-Intelligence-Business-Human-Machine-Collaboration/dp/0367184893
4. Curiosity killed the cat, https://www.phrases.org.uk/meanings/curiosity-killed-the-cat.html
5. The Neuroscience of Everybody's Favorite Topic, Why do people spend so much time talking about themselves?, Adrian F. Ward, July 16, 2013, Scientific American, https://www.scientificamerican...