As a team leader in statistics, you have the responsibility and the opportunity to create a positive work environment for your team members. A positive work environment can boost productivity, creativity, collaboration, and morale, as well as reduce stress, turnover, and conflicts. How can you achieve this goal? Here are some tips to help you.
Communication is vital for any team, especially in statistics, where you need to share data, methods, results, and insights with your team members. You should communicate clearly and frequently with your team, using different channels and formats, such as emails, meetings, reports, presentations, and feedback. You should also encourage your team to communicate with each other and with you, and listen actively to their ideas, concerns, and suggestions.
In my tenure overseeing data science projects, I've seen firsthand how miscommunication or lack of communication can hinder a project's progress. For instance, in one project, a lack of clarity in the initial stages led to weeks of unnecessary work. It's not just about relaying information; it's about ensuring comprehension. I am a fan of the "two-pass" method: after explaining a concept or directive, ask the individual to explain it back in their own words. This active engagement ensures that the message has been both received and understood.
One thing I find very helpful is having continuous mentorship programs with the team and availing opportunities for the team to keep practicing and showcasing what they know and the challenges
My experience is that dry models are unhelpful. The team need to thoroughly understand what they are doing before they can make the appropriate assumptions and make the appropriate model choices. Clinicians need to be educated, but the stats team need to abandon rigor and simplify the concepts so the clinicians understand the question being asked.
Another thing I have discovered is that it's beneficial to clearly articulate the "why" behind our work. This includes specifying the business problems we aim to solve, the significant actions resulting from our analysis, and the value our work brings to the business.
In my experience it is fundamental to show respect for people's work, especially when one has to have a difficult conversation. Make sure they believe you are really listening (there are things one can do that helps us truly listen and prove that to them). Another fundamental aspect (confirmed by the sheer number of people who mention this) is to be clear and have frequent communication. And finally, a trick I used to use was to tell people to come to me if they can't do something. I would usually say to my teams: "I'm the only one who is expected to know everything. It is part of your job to reach out when you are stuck"; I found this to foster a more collaborative environment.
Another way to create a positive work environment is to set realistic and meaningful goals for your team. Goals should be specific, measurable, achievable, relevant, and time-bound (SMART), and aligned with the vision and mission of your organization. You should also involve your team in the goal-setting process, and make sure they understand the expectations and the criteria for success. You should also monitor and evaluate the progress and performance of your team, and celebrate their achievements and milestones.
When agreeing goals remember that this is a two way street and as a leader your responsibility if to empower individuals to meet the goals that you have agreed with them. Where goals are based on corporate strategy, explain how the work the team is doing leads to the accomplishment of that goal and how you as a leader will demonstrate that to the wider organisation on behalf of your team.
Incorporating the input of your team when setting goals can provide invaluable insights into the challenges and opportunities that exist at ground zero. This collaborative approach not only enhances the goal-setting process but also reinforces the overall system, ultimately leading to more optimal and effective results.
Let’s face it, deadlines work and get things done. When setting a hard fast deadline you inherently also are setting a goal or a specific tasks to be accomplished. If you work as a leader of a group, it’s necessary that you have a deliverable or end result, otherwise statisticians will feel time has been wasted. Goals make sure this doesn’t happen.
A goal is only meaningful when it can be measured; otherwise, it remains a wish. While collaborating with the UAE's Ministry of Labour, the Prime Minister aimed to make the UAE the world's best place for living and working. This aspiration was transformed into a concrete goal, backed by a Balanced Scorecard featuring relevant metrics and dimensions.This approach facilitated the translation of the ministry's objective into a precise and statistically-driven model. Today, the UAE is on track to achieve this objective by 2023.
One of the many things that I found interesting about statistics is : you have a number! How to use it to set SMART goals for your company is the big question. The team should be involved in the goal setting process by using accurate data.
Statistics is a dynamic and evolving field, where new techniques, tools, and applications are constantly emerging. You should provide your team with training and development opportunities, to help them update their skills, learn new ones, and grow professionally. You can offer them online courses, workshops, seminars, webinars, mentoring, coaching, or other resources that are relevant and useful for their work. You should also encourage your team to share their knowledge and expertise with each other, and create a culture of learning and curiosity.
Encourage team members to engage in knowledge-sharing activities, such as presenting their findings at conferences, writing papers, or attending seminars. This not only helps individuals develop professionally but also enhances the team's overall expertise in statistics.
This is a very important reward that good Data Scientists love and it is very important in our industry, since there are many innovations every day. Therefore, promote spaces to try new things, do not penalize errors and to have an applied research environment where idea sharing is highly appreciated, it is a good way to promote team growth and better outcome for data science solutions.
As many technical disciplines, statistics and data science is one where continuous learning is essential. Both for you and your team. Especially, with ever fast evolving landscape for the theory, methodology and the tools. What I observed is seminars and workshops etc requires too much effort compared to susceptible benefits. I foster "self learning", where I encourage and direct team members to select their own methods and practices for learning.
Training and development (T&D) represent an infusion of intellectual capital: balance the hard and soft returns from this investment. For technical T&D, build acumen (applied expertise) for current and future needs. DO NOT neglect the soft skills like active listening, emotional intelligence and managing conflict. I have found these soft skills are essential in requirement gathering from the business clients.
A key aspect of team development is collaboration and ongoing learning. That learning can be in the form of traditional coursework, having a mentorship program within your team, and regular meetings to discuss projects. Those meetings can provide space for the team to share methods, ask each other questions, and offer solutions. When analysts and programmers don’t have these opportunities, the work can be less efficient and can feel isolating. Most people may benefit from industry involvement in the form of conferences and other networking groups or events. This is another great option for smaller teams.
Collaboration and diversity are essential for a successful statistics team, as they can enhance creativity, innovation, problem-solving, and quality. You should foster collaboration and diversity among your team members, by creating a trusting and respectful atmosphere, where everyone can contribute, express their opinions, and learn from each other. You should also promote teamwork, cooperation, and mutual support, and avoid competition, isolation, and silos. You should also value and appreciate the different backgrounds, perspectives, and strengths of your team members, and leverage them for the benefit of the team and the organization.
Create opportunities to review your team's work, in two different flavors: - Technical/methodology review, during project execution, to ensure the best statistical tools and approach are used to solve the problem. Talk about feature engineering, hypotheses and assumptions, drawbacks of some techniques (e.g. risks of overfitting, poor explainability), etc. - Business review, after the execution or a milestone, to focus more on the impact the data science project had on the product/company. Talk about customer experience, cost savings, non-technical learnings, etc. During these, be transparent about your choices and welcome feedback. Feedback denotes people care. Conversely, attend others' review, give actionable feedback, show you care.
Recognize that there's more than one way to do things, especially in research design and statistics. It's easy to get set in our ways, but a diverse team has a lot to offer. I love it when different perspectives from team members get incorporated into our general approach.
Diversity and collaboration is needed more than any other field in statistics and data science. Because, as I never get bored to say, it is a field where there is almost never a one-fits-all solution. So, I have always benefited having different perspectives throughout my career.
One time at work I suggested a task to my boss for him to do. It was a task I knew was in his wheelhouse and that he loved to do. We needed that step completed fast. And I could do the other step needed fast. And immediately the response was positive. This was when we were under a high amount of stress to create and build a new product quickly and get it out the door. No matter who you are, compliment everybody. Get to know others on your team. Get to know what they like to do. Then be proactive and let genuine compliments flow... and get stuff done!
Encourage team members to work together on statistical projects, share their knowledge, and contribute to joint problem-solving. This could involve organizing regular team meetings, workshops, or brainstorming sessions focused on statistical challenges.
One of the most effective ways to create a positive work environment is to recognize and reward your team for their efforts, contributions, and achievements. Recognition and reward can motivate, inspire, and retain your team members, as well as increase their satisfaction and loyalty. You should recognize and reward your team both individually and collectively, and both formally and informally. You can use different methods, such as praise, feedback, bonuses, incentives, awards, recognition programs, or other forms of appreciation that suit your team's preferences and needs.
Acknowledge individual and team accomplishments in statistical work, both in terms of technical excellence and innovative thinking. Celebrate successes and milestones to maintain motivation and demonstrate appreciation for their hard work.
Recognizing your team is strategic, not just a feel-good move. Consider a 'Monthly Spotlight' to highlight standout work, boosting morale and setting performance benchmarks. For big project wins, schedule a 'Team Victory Day' to celebrate and unwind. Financial rewards are effective, but be creative. Offer experiences that enrich team skills, like workshops or seminars. Small gestures count too. A handwritten thank-you note can make someone's day. Establish a 'Recognition Wall,' a dedicated space to display team accomplishments. Make it a routine, not just a one-off, to create a culture where everyone feels valued and motivated to do their best.
Enhance their communications skills and let them present their own work, if that is not the case talk using, we did, instead of I did, and recognizes publicly who is/are behind solutions. Promote your team at all times!.
Acknowledging work consistently and often is so important and even intangible rewards and recognition can really increase the teams sense of cohesion
While the specifics of reward will depend on the company and industry, a key aspect of this is consistency. Ensure that recognition comes naturally and regularly, rather than something your team has to ask you to provide, and that significant wins and accomplishments are communicated to other teams and management. Then, when the opportunity comes to provide reward to the teams, those consistent recognitions and shout-outs can be used to robustly quantify accomplishments, and ensure star performers are not forgotten or under-appreciated.
Finally, you should support your team's well-being, both physically and mentally. Working in statistics can be challenging, demanding, and stressful, especially when dealing with complex data, tight deadlines, high expectations, and changing requirements. You should support your team's well-being by providing them with a safe, comfortable, and ergonomic work environment, where they have the necessary equipment, tools, and resources to do their work. You should also encourage your team to take breaks, rest, relax, and balance their work and personal life. You should also be empathetic, compassionate, and supportive, and help your team cope with any difficulties or challenges they may face.
Seasoned statisticians may give a robotic impression, with their numerical jargon, talking about everything is as it is a probability distribution to explain. However, statisticians are human, too. And field of data science and statistics can be particularly stressing sometimes due to unrealistic expections. So make sure to cultivate hapiness management properly on your data team.
Couldn't agree with you more. The compounding stress in data science teams is more often a mix of assumed unrealistic expectations which are often not well articulated. A keen eye needs to be kept on what indeed can be called a happiness quotient within a team. Personal engagement within a team in and outside work is a key ingredient to achieving a higher quotient.
I agree with Arnab - - folks on data science and research teams often will shoulder whatever burden is perceived to be theirs, regardless if it represents realistic expectations. To combat this I found that I had to start modeling what that looked like. So I started scheduling emails that I felt needed to be sent late at night so that they wouldn't get delivered until the AM (or start of work week), took my PTO and actually didn't respond to some (cherry-picked) emails, etc.
We don't run engines in the red for long periods for good reason, and the same considerations should be made for your team as well. While any team should be able to push above and beyond, keep a close eye out for signs of burnout and be prepared to step back to normal levels of output if those signs start cropping up. A team given a chance to recover can then push again or pivot to tackle other challenges, while a team run ragged from unending pushing will be at risk of burnout, leavers, and poor morale.
A healthy degree of independence - both in methodological approach and working/communication style - goes a long way. It ensures ownership of tasks and fulfillment.
The core principles of effective leadership, such as communication, setting expectations, and fostering a positive work environment, remain the same across different domains. However, the specific knowledge and challenges can vary, so a team leader should adapt their approach to suit the needs of their team in their specific field. In a statistics team, a team leader may need to have a strong understanding of statistical methods and data analysis techniques, which may not be as critical in other domains.
Culture, discipline , coherency and consistancy and hard work ensures progress in any field or domain, but being leader is not only taking responsibility but also caring to the people you lead.
Stick to transparency and honesty: While it may be tempting to sugarcoat the data, transparency is key. Present the data as it is, acknowledging any negative trends or challenges. Emphasize that an honest assessment is the first step toward improvement.
Provide access to necessary software, tools, and training that will enhance your team's statistical capabilities. Encourage team members to enroll in workshops, webinars, or courses to stay up-to-date with the latest statistical methods and technologies.