Listen to this story
“The strength of the team is each individual member. The strength of each member is the team.” – Phil Jackson.
Businesses are seeking to place data in the driver’s seat of their business and product strategies as they become more aware of the decisive potential of data to achieve organisational goals. This requires assembling a solid data team that can successfully spread its insights across many business domains. However, that’s easier said than done.
There is a need to engage the data team to ensure they are effectively aligned with the goals and objectives of the organisation and ensure they are contributing to the success of the organisation. Engaging a data team aids data-driven decisions, helps with organisational goals, improves communication within the organisation, increases productivity and leads to better collaborations.
Mindful of its importance, we sought to know what our industry leaders think when it comes to data teams and their significance. Industry experts like Vijoe Mathew, Global Director – Supply, Logistics & Finance at Anheuser-Busch InBev; Sanjay Srivastava, Vice President – Analytics and Reporting at American Express; Swati Jain, Vice President, Analytics at EXL; Gaurav Bansal, Head – Analytics at L&T Financial Services; Dhruv Rastogi, Vice President & Head of Data Science at IKS Health joined us for our Online Meet-up.
Expectations of a team
It all boils down to two components: learning and development. People are either looking to learn something or feel challenged and grow as professionals. What they are doing is that they’re contributing their skills to the objectives of the company by bringing impact and value.
– Sanjay Srivastava, Vice President – Analytics and Reporting at American Express
Work delivery aspect
Everything begins with the leadership and how they see the engagement is what the culture has been set up as. If it is a learning culture, everybody appreciates what others bring to the table, sharing and exchanging knowledge in different ways. The people in the industry get a kick by enhancing this learning as a part of delivery. On the delivery side, it is the spirit of excellence which keeps them engaged. That spirit, again, comes when the lead reveals the project, and the team is smart enough to get it done from anywhere. But that vision is important. As far as the delivery is concerned, how do we do world-class? That means we aspire to make something that no one else can better. That itself brings a lot of engagement by delivering on a project and doing any outside research to see what is happening in that area and make it to the next level.
–Swati Jain, Vice President, Analytics at EXL
Going hand-in-hand with data scientists
There is one more dimension – culture. Anybody who works in an organisation should know what the culture of that company is, the growth opportunities, and the learning opportunities included. There’s a space where there are a lot of opportunities when everybody gets a lot of opportunities to explore. So nobody is tied to a company. Despite the best salaries, the attrition rate is 25 to 30%. This means that people have a lot of opportunities in this space.
One of the biggest challenges with the technical crowd is that they are very good at the technical craft. But managing people is a different ball game altogether. A big challenge for us was how to develop leaders who are empathetic, who know how to manage a technical crowd rather than just being technical members and leaders of the company. Leaders build culture. The priority for us is to bring or develop leaders who know the art of managing or developing technical talent. About 80% of all analytics problem statements are by either a regression classification, or clustering. But the fact is that most organisations don’t have that opportunity. Because we all work with structured ERP data, we don’t know how to work on terabytes of text, image or video, or kinds of datasets, where we can use fancy stuff, and be super creative. We have to create an environment for them to explore, that would never come from projects, since projects are all going to be machine learning based. And it never will reach a level of deep learning.
–Vijoe Mathew, Global Director – Supply, Logistics & Finance at Anheuser-Busch InBev
Out of the blue solutions
We started something called the ‘Stretch Project’. It’s a formal business problem that you want to solve as a stretch project. In this, we give a problem statement and are willing to form groups, we tell them what needs to be done. There is a leader assigned to the groups, and we tell them that it would require at least one or two hours each day, in addition to their existing work. This is an introduction. The catch is that though people will have to invest their time, they will end up learning a lot. We give them something very different from their mundane tasks. This gives them a good opportunity to get recognition, and learning.
–Gaurav Bansal, Head – Analytics at L&T Financial Services
Do you have the time?
A mandate should be that a minimum of 10% of your time must go into learning new stuff. The learning could be technical in nature, domain-specific, industry-specific, or even behaviour-specific. Just learning how to deal with a difficult situation is also learning. For certain corporate programs, which they subscribe to, employees are supposed to complete certain modules which their managers assign, depending on their areas of development. And lastly, encourage a lot of peer-to-peer learning. So in a nutshell, people learn by themselves. And the motivation levels vary across people. The second thing is, as an organisation, to introduce certain corporate programs which people learn forms a part of performance evaluation. And the last is peer-to-peer learning, in which people talk about the projects that they worked on or certain emerging technologies that they have recently come across.
–Dhruv Rastogi, Vice President & Head of Data Science at IKS Health.
Motivation is key
There is so much you can do as a manager or as an organisation to get the people motivated. This is something that every manager comes across, whether it’s data science or any other industry. It’s not unique to our own function. Whether it’s through gentle nudging or harsh nudging, there is so much you can do and after that, everybody has their own career, their paths, interests and motivation levels. We ensure as an organisation or as leaders, we do as much as we can. And after a point, this also starts showing in their performance evaluation. People who are more motivated, hardworking, progress better and faster in organisations compared to those who are more relaxed in their approach.
–Gaurav Bansal, Head – Analytics at L&T Financial services
Need for a vision
As leaders, we beat ourselves down if there isn’t a lot of learning happening in the team. I personally think that providing opportunities in the enabling mechanism is really important. But I also do not want that every single individual on my team is only learning new things. I need a big chunk of people who actually do the ongoing, regular, boring day-to-day work and are not looking for the shiny star every single day. We have seen the fact that a majority of the work is regular stuff. And in the bulk of the population that is average, if all of them start to do the big transitions and big changes, we’ll be in trouble. So, for those who are motivated, provide them with all the opportunities. For those who are not, make sure that if they’re doing their work, they feel valued. And they know that they have an opportunity, whenever in life they intrinsically get that motivation.
–Sanjay Srivastava, Vice President – Analytics and Reporting at American Express
In conclusion, engaging a data team is critical for the success of a data-driven organisation. By providing the resources, support, and alignment with the goals and objectives of the organisation, you can help ensure that the data team is able to deliver the insights and information needed to make informed decisions. Engaging a data team is an ongoing process that requires regular communication, collaboration, and investment in the development and training of the team. By making this investment, organisations can reap the benefits of a well-engaged data team and stay ahead in a data-driven world.
This article is written by a member of the AIM Leaders Council. AIM Leaders Council is an invitation-only forum of senior executives in the Data Science and Analytics industry. To check if you are eligible for a membership, please fill out the form here