No matter what the industry is, top-level executives play a crucial role in the organisation’s growth. They have to be very active when it comes to growth strategies. Talking about data science, it is lucrative as well as a vast domain, and for a company’s data science department to grow, it requires some of the top-notch strategies.

Today, with technology reaching the sheer heights of transformations, it has become imperative for leaders and executives to embrace the changes in order to take a significant lead in the industry as well as in the data science domain.

Here in this article, we have listed down the key positively disruptive forces that every leader should incorporate in their data science growth strategies.

• Leverage Latest Technologies

Every year, new technologies keep entering the industry and leaders should always stay updated with every new tech. There was a time when there were only gadgets; however, today the same gadgets have turned into connected gadgets and are playing a vital role. Also, they should figure out how to incorporate the latest technologies that could help them with their growth strategies.

Data science is a weighty field of work — it takes a tremendous amount of focus and knowledge for data scientists. So, if there is a technology that has the capability to reduce the stress of a data scientist as well as reduce the work, a leader should always consider incorporating that.

• Automating Complicated Processes

No matter how knowledgeable or skilled a data scientist is, there are times when work gets hectic that the need for some automated system becomes more and more imperative. So, incorporating automated systems is considered to be a good idea when it comes to increasing efficiency.

Cyber-Physical System (CPS) is one of the major examples. CPS is a mechanism that is controlled or monitored by computer-based algorithms, tightly integrated with the Internet and its users. It not only helps in efficiency but also automates manual tasks, helping professionals to a great level. It is also a great way to control costs.

• Responsibility Distribution Strategy

Having a talented team is one thing, but without a leader who doesn’t have the best growth strategy, the team might not reach to the highest level of efficiency.

One of the most effective ways to make a team significantly efficient is to distribute responsibilities. Make sure you follow the policy of empowering people at all levels to make decisions. This is considered to be a great practice when it comes to team management. It gives you the opportunity to have a look at the outcome when different team members make decisions.

Data science is a field of work where teamwork and involvement of multiple minds play a vital role. So, it would be a great way to make the most of every single team member.

• Verify and Then Hire Talents

Data science is a domain with several work fields, meaning, a not every data science professional will have all the skills from all the field of work. In order to fill the talent void in the team, go with a strategic hiring process, considering capabilities and experiences.

Being of one of the most sought after career option, and being a vast domain, one cannot compromise with skills and experience when hiring a data scientist. And one of the bitter truths in the industry at present is “faking experience” and over the past couple of years, the number of data scientist faking experience has increased. So, when you go through a CV with a significant experience level, make sure you do your research about his contributions to the previous workplaces.

• Explain Other Domains Of The Business To Data Scientists

When you are leading a team of data scientists, don’t limit them to only data science-related works. It is imperative for an organisation to run efficiently is to make each and every employee familiar with other domains, and data science is no exception.  

“There is a lot to learn in this space and it is imperative that one builds on his/her knowledge as it continues to draw more accurate conclusions from the dataset,” said Manoj Sharma, Director-Human Resources, NetApp in interaction with AIM.

When you explain other business processes and domains to your data science team, it only gives them the idea of how the company works and make a profit but also helps them in coming up with ideas that could be incorporated to better the process. This comes under employee empowerment.

So, make sure you’re data science A-team is also familiar with other business processes so that they can relate and work to make things better.

Outlook

With time, the world of data science is evolving, making it imperative for executives and leaders of organisations across the world to make use of more effective growth strategies. Today, the number of opportunities for data scientists across the globe are increasing at a jet speed, making the competition tough globally. So, keeping that in mind, an organisation that is keeping abreast with the latest trends and strategies will only win the race.