"Data scientist" is among the most in-demand and highly paid jobs available right now, which tells you a little about how many industries are prioritizing data science. That's because it can mean the difference between stagnating and skyrocketing if you know how to wield it.
Companies seek out data scientists to help bring greater insight to their efforts across departments. They can provide everything from broad market predictions to granular audience behavior analysis, and arm research and development, sales, marketing, and customer service teams with the information they need to be more efficient, effective and fulfilled at their jobs.
While many organizations understand that data and insights are important to them, many are still hesitant of or unsure how to start and how, specifically, it will affect their day-to-day operations. Here are some ways data science will reshape the workplace in the coming years.
1. Data science specialization
"Data science" has become a broad-sweeping term for anything related to the collection and analysis of data. Not all data science and data scientist roles are the same, however, as there are dozens of applications across industries, companies and departments. Some data scientists are tasked with examining patterns and identifying problems in an organization; others might be tasked with figuring out why those problems are happening. Others focus on innovation, determining what the company’s consumer base wants and needs and making recommendations to C-suites and product development teams.
As such, many people could call themselves data scientists simply because their job, like most jobs, incorporates data. Today, however, we’re putting finer points on data science and determining how to use it. Look for increased specialization in the field of data science and more ripple effects throughout organizations as a result.
2. Shifting company structures
Data scientists have proven invaluable in recent years in not only identifying strengths and weaknesses in a company's offering but also in identifying those things internally. This insight has led to changes in how companies get structured, both according to those findings and in order to support the process of data gathering and analysis itself. This means establishing new departments, bringing in new equipment and training, and creating new processes that both support and implement data science.
3. Who gets hired
For companies to leverage data science, they need, obviously, data scientists. As noted above, data scientists are highly sought after and well compensated, so there is a growing influx of talent moving into that field. HR departments will need a solid understanding of the data science field to determine the most qualified candidates for every specialty.
Data science can also inform hiring practices in other areas by determining specific company and department needs, and analyzing how well applicants suit those needs. It won’t replace in-person interviews, but it will help narrow the field and find the best people.
4. A different review process
Not only will data scientists change who companies hire, but they'll also change the way we understand our workforce through a new perception of data analytics. New measurements for employee data can determine how work hours are spent and help teams develop new operational efficiencies. A data-centric review approach can help quantify productivity, identify areas for advancement and improvement and streamline annual reviews and raises. This could lead to new hierarchies, new processes, reduced meeting times, increased promotional opportunities, decreased attrition and an overall change in the approach to work scheduling and performance evaluations.
5. Tech-forward workplaces
Data science doesn’t occur in analog, so companies are beginning to structure their companies and workspaces to keep technology at the forefront and ensure the insight derived from their data scientists is appropriately utilized. This could mean project management and CRM systems that automatically populate with information from the data science teams, workflows designed around data science, and an investment in new tools and training to optimize those efforts. Data scientists at data-focused companies will have this built in, but those companies in other industries that are just beginning to embrace data will also have to embrace the tools and structures needed to make them work for you.
Data scientists create a path for forward thinking by analyzing past patterns and current trends. They find ways to make things work better, and more efficiently. They make the lives of their colleagues easier and drive measurable success for companies, whether those companies are data/tech-focused or not.
The startup world, in particular, has embraced data science. Companies are finding new ways to manage data in order to change industries, introduce new products and revolutionize tradition. Emerging technologies have almost created a divide, and to survive, organizations of all ages, sizes, and industries will have to evolve in a way that incorporates this change.