Why You Should Outsource Your Data Science Tasks
We’re living in the age of Big Data where the amount of data we have is growing exponentially. It’s estimated that around 90% of the data that currently exists was created in the last couple of years alone. Additionally, by 2025, the collective sum of the world’s data is expected to reach a whopping 175 Zettabytes!
As data grows, so does our ability to gain actionable insights from it. Businesses around the world are now investing heavily in data science in an effort to unlock the insights in their data and push their business to the next level. This is also reflected in the Big Data analytics market, where the market is gaining $7 billion in value each year and is expected to bit $103 billion by 2023. Let’s take a look at what data science can do for your business and the pros and cons of outsourcing your data science tasks.
What Data Science Can Do For Your Business
Customer Analytics: This is the process of collecting and analyzing customer data to gain valuable insights into customer behavior. This can help your business identify customer pain points, design robust marketing strategies, offer personalized recommendations to customers, and more.
Optimizing Processes: data science can help you identify where inefficiencies exist in your workplace operation so that you can fix them. Data analytics has a varied set of use cases that can be implemented across all industries. You can identify where there is friction, time lost, or erroneous outputs within your business.
Market competitiveness: Investing in unlocking your data and utilizing the latest machine learning and AI technology can put you ahead of your competitors. Advanced tools lead to advanced insights that you can then turn into actionable goals for your business. Advanced machine learning and data science tools can also help you identify problems you didn’t know you had, or identify problems before they arise.
Digitization: Data analytics and data science go hand-in-hand with digital transformation. As companies become increasingly digital, they enter the realm of data collection and analysis. Companies stand to gain a significant amount by digitizing in as many areas as possible and taking a data-driven approach to their business.
The Pros and Cons of Outsourcing Your Data Science Tasks
Access to Highly Skilled Data Scientists
The Harvard Business Review, a publication owned by Harvard University, dubbed Data Scientist as the “sexiest job of the 21st Century”. You’d think with such a glowing review that there must be an abundance of data scientists out there. The reality is quite different. There’s a huge shortage of data scientists but an increasingly high demand for them.
This shortage of skilled data scientists is a cause for serious constraints in some industries as they struggle to fill these roles. Research conducted by IBM pegs the opening for data science jobs in 2020 to reach approximately 700,000 globally. Put simply, everyone wants data scientists, but they are struggling to find them.
By choosing to outsource your data science tasks, you get instant access to highly skilled data scientists with a wealth of industry experience that is ready to start working straight away.
Scaling Your Data Science Operation
When starting, it can be difficult to decide what level of data science your company should invest in. You may decide to focus your efforts on a few tasks initially. However, in the future, you may find there’s a need for a heavier data science operation. By outsourcing your data science tasks, you can easily scale up your data science operation as the need for more data science scales up. If you handle all of your data science in the house, this can be a much more complex process that involves hiring new employees, training new employees in your business, and writing business plans.
Outsourcing your data science tasks gives you a high degree of flexibility when it comes to deciding which tasks to focus on. Your focus might shift over time as you realize the value in some data science tasks for your business, as well as areas that you think require less focus. With outsourcing, you can tailor your experience to suit your company, and allow you to try new ideas and Proof of Concepts (PoCs) without any further obligation.
It’s Often More Cost-Effective
If you’re unsure of exactly how your data science operation will look, outsourcing is the best option. You can pick and choose what data science tasks will provide the most benefit to your business and limit your spending in these areas. You can choose to scale up or scale down the level of data science tasks according to your budget. If you handle your data science in-house you may spend more money by hiring employees only to find there isn’t enough work for them to do, or that your data science needs are different from what you initially envisioned.
There are Times Where It’s More Expensive
Although outsourcing is more cost-effective the majority of the time, there are situations where it can be more expensive. This is usually when you want to run a large data science operation with a rigid set of goals and a tight timeline. If you have a clear plan for your data science operation, then it may be best to hire in-house staff where you can closely monitor their tasks and output.
Communication and Workplace Culture
Since outsourced staff is usually off-site, this can lead to a breakdown in communication at times. There are tools and techniques you can adopt to reduce the risk of this happening, but it’s still a risk when you can’t simply wander up to someone’s desk. Additionally, if you have a unique workplace culture then you may find that the culture doesn’t mesh well with the outsourcing team.
What’s Right For Your Business?
For the majority of businesses, outsourcing data science will be the right option. Outsourcing grants you a high degree of flexibility and scalability and frees you of the burden of finding the right employees in a highly competitive industry.
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