Outsourcing data analytics management can provide businesses with a whole host of benefits, including cost savings in talent and software.
The benefits of businesses incorporating data analytics into performance reviews and decision making are numerous, but for a lot of organizations the process of building an analytics team, or continuing to fund it, can be challenging on a cost and talent basis.
This will lead some companies to outsource some or all of their data analytics needs to service providers, which are able to provide infrastructure setup, data management, and any other needs that arise. According to Allied Market Research, the data analytics outsourcing market is expected to grow by a compound annual growth rate of 34 percent between 2021 and 2028, reaching a market size of $60 billion.
But is outsourcing data analytics the way to go? In this article, we outline some of the key benefits which can be achieved when a business outsources their data analytics needs.
The cost savings from outsourcing data analytics are numerous. The most immediate ones are hardware and software costs, which should be much lower if the outsourcing firm is managing it. In the long-term, not having to pay a team of data scientists full salaries is the biggest cost reduction, alongside all of the necessary costs to hire, reskill, and retain staff.
As we said in the previous point, hiring talent for data roles can be a nightmare, with demand far exceeding supply for data scientists. Organizations that run data analytics in house will be competing against thousands of other firms for talent, and will naturally have to pay these employees high wages and bonus to retain them long-term.
By outsourcing, businesses have access to high-end talent without having to go through the process of hiring and retaining. Outsourced teams often have a wider variety of clients than in-house, and can provide broader observations of methodologies and best practices.
Outsourced teams can increase and decrease in size depending on the needs of the client, which is valuable for businesses which require higher levels of flexibility, such as startups. With in-house teams it is more difficult to acquire the talent at a fast rate, or inversely it is harder to reduce the size of a team in times of scaling back operations.
Having access to better talent brings a lot of medium to long term benefits to data analytics projects. The first is efficiency, as specialist data teams can process larger volumes of data and provide more sophisticated analytics. By using standardized practices and methodologies, businesses are also able to move from one outsourced team to another, or even move analytics in-house, without it being a huge hassle.
Businesses are often at the mercy of changing regulations and compliance codes, which are becoming more unique to each region. By outsourcing the management of data platforms to a third-party, it reduces the exposure to risks which can come from lack of compliance and data breaches, especially as data teams will be more well equipped to meet national and intranational compliance and regulatory standards.