Organizations are tapping the many advantages of data analytics for their companies. Data-driven businesses perform better and leaner than their competition but, depending on your needs, it can be a heavy burden on a team. Outsourcing data analytics is a valid option to keep the same agility and competitiveness.
Hiring data service providers can create a boon within the business. It can also result in several risks that can put your business in the red. Outsourcing data analytics does not always make sense for everyone, but it’s a viable business strategy.
Should you keep your data analytics in-house? Or does it make more sense to let expert teams outside your own business handle it? Here are the many pros and cons of outsourcing data analytics in your company.
Pro: Hire Data Analytics Teams Without Recruitment
Data analytics are among the scarcest IT skills on the planet at the moment. While many people point out that people are learning data science in droves, the profession itself is a rather new addition. Not all people have an opportunity to learn the skills necessary to build a competitive data analytics team.
Skills in cloud computing, data lakes, big data, and more take years to learn and crucial experience to master. These years needed for mastery mean fewer people take on the challenge to learn it. You’ll likely build a small analytics team yourself, but an in-house team can take years of recruitment without pouring resources.
Organizations that have vital needs like increasing onboarding and offboarding security and provisioning data lakes need bigger teams. It doesn’t stop at having more manpower too. A bigger in-house IT team does not necessarily mean they have the appropriate skills.
Outsourcing data analytics means you can get the results you need without headhunting for a bigger in-house team. You can leverage the skills of a veteran IT team without needing to hire them at all.
Con: Potential Security Risks and Data Loss
At a time where data is almost everything, it’s safe to say that some data can be more valuable than actual gold. It helps run your business in a clockwork fashion, so it’s crucial to have a secure way to hold your data and keep it in perpetuity. Data loss can be a big problem, especially if it happens through an outsourced team.
Data loss may mean many different kinds of things, including the literal breakdown of data storage to exposure of sensitive company data. By losing your data’s trustworthiness and confidentiality, it loses its value too. There’s also the potential for hackers to gain valuable analytics data that can be used against your company.
The solution to such an issue is performing consistent checks for existing data security protocols. A security contract is crucial to deter companies from neglecting their responsibility to protect your data. Such contracts should also include consequences in the event of a breach or loss of security assurance.
Pro: Outsourcing Prevents Disruptions
Business disruptions are commonplace for many companies in the current global landscape. A good example of such issues includes the pandemic, which rerouted teams to work in remote and work-from-home environments. Big economic issues like recessions, stock drops, and more can be problematic for your business.
Most companies resolve such issues by moving their data analytics infrastructure through the cloud. Companies without such expertise can outsource their need for data science/big data outside their team. They can even move it towards business process outsourcing (BPO) companies that offer it for a much cheaper price.
By having an outsourced team handle your data infrastructure, you keep your processes intact without too much disruption. Keeping it in the cloud with remote experts means you can put your team anywhere and be assured that your protocols are running in place.
With the right automation, you keep your daily data analytics running even if your actual business receives a big disruption.
Con: You Might Not Be A Priority
Is your business a priority for the company you’re outsourcing to? It’s a common question that puts into perspective if you’re getting the most out of the process outsourcing company that you hire. In any situation, there’s a possibility that you’re not utilizing the raw data analytics processing that the outsourcing firm can provide.
In many situations, outsourced firms rely on having multiple companies outsourcing their businesses to them. Depending on the size of the team, they may handle several companies with differing data analytics requirements from each other. This can stretch out the firm too thin, usually to detrimental effects.
Errors are more likely. The speed of delivery may suffer and, if you’re not among the priority clients, you’ll get scraps for the amount you pay.
Always make sure that your business contract with the outsourcing firm is airtight. You want to be clear about details like the scope of work, output details, and even timelines. You want to clarify with the outsourcing team the roles expected from each other and pen a clear service-level agreement with consequences for breaking it.
Pro: Outsourcing Has Lower Cost Per Result
Much like any business decision, cost is the biggest rate-limiting step to getting any type of service. Any high-performance data analytics and business intelligence in-house will cost you a lot of money. A qualified data analyst, for example, will cost around $70,000 to $150,000 per professional.
If you need a team, your cost will rack up to millions per year, which not all businesses can handle. Outsourcing can get you a different result, with a lower cost per result in your business analytics. Outsourcing also has other advantages, which can include anything from analytics app development to integration.
All you need to do when outsourcing is to pay for specific deliverables that you need in your business. Rather than get an all-out approach that creates a lot of noise, you can work with the results that you want instead.
The Bottom Line
When it comes to data analytics, the big question stands: should you outsource or should you go in-house? As we listed all the pros and cons of outsourcing, the answer depends entirely on your needs as a company.
Inhouse teams allow your company to keep business agility and have tighter data security at the cost of money and recruitment speed. Outsourcing your data analytics needs have lower costs and afford you a bigger team at the expense of risks like data loss, errors, and security issues.
Look at the pros and cons we listed and keep your data analytics airtight. Whether you opt for an in-house team or outsourcing, knowing what works for you can mean the difference for your bottom line.