What is data analysis, and why is it so important?

We are constantly surrounded by data. We create it every minute, we look at it, we dispose of it, yet research shows that we analyse and use only 0.5% of it. Given the amount of data there is, analysing 0.5% of it is still a huge job and it requires skilled and experienced people if it is to be done well.

What is data analysis? Simply put, it’s a process of inspecting, collecting, transforming, and modelling data. Its purpose is to discover useful information that would support decision-making processes, which is crucial in all types of businesses.

And it’s exactly the reason why it is so important – it enables organisations to transform, minimise risks, reduce overheads, and improve performance.

Let’s look into some examples. If you are selling goods, knowing what your customers like, what’s their background interests and how much they are willing to spend is vital if you want your marketing strategy to be effective and bring you more money.

The very same is true when you are looking to expand your company and need to know which areas you need to invest in. When making such a decision, you cannot rely on intuition. You need facts that will make your investment worth it.

Data analytics is crucial when it comes to maximising profitability and revenue, as well as improving productivity rates. But to get the information you are after, you need to gather and analyse a vast amount of data – something you simply may not have the time, knowledge, and resources to do.

The global shortage of skilled IT professionals makes the whole venture even more challenging.

What does data analysis outsourcing mean?

Data analysis outsourcing means entrusting a data services provider with your company’s data. In turn, the service provider delivers insightful reporting and takes care of the whole infrastructure, data management, analysis, and compliance.

According to Data Analytics Outsourcing Market – Growth, Trends, COVID-19, and Forecasts (2021 – 2026) by Mordor Intelligence, in 2020, the global data analytics outsourcing market size was valued at USD 3.04 billion. By 2026, it is expected to reach USD 9.46 billion at a Compounded Annual Growth Rate (CAGR) of 21.5% during the period from 2021 to 2026.

This trend clearly shows a huge increase in demand for data analytics outsourcing services, due mainly to the rise in the amount of data we produce, which is a consequence of the increased use of the internet and social media.

As revealed by IBM, over 90% of the world’s data was created in the last two years. Large investments in data analytics by organisations to increase their productivity are further expected to drive the market’s growth over the forecast period.

The trend is global and not industry-related. As shown in the graphs below, outsourcing of data analysis is done by companies across all industries and from all over the world.

Common challenges of conducting data analysis internally

There are several obstacles to overcome when performing data analysis in-house.

Internal data analysis has a number of advantages (including protection of sensitive information, adaptation to unique business requirements, and access to more in-depth insights) but also faces the following challenges:

• Expertise gap: In-house teams may lack the specialised skills needed for comprehensive data analysis.

• Scalability: As data volume grows, existing infrastructure might become inadequate.

• Data integration: Merging data from different sources can be complex due to varied formats and structures.

• Cost: In-house systems have associated expenses, including software, hardware, and personnel training.

• Technological evolution: The fast pace of change in data analytics tools and techniques can be challenging to keep up with.

• Data security: Maintaining control over sensitive data requires strict security protocols.

• Resource demands: Performing data analysis can be a task that requires a significant amount of resources, which can impact the allocation of computational power and personnel.

Benefits of data analysis outsourcing:

Discover the benefits of outsourcing data analysis and unlocking specialised expertise and see how it could revolutionise the way you approach decision-making and business strategies.

Professional, high quality and industry-related reports at your fingertips

A professional data analytics outsourcing partner will equip you with the very best reports, focusing on your business’s needs and using inside knowledge of the industry. Thanks to their experience, your reports will be highly valuable and will help you make the right decisions, which is crucial if you are keen to further expand your business and simply be successful.

They will also help you improve your day-to-day operations.

A service that is reliable and ready to use

When you decide to use an external provider for your data analysis, you just need to sign a contract and give the provider access to your data. Everything else will be taken care of.

You don’t need to worry about the service itself, about how it works and whether your data is protected. It all lies with professionals who take care of those types of services daily and simply know what to do.

Data outsourcing accelerates decision-making

By working with an experienced external partner, you gain quick and easy access to a pool of talented and skilled Business Intelligence Developers and Data Engineers who are not so easy to find and retain in today’s challenging job market. They will be there for you when you need them, offering you all the skills and experience you are after.

Compliance with regulations on data security and protection

When you decide to work with an external provider, all the burden of compliance with proper regulations is on them. They will take care of your data security and be ready to help you should you have any questions.

The financial advantages of external data expertise

Outsourcing data analytics can lead to significant cost savings for businesses. By hiring outside experts instead of recruiting in-house specialists and providing them with benefits and ongoing training, companies can save a lot of money.

Additionally, outsourcing eliminates the need for organisations to invest in costly analytical resources since these outside professionals already possess all the necessary tools. This approach also provides scalability since businesses can avoid hiring extra staff to meet increasing demands.

Learn more about outsourcing services:

The 4 most popular types of outsourcing contracts

Farshoring vs. Offshoring vs. Nearshoring – 3 visions of IT Outsourcing

Outsourcing costs – it’s not all about the money!

Cost-effectiveness and flexibility in nearshoring

What you need to know before data outsourcing

Before you consider data solutions consulting and outsourcing, it’s essential to have a clear understanding of the process, its implications, and what to look for in a potential partner.

Protecting your data is crucial, and it’s essential to understand how it’s being secured. This involves techniques such as encryption, access controls, and periodic checkups. If your business operates in specific sectors, there may be regulations like GDPR or HIPAA that you must adhere to, so ensure that you are informed and that your partners are aware of them.

It’s also important to explain precisely what data tasks you require assistance with, whether it’s all or just a portion of the data work. Understanding the total cost, including any additional services or hidden fees, is also important.

Keep in mind that outsourcing data analytics has some risks, such as potential data breaches or miscommunications, so have a contingency plan.

Finally, ensure that the work you receive meets your standards by having regular check-ins and reviews.

Choosing your data analysis outsourcing partner: key factors to consider

Selecting the right data analysis outsourcing partner can significantly influence the success of your business decisions.

Here are the crucial factors to weigh when making your choice:

• Reputation and references: Check their past work, client reviews, and testimonials. It’s always good to contact some of their past clients for direct feedback.

• Technical expertise: They should have proven expertise in the tools and technologies relevant to your needs. This can range from specific programming languages, tools like Tableau or PowerBI, or platforms like AWS or Google Cloud.

• Communication skills: Effective communication is vital. They should be clear about their processes, timelines, and any potential roadblocks.

• Confidentiality and NDAs: Ensure they are willing to sign Non-Disclosure Agreements or any other contracts to protect the privacy and security of your data.

• Cultural and time zone differences: If outsourcing overseas, be aware of potential challenges related to cultural differences and time zones. It’s essential to find a partner who can adjust their working hours if necessary or has efficient methods for handling such differences. Look at ours “7 tips for a successful nearshoring strategy“.

• Pricing model: Understand their pricing model. Is it fixed-price, hourly, or something else? Make sure it aligns with your budget and the project’s complexity.

• Exit strategy: What happens if things don’t work out? Understand the process for ending the contract and retrieving your data.

Outsource your data analysis to Future Processing

At Future Processing, we are skilled at providing the best service to all our clients. Data science and engineering is something we excel at.

We design and create solutions from scratch to empower your decision-making processes and support your analysis procedures. Check out what we do and how we can help you achieve your goals!