Small and medium-sized businesses should expect to spend $10,000 to $100,000 per year on data analytics. The amount you will pay is determined by the number of employees and the needs of your firm. Companies should, however, allocate around 2-6% of their total budget on data analytics.

Data analytics is no longer limited to huge corporations. Small and medium-sized organizations now create a significant amount of data. Data analytics can help business owners get useful knowledge and make better educated decisions.

Most businesses spend around 2-6% of their total budget on data analytics, which includes tools, personnel, and services. It promises significant growth and has announced that additional tools are in the works. These tools have assisted in the conversion of raw and unprocessed data into insight.

Data has also increased as a result of the Internet of Things (IoT) and connected gadgets. Its volume has increased as its diversity and richness have expanded. The available data network must be optimized for a firm to be successful. It provides the potential to make better-informed company decisions and enhance items or services offered to provide a better experience to customers.

Based on a study done by SAS, it has been revealed that 72% of organizations claimed that data analytics has been critical to their innovativeness. The difference in the performance of more prominent corporations and SMEs has been traced back to analytics as a competitive landscape. Thus, this highlights the need for data analytics.

For example, if a company has a revenue of approximately 2M$, it would require almost 100K$ every year. Ordinarily, this seems like a large amount to spend out of the revenue available, but most companies with this range barely have the required data analytics tools. However, this global estimate takes into consideration the time that would be spent on the data analysis and reports by all the teams.

Various options are available for consideration when engaging in data analytics, and all of this depends on your company. Thus, the human cost, services, and tools have to complement each other.

Human Cost

People are also crucial when conducting data analysis as the end goal is to influence the willingness of your customers. It is essential to look at how you source and enable the necessary talent. Thus, the human cost demands that you identify those who can help integrate data-driven activities within the organization.

Read Also: How do You Teach Data Analytics?

Those who do it already have analytical skills in your company, and you can build their skills to reduce the cost of hiring experts. It involves adopting user-friendly training with tools that can be accessible to those trusted with the duties.

Small or medium-sized companies can use this to reduce human costs in the long run. Yet, you may need to get experts to start the process and train your in-house employees.

Services

Your company’s investment in data analytics has to place into perspective if it is a service acquired. There are agencies and other companies that take up the task of data analysis for other companies, which would be important in determining the cost for your SME.

For instance, you could contract a Customer Relations Management (CRM) agency to build some automated marketing workflows. In this case, the agency would spend enough time reconciling some customer data sources. It would help develop a certain level of customer knowledge to aid the analysis or some RFM segmentation and then move on to email workflows.

Just as the human cost, this workflow level would cost separately and play a vital role in your company’s money on data analysis.

Tooling

Specific essential reporting tools are used in data analysis suitable for your SME. Selecting one should begin with some popular reporting tools like Google Data Studio. The device is based on Gheet data and Google analytics, which have proven efficient in analyzing company data.

Companies still find simple BI tools helpful and purchase the Metabase or PowerBI, which leads to the next stage. The next step is to implement a basic data infrastructure with a data warehouse. There is Google BigQuery and ETL software like Airbyte or Fivetran. These tools have licenses, and these cost differently while influencing how much your company needs to spend.

Here is a breakdown of how much an in-house data science team costs vs. the price of outsourcing data services:

Data Analytics consulting firms

Using data analytics firms is known to be reliable due to several factors. Consultants are known for their experience in various industries. However, this makes it easier for them to deliver results faster.

An advantage of this is the level of commitment it requires compared to when having to hire a full-time employee. However, it is essential to note that these traditional consulting firms would cost approximately $50-100 per hour. In some cases, the costs are even higher, as the job would span through weeks or months.

So, engaging a consulting firm would require at least $2000 – $4000 for a week’s work. Even though this may be the first option for data analytics for your company, it may not be the most cost-efficient. It may not be a sustainable alternative as it relies on external factors.

Outsourced data analytics freelancers

Freelancers can serve the same function as consulting firms but with a lower price due to the workforce needed. It could be a single freelancer with enough experience to help analyze your company’s data. 

In most cases, it is still reliant on the project’s scope as it drives the cost of the analysis.

The project would be short-term, just as found in traditional consulting firms, which means minimal commitment. Engaging freelancers would be estimated at $1000 per week, which is considerably affordable. Outsourced freelancers can also differ in their quality, and research is critical.

However, the return on investment (ROI) and value-added to the business can not be determined. Language and cultural barriers can be a problem with outsourcing freelancers as most are in places like China and India.

This could constitute friction between your company and a data analytics service provider. Though outsourcing freelancers may help reduce spending, you must consider the differences.

In-house data analytics team

With an in-house consultant, there is someone who is always on call and has been a part of the company for a while. This provides an opportunity to have someone who is considered an outsider handling the company’s analytics. The only necessity for this to work is training the employee to understand your business and industry context.

Compared to working with consultants, this reduces the level of friction with delegated tasks. Finding the right analyst can be time-sensitive, obstructing the quality of service provided. The hiring process can also be tedious and require a commitment to ensure that you find the perfect fit.

There are equal concerns that full-time analysts may become redundant during the offseason. The minimal cost of keeping an in-house specialist is approximately $60,000 compared to what other data analysts cost.