Can a small data team have a big business impact?

It’s easy to assume that “bigger is better” when it comes to the size of your data team. With everything that comes with being part of a data team, many people assume that a small team struggles to handle it all.

Small data teams CAN have a big business impact! At Datavault, we’ve seen some small teams have a bigger impact than larger teams.

In this blog, we’ll go in depth on our latest webinar with Datavault Builder to answer the question “Can a small data team have a big business impact?”.

Can a small data team have a big business impact?

In short, yes – a small data team can have a big business impact. But what does that ?

What is a “small” team? How do you measure “business impact”? And what skills do your team need to bring value to your business?

Understanding business value and small teams

Before you can understand why a small data team can provide big business impact, you must understand what those terms mean. These may be unique to your business, but we’ll now explore the definitions.

Business value

• Return on investment (ROI) – You can achieve business value in various ways. One of the ways is through Return of Investment (ROI). If you were to invest £500,000 into your data team, you would expect more in return to make it worthwhile.

• Payback Period – To measure ROI, you need to consider the payback period. This is the duration it will take to get back the money you invested.

• Degree of certainty -It is important to consider the degree of certainty or acceptable risk when calculating business value. By using the right tools and techniques, you can increase the chances of success and reduce the risks.

• Value Strategy – Ultimately, achieving business value requires having a strategic and/or business impact. You can achieve this by aligning your investments with your objectives and vision.

3 benefits of business impact

Business impact can have significant effects on your organisation’s success. Here are some benefits to consider:

1. Revenue

Revenue generation is one of the most obvious benefits of business impact. For example, by analysing sales data, you can gain insights into customer behaviour and monetise it to increase profits.

2. Reduce costs

Another benefit is the ability to identify and reduce costs. You can identify areas of waste and measure waste stratification to reduce expenses. League tables also encourage healthy competition among employees and further reduce costs.

3. Improve service

Improving service is an extra benefit of business impact. Companies can enhance the customer experience by improving response time and service performance. Capacity analysis can ensure that you are operating at maximum efficiency and to identify any bottlenecks in the process. Additionally, backlog analysis can help you prioritise tasks and ensure that you meet all customer needs on time.

Compliance

Compliance with regulations and laws is also a crucial aspect of business impact. By complying with regulations, you can avoid potential legal issues.

How do Business intelligence teams work?

The process of data management involves working from both right to left and left to right. On the right side, data services end users need reports for proper analysis. For the left side, a data sourcing pipeline stage is necessary to manage raw and business vault data.

To build a data warehouse, you must prioritize user needs, and the warehouse should be based on user demand. Agile delivery is crucial in this process.

Business analysts play a vital role in investigating business needs. While data modellers investigate concepts from raw data and devise a Data Vault model. Dashboard developers load the raw data using rules and build data products. Dashboard developers then produce visualizations for business action.

In the process, platform engineers work on tooling and automation.

Also, data scientists, data analysts, and data managers use clean data sets for machine learning analytics and insights. This approach ensures that the data management process is streamlined, efficient, and effective. Catering to the needs of both the business and end-users.

What is the right size for a data team?

Is there really such thing as the “right” size for your data team? We have highlighted some advantages and disadvantages of a small data team below.

Advantages of a small data team

• Fewer communications paths

• Easier to manage

• Fewer hand-offs

• More productive

disadvantages of a small data team

• Dependence on key individuals

• Difficulty scaling for larger projects

• Rarity of multi-skilled people

• Constant need for training and development

How to define a small team

When it comes to team size, there is no one-size-fits-all approach. However, a small team is one that is in control of its value stream.

Being in control of the value stream means that the team can work without relying on other teams to get work done. This allows them to work more efficiently, with fewer delays.

To achieve this autonomy, each small team should be cross-functional. They should have all the necessary skills and resources to complete the entire value stream. There should be no handoffs to other teams to get work done.

Of course, this doesn’t mean that small teams should work in isolation. But they should collaborate and communicate with other teams and stakeholders, as needed.

What skills are needed in your data team?

To have a successful data team that can make a big business impact, your team members need to have the right skills. Here are some of the key skills that should be present in a data team:

Agile Project Management

An Agile Project Manager is responsible for managing projects using Agile methodologies. This includes Agile Scrum, DevOps, communications and facilitation, and problem-solving skills. They should have experience in leading teams and delivering projects on time.

Data Modelling

A Data Modeller creates data models that reflect the business requirements. This requires business knowledge, concept modelling, Data Vault modelling, and reverse engineering skills.

Data Engineering

A Data Engineer is responsible for designing, building, and maintaining the data infrastructure. This includes SQL, ETL/ ELT, orchestration, and testing skills. They should have experience in working with data scientists and data analysts to ensure that the data infrastructure meets the business requirements.

Platform Engineering

Platform Engineers design and implement the cloud infrastructure. This includes skills in Cloud (AWS, Azure, GCP), Terraform, Terratest, and DevOps pipelines. They should have experience in designing and implementing scalable, reliable, and secure cloud infrastructure.

Change Management

The Change Manager handles the change process within the organisation. This includes business knowledge, stakeholder analysis and management, instruction, communications, and facilitation skills. They should have experience in working with project managers and stakeholders to ensure they manage change effectively.

Dashboard Development

A Dashboard Developer designs and develops data dashboards that the business uses to make informed decisions. This requires SQL, dashboard technologies, testing, and human factors skills. They should have experience in working with data analysts and business stakeholders to design effective data dashboards.

Business Analysis

Business Analysts handle the analysis of business requirements and translates them into technical requirements. This requires business knowledge, requirements elicitation and management, modelling, facilitation, and communication skills. They should have experience in working with project managers, data engineers, and data scientists to ensure that technical requirements meet business requirements.

An Operations Manager is responsible for managing the day-to-day operations of the data team. They need to be good at handling customers, troubleshooting, data product management, and change deployment. They should have experience in working with project managers and stakeholders to ensure that the data team is meeting business requirements.

By ensuring that the data team has a mix of these skills, businesses can create a team that can make a big impact. Team members may have a combination of some of these skills, but each member should be able to work collaboratively with other team members to achieve common goals.

Boosting performance with automation tools

Working at scale can be challenging, especially when managing the data model. This is where automation tools come into play. Tools like Datavault Builder provide extra support to small teams. Leading to significant productivity gains.

While automation tools can be very powerful in driving forward efficiency, especially in a small team. However, it is important to seek help when adopting a new method or to ensure that you get the full benefit of automation tools.

A productive team that focuses on the business can bring significant benefits to the company. However, many companies struggle to integrate data with quality. This especially applies to large and complex data warehouse projects. This is where Datavault Builder’s solution can help.

Datavault Builder has developed a simple, automatic, and complete system that can be used for a variety of projects and be customised to fit the specific needs of each team or company.

Summary

In summary, the size of your data team doesn’t determine its potential impact on your business.

At Datavault, we have seen first-hand how small data teams can achieve significant results compared to larger teams. Watch the YouTube video from this webinar where we explore this topic in-depth, answering the question, “Can a small data team have a big business impact?”.

To learn more about Data Vault, get in touch with our experts today.