Top Roles Needed for Harnessing Data in Growing MSPs

In any rapidly evolving business landscape, data is more than just a byproduct of operations-it's a critical asset that drives strategic decisions, enhances operational efficiency and fuels growth. Yet, many MSPs are not fully leveraging the potential of their data. According to AWS thought leadership, only 35% of SMBs use cloud-based analytics, indicating a substantial gap between merely storing data and effectively extracting value from it. To bridge this gap, MSPs need to understand the key roles that enable robust data management and utilization. By doing so, they can transform data into actionable insights, ensuring a competitive edge and fostering sustainable growth.

Let's explore the critical roles of stakeholders, database administrators (DBAs), data analysts and data administrators in data management, particularly within MSPs.

Start With Your Stakeholders

To get started, identify key drivers that lead to desired outcomes. These drivers and outcomes form the foundation for setting organizational goals and determining the key performance indicators (KPIs) to be tracked. To achieve growth, every organization must establish goals and measure their progress towards these objectives leveraging the data collected across all systems.

But data is only as good as what is put in. By engaging all stakeholders who interact with and leverage data, you can ensure a more accurate view of the data. This diverse group includes the executive team, managers and front-line employees, each relying on timely access to accurate data to perform their duties effectively.

Executive team: They make strategic decisions based on dashboards that show the overall health and performance of the organization.

Managers: They rely on reports to determine how well their teams are meeting KPI targets and achieving goals.

Frontline employees: From client success teams to technicians, these individuals create, collect and rely on data to perform their daily tasks efficiently.

Bringing together a subset of each group when developing your data strategy ensures greater adoption of processes and tools while also delivering relevant reporting outputs.

A Fictional Example

Consider a fictional mid-sized MSP, "TechGuard Services." The executive team at TechGuard relies on dashboards to monitor client network performance and internal operations. Managers use detailed reports to track their team's efficiency and client satisfaction metrics. On the front lines, customer service reps and technical support staff collect data on client issues and system performance while leveraging data feeds from various tools. Accurate and timely data allows TechGuard to identify recurring issues in client networks and proactively implement solutions, enhancing client satisfaction and reducing downtime.

Database Administrator (DBA)

The database administrator (DBA) ensures that organizational data databases are secure, available and performant. The need for a professional DBA varies based on the complexity and customization of the organization's data systems.

In smaller organizations using self-contained packaged applications or SaaS products, a DBA might not be necessary. However, where data is housed outside packaged applications or where there are significant custom databases (e.g., a MSP delivering data warehousing solutions), a DBA becomes essential.

Key responsibilities of a DBA include:

• Ensuring data security and availability
• Maintaining optimal database performance
• Managing external database systems like SAP or Fiserv

  In small to mid-sized MSPs, these responsibilities can often be handled by existing IT personnel, such as IT managers and systems administrators.

  For Example

  Consider a small MSP where initially, the IT manager managed the databases for client networks and internal tools. However, when the MSP landed a major client requiring custom data reports and complex database management, the IT manager's workload increased significantly. Recognizing the need for specialized skills, the MSP hired a dedicated DBA, allowing the IT manager to focus on broader IT management while ensuring the new client's data was expertly handled.

  Data Analyst

  Data analysts are the interpreters of the data world, transforming raw data into actionable insights. Their work involves collecting, processing and analyzing large datasets to identify patterns, trends and relationships that inform business decisions.

  A data analyst typically:

• Creates dashboards that provide at-a-glance views of key performance indicators
• Generates reports highlighting specific data points and trends
• Determines the best use of data to optimize operations and drive strategic initiatives

Technical skills are paramount for data analysts, including proficiency in SQL, Python, Excel and various database technologies like MySQL, PostgreSQL and NoSQL databases. Equally important are analytical thinking, problem-solving abilities and the capability to communicate complex data insights to non-technical audiences.

In small to mid-sized MSPs, data analysis responsibilities can be integrated into roles across various departments, such as marketing analysts, financial analysts and operations managers.

For Example

Consider a mid-sized MSP that initially relied on its marketing team to analyze client data and optimize campaigns. As the company grew, the volume of data became overwhelming. The marketing analyst was skilled in data interpretation but struggled to keep up with the increasing complexity. The solution? The MSP cross-trained the marketing analyst and other department analysts in advanced data analysis tools. This empowered them to create comprehensive dashboards and detailed reports, transforming raw data into strategies that improved client retention and satisfaction by 15%.

Data Administrator

Typically found in larger organizations, the data administrator ensures that all organizational data is well-organized, consistently defined, inventoried and documented. They play a pivotal role in managing data access rights and maintaining data integrity across the organization.

In smaller organizations, this role might be combined with the DBA's responsibilities. However, in larger setups, the data administrator may work closely with other key roles, such as the chief information security officer (CISO), chief financial officer (CFO) or chief operating officer (COO), to manage data effectively.

For Example

A rapidly expanding MSP, started with a single office and grew to a network of locations. Initially, data administration tasks were handled by the head IT technician, who also managed database performance. As the MSP expanded, data management became more complex, with sensitive client information requiring meticulous oversight. Recognizing the need for dedicated expertise, the MSP appointed a full-time data administrator. This role allowed the head IT technician to focus solely on organizing and securing data, ensuring compliance with industry regulations and improving client trust through better data management.

Integration and Growth

As organizations grow, the need for dedicated DBAs, data administrators and data analysts becomes more apparent. Initially, smaller organizations can manage these responsibilities within existing roles, but scaling up requires a more focused approach. Here's how to transition smoothly:

1. Start with integration: Train existing employees to handle database management, data analysis and administration tasks
2. Monitor growth: As data volume and complexity increase, assess the workload and effectiveness of current arrangements
3. Plan for expansion: When the integrated roles become too demanding, plan for hiring dedicated professionals to take over these tasks
4. Foster collaboration: Ensure new hires work closely with key stakeholders to align data management with organizational goals

In small to mid-sized MSPs, DBA, data administrator and data analyst roles can be effectively integrated into existing positions. As these organizations grow, transitioning to dedicated roles becomes necessary to maintain efficiency and data integrity. By understanding the importance of these roles and planning for growth, companies can ensure robust data management systems that drive informed decision-making and operational excellence.

The Data Advisory Council helps to build data literacy and training resources that can help foster a data-driven culture that aligns with an organization's business objectives and initiatives. Learn more.

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