Guide Objectives
- To assess whether your organization’s current staffing meets its data needs, and what gaps exist
- To consider critically what types of recruitment may be needed
- To understand different types of data-related jobs
Becoming an increasingly data-driven organization requires an evolving set of data skills and roles.
However, organizations often rush into recruiting for certain positions without fully understanding their organizational needs and the data infrastructure required. Yet, once the hiring process is complete, they realize that they are not ready to optimize the value of that new team member. This then leads to wasted time and money, as well as job dissatisfaction, and a “back to the drawing board” feeling.
This guide is here to assist you in the process of understanding your organization’s data skill needs, the nature of different data jobs and when they are needed, and determining whether your organization should be pursuing them or filling needs internally.
Guide Specific Disclaimer
There are many data jobs commonly seen, and this guide is meant to provide the basic structure of what each of them entails. However, technology is moving fast, and newer job types are constantly joining the list, while others may become less common. It is useful then to understand the job types in this guide but do your research to further understand how common data jobs are adapting to new technologies and environments.
Understand your organization’s future data staffing needs
The first step in this process is to visualize how your organization’s data needs will change over the coming years. You can reflect upon these questions and document your thoughts:
- Where is your organization in its data journey? (The data.org Data Maturity Assessment’s People section may help here.)
- In the next year or two, where would your organization like to be regarding how it uses data in decision-making, developing analyses, and communicating insights for both internal and external purposes? What does this “ideal state” look like?
- What types of data skills are needed within your organization to reach this “ideal state” within the time span?
If there are new associated with this “ideal state”, determine and document them as well. It is important to think about your “ideal state” regarding data use to avoid rushing into a recruitment process that will only address current issues.
These are complicated questions that should be discussed in collaboration with key stakeholders and leadership within your organization. To help with these conversations we have provided a series of questions that you can use with your teams while reflecting and projecting on your needs for data jobs.
Identify data skills gaps in your current team
Equipped with an understanding of your organization’s evolving data needs, it is now time to review and document the data skills that are currently available in your team. This process involves understanding staffing skill sets, responsibilities, and availability as well as leadership understanding and support for data roles.
There is no universal process for identifying the data skills gap in an organization. The skills an organization will need in the future depend largely on the sector. Also, how skills are demonstrated by current teams can differ from one person to the next.
It is important to note that for most organizations, specific data jobs are rare. It is more common to see team members handling multiple roles, one of which may involve various data functions, such as database administration, data analysis, visualization, etc. This can often make the process of identifying data skills difficult. As such, this step often requires individual discussions with team members and managers, and reviewing job functions.
For this step, it is important to speak with your current team members who are involved in data-related tasks. Prior to doing so, you should identify the data core competencies (data analysis, visualization, modeling, etc.) needed for your organization, so as to ensure you ask the right questions of your team. Then design the interview script, customized to your team. In your conversations, you should identify:
- What data skills are currently present in your team
- What data skills do your current team members need (and are interested) in learning
Once this review of data skills and staffing is documented, you can now compare it against organizational needs determined in Step 1 to identify gaps in data skills and resources.
If your organization is large or complex, it might be too burdensome to handle this interview process. In that case, alternatives include: using a skill, self or peer assessment surveys, or focus groups. As above, these should all be customized to your team and focused on identified core competencies to hone in the design of the assessment approach.
Learn about different data-related jobs
Now that you have built an understanding of your organization’s data needs, the next important step in creating a data-driven organization is understanding the different types of data jobs and how and when they support the management and growth of an organization.
Some of these jobs are more related to strategy, while others are more technical. Not all of these positions need to be filled for an organization to thrive. It often depends on the nature of the organization’s larger mission, and of course, the data it relies on. It is important to have a clear understanding of what these jobs entail to define your organization’s resource needs, the fair market value for such jobs, and your recruitment plan.
This step will be to review the referenced videos and sites to acquaint (or reacquaint) yourself with these job descriptions. Given that data jobs are constantly changing based on new technologies and organizational needs, the references are meant to only give you a flavor of common, current data jobs.
Common Data Jobs
Database Administrator – A database administrator is responsible for overseeing the installation, configuration, and maintenance of an organization’s databases, ensuring they operate efficiently, securely, and reliably. They manage data backups, monitor performance, troubleshoot issues, and implement security measures to safeguard sensitive information stored within the databases.
A few key questions to ask before hiring this position are:
- Is the data system complex enough to warrant a database administrator?
- What type of data architecture is needed and how can the database best meet this need?
Data Analyst – A data analyst is a professional who interprets and analyzes complex datasets to extract insights and inform decision-making within an organization. They use statistical methods, data visualization techniques, and analytical tools to identify trends, patterns, and relationships in data, helping stakeholders understand past performance and make informed future strategies. A few key questions to ask before hiring for this position:
- Is there a large enough group of datasets to warrant a data analyst?
- Is the data clean and reliable to allow for effective analysis?
Data Scientist – A data scientist is a professional who utilizes advanced statistical and analytical techniques to extract insights and knowledge from large, complex datasets. They apply machine learning algorithms, predictive modeling, and data mining to solve business problems, identify patterns, and make data-driven decisions.
A few key questions to ask before hiring for this position:
- Are datasets large enough for a data scientist to perform the tasks above?
- Are data clean and reliable prior to this work being done?
- Is there someone on staff who has an understanding of the types of algorithms, models, etc., that this role would be developing?
Determine data jobs you need to recruit
After determining the data skills gap in your current team the next step is to determine if upskilling internally or hiring external experts is the best way to proceed.
In general, supporting current team members with training or mentorship to help build their skills should be strongly considered to meet data needs. However, if you do need to recruit a new data team member, it is important to hire people in roles that are to be filled.
If the role is not ready to be filled, the new team member will likely become discouraged and less productive than desired.
‘So what’ and next steps
This guide focuses on universal needs when staffing for data capability in your organization. As you build your team, there is a need to recognize the interdisciplinary nature of data for social impact, ensuring the depth of technological understanding is matched with the discipline and understanding of social sciences. Discover curated data for social impact jobs here. If you are interested in engaging with people in similar roles and learning about other roles visit the Community Groups page.
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