Hiring an analytics team is not necessarily a straightforward process. In this era of expansive data, it’s so much more than simply hiring an analyst, or a professional fluent in Google Analytics, Tableau or countless other data analysis dashboards, platforms and tools. Rather – the process of hiring and staffing a successful data team should be the outcome of a deeper process into what the needs and goals of your company are. Below, we outline steps that identify your needs and how to hire the best team that scales to meet them.
1. Define what your objective is for the team.
In today’s business environment, it’s not enough to just say “we’re going to do analytics” – you have to think about what you specifically want that team to accomplish and measure. What are your data objectives? Consider two different pieces:
- The business side: Moving products off shelves, store performance, etc.
- The marketing efficiency side:, Focusing on budget and asking questions like, “am I extracting all of the efficiency out of every channel I’m running media through?”
2. Identify the blind spots of your organization.
What does your organization not currently have, and what does it need? Think of blind spots as “I Wish I Knews” or IWIKs—an easy place to start. Being able to articulate those will inform what kind of candidates you’re searching for and even the kind of questions you’ll ask of those positions. Then, you can focus your search on finding people who are really experienced in a particular segment or sector that aligns with your organizational needs.
Here are a few of the key roles that often play a significant part in a strong analytics team:
- Business analyst – a position that helps a company understand where its routed
- Campaign analyst – for when you need an in-depth understanding of how your marketing affects business
- Data administrator – to look at massive pieces of data for insights
- Data scientist – an aspirational hire usually made about two years after establishing your analytics team, essentially a reporting analyst who has a background in data cleansing, communication and leadership
3. Determine if your organization needs more technology or more analysis from an analytics team.
If you have the technology, maybe you already use a database, Tableau or other software tools, then you can look for more strategic thinkers in your hiring search, perhaps those who are already fluent in the tools or platform your organization uses. If you don’t have technology in place, look for someone with more of a technical background, perhaps with experience setting up and integrating technology solutions that go well beyond using Excel.
4. Make sure your analytics team communicates effectively.
Analytics can be an intimidating and seemingly difficult topic to understand. Having a team member who can articulate complicated ideas or analysis from complicated analytics is just as valuable as the more technical skill sets.
5. Questions to ask in an interview for these roles
If you’re looking for someone who’s going to be more focused on business analysis, ask him or her to:
- Tell you about a similar project she or he has completed.
- Run you through the details of a past project of which he or she is especially proud.
These questions may feel too broad or basic, but your candidates’ responses can be very telling. Listen for three key points in the answers:
- How the data was acquired
- What the data was used for
- What the business result was that the data produced or led to
Every analytics hire is different and unique to the organization’s needs. Still, there are some general benchmarks you can refer to in the first few months of your hire:
- First one to four weeks: Hire(s) are integrated and introduced to teams inside the organization to get a sense of what’s needed, what’s necessary.
- First two months: New hires are set up or become fluent in your company’s existing technology stack.
- First three to four months: Hire(s) start producing actionable insights and results relevant to the business and internal teams.
Of course, different organizations run at different speeds. But from our experience, one or two months is generally what it takes to establish a basic working technology stack. By establishing a clear purpose for your data team, and the needs of your organization, you can start to understand the kinds of roles you need to hire and how to identify the best people for those positions.