Make an Impact: Data Team Building

COL01x - feature image for algminWelcome to my refreshed column! We decided to align the title, Make an Impact, more closely with other Data Leadership projects I’m working on including an online training course, and a book coming out later in the year. Fear not — if you enjoyed reading the old columns, this is basically the same thing but with more consistent branding. And if you didn’t enjoy the old columns, this new one is going to be way better!

Okay, enough business talk. Let’s talk business!

Many folks starting off on a data journey begin as a merry band of one. There is some truth to the old saying:

When you want something done right, do it yourself.

That may be true, but have you ever tried to architect and develop an entire data value chain by yourself? I have, and it is unpleasant.

Most of the time we need to create a team, and our superiors will want to know what kinds of folks should comprise the core group. Over time that group will hopefully grow into more people with increasingly specialized roles — but the makeup of the early days will have a material impact on how our young data team will someday blossom into a mature, fully-functioning department.

Generally speaking, if you are starting things off on a mission to create data value in an organization, these are the roles worth considering:

  • Senior Leadership / Executive: Ability to reach top decision-makers for organizational support and resources. This is probably an advocate/project sponsor role, and not so much a regular contributor.
  • Business Strategy: Versed enough in the operational vision to align data efforts with strategic objectives throughout the organization.
  • Marketing / Sales: Able to generate support in order to implement data efforts.
  • Business Process / Operations: Understand the detailed workings of the organization so that data efforts are feasible and implementable.
  • Data Analysis: Able to turn raw data into meaningful insights that will lead to business outcomes.
  • Data Management: Able to lead and perform hands-on activities with Data Governance, Data Quality, Metadata Management, Master Data, etc.
  • Technology / Database: Able to develop and use technology systems to prepare and process data so that analysis can be performed.

The above are not ordered by importance, but loosely grouped in such a way that if you have 3 people in your data team, for example, it will be more likely that one person does the first two, the second the next two, etc. But remember, just as every organization is a little bit different, so are data teams and the skills of the individuals within them. You will need to adjust accordingly — use this as a guide, not as a rule!

In upcoming Data Leadership articles we’ll talk more about putting these folks to work in a productive way, but first we need to recruit them. Assuming you don’t have a bunch of data wizards hanging out around the water cooler just waiting for some work to do, you will need to hire some people.

The secret of hiring for a new team is that the harder we try to drive recruiting efforts to find exactly what we mapped out above, the more likely we will end up with some sort of crazy Frankenstein monstrosity that we pay too much and gets too little done.

Instead, here’s what I try to look for when recruiting a data team:

  • Is the candidate currently, or on the path to, becoming great at something? If so, do we need more of that something?
  • Is what we have to offer them among their best career options at this point (in terms of challenges, compensation, growth)?
  • Will they be compatible working with the rest of the team?
  • Will they deliver a positive return-on-investment for the organization?

We’ll ask additional questions to help figure out some specifics, obviously, but these are the most important. I find that if the interviewee is the most capable candidate to help us achieve something important, and we are the best organization and opportunity for them, then the whole process feels easy. Finding that diamond needle in the rough haystack is the hard part.

To accomplish this, first establish a funnel of candidates. Sometimes I review piles of resumes myself — and for reference, candidates have at most 10 seconds to capture my interest before the resume hits the old circular file. I err on the side of doing a phone screen for someone that seems to be a reasonable fit, but has resume issues or other minor red flags. Sometimes a good candidate simply has a terrible resume.

In some situations, recruiters, either internal or external, do the initial resume screens to fill the funnel. They do their phone screens and/or interviews of viable candidates, and then send the good ones to me. I will typically personally do 30-minute phone screens where I will cut ~90% of the people I talk with — this is when I err on the side of protecting our people’s time.

If I’m bringing in somebody, that means I’m endorsing that candidate enough to spend at least a thousand dollars’ worth of people’s work day — before bringing them in I want to think the candidate has a 50% chance or better of getting an offer. Over time my best recruiters learn what we’re looking for well enough that their pre-screened candidates go straight to in-person interviews. Those recruiters earn their fees by saving me (and my team) lots of time.

For the candidates that make the in-person interviews, the ideal setup is a half-day to meet with a barrage of folks in ~30-minute sessions — some individual interviews and some 2 or 3-on-1’s. What I ask of the interviewing teams is that they attempt to determine whether the candidate has the requisite skills for the job, where the candidate excels, if the person would be compatible to work alongside, and if they think the candidate’s career objectives are aligned with the position. I don’t ask for any negatives, but somehow they always come up.

If that process comes back positive, we work with the hiring manager or HR to evaluate potential offers and how they might translate to the company’s ROI. I’m an advocate of paying people well, and generally motivating them to accomplish great things over extended periods of time. That said, you cannot run a lasting business by paying people more than they contribute to the bottom line!

If there’s an offer that makes sense, we turn it back over to HR with acceptable parameters. It is important to establish a distance between our team and the candidate at this point, because if the negotiation becomes tough but gets done successfully, we do not want any lingering resentment between the candidate and their new team. Plus, sometimes I forget that many people don’t enjoy a good negotiation the same way I do. I’m not saying I go to car dealerships on Saturdays just to haggle for fun, but I can think of worse ways to spend a weekend.

You should now be a little better prepared to go out and hire your data team. Good luck!

And until next time, go make an impact!


Share this post

Anthony Algmin

Anthony Algmin

Anthony J. Algmin is the Founder and CEO of Algmin Data Leadership, a company helping business and technology leaders transform their future with data. His book, “Data Leadership: Stop Talking About Data and Start Making an Impact!” is available now at

scroll to top