Data Talent: A Powerful Weapon for Good or Evil

Revenue teams in the professional sports sales, higher education, and entertainment have a mountain of data at their fingertips.  Some of this data is valuable. Some isn’t. Because “data analysis” is not included in the job descriptions of most revenue leaders, these industries have looked to a new breed of data talent to help vet data partners and decipher the messages hidden in data sets. However, these highly specialized positions are difficult to hire. Data analysts who do not have the necessary qualifications or knowledge put their organizations at significant risk. So, without a background in data science or analytics, does the leadership team know how to hire the right person? And how will they know if their analytics teams are any good? There are a few warning signals to look out for when spotting or evaluating data talent.

Helpful data professionals will explain concepts using common language 

Dangerous data scientists and analysts over-rely on complex terms to defend their output. Whether they do this to buy credibility for themselves or to ensure that you don’t ask questions, the result is the same – you don’t completely understand the output. Not understanding the output means that you can’t or won’t completely trust it. And almost certainly, you won’t use it to make smarter decisions.

The helpful data professional will take the time to explain what they have done, why they did it that way and what it means. They will break their approach down to basic language and ensure that all stakeholders understand what they have done.

Confident data talent doesn’t always know everything

Confidence is the best friend of data professionals. Arrogance is their killer.

Arrogant data scientists and analysts have all the answers and an uncanny knack for making definitive proclamations before even hearing your full questions or thinking through their ramifications. They would have you believe that their abilities have no bounds and become instantly offended when you question their output. Often they are threatened when industry peers suggest another course.

Confidence comes from competence, and competent data professionals recognize that they don’t have all the answers. They recognize that the world of big data is moving too fast to know everything. The best data professionals are humble, intellectually honest, and academically curious. They work best in teams, knowing that their jobs are too big to do on their own. They are constantly reading, learning and seeking advice from their peers.

Competent data talent will share credit for success

On a daily basis, revenue leaders pull dozens of levers that will impact results. Some of those decisions will be informed by the analytics team, but not all. When analysts take too much credit for the revenue team’s success, they are either misinformed, contorting numbers to spin narratives that only help themselves, or using anomalous circumstances to bolster their credentials. For example, if your basketball team has gone to the finals 3 years in a row, ticket sales will be a little easier in the short term. Likewise, if your baseball team’s leadoff batter is about to break Joe DiMaggio’s 56 game hit streak, you are going to sellout that night.

Competent data professionals will recognize and understand the impact of these unusual circumstances and will show you data that supports maintaining momentum as situations beyond your control change. Additionally, intelligent data professionals recognize that they are part of a team and are proud to share in the team’s success. They will never tell you that they caused success, because intellectually honest analysts know that they would also have to own 100% of the blame when results fall short of expectations.

Great data professionals recognize that their job is to generate reliable insights that support broader strategic initiatives. When successful, they function as part of the team, helping achieve greater sales and reducing costs.

Great data talent will recognize the need to modify KPIs

What effectively drove revenue yesterday isn’t guaranteed to work tomorrow. Incompetent analysts are comfortable with the status quo and rely on the same tired KPIs to guide sales. Over time, these organizations regularly find more and more salespeople that hit those KPIs. However, they fail to hit the only number that ultimately counts: revenue!

Changing technologies, market preferences, demographics, seller/fundraiser abilities and financial considerations will result in evolving key performance indicators by which teams measure and predict success over time. Great analysts recognize this and work with the revenue leadership team to define KPIs based on recent data trends.

Results-oriented talent is supportive

The most dangerous analytics professionals create more work for the revenue teams they support. Often they confuse salespeople and fundraisers with professional market researchers and add scores of fields to the CRM system – expecting the frontline professionals to perfectly fill all of them out. Viewing all data as equally valuable, they encourage their revenue colleagues to waste more time collecting the most trivial pieces of information – but then complain and point fingers when their data sets aren’t perfect.

Results-oriented data talent will create tremendous efficiencies for their sales and fundraising counterparts. In short, they make it easier for sales leaders to do their jobs effectively.

In sum, when spotting or evaluating data talent look for professionals who are helpful, humble, honest, agile, and team-oriented. When they embrace the cutting edge, they will help create positive momentum for the organization and the individuals in it.