Does Your Non-Profit Have a “Data Culture”?

Culture, Noun.

Definition: The arts and other manifestations of human intellectual achievement regarded collectively.

Data, Noun.

Definition: Factual information, especially information organized for analysis or used to reason or make decisions. The quantities, characters, or symbols on which operations are performed by a computer to be stored, analyzed and transmitted.


Data Culture, Noun.

Definition: An organization that asks ‘what do the data say?’ and then acts on the results even when convention or tradition may disagree. It is using an analytic process to leverage relevant Big Data insights to transform the way business is done internally and externally. The culture depends on staff at all levels to measure outcomes, act based on available data, and build on existing knowledge over time.

Big Data and “Data Culture”

Big Data is revolutionizing the way we live, communicate and do business. However, harnessing the full power of Big Data has only begun to be realized by those who can afford it.

Though data has become cheaper to produce and thus more readily available, it can be costly to hire the right minds to analyze the wealth of data that exists. Of course, the alternative- ignoring the data- can prove even more costly.

How do small, cash-strapped nonprofits compete in this Big Data landscape? The answer: adopt a “Data Culture.” The focus becomes building a base level of data analysis competency throughout an organization. It is building a culture where staff don’t balk at numbers and metrics. They don’t tune out when the data analyst in the room makes her presentation. Rather, they embrace the data and use it to inform decision making and challenge conventional norms. Similar to the way a great organizational culture is built, the entire staff must contribute and continue working toward the vision.

The Data Analyst as the “Culture Carrier”

Within great organizational cultures there are “culture carriers.” That is, people who embody the ethos of an organization and constantly spread it (HBR “Six Components of Culture“). In a “Data Culture,” those people are the data analysts – and we need more of them! For 2013, global IT spending around data is forecasted to exceed $3.7 trillion. By 2015, it will create up to 1.9 million IT jobs in the US (Gartner Inc.).

The incoming US labor force is responding to this increased demand for analysts. According to Linkedin.com/Skills, the skill of “Data Analysis” is already up 13% from last year. In fact, 25-34 year-olds represent 46% of the market. This is more than the entire 34-64 year-old workforce which represents 44% of all people with the skill. Now, either this demographic isn’t updating their LinkedIn accounts or we have a problem.

New Data Culture

In order for a data analyst to truly impact change, there needs to be an established “data culture.” Organizations cannot afford to be bottlenecked by having a limited supply of data analysts. In other words, people at all levels should know how to interact and assess the incoming data to ensure that all relevant metrics are being accounted for. Which means everybody in an organization should have “data analysis” as a skill.

 

Destroyers of “Data Culture”

2 biggest “Data Culture” enemies are the HiPPO (Highest Paid Person in Organization) and Data Fiefdoms

There are several obstacles that can get in the way of establishing a “Data Culture.” The two biggest enemies are the HiPPO (Highest Paid Person in Organization) and Data Fiefdoms. Let’s start with Data fiefdoms. These are named after the Feudal system in which kings granted rights to their land in exchange for taxes (and controlling the local population). In a Tech Fiefdom, technology is over protected and data is kept in a silo. Because knowledge is rendered exclusive and not made readily available to people at all levels, a “Data Culture” cannot grow. Undeniably, a cornerstone of a “Data Culture” is that there exists widespread access to data.

Now on to the HiPPO. The HiPPO is typically the one who makes the final decision. In doing so, a HiPPO may be reluctant to let data trump their experience or allow numbers go against their instincts. The data may even challenge what they aim to do. It is critical that the HiPPO knows how to operate within a “Data Culture” and still be able to provide leadership and vision. When JFK delivered his Moon Speech to Congress in 1961, he provided the vision and motivation of landing a man on the moon – not the engineering details necessary to do it.

Whole Whale’s mission is to increase the impact of our client by building “Data Cultures” within the organizations we work with. We love this stuff, and would love to work with you.