How to Clean Your Startup’s Data — Part I of IV
I believe we have all heard or said these familiar words: “I don’t trust the quality of our data.” Too many high-growth startups allow these words to be stated over and over like a corrupted audio file on repeat. If you find yourself in this unfortunate situation, where do you start?
The following is the first part of a four part mini-series on how to achieve a gold standard of data quality at your startup, with commentary on how following these tips have helped us at Weave.
Part I: The Importance of Data Culture
After many years of being a part of and observing a variety of data cultures, I am convinced that a healthy data culture is a predominant driver of good data quality and the absence of it inevitably leads to poor data quality.
There are a few reasons why leaders fail to define and nurture healthy data culture at their companies, such as 1) they didn’t know there was even a thing called data culture and the role it might play in driving data quality or 2) diving deeply into data culture and strategy might be outside of their comfort zone.
What is data culture?
While many might not completely understand how data culture is different from company culture, they do understand the importance of company culture.
At Weave, we strongly believe in the importance of company culture. Our CEO and Co-Founder, Brandon Rodman recently posted:
We recently formalized what we call the People, Not Employees OS. It’s a set of three core values, ten principle…Importantly, our 10 “Leadership Principles” apply to everyone…The biggest threat to most companies isn’t external; it comes from within. Either you pour energy into your culture, or your culture starts to erode. We are pouring a LOT of energy into our culture, and you should, too.
I love this and I love our core values — hungry, creative, and caring. These values matter to me and they matter to all of my colleagues. Regularly, I hear others complimenting one another, referencing these values. It is empowering as it is a constant reminder of who we are and how we do things at Weave.
In 2014, Satya Nadella, CEO of Microsoft, wrote a piece titled, “A data culture for everyone”. He defined data culture in the following way:
We believe that with the right tools, insights can come from anyone, anywhere, at any time. When that happens, organizations develop what we describe as a “data culture.” However, a data culture isn’t just about deploying technology alone, it’s about changing culture so that every organization, every team and every individual is empowered to do great things because of the data at their fingertips. This means bringing together people, IT and developers to create a cultural shift that is just as important as systems and infrastructure. In a data culture, everyone benefits when more people can ask questions and get answers. In a data culture, the entire effectiveness of an organization can elevate.
At Weave, we don’t need to create data values that are different than our company values because of how strong our company culture is, but we darn well need to associate them. Why? Because if left to its own vices, data culture will erode. I have seen this happen time and time again. It will decouple from your company culture if not bound together tightly and if company culture is not strong, data culture will default to its lowliest state depending on how things are going that month or quarter — data will be used to attack one another, data will be hard to find since people will be reluctant to share it, data will not be trusted anywhere, etc.
So, with regards to our data culture, we are hungry, creative, and caring. And we apply the company’s ten leadership principles directly to how we drive our data vision and strategy.
How does data culture drive data quality?
There is something special about knowing who you are, how you do the things you do, and what you are seeking to achieve. No spoiler alert here: this applies to data professionals as well. The vast majority of data quality work is not very glamorous. And it is typically not fully appreciated by the rest of the company — for example, rarely does someone win a company award for creating a data catalog.
In the thick of it, when there are a lot of competing priorities and fires that need to be put out for all employees at a startup, data professionals need a guiding star and an understanding on how their commitment and contributions will achieve something special.
This is how you drive data quality.
Making Data Culture Special at Weave
As previously stated, the data culture at Weave is tightly linked to our company culture, with shared values of hungry, creative, and caring.
We care deeply about creating impact through data, so just last month, we launched the IMPACTNOTDATA Revolution and all business intelligence function leads became part of the Impactors — a team of data superheroes.
The reasoning for the IMPACTNOTDATA Revolution was that we wanted to: 1) empower and engage our data people, 2) create a unifying experience that would promote their expertise, elevate their skills, and solidify their place as critical members of our business intelligence team, and 3) position them as leaders within their own functions to reap the benefits of our hub and spoke BI model.
The Impactors all have superhero names and superpowers. For example, the function lead for Support is nicknamed The Paci-fist and has a superpower to calm minds. He also has a mean right hook. J
There are special prizes that are awarded to each superhero after strategic milestones are achieved, such as personalized superhero t-shirts, socks, a personalized action figure, a professional illustration for each superhero that will be posted on our IMPACTNOTDATA Revolution wall, and finally, a key (to the city) ceremony and dinner.
While still early, I believe we are already seeing the benefits of clearly defining a data culture at Weave. We are united in our purpose and our objectives in protecting data integrity.
Conclusion
Data culture is critical to driving data quality. Without a healthy data culture, I believe it is extremely difficult to improve and maintain data quality. As such, data culture must be clearly defined and in the case where it mirrors the company culture, it should be explicitly associated. Data culture can provide meaning and purpose to those that carry out bland data quality work that ensures data integrity. We have found that building our data culture through a special program tailored to our company culture is already paying dividends as it relates to data quality and beyond.
