The Unfair Ask that Limits the Success of Most Data Teams
There may not be any skill that is more in-demand right now than data analysis and business intelligence, but?even the best Data and BI teams may be struggling to live up to an unfair expectation, creating frustration and limiting the value they create. Recognizing and solving this disconnect is the key to a more successful (and more satisfied) data team.
Demonstrating proficiency and expertise is a good?thing, right? Showing that you have mastery over a complex skill should set you up for success, but in some cases it can also lead to unrealistic expectations being placed on you. This is especially true for Data and Business Intelligence teams. A function that was a side-task of the IT team 20 years ago is now a mission-critical, dedicated group in most mid-to-large organizations.?
The Data team are expected to be the masters of all things data. They have to know how to source data, pull it into the organization, clean it, validate it and classify it. Then they have to know how to analyze it using a plethora of advanced methods and technologies. The data team is expected to turn that ocean of data into useful value for the company, digging in deep to find answers. The problem is that, in many cases,?they are also expected to be the source of virtually ALL of the data-driven insights for the business.?
The reality is that while the Data/BI team may be experts at working with the data, they don’t possess the domain expertise for the other functions of the business.?The Marketing team?knows far more about marketing, and all of the intimate details of the company’s marketing program than the data team does.?The Product team?knows far more about the products.?The Finance team?knows far more about the finances. Likewise for functions like?Customer Service,?Sales,?HR, etc.?
These functional teams, with their deep domain expertise should be a major source of data-driven insights. They will be able to see patterns and relationships in the data that nobody outside of their function would recognize. They probably won’t have the data science skills to fully and formally analyze these insights, but that’s where the Data team comes in.?
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Here’s a real world example:
When?AMC Networks?first launched the?AMC+?streaming service, it was only available on Apple Channels and Amazon Channels. These partners provided data on acquisition and subscriber viewing. Looking at that data paint a picture of which series were the most successful at driving subscriptions and engagement. That data was accurate, but in a way the picture it painted was misleading, because it was lacking key context. These channel partners had their own editorial teams deciding which series to promote on their platforms, creating a very uneven playing field between series. The Data team, looking at just the data in isolation, might come to the conclusion that Series A significantly outperformed Series B. The Marketing team, with the benefit of knowledge that the partner’s editorial process heavily favored Series A, might look at that same data and recognize that Series B is much more promising.?
This is in no way a knock on the Data and BI team.?They shouldn’t be expected to know everything about everything.?Their expertise should be largely devoted to using the data to answer critical questions and to giving the other functional teams the best possible visibility into the available data. Those functional teams will be the source of many of these key questions, and the truth is that using data to ANSWER questions is very different from using data to find the right questions to ASK.?
Freeing the Data/BI team from this unrealistic expectation, and?empowering the other functional teams?to participate more heavily in finding actionable insights, doesn’t just take some of the pressure off the Data team. It also enables them to focus their precious resources on answering the right questions in ways that create the most value for the company. This increases job satisfaction, reduces burnout, and fosters greater collaboration with other departments.?It’s better for the Data team and better for the company!
Glymr can give your functional teams the skills to find actionable insights in the data, allowing your Data team to focus on what it does best.?