Building a Data-Driven Culture

4 Ways to Improve Your Team

If a data scientist identifies a powerful new insight, but no one around her understands it, does it even matter? This question gets to the heart of why building a data-driven culture should be a core objective for your organization. While building a data science team is a strong start, it is only a piece of a puzzle. 

In order to ensure that you’re leveraging your data science team (and your data) to its fullest capacity, you need to empower your other staff and executives with data skills. By building out a culture of evidence-based decision making and a common data vocabulary, you will establish a future-proof organization that can adapt to new trends and technologies and improve corporate efficiencies.

Here are four steps to start shifting your organizational mindset to become more data-driven:

Identify KPIs for anything that can be quantified

Without a basic understanding of the organization’s KPIs, it’s going to be very difficult to become data-driven, so start gathering KPI data first. Clearly define your organization’s business objectives and identify the success metrics for every department/group, from product to marketing, financial/accounting, engineering to human resources. If the metrics can’t be quantified very clearly, it’s better to have some qualitative measures than nothing. For example, if it’s hard to know the exact accurate a customer value, it is better to use the categorical value: high/medium/low. You may need to use some special reporting platforms to generate the reports that you need. Once you know what kind of data you are collecting, the next step is to think through how to use and analyze data.

Critical thinking and evidenced-based decision making

At your meetings, you can start with a quick review of the KPI numbers first. Make sure everyone in the group/department knows what’s going on and the performance metrics. Don’t make any decisions without data and try to avoid ‘I think’ conversations. When a decision is being made during the meeting, you need to ask people how they came up with the conclusion. Is the decision based on intuition or data? If it’s based on intuition or personal experience, ask them to find data to support it. Is the HR department making hiring decisions? Ask them to use data to prove the necessity to hire the position. Does the marketing team want to increase the marketing budget? Ask them to use data to prove why they need to increase marketing spend, and what type of investment they can expect. Which KPI will this decision affect and in what way? Is there any data to support this? Can they try some small sample test first? Since all the communication is based on data, it’ll become a routine to consider data in all decisions and form evidence-based decision making.

Train employees in data analytics

At first, your employees may struggle with incorporating new metrics into existing practices. If you’re finding that your team needs some extra support to generate insights from the reports, and use advanced data analytics tools (like Python, Tableau, R programming), then incorporating a data training academy should be part of your rollout plan. This doesn’t mean that you need to turn everyone in your team into the data scientist, but they should feel comfortable enough to collect, work with, and perform basic analyses on data. Employees from all departments must be trained in common data practices and vocabulary in order to effectively communicate and leverage data.

Accelerator: Start a data competition inside your organization

One of the best ways to bring data analytics to the forefront of your organization is through a company-wide data competition. A data competition is a great opportunity for your current employees to learn how to leverage the data they are familiar with. A data competition usually consists of identifying a business problem with a clear cut objective that teams then try to solve using their data analytics and business intelligence skills. It’s also a great way to identify some of your top talents, highlight the impact that data analytics can have, and improve cross-departmental collaboration.

Creating a data-driven culture takes time

Creating the culture will never happen overnight, so be patient and take your time. The journey of one thousand miles begins with one step. Start small, identify KPIs for anything that can be measured first and then build an evidence-based decision routing to form a critical thinking habit. Provide professional data trainings, and celebrate your data superstars. Before you know it, you’ll have a data-driven organization ready to take on the future.

 

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