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Building a Data-Driven Culture

machine learning
Ellen K. Begley, Esq.
machine learning
May 4, 2021
data driven decision making

The Data-driven Workforce People Love

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:
 

 

Corporate Data Science Bootcamp
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.
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.

 


Corporate Data Science Bootcamp


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.

Corporate Data Science Bootcamp
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.
Corporate Data Science Bootcamp

Ellen K. Begley, Esq.

Organizational Learning Strategist

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