Building from the ground

09 November 2022


Building Data Science Capabilities Within Your Enterprise

While many companies have a high volume of valuable data, few have strategies in place to use it to produce business-critical insights. Without data science, your enterprise is likely only scraping the surface with basic analytics and metrics. 

By embracing data science capabilities, you can incorporate data across the entire fabric of your organization, enabling every department to build a data-driven strategy, rethink their processes, and optimize their performance. 

In this post, we’ll break core data science capabilities into three major categories and walk you through how to leverage them to make sure your enterprise stays one step ahead of the competition. 

How to Build Your Enterprise’s Data Science Capabilities 

Building your data science capabilities can be a daunting task. We’re breaking your core focus areas into three parts: people, expertise, and data.  


An organization’s people are their biggest asset. So, when trying to infuse data science capabilities throughout the company, your people are where you should start. However, before you get started, it’s important to think about how to best leverage the people you have to formulate your AI dream team. Here are a few examples: 

Once you have a better idea of who will be impacted by incorporating data science throughout the org (hint: everyone) and how it will change their daily roles, it’s important to also prioritize creating a data-driven culture. This is easier said than done as over 90% of organizations say culture is the biggest roadblock to becoming a data-driven organization.  

 To get everyone invested in what data science can do for them, you need to bake data into the organization’s foundation—and show your teams what it can do for them, too. 

Transparency is Key 

When building a data-driven culture that supports your people, it’s essential you communicate openly and transparently. Make sure you tell your teams: 

Resist the temptation to keep things close to the chest. Put yourself in your employees’ shoes and think about any concerns adopting data science capabilities could cause. 


When we say “expertise,” we’re not talking about finding a data science unicorn to champion your data science capabilities (while we definitely wouldn’t complain if that were the case!). Instead, focus on your current workforce, particularly by giving them the skills they need to wield data science tools successfully. In conjunction, make sure you’re leveraging your domain experts, too—they have a wealth of specialized knowledge that will lead to better, more accurate models. 

Your domain experts understand better than anyone how their teams’ processes work, what obstacles they face, and where data science could be most helpful. Sharing this knowledge with your data scientists before they start building a machine learning model will lead to more relevant and useful end results. This knowledge sharing and deep, cross-functional understanding is part of what we refer to as upskilling

Suppose you were adopting a machine learning system to improve a core process, and each of your current team members has a different level of comfort with machine learning. By upskilling your teams to have a basic understanding of AI and ML, they’ll know better where data science can be useful, and where it can’t, allowing them to communicate better with your data scientists. Your upskilling program should focus on: 


How you put your data to use will most likely involve data governance and management, building your infrastructure or using a platform, and identifying core capabilities. Here’s what each of these entails: 

Maximize Business Outcomes with Data Science Capabilities 

Data science can impact a business’s ability to use data to improve profitability, retain talent, and ensure positive customer experiences. You have loads of data at your fingertips—don’t waste it! By implementing data science throughout your organization, you can analyze ways to boost efficiency and build new revenue streams. 

Your data is your most powerful resource, and data science ensures it doesn’t go untapped. By working to establish a data science culture, earning the trust of your team members, upskilling and leveraging existing domain experts, and optimizing how you use your data, you’ll position your organization for success.  

Curious to learn more ways to utilize data science throughout your enterprise? We’ve compiled 50 cross-industry customer case studies in 50 Ways to Impact Your Business with AI. 

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