The Role of Data Science in Effective Digital Transformation
Digital transformation is a commonly used term with an inconsistent definition. When digital transformation entered into the conversation in the early 2010s, the term was mainly used to describe organizations beginning to embrace the digital revolution, and what the shift to digital could mean for creating new business opportunities.
Flash forward to the 2020s, and digital transformation is more than making changes or improvements to digital technology. It’s now about eliminating messy technical stacks, connecting online and offline data, and implementing unified tools to improve data strategy and management. The primary goal is to develop a process that makes for improved business decision-making rooted in data.
The details of what’s included in a digital transformation will vary from organization to organization, but the importance of the process: to obtain quality data as a resource, and use the information for decision-making is equally important for all. In fact, according to Gartner, by 2022, 90% of corporate strategies will explicitly mention information as a critical enterprise asset and analytics as an essential competency.
Digital Transformation for Customer Experience
Digital transformation, when paired with a customer experience initiative, can have a positive impact on brand loyalty, market differentiation, and of course your bottom line.
For example, Aditi Consulting recently worked with a Fortune 100 company that realized their messy tech stack, and slow time to insights, translated into lackluster supply chain efficiency.
The company, which provides large machinery and equipment to its customers, realized that when a piece of equipment broke, it was taking a long time to replace due to a lack of visibility into available inventory.
For this use case, the enterprise relied on digital transformation by way of improving machine learning algorithms like K-Means clustering, Hierarchical clustering, and Multiple logistic regression to better match dealers with machine parts when they were in need.
The shift from calling around looking for available parts, to having concrete, data-based insights, translated into a reduction of 25% on late delivery and shipping, and a 15% increase in sales.
Data Science's Role in Digital Transformation
In order to make meaningful change, like the use case described above, line of business owners must work together to understand broader business objectives, data engineers must build relevant pipelines of data, and then in most cases, a team of data scientists is leveraged to interpret massive amounts of unstructured data and find answers to customer experience data questions you’re looking to understand.
The objectives of a data scientist during the digital transformation process may include:
- Breaking down and managing data silos
- Solving for data fragmentation
- Drawing conclusions between on and offline data
- Digitizing and visualizing customer journey analytics
- Packaging findings in a way that drives value and insight
- Democratizing data so it’s usable cross-departmentally
The issue many organizations face when it comes to a data scientist's role in digital transformation is simply the fact that they don’t have enough bandwidth to tackle all of the issues data can pose.
For example, according to FiveTran:
- 44% of organizations say that key data is not usable for decision-making out of the box. Instead, data cleaning and prepping and additional ETL may be required before information is accessible.
- 68% of data professionals also say that they could generate more insights from their existing data if they only had the time.
In addition, there are major challenges when it comes to accessing meaningful insights during the digital transformation process, so it's critical that leadership is aligned on the desired outcomes.
The Aditi Approach
Aditi Consulting works to solve the challenges many organizations face when it comes to utilizing data to optimize products, services, and delivery.
Aditi works to help fill talent gaps and skill shortages in your organization by providing subject matter experts to specialize in your organization’s particular digital transformation use case.
Aditi’s approach of:
- Strategy building
- Validation of strategy
- Model development
This means that we start by understanding your team’s goals, and then provide a solution that enables business growth, cost savings, and the ability to more easily collect and analyze data for actionable insights.
Want to learn more? Connect with one of our data science consultants to learn about how Aditi can bolster your digital transformation ambitions.