Digital Transformation Can Be More Than Just a Buzzword
Let’s be honest: digital transformation in 2021 is definitely a buzzword you’ve heard more than once. Whether you were on a sales pitch or in a boardroom, the concept of digital transformation has been brought into discussion. However, what does digital transformation truly mean? And most importantly, what does digital transformation mean for your organization?
Defining Digital Transformation
Digital transformation is the adoption of technology by businesses in order to replace non-digital or manual processes with modern tools, modern processes and straightforward automation.
The above definition is extremely broad, so let’s take a closer look at what this could mean for your organization.
Let’s start with a simple example. A local retail store that sells sneakers is ready to break into newer markets. They have the internal staff to support fulfillment to regional areas, therefore, they decide to break into eCommerce. They stand up a Shopify store, they connect to ShipStation to automate shipping labels, and suddenly they have the opportunity for higher revenues. For the small business, this could be a digital transformation.
However, let’s look at a more in-depth example, one for a Fortune 5000 organization.
A national insurance company is looking to conduct a lifetime value analysis on all customers that reside within their current data management system. However, the current data set resides within an on-premise server that only the IT team knows how to access. Additionally, tapping into this structured database could disrupt current day-to-day operations when trying to pull together these customer records.
For the national insurance company, their form of digital transformation could mean standing up a cloud-based data warehouse on AWS or Snowflake, using ETL tools and processes this data into the data warehouse, and tying a BI tool, like Sisense or PowerBI to the warehouse in order to model out this information and bring data visualizations up to the management team. Eventually, the national insurance company wants to layer in some Machine Learning elements in order to identify high-value outbound marketing segments before campaigns go live. With this proper infrastructure, they now have the ability to do so.
Each concept of digital transformation is correct – it’s just different scale!
Why Is Digital Transformation Important?
Today, all companies are software-first companies. While your business may not develop software applications, it’s apparent that adoption of data-driven tools by your employees and stakeholders are the only way to stay competitive.
Organizations are starting to fall behind. Billions of dollars are lost maintaining legacy systems instead of transforming them. To give some topical examples:
- 52% of the Fortune 500 companies since 2000 have gone out of business.
- 62% of company leaders say that legacy systems are their biggest roadblock to continued growth.
- Only 8% of companies believe their business model will remain economically viable without going through digital transformation.
The tools are changing and being brought to market faster than ever. While estimates vary regarding the global economic impact of digital transformation, leading studies forecast on the order of trillions of dollars annually.
| Increase in Annual Global GDP | Timeframe | Source |
| $15.7 Trillion (Driven by AI) | By 2030 | PwC, 2017 |
| $13.0 Trillion (Driven by AI) | By 2030 | McKinsey, 2018 |
| $11.1 Trillion (Driven by IoT) | By 2025 | McKinsey, 2015 |
| $3.9 Trillion (Driven by AI) | By 2022 | Gartner, 2018 |
Where Do You Begin?
Transforming your business is extremely daunting. However, it starts with taking a step back and understanding where incremental improvements can be made. For the sneaker shop, it was making the commitment to retool their staff to focus on eCommerce opportunities. For the national insurance company, it was committing to transforming its legacy-server system to a modern data stack.
Digital transformation is an evolutionary process. There isn’t a correct starting point, it’s meeting the organization where they are at on that data journey.
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