Last Updated on December 27, 2022 by Guest
The concept of digital transformation varies from one organization to another. However, in its basic sense, it implies the transition of resources, procedures, and operations from the physical to the digital world.
When put into practice, digital transformation can range from adopting or launching a digital app to streamline certain operations to switching to a system that can digitally support your entire organization.
However, you must combine this process with data management for an efficient digital transformation.
This article will focus on the importance of data management in digital transformation and how combining these two processes will improve your business efficiency.
To understand this process easier, just think about all the customer data businesses generate and collect using various digital solutions.
For example, spending on business-generated marketing data has doubled in five years – from $12.3 million in 2017 to $24.7 million in 2022, according to Statista. However, if the customer data is generated and stored in silos, not easily accessible and actionable, its value is pretty limited. Its importance grows if the information is shared across different apps or systems to support other operations.
Going digital and collecting potentially valuable data is still miles away from putting that data to good use – implementing it to deliver superior, actionable insights and make data-driven decisions.
So, a truly effective digital transformation is more than implementing new digital software. Instead, the process should always revolve around data management, which collects data, uses it intelligently, and combines tech and data to deliver exceptional customer experience.
So, what are the things to consider to drive an effective data-driven digital transformation in your business? Let’s break it down into essential steps.
Before you start your digital transformation journey, consider what you want to achieve with the process and in which areas.
For example, your primary objective may be simply moving your data from on-premise to the cloud. Or, you are already using MarTech and want to derive more value from the data you already gather.
As they use many different ways to engage with their customers, businesses often choose digital transformation to solve the issue of data fragmentation and improve the customer experience. They opt for data-driven marketing solutions that unify fragmented customer data across various touchpoints, platforms, and apps.
Similarly, some businesses want a data archiving system to safely store all their digital business correspondence, including email communications and social media channels, for more efficient searchability, lawsuit management, and compliance with data privacy regulations.
When you plan to adopt new technology solutions for digital transformation, always think about whether it will add more value to your data, make it actionable and easily accessible, as well as integrate with other solutions or just fragment it further.
Once you’ve identified your business needs regarding digital transformation, it’s time to create an efficient data management process to enable the company leadership to make informed, actionable decisions.
Here’s what your data management process should focus on:
- Collecting data. Determine the channels your business uses to gather data, and determine whether the data your company collects fits your needs.
- Preparing data. Ensure that the data you gather is clean, organized, and tested for analysis.
- Data archiving. Store your data for easy and controlled access securely. Unless you already use a cloud-based storage system, make this a priority.
- Data Analysis. Capitalize on your data by acquiring actionable insights based on your business goals.
- Data Distribution. Define how you will disseminate reports while keeping data secure and staying compliant.
At the same time, think about setting rules and procedures that will streamline your data management. For example, these rules will define which one of your employees will take action and when. This will make your digital transformation process much more manageable.
Choosing the right tools for digital transformation is crucial for any business that wants to reap all the benefits of this approach. When considering adopting new apps or systems, consider how they benefit or fit into your data management process.
For example, to make the digital transformation more efficient, stay away from digital solutions that fragment the data you gather. If you already use specific software and want to adopt new solutions to streamline other operations, look for a way to integrate these solutions meaningfully and make the best use of your data.
Let’s say you already use an excellent payroll app but want to automate time tracking to eliminate paperwork and have accurate and reliable timesheets ready on time. Instead of having two uncommunicative data sources and still having to enter data manually, look for ways to combine their functionalities and create a smooth, automated workflow.
To ensure the success of your digital transformation, you should ensure all your employees are aware of its benefits and ready to implement new solutions in practice.
To avoid any potential challenges to digital transformation, involve your employees early in the process, and emphasize why this process will be a game-changer for your organization. They must be reassured that this new technology won’t make them lose their jobs.
Besides explaining how digital transformation can help your business achieve its goals, focus on employee benefits too. For example, they will be able to get more work done in less time, and instead of being stuck in a vortex of low-level tasks, they will have an opportunity to expand their skill set and develop professionally by concentrating on meaningful work.
Implementing solutions and apps to streamline some of your business operations may be a step toward digital transformation. However, to make this process efficient and make the most of your investment, approach it strategically, combining it with a broader data management strategy to integrate data and make it actionable.