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Top 6 Digital Transformation KPIs to Track Your Evolution in 2024

Written by
Gulbahar Karatas
Gulbahar Karatas
Gulbahar Karatas
Gülbahar is an AIMultiple industry analyst focused on web data collection, applications of web data and application security.

She is a frequent user of the products that she researches. For example, she is part of AIMultiple's web data benchmark team that has been annually measuring the performance of top 9 web data infrastructure providers.

She previously worked as a marketer in U.S. Commercial Service.

Gülbahar has a Bachelor's degree in Business Administration and Management.
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According to Gartner, half of the businesses do not define metrics to track the success of their digital transformation. Companies need pre-determined metrics (KPIs) to track whether or not best practices are being implemented and the digital transformation process is creating the intended value. 

In this article, we present the top 6 KPIs that can make it easier for you to track the success of your digital transformation journey.

1. Cost benefit analysis of digital adoption

Digital adoption means leveraging digital tools to their fullest capability for the desired goal. For example, suppose your organization started using chatbots to improve customer service. What are the outcomes/benefits you achieved with this digital technology? For instance, what percentage of consumer compliance is solved by using a chatbot? How is the customer satisfaction rate affected by this implementation? By automating customer service, how much money does the company save?   For more on benefits, you can check our article on the top 14 benefits of chatbots.

Also, companies should consider the cost of digital transformation for instance cost of chatbots development and deployment (including training data preparation, data annotation model building, testing, data versioning, and monitoring)

2. ROI of digital transformations

You should measure the ROI of new technologies that you integrate into your business processes on your overall organizational strategy. Not every digital transformation investment may yield the desired outcomes for the organization, and not every positive outcome is equally impactful. The benefits of the technologies you incorporate into your organization must outweigh the cost of resource use such as time and investment spent. 

You can evaluate the return on ROI of your digital investment by tracking how the digital tools you include in your business process improve your strategy goals, whether it is cost savings or customer experience improvements. For example, is there an increase in the number of customers, or is there an improvement in the customer experience?

It is also advisable to determine investment and value metrics and set a time frame to achieve predetermined goals.

3. User engagement numbers

User engagement means how many customers interact with your products or services. Good engagement gives information about whether your customers are adopting your technology. There are three user engagement metrics to measure the number of users who engage with your service or product:

  • Daily active users: DAU measures the total number of people that log in and engage with a specific product or app in a given day.
  • Weekly active users: WAU is the number of people who interact with an app or platform in a week.
  • Monthly active users: MAU is the number of people who visit or interact with a product in a month.

The number of customer compliance per month: If your company has less compliance without a decrease in the number of monthly active users, it means that customer satisfaction is increasing.

4. Digital capabilities

Organizations’ IT infrastructure and employee skill levels are important factors affecting the digital transformation processes. The success of the integration of new technologies into organizations is directly proportional to organizations’ digital maturity level. Technologies that are already in use and digital skills (skill level of the employees who will use new tools) are among the factors that affect the digital maturity level of the organization.

5. Evaluate reliability of digital transformation

Switching from operational workflows that rely on manual processes to a digital business model may cause security issues for organizations. You must evaluate your organization’s availability (customers’ ability to access products or services when they need them), security (customers’ belief that their data will be handled securely by the organization), and system performance to notice potential reliability issues. Some of the most common metrics that provide insight to evaluate the performance are:

  • Mean Time to Failure (MTTF): Average time to the first failure of the system. It is a statistical parameter that shows the reliability of the system. It is used for non-repairable system failure, after a failure occurs the relevant component of the system should be changed.
  • Mean Time to Resolve (MTTR): Metric that measures the average time it takes to identify and correct the cause of the failure after it has occurred.
  • Mean Time Before Failure (MTBF): The average time between two failures. Unlike MTTF, the component can be repaired when a failure occurs.

6. Employee productivity

Employee productivity refers to output per each employee in the organization in a given amount of time. After a successful digital transformation, the amount of work done by employees is expected to increase. By tracking employees’ productivity (improvement in time to complete work by a worker), you can measure the efficiency of your digital transformation process. For example, when more basic tasks are automated such as document capture automation, employees can focus on more productive tasks.

Further readings

You can also check our other articles on digital transformation:

Also, don’t forget to check out our sortable/filterable list of digital transformation consultants.

If you have questions, we would like to help:

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Gulbahar Karatas
Gülbahar is an AIMultiple industry analyst focused on web data collection, applications of web data and application security. She is a frequent user of the products that she researches. For example, she is part of AIMultiple's web data benchmark team that has been annually measuring the performance of top 9 web data infrastructure providers. She previously worked as a marketer in U.S. Commercial Service. Gülbahar has a Bachelor's degree in Business Administration and Management.

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