According to a Forbes article in June 2021, the cost of Digital Transformation program failures would be close to $3.3 Trillion by 2025. An astounding amount and while it also stated the top five reasons for the failure Cost, Company Culture, Leadership Decision, Business Problem, and Success Measures, in my perspective there is one more reason - the confusion between digital readiness vs. data readiness.
In today's society, it seems like almost everything is done digitally. We shop online, bank, and even communicate with one another electronically. As a result, the amount of data being created and shared daily is rapidly increasing. This explosion of data has caused many people to start questioning if "digital" is ready for the amount of data created.
Digital transformation is transitioning from traditional, analog business processes to those that are digital. It's an ongoing journey that requires organizations to change how they think, work, and operate. As more and more data gets created, businesses need to become data-ready to keep up.
What is data readiness, and how can businesses achieve it?
Data readiness is the ability of a company or individual to use data to make decisions effectively. It is about taking all of the available data and turning it into something that can be used to improve the business. This can include anything from increasing sales to enhancing customer service.
A company needs to have the correct tools in place to be data ready. This includes everything from storage capacity to analytics software. The company also needs to have employees who can interpret the data and make decisions based on what they find. It is becoming increasingly important for companies to be data ready as the amount of data grows. The world is creating more data than ever before, and much of it is being shared digitally. This means that companies need to store and manage this data effectively to make use of it.
Digital transformation is the process of using digital technologies to create new or different business processes. It can involve anything from automating manual processes to improving customer experience. To be successful, a company needs to have a clear plan for using digital technologies to enhance its business. Without effectively using data, it will be difficult for a company to improve its business processes. Digital transformation can be an excellent way for a company to improve its competitiveness, but only if it can effectively use data.
When it comes to data readiness, businesses need to have a plan in place for what they want to do with the data they collect. They need to have systems set up that can handle the influx of data and be able to analyze and use it to make better business decisions.
There are a few key ways that businesses can achieve data readiness:
Enabling self-service analytics: Giving employees the ability to analyze data on their own can help them make better decisions about improving their work processes.
Collecting the correct data: Not all data is created equal, so businesses need to be selective about what they collect and store.
Developing a data governance plan: Having a clear plan for how data will be collected, stored, and used can help ensure that it is used effectively and efficiently.
Creating a data-driven culture: Encouraging employees to use data to drive decision-making can help create a more data-centric organization.
Training employees on data analytics: Providing employees with training on how to use it can help them better use the data available to them.
Digital readiness is necessary to keep up with the increasing demand for storage. We are quickly reaching a point where digital will have to become data-ready to keep up. Businesses need to take steps to ensure that they are prepared for the future. By enabling self-service analytics, collecting the correct data, and developing a data governance plan, businesses can make sure that they are ready for anything that comes their way.
The benefits of transitioning to AI to become data-ready
One way to become data-ready is by transitioning to artificial intelligence (AI). AI can help businesses make sense of all the data they are collecting and turn it into insights that can help them improve their performance. In addition, transitioning to AI can help enterprises become data-ready much faster. By automating the process of data collection, processing, and analysis, AI can help enterprises make sense of all the data they are collecting in a fraction of the time it would take humans to do so. This means that companies can start using their data much sooner, which is essential in today's competitive market.
Some of the benefits of transitioning to AI to become data-ready include:
Increased efficiency: With AI handling all the data processing, businesses can free up their employees' time to focus on more critical tasks.
Improved decision-making: By having access to insights and trends that would otherwise be hidden in large data sets, businesses can make better decisions based on facts, not just guesses.
Enhanced customer experience: With AI's ability to personalize interactions, businesses can create a more personalized experience for their customers, likely to result in increased loyalty and better ROI.
It is clear that to keep up with the ever-growing demand for data storage; businesses need to start transitioning to AI. Not only will this help them become data-ready, but it will also allow them to reap the many benefits that come with using AI.
What is digital readiness, and how does it link to data readiness?
Digital readiness is an organization's ability to use digital technologies to enable its desired outcomes. It is important to note that this is not just about having the technology in place but also about using it effectively.
One key aspect of being ready for digital is data readiness. This involves having the ability to manage and use the data created as a result of our increasingly digital world. With so much data being generated every day, it is more important than ever to make sure that we are prepared for it. There are many factors contributing to the increase in data. One of the biggest drivers is the growth of digital transformation. This is when organizations use digital technologies to change the way they operate. As more and more businesses move to this model, the amount of data being created grows exponentially.
While digital readiness is about being able to use digital technologies effectively, data readiness is about managing and using the data that is being created. We are rapidly reaching a point where digital will have to become data-ready to keep up.
How will be becoming data-ready help businesses stay ahead of the competition?
The amount of data created and shared is constantly increasing, and businesses need to be ready for it. As a result, digital transformation is no longer optional – it's essential to keep up with the competition.
To survive in today's digital world, businesses need to handle large amounts of data. This data comes from various sources, including social media, the internet of things, and artificial intelligence. As data becomes more complex, businesses need to find ways to make it more manageable and actionable.
Artificial intelligence is becoming increasingly important in the world of business. With AI, companies can make better decisions by analyzing and understanding all of the available data. AI can also help to improve customer service and create new products and services.
The importance of being data-ready in today's society
As we continue to rely more and more on digital platforms to do everyday tasks, the importance of being data-ready becomes increasingly evident. With the rapid expansion of data comes an even greater need for storage, becoming more challenging to obtain. If we want to keep up with the ever-growing demand for digital experiences, we will need to find a way to become data-ready.
To become data-ready, we will need to implement a few changes. First, we need to collect and store data more effectively. This may mean investing in new storage solutions or finding ways to optimize existing ones. Second, we need to be able to process this data more efficiently. This can be done through the use of artificial intelligence and machine learning. Finally, we need to be able to share this data with others securely and efficiently.
By becoming data-ready, we will keep up with the ever-growing demand for digital experiences. We will also be able to provide better experiences for our users by collecting and processing data more effectively.
The bottom line is that digital needs to become data-ready to keep up with the amount of data created. It will require businesses to transition to AI use of all the available data. Doing so will allow them to stay ahead of the competition and continue to thrive in today's ever-changing world.