If the past two years taught us anything, it’s that we need to be prepared for anything that gets thrown our way. Cloud-driven business agility allows organizations to turn challenges into opportunities before competitors are able to pivot. However, organizations can’t just stop at lifting and shifting their existing data into the cloud as is. Changing the underlying infrastructure is a good start but it does not shift the dynamic or give you a competitive advantage. Your cloud journey needs to be a data modernization journey. Cloud transformation provides organizations with an opportunity to reduce duplication, simplify the architecture, speed up data pipelines and leverage cloud-native services.
Cloud transformation can also be an opportunity to rethink how you use data to bring value to the business. How do you consolidate data from across the organization? How do you eliminate complexity? How can you make data more accessible, actionable or trustworthy? How can you get data scientists and business users to experiment freely to come up with some truly revolutionary insights? Migrating to cloud allows you to hit refresh and truly transform into a data-driven organization.
The Cloud is the Backbone of Any Data Modernization Journey
Organizations need to view cloud data services as business enablers, not cost centers. Cloud data transformation provides agile organizations with a flexible, scalable architecture that extends data accessibility to highly distributed systems and users spread out across the world. With cloud, organizations can unify their data, put it to work with secure and well-governed access, allowing them to make data accessible to stakeholders wherever they are.
The power, flexibility and scalability of cloud also enables business process automation powered by artificial intelligence (AI) and machine learning (ML). Reliable, fast and secure access to data informs decision making by humans and machines, allowing organizations to respond in real time and take advantage of opportunities quickly.
AI/ML is only as good as the data you feed into it. You can’t just gather as much data as you can, pump it into an algorithm and expect to get the right answer. Data changes all the time and needs to be constantly pulled, monitored and managed appropriately in the cloud. Data modernization enables the business value you get from AI/ML and analytics—and ensures you get the right answer based on real business objectives.
Data Modernization Delivers Business Innovation
Cloud transformation also allows organizations to leverage cloud-native analytics and AI services. AI/ML and advanced analytics allow organizations to get meaning and insights from data. This requires pulling accurate, relevant data, cleaning it up and making it accessible to stakeholders throughout the organization. Done right, data-driven organizations will see business users start to ask for more data. Once they start seeing the value that data brings to the business, they can’t get enough, which creates a demand that continues to accelerate digital transformation.
Here are four insights we’re seeing from organizations that are undergoing data modernization projects:
- The role of the CIO (and CDO) is changing
Data modernization is a team sport. Sure, it’s led by the Chief Data Officer (CDO) or Chief Information Officer (CIO), but these roles have shifted from a technology or platform focus to a data innovation focus. Their goal is to educate stakeholders across the organization about the power of a data-driven business and how they can use AI/ML to automate processes, create efficiencies, drive decision making or speed time to market. These people can work with data scientists, developers and UI experts to tackle real problems more accurately and more successfully. The role of the CDO or CIO is to bring parties together, give them meaningful data that leads to actionable insights and get them out of their individual silos.
- Data is becoming more aligned to business outcomes
The data stack is not just technology or infrastructure. It’s business value. Your data management strategy needs to align to individual stakeholder’s priorities—whether it’s to improve customer experience, increase development velocity, lower support costs, create upsell opportunities or other KPIs. And don’t be afraid to make it personal. The best examples are personalized to a business stakeholders’ objectives, fears, worries and goals. How can I help you succeed in your job? How can we close the gap with competitors? Successful data modernization shouldn’t just make data accessible or provide insights. It needs to enable key business initiatives.
- Communication of data-driven ROI is critical
Successful data modernization initiatives are driven by the value they bring to stakeholders, requiring open-ended conversations focused on how data-driven AI/ML can help the organization meet business objectives. Put yourself in your stakeholders’ shoes to better understand their goals and communicate how the right data management strategy could help them. It’s important to understand that most business leaders didn’t grow up around data and they’ve run businesses mainly through spreadsheets. They fear what they don’t know, and fear gets in the way of progress—making it essential that you communicate using business language. Resist the urge to have an architecture discussion or try to explain how the technology works. Instead, work with stakeholders to understand their needs and what’s holding them back and how a more robust, flexible data modernization strategy focused around cloud transformation is better than legacy approaches and how they enable better decision making.
- Your toughest critic is also your closest ally
People do not like change—especially people who have spent their entire career working with legacy technologies. In many cases, their expertise is wrapped up in their work identity, and any attack on the technology will be seen as an attack on them. This could describe your CTO or CIO, or perhaps another teammate. Fortunately, you don’t have to change their way of thinking. You just have to enable them to see the business value, the impact and the potential of the transformation. Once they see what you see, they can bring their unique perspective to the table—happily applying their own expertise to the project. This will force them to see the value in data modernization and cloud transformation and turn into your biggest advocate. They created the business that exists today, and they will jump at the chance to be a part of the next generation of the business.
Empowering Business Agility through Data
Empowering your stakeholders with the information they need to make quick decisions in the moment is foundational to digital transformation. However, simply moving applications and data to the cloud isn’t transformative. Business transformation through the cloud requires data modernization—a complete rethink of how people create, manage and access data within your organization.
Bret Greenstein is a cloud and digital partner at PwC. Steve Cooper is the data strategy lead at AWS.