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Cloud data migration: Five considerations for every enterprise
Research shows why leading enterprises connect data, analytics, and cloud services
In today's uncertain and volatile business landscape, anything from a pandemic to an influencer tweet has the potential to disrupt. As a result, adapting is key to survival – and best achieved with data-driven, cloud-powered decisions.
How enterprises build data-driven enterprises was the focus of our recent research conducted in partnership with Corinium Global Intelligence. Unfortunately, although a cloud foundation is crucial for data-driven decisions, only 8% of enterprises say their cloud migrations are complete. Even fewer have fully embedded data and advanced analytics into company processes and modernized them in the cloud.
The solution? It's time to rethink your cloud data migration strategy.
In simple terms, cloud migration services move business operations into the cloud – and data is a crucial component of this. Though cloud services have been around for years, a shift to remote working and surging demand for digital commerce has heightened its importance.
However, for those who have always worked in on-premises environments, it's important to remember that a move to the cloud takes more than a lift-and-shift approach. Instead, a cloud data migration strategy must connect to broader business objectives for the greatest return.
It's why data, analytics, and cloud leaders must work in partnership with business leaders. They need to see where cloud migration and modernization will deliver the greatest business benefits across different functions. Especially as 51% of organizations have lost revenue due to the inability to make consistent, data-driven decisions.
To help smooth your journey toward developing a data-driven enterprise, we've identified five critical steps for successful cloud data migration:
1. Strategize first: Evaluate what data you want to retain, rehost, rearchitect, or retire in the cloud – this is your cloud migration strategy's foundation. Look for partners that understand your industry and business processes, not just the technology. Cloud providers such as Google, Microsoft, and Amazon Web Services play a major role too. A partner like Genpact, which has relationships with all the leading cloud providers, can help you find cloud services that best suit your current and future business needs. And help you develop a strategy that doesn't break the bank.
2. Seize the machine learning opportunity: Pretrained data and machine learning models can help accelerate cloud migration. Bring cloud and analytics leaders together to identify opportunities to put these capabilities into practice. A cloud-based data foundation that supports prescriptive engines and smart processes will help your employees make more informed decisions about your migration to cloud.
3. Evaluate your talent: Rearchitecting cloud applications calls for a blend of industry, technology, and data expertise. It's why 43% of leaders (according to the Corinium report) have budgeted for recruiting or retaining data and cloud talent. Similarly, 45% have budgeted for appointing 'data translators' to act as a bridge between data teams and other business units. Ask yourself where your business needs to recruit or train talent for successful cloud migration.
4. Develop new ways of working: Cloud migration is a journey, and the real value comes when you rearchitect for a new cloud environment. Set up data and analytics pods – groups of multidisciplinary employees with skills in data engineering, data visualization, data science, business analysis, and industry expertise – that can work to rapidly develop new cloud-native solutions. This helps to cultivate a cloud culture – in other words, a culture of innovation and agility.
5. Manage infrastructure costs: It wasn't so long ago that the main motivation for leaders considering cloud migration services was to lower the total cost of ownership. But when you lift and shift solutions to the cloud, the opposite can happen. You can end up with spiraling costs and inefficiencies – also known as cloud sprawl. Instead, make sure to proactively control the costs of cloud services, enlisting help from your partners if you're unsure how.
With these considerations in mind, let's look at companies that have successfully moved their data to the cloud.
A global energy provider was struggling with its on-premises data center and an outdated data and analytics strategy. A lack of inventory visibility led to poor decision-making, which had a huge impact on employee, customer, and supplier satisfaction.
By migrating to the cloud, the organization was able to connect data across 80 plants and 35 IT systems to provide a complete, real-time view of inventory. As a result, leaders make more informed, data-driven decisions – equating to $35 million of inventory cost savings. Going forward, the future-proof and scalable solution will help turn data into insights at speed, so teams can respond quickly to demand fluctuations to deliver sustained profitable growth.
To deliver an exceptional customer experience, one US bank relied heavily on advanced analytics to uncover insights into its customer base. However, the bank stored petabytes of data in hundreds of disparate servers and on-premises environments – not an ideal setup for integrated insights. When the bank began to reach the limits of its analytics capabilities, it began to explore the benefits of cloud migration services.
In its rearchitected cloud environment, the bank has virtually unlimited processing capacity and the ability to control computing costs by only paying for the data in use. To manage this change, the bank trained its employees in cloud-based analytics. As a result, analyst productivity has improved, while the bank has uncovered new insights into how to effectively attract and retain customers.
A short-term push for cloud-based data and analytics is a long-term investment in business resilience and agility. Especially as the ability to act on insight has become a competitive advantage.
However, our research shows that 78% of data and analytics leaders find it challenging to get executive buy-in for data, analytics, and cloud initiatives. It's why we recommend focusing on improving your executive team's data literacy. Help them to make the connection between cloud data migration and surpassing their business objectives.
Remember, there's no time to spare to invest in cloud data migration. The longer you wait to start, the greater gains your competition will make and the harder it will be to catch up.