Authored By: Joe Ong, Vice President and General Manager, ASEAN, Hitachi Vantara
Because of the COVID-19 global pandemic, almost every industry is experiencing volatility, risks and changes to buying behaviour. Nevertheless, in crisis often comes opportunity and a forcing factor for businesses to redefine themselves. Those looking to innovate after (or even during) this crisis should focus on two key concepts — data monetisation and data modernisation.
We all know the stories of businesses having achieved significant success monetising data — Netflix and Airbnb, for example — but most organisations are struggling to get started.
At the onset, it is important to understand that you must think beyond your traditional data method and platform. Data monetisation requires flexible, adaptable data management approaches that support innovation and the development of new business models and revenue streams. The opportunity is in reimagining your business to discover sources of revenue previously obscured by data silos and disconnected processes.
But often, businesses are saddled with legacy approaches and systems that collect, store and analyse data as they were designed to, but whose outdated designs are unable to deal with the sheer volume of data flowing through the business today. They need data analytics that deliver fast, meaningful insights, but their legacy systems can’t meet that demand.
This issue is compounded as the volume and variety of data continue to increase. Organisations need to start preparing for data modernisation now or risk falling even further behind.
Here are five strategic steps you can take that will help you modernise your data ecosystem to gain the greatest value from your data.
1. Adopt an agile mindset that seeks out digital innovation.
Modernisation and monetisation are two sides of the same coin, with enterprise modernisation primarily led by IT and monetisation driven by business decision-makers. Both sides must embrace agile development and a more collaborative environment to advance beyond the status quo. The key to doing so is to adopt intelligent data operations — DataOps — to align people, processes and technology for a more agile and automated approach to data management.
Start viewing technology as an enabler. With this mindset, you’ll stop investing in technology as technology, and start investing in technology to solve your business problems.
2. Use technology that supports an agile business model.
Modernisation requires a shift in technology, architecture and design. For the greatest agility, choose a multi-cloud environment and invest in cloud-agnostic solutions and technologies. This will enable you to run open-source and third-party technologies in different clouds and seamlessly shift your workloads from one cloud to another, freeing you from being locked in with one technology or vendor.
Your data modernisation infrastructure should encompass your entire organisation, forming a data fabric or data ecosystem. Only in hyperconnected environments can artificial intelligence, machine learning and other analytics tools be effectively deployed at scale. An ecosystem integrates distributed data so that you can extract analysis and insight quickly, producing a faster return on investment.
3. Start with specific use cases and expand outward to establish the big picture.
Choose five to 10 use cases that have the highest potential to generate significant new revenue streams so that you see an early return on your modernisation investment. Then work your way backward to the data, technology and source systems you need to organise the data and enable the new model. Build each use case as a repeatable solution to reduce time to market for future initiatives and drive efficiencies in cost and operations.
4. Build in data governance.
A modern data ecosystem can automate data quality and data lineage, ensure adherence to regulations and detect abnormalities that may indicate fraud. Today’s multi-cloud infrastructures are certified and often equally or even more secure than on-premises infrastructures and can meet even the most stringent security requirements.
DataOps plays a critical role in data governance because it brings all of your data together into a single, interconnected data fabric that has metadata data cataloguing, data security, life cycle management capabilities and more.
5. Make change management a way of life.
Change management is the heart of digital transformation. You’ll need new methodologies to support an agile way of working. You’ll need to prepare your company’s talent for change. Your organisational structure will change as boundaries between business units blur. A strong change management program is critical to your modernisation and monetisation efforts — and your long-term success.
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