As data management technology advances, organizations are discovering new and exciting opportunities for business growth. They’re seeking better ways to manage the huge volumes of data, garner insights and make data-driven decisions. New roles like data scientists and chief data officers (CDO) indicate the importance companies are placing on data management and quality.
Companies are looking for ways to go the beyond basics to make data management part of their competitive advantage – that may include the ability to deliver personalized customer experience or reduce the time to market for a product launch.
The speed at which companies can make data-driven decisions determines whether they can get and stay ahead of the competition. Here are five trends enabling organizations to capitalize on their data assets better:
In the big data world, blending data from multiple internal and external sources to create consolidated profiles can be a challenge. For example, your customer data may be fragmented across dozens of systems like CRM, marketing automation, advocacy, ordering, shipping and billing applications.
Simple rules-based matching may not be able to solve complex data matching and merging issues. More and more companies will leverage machine learning to identify data patterns and monitor manual matching behaviors to improve the matching. However, there is still distrust in the machine learning if results are delivered as black box "voodoo" magic.
Initially, companies look for transparency where machine learning suggests the matching rules that drive the merging of data and then it’s up to the user to evaluate if the discovered rule should be persisted in the system.
The next significant advancement is graph technology to help enterprises understand relationships across all real-life data entities. The graph aids to establish many-to-many relationships across people, products and locations. With relationship information available, companies can now solve complex problems that were otherwise too tedious.
Uncovering relationships using graph technology helps you with householding in retail, finding influential people in major accounts and with identity resolution.
With increasing volume and variety of data, companies need help from intelligent systems to guide users and provide recommendations for next best actions. Intelligent systems help analyze various profiles, past transactions and omnichannel interactions to recommend how to improve data quality. They can also suggest new relationships in your network, like LinkedIn or Facebook.
Sales and marketing can also obtain recommendations about next-best-actions such as the right time and channel to connect with a customer or what to offer a client by understanding their needs and preferences.
Sharing data across all systems and functional groups helps realize the full value of data collected. A single source of truth, such as single customer master, improves sales effectiveness and customer experience. Marketing, sales, services and support should all not only leverage the same reliable, consolidated data (product or customer), but also collaborate and contribute to enriching the data.
Organizations are creating data-driven applications that include capabilities like discussion threads, voting and workflows to enable collaboration.
The charter of a CDO is not just to ensure data governance, data integration and management across the organization – increasingly, companies are asking CDOs to turn this data into new revenue streams. With cloud-based, data-as-a-service platforms, businesses can quickly monetize their data and become data providers. Businesses can now collaborate with each other to create common data resources to share or exchange data easily.
These trends are top of mind for many organizations and are bringing us to the age of modern data management where data is considered a strategic asset. It’s time to go beyond basic data management and develop competencies to leverage and capitalize on data, keeping pace with the speed of the business.
Article written by Ajay Khanna
Image credit by Getty Images, DigitalVision Vectors, DrAfter123
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