How to Become a Successful Data-Driven Business
Data plays an increasingly important role for today’s enterprise – it is the engine of businesses, economies and societies in a growing digital economy.
Every service, system and device used worldwide generates new data – and the volume, variety, speed and value of that data is constantly increasing. By extracting valuable insights and monetizing that data, 21st century organizations are able to catch up with their competitors in the race to win customers. Future success lies in becoming a data-driven company.
This is a fairly new realization. According to Gartner, in 2019, less than 50 percent of business strategies were data and analytics as key components to delivering business value. If companies are to excel and become autonomous digital enterprises (ADEs) of the future, they must transform, and capturing data strategy within operations will be a critical first step.
To compete in a global marketplace, companies will need to derive real value from the vast amounts of data generated within their organization. In addition, they will then have to enter the insights from that data into their daily processes. Creating a data-driven mindset – supported by analytical capabilities – will play a key role in achieving this in the future.
What is a data-driven mindset?
A data-driven mindset lays the foundation for new technology development and a better understanding of the customer across the business. Companies that want to create a strong data culture must first focus on extracting value from their data sources and try to treat and manage data like any other business asset. Making money from these data assets allows companies to become more sophisticated and autonomous, shifting their focus from cost reduction to business growth.
Generating data from multiple sources is also important. Becoming a data-driven company requires more than just collecting data from traditional sources; it also includes capturing new data from Internet of Things (IoT), social media and customer engagement systems, and creating artificial intelligence (AI) and machine learning (ML) systems to improve and run enterprise-wide operations.
As the number of data generating devices – and the amount of data they generate – continues to increase, so does the complexity of the IT infrastructure required to collect and analyze the data. Systems and tools that can sort the data and effectively train and implement the associated predictive models must be integral components of a company’s data strategy. Having the right tools is crucial if companies are to successfully handle the increasing data volumes.
Extract business value with AI and ML
Collecting endless amounts of data does not in itself bring real rewards; the real value lies in data extraction and analysis, and AI and ML are both fundamental to achieving that. Predictive models based on AI and ML can use data to analyze and predict the behavior of both humans and technology, which in turn can help optimize actions and operations at a lower cost.
As these systems become increasingly important, it is important to understand that the associated infrastructure and management models can also be complex. Businesses will need to embrace the idea of IT and OT (operational technology) convergence between operations so that data is shared with – and used by – the entire business for real-time decision making and insights.
While businesses strive to get there, there is still room for improvement when it comes to data. Most have yet to fully transition to a truly data-driven company, despite understanding the value of data assets. Data sources and the value they generate continue to grow, so it will become increasingly important for enterprises to give teams the tools they need to make optimized, data-driven decisions.
Monetizing data as an asset
Monetizing assets is a vital part of business operations and data is rapidly becoming a critical currency that also needs to be monetized to facilitate analysis and insight. Some ways to monetize data include insight and data sharing, business intelligence, and data brokerage. Establishing a central data strategy with the right governance models will also be essential for any organization looking to get value from their data.
The future will be data-driven
Ultimately, the technology landscape of companies is evolving rapidly, and companies that want to succeed must strive to become an ADE. To do this, they will have to reinvent existing tools and processes and re-evaluate how they generate value across all operations – while ensuring that existing processes across the business are not disrupted.
By deploying data-driven processes and generating value from data assets, companies will be able to develop a better understanding of the behavior of customers, employees, competitors and existing technology processes. This, in turn, will help them identify areas that need to be transformed across the business. Companies looking to thrive in the future can start now by harnessing the potential and value of data within their operations.
- Herb VanHook, Vice President, Enterprise CTO Services, BMC software.