Every company wants to be a data-driven organization. But few have truly achieved that goal. Those who have are primarily companies born in the digital age, having built data analytics and machine learning algorithms into their business processes from the start.
It’s a tougher game for traditional organizations that have inherited technology debt. Although many are experimenting with the development, testing and creation of business processes informed by data analytics and machine learning models, many have yet to deploy production applications based on predicted outcomes. Rather than focusing on overhauling established systems, these organizations can start with incremental and cost-effective initiatives that deliver sustainable results.
It’s imperative to move things along. The value of becoming a data-driven business — one characterized in large part by data democratization — is clear. Forrester Research says that insights-driven businesses grow at an average of more than 30% annually. According to a recent survey of Fortune 1,000 executives conducted by NewVantage Partners for the Harvard Business Review, more that 49% of the organizations that began data-driven initiatives to decrease expenses have realized value from their projects. A majority of executives whose companies have adopted AI reported an uptick in revenue in the business areas where it is used, and 44% say AI has reduced costs, according to McKinsey & Company.
What can you do to create a data-driven business? Here’s some advice:
1. Create a data-centric culture.
You can’t become a data-driven organization unless you have a data-centric culture — one where employees see analytics as integral to the business strategy.
Business leaders needn’t understand every tech step to move the enterprise down the right path to leveraging data, analytics and machine learning across processes. But you do have to set the agenda for the organization: Identify the business outcomes and measurable value you expect before analytics and AI/machine learning models are implemented in business operations.
Becoming better at blending advanced analytics technologies with how people think and how they work accelerates the fusion of minds and machines. As work becomes more automated, the information worker becomes a creative contributor who drives business growth.
2. Industrialize data and AI.
To manage and get value from large and complex data, your organization must industrialize data and analytics. As a business leader, you should mandate that the organization adopt a “data first” approach. That means standardizing data-based systems and processes to support the seamless flow of data, from initial analytic discovery to embedding predictive and prescriptive analytics into business operations, applications and systems.
A large gas distributor in Japan has succeeded in realizing value out of its massive data environment. It has integrated its home network with a scale-out internet of things (IoT) platform to collect and manage gas usage data from hundreds of thousands of meters. It processes a massive number of meter reads to safely provision gas to its customers and is now enabling new digital business solutions such as a smart lock that opens doors remotely.
Cloud-based data lakes and warehouses provide a strong foundation for industrializing data and AI. They provide secure, massively scalable and cost-effective data storage, and using the cloud for machine learning enables building, deploying and running scalable, compute-intensive analytic models.
3. Adopt a continuous improvement approach.
To continually find new ways to apply data and deliver fresh business insights quickly, you must promote a test-and-learn approach that encourages experimentation and learning from failures. Support a continuous improvement approach across the analytics pipeline and you’ll achieve your desired business outcomes with greater speed and accuracy. Taking this tactic enables your data teams to improve their ability to work with data at scale and to respond to business events as they happen.
In the end, as a business leader, perhaps one of your biggest jobs to foster a data-driven enterprise will be to build company-wide participation. Reaching this state will be a huge asset in helping your business make great strides in performance and value.
Always remember: Building a data-centric enterprise needs your constant care and attention.