The data byproduct of an average large enterprise is being fed by a constant stream of customer and employee activity. As this wake of information grows in volume and density and as organizations improve their ability to process it, it can easily be seen how data is set to replace all assumptions, personal experiences, and bias when it comes to making business decisions. Companies quick to embrace this reality, and that are keen to leverage data for their corporate and digital transformation strategies, will be the most successful in conquering the digital age. The role of IT within these progressive organizations therefore becomes all-important, as they will need to develop the capacity to tap into the data lake and harness its power to support business teams with analytics and insights.
The best leaders today use analytics to develop corporate & digital transformation strategies
Most digital transformation initiatives today are reactions to competitive or customer-driven actions. Among the companies that responded to the Trasers Analytics IT Surveys, about 7% comprise those reporting the most effective transformations, highest business impact and industry leadership. By no coincidence, these same 7% are the most aggressive users of analytics with investments in BI, dashboards, data lakes and predictive analytics. These are the types of resources that help management establish a “proactive and predictive” posture in all aspects of their business, from strategy to operations.
As organizations move forward, simple availability and the lower cost of technology (e.g., analytics on the cloud) are what will help accelerate further investments into analytics. Over time, predictive analytics will determine what to transform, when to transform it and to what extent.
Evolving from Enterprise Data to Ecosystem Data
Digital transformation is essentially an effort to reimagine products, services and experiences from the customer’s point of view. Data is generated within the enterprise through sales, marketing, services, support and other transactions that take place between customers and the organization. While this data is incredibly useful in analyzing specific products, sales, support, customer satisfaction and financial trends, it only tells a part of the story.
In the digitally connected world, data generated outside the company is just as important to fully understand business dynamics and provide the right insights to inform strategy. Over 50% of the data that affects a business—e.g. customers and partners, competitors, and technologies—resides on various platforms, social or otherwise. A majority of this comes in the form of unstructured data. CIOs and IT leaders need to take note of this and work first to establish a strong understanding of their “ecosystem” which is essential for driving higher quality analytics.
What does it take to drive ecosystem analytics?
There are several layers of capabilities required for creating strong, real-time analytics capabilities. This begins with the deployment of a strong data foundation that comprises master data management (MDM), data governance, quality, as well as both automated integration and efficient storage covering structured and unstructured data from all corners of the ecosystem. Analytics IT can only provide accurate, real-time analytics with powerful visualizations when such a data foundation has been deployed—otherwise, analytics remains little more than an aspiration.
Analytics IT must be business-driven: leaders must be engaged and study closely how the business is changing and what outcomes are desired. Only when they are business-aligned will they understand what data is required and how it must be integrated via a strong data foundation. Therefore, while almost all industries report significant investments in analytics, a majority of them have not invested enough in the necessary data foundations.
As the 2019 Trasers Industry Transformation Quadrant for Analytics shows: High Tech, Media & Entertainment, Consumer Products and Telecom are miles ahead of other industries. They are succeeding because they make equally aggressive investments in the types of data foundations required for advanced analytics applications. It is also no wonder these industries lead in the velocity of their digital transformations.
