How This Teleco Turns Into A Data-Driven Business, IT News, ET CIO
Today, businesses collect data not only from traditional sources, but also from a multitude of other sources, including social media, online interactions, market information, and more. If put together properly, this data could be a game-changer for the business.
With a similar focus and focus, to become a data-driven business, Colt Technology Services, a modern telecommunications company, envisioned a five-year journey.
âWe have a huge amount of data that is spread across multiple functions including marketing, finance, operations, and sales teams. We also collect a lot of data on network usage as well as call data records which is largely an untapped area for us. The amount of data is huge and difficult to manage, but we have action plans in place and the right direction to make sure we can, âsaid Ram Narasimhan, director of the data office, Colt Technology Services.
Colt adopts a holistic data strategy that addresses all data sources. The aim of the company is to consolidate business data in all functions, generate better information to help and follow the strategy and at the same time try to put it in order
âIt’s a three to five year journey for us. We understand that to make sure all elements are covered, we need to be methodical in our approach. Our management team fully supports us and understands the initial commitment required to lead in the longer term. results, “he added.
Colt has based its data-driven organizational strategy on three main pillars: business results, underlying fundamentals and governance, and technology.
It is important to consider what the business expects from the data. The data strategy must be aligned with the vision of the company. Narasimhan believes that if the vision of data strategy is not aligned with the vision of the business, there is no point in having a data-driven organization.
âThe underlying foundation of the data is just as important to a business. It is a hygiene factor, it is not visible but is essential. Elements such as data governance, master data management, data quality, data cataloging form the basis of the data strategy. The people entering the data are usually not the ones using the same data, so there may be a disconnection resulting in poor quality. Thus laying the foundations for good data governance. We know where we want to go and how to create a master data and data catalog. âHe explained.
In addition, Narasimhan believes that in order to become a data-driven organization, each individual must know how to better appreciate data in their professional roles. The underlying data culture must transform. Therefore, to work on data literacy, Colt’s data office partnered with their learning and development to develop a data literacy framework and intervention for employee learning and development.
Colt divided the whole company into several characters. And for different characters, it offers different learning modules depending on what they need to know about the data.
âWe understand that different levels of our organization have different learning requirements. For example, for leaders, we want them to understand how they can consume data. For some business leaders, we also want them to learn how to examine data. , or how to read it correctly, or how to be able to make data decisions for their teams. But for reporting teams, we want them to understand data science, data entry, and data quality. As a result, we have tailor-made the learning and development programs to ensure that we don’t lead to information overload and learning fatigue, âhe said.
The third pillar is something that a lot of companies invest heavily in – technology. However, Colt’s goal is to ensure that the technology it adopts fits into its data strategy as well as the technology strategy.
âTechnology must be flexible to adapt to changing trends, changes in the environment and must keep up with our needs. Instead of investing heavily in large landscapes, we’re transforming use case by use case, allowing us to pivot when needed and respond to unforeseen events like the pandemic. Ultimately, technology should be able to support our data strategy, deliver business results and adapt to the needs of key stakeholders, âhe concluded.