By: Tom Christensen, Head of Thought Leadership - Nordics, LTIMindtree

At the heart of creating a data-driven enterprise lies unlocking data freedom. It requires solving cumbersome challenges from rapidly changing markets, disruption of business models, and the need to follow the product out of the door alongside new advanced digital services. For this reason, business leaders demand faster delivery of new digital services, adoption of new technologies to gain insight from data. Businesses are rightly investing in new digital services using the entire data landscape as the key source of information.

To explore this further, a CIO roundtable was held recently in Stockholm, where various experts discussed these critical challenges related to creating the right culture for data-driven decision-making across an organization. Joining the discussion was a senior executive from a global commercial vehicle manufacturing company responsible for driving its digital transformation journey who shared valuable insights through the lens of business, process, and technology perspectives. Read on as we delve deeper into this exciting case study!

Data-driven maturity

The roundtable started with a poll among the delegates on their data-driven maturity and who drives these projects in their organization. This showed that organizations, where the business model had been disrupted, are the frontrunners in becoming truly data-driven. In contrast, others are more exploratory, curious, and in the planning phase to take the first steps towards becoming data-driven.

Data freedom drives business freedom

To warm up and inspire the roundtable conversation, a global commercial vehicle manufacturing company from Sweden was invited to give insight into their digital journey. It was clear from the beginning that business leaders had recognized that their business model had been disrupted and required a digital transformation to stay competitive. We were left with the impression that yesterday’s truck companies are becoming today’s mobility companies with advances in autonomous driving, vehicle connectivity, electric vehicles, and charting station control. Thus, the IT organization had to undergo a transformation to prepare themselves for a future, where the data landscape is key to success. The focus was to establish a unified data layer across decentralized data to achieve centralized IT and data management.

The data layer

Their Head of Data and Information Management walked through the case study on “How to become a truly Data-Driven Organization” with a focus on how a modern data layer can help break down data siloes, curate data, and share data with data scientists and business stakeholders. The new IT organizational structure was also mentioned to ensure that people and processes are on the journey.

The IT department had moved away from a time-consuming data integration with extract, transform, and extract, load, and transform (ELT) data from multiple sources into a large, central repository like a data lake. This approach has been replaced with a more agile data mesh architecture supporting internal and external data sources from cloud to even connected vehicles.

Breaking down silos!

There was mutual agreement among delegates that whether your company is innovating and producing products, optimizing operations, or improving customer experiences, decision-making processes need to be close to real-time, reliable and predictive. Senior managers can’t rely on historic trends or intuitions, which may be filtered, biased, or delayed. Digital businesses depend entirely on their data being accessible to achieve excellence across all disciplines. However, some delegates expressed that they struggled with legacy technical debt, such as ERP systems, from business mergers over the years, and found it challenging to move forward.

Who funds and drives digital transformation?

A delegate asked if the data-driven organization is experiencing an IT cost reduction or increase.

This led to a discussion about what is most important: reducing IT costs by 5% or achieving 500% business growth. Many in the room agreed that a data-driven organization aims to increase the company’s competitiveness and revenues. One from the oil & gas sector said it was about finding new business for them. These projects are funded and run by business leaders. They understand that IT must master advanced technologies such as AI, ML, deep learning, recommender systems, natural language processing (NLP), and computer vision to become successful.

GenAI has gone wild

Another delegate opened up the question about the impact of Generative AI (GenAI) –a subset of AI that generates new data or content based on patterns and information learned from the existing data landscape. One said that today, it is mainly used by their application developers on an experimental level. However, it is expected to be a more significant part of their application to improve customer experience and increase innovation. All delegates agreed that it would significantly boost the machine learning and predictive analytics we know today. However, some delegates appeared more cautious about introducing GenAI techniques. Concerns centered around the quality of the input data, GDPR sensitivity when used for external digital service, the ability to track the workings of ‘black box’ GenAI models, and the scarcity of skills required to apply such techniques.

Walking the talk

At LTIMindtree, we approach these challenges holistically and attack them on multiple levels. From creating and implementing a digital strategy, we select the right architecture with a supporting toolset. We bring the right resources, experience, and education to succeed in digital transformation.

To amplify the implementation, we bring our digital know-how from similar projects. However, it is equally important to focus on budgeting, planning, and technical readiness to ensure a successful migration while managing costs and technical challenges. A collaboration with an experienced partner like LTIMindtree minimizes the risk and helps navigate these complexities effectively.

Explore more here:

LTIMindtree Launches Canvas.ai, A Generative AI Platform To Accelerate Concept-To-Value Realization For Enterprises

Fast-track to the Future with GenAI-Powered Data Lakehouse

DataOps as a Service: Transforming Your Business

LTIMindtree’s Fosfor helps monetize data at speed and at scale–enabling Data commerce for your  organization

LTIMindtree’s PolarSled – Accelerate your Snowflake cloud journey