“Before going on acting, I think we should first delve on how to get this thing, get the engineering running backend every time where your stakeholder will help you to get the data rather than you fighting for that.”
Sanchari Chakraborty, a Program Manager at Birla Carbon India, part of the Aditya Birla Group (ABG), shared the challenges and learnings from her team’s journey in driving data and analytics initiatives across the conglomerate’s diverse businesses.
Starting with the “Why”
Chakraborty emphasized the need to first define the purpose behind creating data frameworks, rather than seeing it as just a mandatory exercise. She highlighted two key reasons – aligning data initiatives with the actual needs of the business, and bridging the gap between how companies manage data versus how customers perceive that data management.
Tackling Data Challenges Head-On
Chakraborty’s team at the ABG central data and analytics group faced a host of obstacles in accessing and leveraging data across the group’s 50+ companies. These included:
Data Silos: Data residing in disparate sources like ERPs, DCS systems, Excel sheets, and even handwritten logbooks
Data Quality: Inconsistent and often dirty data that would hamper analysis efforts
Integration: Difficulty in integrating these varied data sources
Volume: Dealing with the sheer scale of data generated by 24/7 operations
To address these hurdles, the team adopted a three-pronged approach – first, consulting with business stakeholders to deeply understand their problems; second, developing data-driven solutions; and finally, scaling these solutions through external partnerships.
Building a Collaborative Ecosystem
Chakraborty emphasized the importance of fostering organizational ownership, rather than just imposing solutions from the central team. They created “self-managed pods” within each business unit that would own and sustain the data initiatives on a daily basis.
Additionally, the team leveraged the external ecosystem, including startups and technology giants like Databricks and Microsoft. This allowed them to rapidly deploy ready-made solutions instead of building everything in-house.
Aligning with Strategic Priorities
A key aspect of their success was tying data initiatives directly to the long-term strategic goals of each business unit. This helped secure sponsorship and funding from leaders like the CFO, who needed to see the tangible impact on metrics like revenue, EBITDA, and market share.
“Until and unless your stakeholder sees value in your solution, the framework is useless.”
Chakraborty also highlighted the importance of assessing the AI/digital maturity of each business, as there were significant differences between the group’s global and domestic operations. This allowed them to tailor their approach and create change management programs accordingly.
In conclusion, Chakraborty’s experience underscores the criticality of adopting a collaborative, business-aligned, and change-driven approach when implementing data-driven transformations across a large, diversified conglomerate. By empowering local teams and demonstrating tangible value, her team was able to drive sustainable adoption of data and analytics throughout the Aditya Birla Group.
