Don’t bolt AI onto ERP—build a connected system from day one

SLMG Beverages, a major Coca-Cola bottler in India, has instituted a significant digital transformation across its entire business. Improvements to operation efficiency utilizing SCADA-enabled process control, AI-enabled inspections, cloud ERP and TenX's SaaS for intelligence for real-time business intelligence have reduced defect levels across SLMG's operations to below 0.1%, while also facilitating a 95% reduction in safety incidents, and ramping production to 33,000 bottles/minute. In addition to efficiency, these various structures have led to a more consistent product, faster decisions and more customer trust.

The following discussion with Joint Managing Director Paritosh Ladhani unveiled the mindset around technology, learning and leadership that made SLMG's evolution to a smart factory from a more traditional warehousing and bottling business even possible.

What operational gains have you seen from deploying SCADA, AI-powered inspections, EHS solutions, and automated ingredient handling?

SLMG Beverages has taken a modern approach to plant operations by employing SCADA-controlled processing, AI-powered high-speed camera inspections, AI-supported EHS solutions, and automated ingredient handling that provide tangible improvements in quality engineering, safety, efficiency, and cost savings.

Defect detection accuracy has topped 99.9%, resulting in defects rates below 0.1%. Real-time rejection analysis allows for the immediate traceability of issues, and, in combination with automated systems, it has now resulted in an estimated 80% reduction in the manual inspection workforce. These changes have also allowed for inspection costs to be trimmed by 15-25% while simultaneously strengthening compliance with FSSAI, FDA, and ISO 22000 standards through improved traceability.

On the safety side of the house, SLMG's tailored AI-based EHS solution—developed jointly with external expertise in partnership with in-house Tech & QC teams—has provided round-the-clock CCTV-enabled visibility into the plants. With the predictive analytics tools embedded in the system, automated risk prioritization, and active real-time monitoring of workers, safety incidents have dropped by 95% and timely, informed interventions for risks, stressors, fatigue, and health concerns are now possible.

That said, use of SCADA systems ensures continuous monitoring of temperature, pressure, and Brix—eliminating manual intervention, building assurances against data falsification, and presenting real-time options for data-driven decisions to maintain quality.

Cumulatively, all of this has resulted in reduced downtime, reduced rework, reduced costs, and ensured a safer workplace; and with these developments, SLMG Beverages has surpassed the efforts to create consistency in every bottle produced thereby enhancing customer trust.

You’ve reported capacity of 33,000 bottles per minute across multiple plants, with plans to reach 13–14 large-scale plants within five years. How has automation helped unlock and optimize that capacity?

Automation has been a key enabler in unlocking and optimizing our reported capacity of 33,000 bottles per minute. With high-speed filling lines, automated quality inspection, and advanced conveyor and palletizing systems, we’ve been able to drive higher throughput while ensuring precision and consistency.

AI is also playing an important role—helping us enhance safety through real-time online monitoring in partnership with our tech partner, and enabling continuous tracking of line efficiencies for proactive improvements. Automation and AI together minimize downtime, ensure better resource utilization, and allow our teams to focus on innovation.

As we scale towards 13–14 large-scale plants in the next five years, these technologies will remain central to standardizing best practices, maintaining consistent output, and meeting evolving market demands.Bottom of Form

The shift to Microsoft Dynamics 365 cloud ERP reportedly unified your legacy IT stacks across four legacy bottling units without disrupting daily operations. What operational gains—from planning to distribution—did that consolidation deliver?

With the introduction of Microsoft Dynamics 365 Cloud ERP, SLMG Beverages has integrated four legacy bottling facilities into a single connected platform, enabling end-to-end operational transformation without negatively impacting day-to-day activities. It has simplified planning, manufacturing, quality assurance, and distribution—resulting in measurable improvements in speed, efficiency, and the customer experience.

With one cloud backbone, SLMG is now able to run seamless operations 24x7 in plants, warehouses, and offices in Uttar Pradesh, Bihar, and Uttarakhand with no dependency on any legacy local IT infrastructure. The real-time visibility into sales, purchases, inventory, goods in transit, production, and financials has allowed SLMG to make decisions faster and more crisply with data.

The result has been significant: supply chain productivity improved by 88%, inventory shrinkage declined by 97%, and the time to close financials has been reduced 25–35% faster. Additionally, improved production planning has also resulted in better product freshness and on-time delivery, enabling customer service levels to reach 90%.

In summary, by consolidating SLMG onto Microsoft Dynamics 365, not only is the SLMG operation now modernized, there is also improved decision-making, product quality, and customer confidence; enabling SLMG to be agile and prepared for the future.

With the SLMG One mobile app and Power BI dashboards in place, how has real‑time visibility into sales, logistics, and operations changed the way decisions are made on the ground?

SLMG Beverages has redefined decision making with the SLMG One mobile app and Power BI dashboards, both seamlessly integrated with the Microsoft Fabric Data Lake—the world's fastest data lake technology. As the first Coca-Cola bottler in India to implement Fabric, SLMG now has every member of the leadership team and every second-line manager receiving real-time business intelligence that is at their fingertips. 

This single source of truth means hourly and daily performance can be monitored across the value chain across sales, NSR, inventory, breakage and damages, order and production status, purchases, SKU-level trends, and even team performance. 

The effect on the business has been profound. Managers can respond to deviations or opportunities in real time, teams are more accountable with transparent and real-time performance data, and leadership has shifted from reactive firefighting to proactive management, where problems are anticipated and diverted before they can escalate into larger problems, and opportunities can be seized in real time. 

In short, mobile-first, real-time intelligence has made SLMG faster, leaner, and more competitive, changing the agility in business and the culture of decision making throughout the organization.

For other traditional bottlers or FMCG manufacturers looking to digitise, what is the one foundational step or investment (e.g. ERP, IoT, AI inspection) that produced the strongest ROI?

Our experience at SLMG Beverages is that no one technology is your silver bullet to best ROI alone. The most effective value comes when ERP, IoT, AI, and Analytics exist as one unified ecosystem. 

Your ERP and IoT systems are the backbone — capturing every transactional and operational signal from the work you do in the business. At SLMG, for example, all this data flows into our Microsoft Fabric Data Lake and serves as the high-speed central data warehouse. 

Once ingested, AI and advanced analytics allow us to turn that raw data into real-time insights for leadership visibility and expediency in decision-making. 

The point is: don't think of ERP, IoT, or AI as separate projects as much as you would like to think about investing in an integrated backbone. That is where you obtain the strongest and most sustainable ROI.

In executing big‑ticket technology interventions—ERP rollout, Smart Factory integration, AI inspection—what practical change‑management lessons did you learn in bringing legacy teams up to speed?

If we look at SLMG Beverages’ journey—rolling out Microsoft Dynamics 365 ERP, Smart Factory integration, and AI-based EHS (Environment, Health, and Safety) & inspection Solution —the real test wasn’t just the technology. It was moving a large, legacy workforce from decades-old habits into a fast, data-driven way of working without breaking daily operations.

Here are the practical change-management lessons we learned that could help any large bottler or manufacturing company facing a similar leap:

1. Speak in “Benefits They Feel”, Not “Features You Like”

• What didn’t work: Talking about “cloud ERP” or “AI vision systems” in IT terms—most frontline teams just heard “more work” or “more control.”
• What worked: Explaining in their language:
  • “You’ll spend less time on manual reporting.”
  • “The system will alert you before the line stops.”
  • “No need to count crates by hand every night.”

Lesson: Frame every tech change as a personal win for the user, not a corporate win.

2. Create Change Champions at Every Site

• Hand-pick respected operators, supervisors, and plant accountants to be “change champions.”
• Train them first and deepest—they become in-house experts and trusted voices.
• Reward them visibly when adoption milestones are hit.

Lesson: People trust peers more than they trust IT or corporate.

3. Train for Tasks, Not Just Tools

• What didn’t work: One-time “system overview” training. Users remembered 30% after two weeks.
• What worked:
  • Task-based micro training: “How to post a GRN” or “How to check downtime alerts.”
  • Role-based user manuals and quick video clips in local languages.
  • Refresher sessions after 30 and 90 days.

Lesson: Training must be practical, simple  and repeated until everyone remembers.

4. Don’t Underestimate Emotional Resistance

• Some senior staff saw automation as a threat to job security.
• We addressed it head-on—positioning tech as a skill upgrade opportunity, not a replacement.
• Offered reskilling for those moving from purely manual roles to system-driven ones.

Lesson: Address job security fears openly, not with vague assurances.

5. Make Early Wins Public and Visible

• Example: Smart Factory reduced line downtime alerts by 15% in one plant within 2 months—we celebrated that across the company.
• AI inspection reduced manual QC checks by 40%—shared the story with photos and data.

Lesson: Success stories accelerate adoption faster than policy memos.

6. Integrate IT and Operations Teams from Day One

• In the past, tech projects sat with IT until handover.
• For Smart Factory, we embedded IT engineers into plant ops teams during rollout.
• This meant issues got solved in hours, not escalated in weeks.

Lesson: Break silos—make it a joint business-IT project from start to finish.

Final Learning: Change management in big-ticket tech at a legacy manufacturing giant isn’t about the software—it’s about building trust, lowering fear, and proving value fast. Once people believe the system makes their job easier and safer, adoption becomes self-sustaining.

The leadership pushed to implement Dynamics 365 during the pandemic lockdown but managed to go live ahead of schedule. What made that possible—and what would be your advice to firms wanting to replicate such seamless execution? 

Launching Microsoft Dynamics 365 ahead of schedule during a pandemic changed the technology conversation from being a technology to a matter of culture and leadership.  One of the reasons was that lockdowns and remote work made establishing relationships difficult when teams across functions within the organization treated the ERP rollout as a mission, not just a project.

Discipline kept execution moving, with daily check-ins to get fast decision making and be accountable to get through roadblocks. Employees, who had never used a cloud ERP before, adopted online learning and adapted to new processes quickly due to the on-going leadership support and resources made available, removing blocks for engagement and knowledge sharing a primary objective of an organization to support change - being signaling change was a business priority.

Equally important was collaboration. IT, Operations, Finance,, Sales, and partners became part of the same team sharing ownership, and solving problems "as one" in all areas. A seamless go-live demonstrated that technology really only works when driven by dedication, discipline, and culture of learning.

Having now implemented Smart Factory and full cloud deployment, what role do these systems play in achieving scalability, traceability, and predictive control in your smart factories? 

With Smart Factory systems and full cloud deployment, SLMG Beverages gains real-time data visibility and precise process control across all plants—enabling faster, predictive decision-making. End-to-end backward and forward traceability ensures that any product issue can be quickly identified, isolated, and addressed, safeguarding quality, compliance, and customer trust while supporting seamless scalability.

What guidance would you offer other Coca‑Cola bottlers in India or Asia considering a fully cloud‑based ecosystem, given SLMG’s experience as the first to adopt Microsoft D365 ERP in the region?

For SLMG Beverages, migrating to Microsoft Dynamics 365 was not an IT project, it was a business transformation. The success of the project relied on the engagement and collaboration with leaders across the sales, manufacturing, finance, and distribution departments from day one - as business-driven priorities guided overall adoption, not just technology.

At the heart of the project were standardised processes and clean data. By standardising the core processes across the plants and cleaning the master data up front, SLMG avoided costly issues and created efficiencies once they went live. When D365 was live, the ability to connect to tools like Power BI and Power Automate opened the way for real-time dashboards, automations, and pilot IoT connections to production lines that were directly connected to the ERP.

SLMG also invested heavily in connectivity, a staged rollout, and managing change. Upgrading the networks, treating each location as a phased rollout, and training champions at each plant so that the transition didn't disrupt the operation during peak months of sales was a priority. The frontline users got behind the system once they saw the true benefits — less manual data entry, faster reporting, and more transparency.

Today, shifting to a fully cloud-based Microsoft ecosystem has provided SLMG with real-time visibility into manufacturing, distribution, and sales. What used to take days to assess can now be made into immediate decisions and a

foundation for AI-driven forecasting, route optimise and trade promotions analytics.

If you had to start this transformation today in 2025—with AI, cloud, and manufacturing tech advancing rapidly—what would you do differently to stay ahead?

If I were commencing digital transformation in 2025, I wouldn't treat ERP, AI, cloud, and IoT as disparate initiatives. Instead, I would design them as a cohesive digital nervous system that continually transforms as the business undergoes continuous transformation. The beginning point isn’t the technology, it’s the operating model you want to have in 5 to 10 years—then you will configure your tech stack to support it.

That includes treating ERP as an adaptable, flexible platform with APIs and low-code extensions; putting AI into the flow of decision-making from the first day; and cloud and edge running in parallel for scale and speed. Manufacturing technologies like IoT and digital twins should offer a secure connectivity layer between operations technology (OT) and IT. A single governed data lake should provide the real-time insights and context necessary for leadership dashboards and usage throughout the organization. And because the risks of cyber threats will only increase with time, designing in zero-trust security and resilience will have to be built-in, and from the onset.

Success is above all about the people, not the platforms. Upskilling teams regarding data and AI-informed decision-making, creating change agents in every department, and transforming the business from an "IT project" mindset of generating "new" technology to a constant mindset of transformation will drive sustainable adoption. In brief, don't implement ERP first and then consider how AI can be added later. Integrate everything together as a system, in one embrace—because the competitive differentiator is not the latest software, it is the speed with which a company can adapt to anything that happens next.