SLMG Drinks, a significant Coca-Cola bottler in India, has instituted a big digital transformation throughout its whole enterprise. Enhancements to operation effectivity using SCADA-enabled course of management, AI-enabled inspections, cloud ERP and TenX’s SaaS for intelligence for real-time enterprise intelligence have decreased defect ranges throughout SLMG’s operations to beneath 0.1%, whereas additionally facilitating a 95% discount in security incidents, and ramping manufacturing to 33,000 bottles/minute. Along with effectivity, these numerous buildings have led to a extra constant product, quicker choices and extra buyer belief.

The next dialogue with Joint Managing Director Paritosh Ladhani unveiled the mindset round know-how, studying and management that made SLMG’s evolution to a sensible manufacturing facility from a extra conventional warehousing and bottling enterprise even attainable.

What operational positive aspects have you ever seen from deploying SCADA, AI-powered inspections, EHS options, and automatic ingredient dealing with?

SLMG Drinks has taken a contemporary strategy to plant operations by using SCADA-controlled processing, AI-powered high-speed digicam inspections, AI-supported EHS options, and automatic ingredient dealing with that present tangible enhancements in high quality engineering, security, effectivity, and price financial savings.

Defect detection accuracy has topped 99.9%, leading to defects charges beneath 0.1%. Actual-time rejection evaluation permits for the fast traceability of points, and, together with automated programs, it has now resulted in an estimated 80% discount within the guide inspection workforce. These modifications have additionally allowed for inspection prices to be trimmed by 15-25% whereas concurrently strengthening compliance with FSSAI, FDA, and ISO 22000 requirements by means of improved traceability.

On the protection aspect of the home, SLMG’s tailor-made AI-based EHS resolution—developed collectively with exterior experience in partnership with in-house Tech & QC groups—has supplied round the clock CCTV-enabled visibility into the crops. With the predictive analytics instruments embedded within the system, automated danger prioritization, and energetic real-time monitoring of staff, security incidents have dropped by 95% and well timed, knowledgeable interventions for dangers, stressors, fatigue, and well being issues at the moment are attainable.

That stated, use of SCADA programs ensures steady monitoring of temperature, strain, and Brix—eliminating guide intervention, constructing assurances towards information falsification, and presenting real-time choices for data-driven choices to keep up high quality.

Cumulatively, all of this has resulted in decreased downtime, decreased rework, decreased prices, and ensured a safer office; and with these developments, SLMG Drinks has surpassed the efforts to create consistency in each bottle produced thereby enhancing buyer belief.

You’ve reported capability of 33,000 bottles per minute throughout a number of crops, with plans to achieve 13–14 large-scale crops inside 5 years. How has automation helped unlock and optimize that capability?

Automation has been a key enabler in unlocking and optimizing our reported capability of 33,000 bottles per minute. With high-speed filling traces, automated high quality inspection, and superior conveyor and palletizing programs, we’ve been in a position to drive larger throughput whereas making certain precision and consistency.

AI can be enjoying an essential function—serving to us improve security by means of real-time on-line monitoring in partnership with our tech companion, and enabling steady monitoring of line efficiencies for proactive enhancements. Automation and AI collectively reduce downtime, guarantee higher useful resource utilization, and permit our groups to deal with innovation.

As we scale in the direction of 13–14 large-scale crops within the subsequent 5 years, these applied sciences will stay central to standardizing finest practices, sustaining constant output, and assembly evolving market calls for.Backside of Type

The shift to Microsoft Dynamics 365 cloud ERP reportedly unified your legacy IT stacks throughout 4 legacy bottling items with out disrupting day by day operations. What operational positive aspects—from planning to distribution—did that consolidation ship?

With the introduction of Microsoft Dynamics 365 Cloud ERP, SLMG Drinks has built-in 4 legacy bottling amenities right into a single related platform, enabling end-to-end operational transformation with out negatively impacting day-to-day actions. It has simplified planning, manufacturing, high quality assurance, and distribution—leading to measurable enhancements in velocity, effectivity, and the client expertise.

With one cloud spine, SLMG is now in a position to run seamless operations 24×7 in crops, warehouses, and workplaces in Uttar Pradesh, Bihar, and Uttarakhand with no dependency on any legacy native IT infrastructure. The actual-time visibility into gross sales, purchases, stock, items in transit, manufacturing, and financials has allowed SLMG to make choices quicker and extra crisply with information.

The consequence has been important: provide chain productiveness improved by 88%, stock shrinkage declined by 97%, and the time to shut financials has been decreased 25–35% quicker. Moreover, improved manufacturing planning has additionally resulted in higher product freshness and on-time supply, enabling customer support ranges to achieve 90%.

In abstract, by consolidating SLMG onto Microsoft Dynamics 365, not solely is the SLMG operation now modernized, there’s additionally improved decision-making, product high quality, and buyer confidence; enabling SLMG to be agile and ready for the longer term.

With the SLMG One cellular app and Energy BI dashboards in place, how has actual‑time visibility into gross sales, logistics, and operations modified the best way choices are made on the bottom?

SLMG Drinks has redefined determination making with the SLMG One cellular app and Energy BI dashboards, each seamlessly built-in with the Microsoft Material Knowledge Lake—the world’s quickest information lake know-how. As the primary Coca-Cola bottler in India to implement Material, SLMG now has each member of the management crew and each second-line supervisor receiving real-time enterprise intelligence that’s at their fingertips. 

This single supply of fact means hourly and day by day efficiency could be monitored throughout the worth chain throughout gross sales, NSR, stock, breakage and damages, order and manufacturing standing, purchases, SKU-level developments, and even crew efficiency. 

The impact on the enterprise has been profound. Managers can reply to deviations or alternatives in actual time, groups are extra accountable with clear and real-time efficiency information, and management has shifted from reactive firefighting to proactive administration, the place issues are anticipated and diverted earlier than they’ll escalate into bigger issues, and alternatives could be seized in actual time. 

Briefly, mobile-first, real-time intelligence has made SLMG quicker, leaner, and extra aggressive, altering the agility in enterprise and the tradition of determination making all through the group.

For different conventional bottlers or FMCG producers seeking to digitise, what’s the one foundational step or funding (e.g. ERP, IoT, AI inspection) that produced the strongest ROI?

Our expertise at SLMG Drinks is that nobody know-how is your silver bullet to finest ROI alone. The best worth comes when ERP, IoT, AI, and Analytics exist as one unified ecosystem. 

Your ERP and IoT programs are the spine — capturing each transactional and operational sign from the work you do within the enterprise. At SLMG, for instance, all this information flows into our Microsoft Material Knowledge Lake and serves because the high-speed central information warehouse. 

As soon as ingested, AI and superior analytics permit us to show that uncooked information into real-time insights for management visibility and expediency in decision-making. 

The purpose is: do not consider ERP, IoT, or AI as separate initiatives as a lot as you want to take into consideration investing in an built-in spine. That’s the place you acquire the strongest and most sustainable ROI.

In executing large‑ticket know-how interventions—ERP rollout, Good Manufacturing facility integration, AI inspection—what sensible change‑administration classes did you be taught in bringing legacy groups up to the mark?

If we have a look at SLMG Drinks’ journey—rolling out Microsoft Dynamics 365 ERP, Good Manufacturing facility integration, and AI-based EHS (Surroundings, Well being, and Security) & inspection Resolution —the true take a look at wasn’t simply the know-how. It was shifting a big, legacy workforce from decades-old habits into a quick, data-driven approach of working with out breaking day by day operations.

Listed below are the sensible change-management classes we realized that might assist any giant bottler or manufacturing firm going through the same leap:

1. Converse in “Advantages They Really feel”, Not “Options You Like”

• What didn’t work: Speaking about “cloud ERP” or “AI imaginative and prescient programs” in IT phrases—most frontline groups simply heard “extra work” or “extra management.”
• What labored: Explaining of their language:
  • “You’ll spend much less time on guide reporting.”
  • “The system will warn you earlier than the road stops.”
  • “No must rely crates by hand each evening.”

Lesson: Body each tech change as a private win for the person, not a company win.

2. Create Change Champions at Each Website

• Hand-pick revered operators, supervisors, and plant accountants to be “change champions.”
• Prepare them first and deepest—they turn out to be in-house consultants and trusted voices.
• Reward them visibly when adoption milestones are hit.

Lesson: Folks belief friends greater than they belief IT or company.

3. Prepare for Duties, Not Simply Instruments

• What didn’t work: One-time “system overview” coaching. Customers remembered 30% after two weeks.
• What labored:
  • Process-based micro coaching: “ publish a GRN” or “ verify downtime alerts.”
  • Function-based person manuals and fast video clips in native languages.
  • Refresher classes after 30 and 90 days.

Lesson: Coaching should be sensible, easy  and repeated till everybody remembers.

4. Don’t Underestimate Emotional Resistance

• Some senior employees noticed automation as a menace to job safety.
• We addressed it head-on—positioning tech as a talent improve alternative, not a alternative.
• Provided reskilling for these shifting from purely guide roles to system-driven ones.

Lesson: Deal with job safety fears overtly, not with imprecise assurances.

5. Make Early Wins Public and Seen

• Instance: Good Manufacturing facility decreased line downtime alerts by 15% in a single plant inside 2 months—we celebrated that throughout the corporate.
• AI inspection decreased guide QC checks by 40%—shared the story with images and information.

Lesson: Success tales speed up adoption quicker than coverage memos.

6. Combine IT and Operations Groups from Day One

• Previously, tech initiatives sat with IT till handover.
• For Good Manufacturing facility, we embedded IT engineers into plant ops groups throughout rollout.
• This meant points obtained solved in hours, not escalated in weeks.

Lesson: Break silos—make it a joint business-IT undertaking from begin to end.

Last Studying: Change administration in big-ticket tech at a legacy manufacturing large isn’t concerning the software program—it’s about constructing belief, reducing concern, and proving worth quick. As soon as individuals imagine the system makes their job simpler and safer, adoption turns into self-sustaining.

The management pushed to implement Dynamics 365 in the course of the pandemic lockdown however managed to go reside forward of schedule. What made that attainable—and what could be your recommendation to companies wanting to copy such seamless execution? 

Launching Microsoft Dynamics 365 forward of schedule throughout a pandemic modified the know-how dialog from being a know-how to a matter of tradition and management.  One of many causes was that lockdowns and distant work made establishing relationships tough when groups throughout features inside the group handled the ERP rollout as a mission, not only a undertaking.

Self-discipline stored execution shifting, with day by day check-ins to get quick determination making and be accountable to get by means of roadblocks. Staff, who had by no means used a cloud ERP earlier than, adopted on-line studying and tailored to new processes shortly as a result of on-going management assist and assets made out there, eradicating blocks for engagement and data sharing a main goal of a company to assist change – being signaling change was a enterprise precedence.

Equally essential was collaboration. IT, Operations, Finance,, Gross sales, and companions turned a part of the identical crew sharing possession, and fixing issues “as one” in all areas. A seamless go-live demonstrated that know-how actually solely works when pushed by dedication, self-discipline, and tradition of studying.

Having now applied Good Manufacturing facility and full cloud deployment, what function do these programs play in attaining scalability, traceability, and predictive management in your good factories? 

With Good Manufacturing facility programs and full cloud deployment, SLMG Drinks positive aspects real-time information visibility and exact course of management throughout all crops—enabling quicker, predictive decision-making. Finish-to-end from side to side traceability ensures that any product concern could be shortly recognized, remoted, and addressed, safeguarding high quality, compliance, and buyer belief whereas supporting seamless scalability.

What steering would you provide different Coca‑Cola bottlers in India or Asia contemplating a completely cloud‑primarily based ecosystem, given SLMG’s expertise as the primary to undertake Microsoft D365 ERP within the area?

For SLMG Drinks, migrating to Microsoft Dynamics 365 was not an IT undertaking, it was a enterprise transformation. The success of the undertaking relied on the engagement and collaboration with leaders throughout the gross sales, manufacturing, finance, and distribution departments from day one – as business-driven priorities guided general adoption, not simply know-how.

On the coronary heart of the undertaking had been standardised processes and clear information. By standardising the core processes throughout the crops and cleansing the grasp information up entrance, SLMG averted pricey points and created efficiencies as soon as they went reside. When D365 was reside, the flexibility to hook up with instruments like Energy BI and Energy Automate opened the best way for real-time dashboards, automations, and pilot IoT connections to manufacturing traces that had been immediately related to the ERP.

SLMG additionally invested closely in connectivity, a staged rollout, and managing change. Upgrading the networks, treating every location as a phased rollout, and coaching champions at every plant in order that the transition did not disrupt the operation throughout peak months of gross sales was a precedence. The frontline customers obtained behind the system as soon as they noticed the true advantages — much less guide information entry, quicker reporting, and extra transparency.

Right now, shifting to a completely cloud-based Microsoft ecosystem has supplied SLMG with real-time visibility into manufacturing, distribution, and gross sales. What used to take days to evaluate can now be made into fast choices and a

basis for AI-driven forecasting, route optimise and commerce promotions analytics.

If you happen to needed to begin this transformation as we speak in 2025—with AI, cloud, and manufacturing tech advancing quickly—what would you do in another way to remain forward?

If I had been commencing digital transformation in 2025, I would not deal with ERP, AI, cloud, and IoT as disparate initiatives. As an alternative, I might design them as a cohesive digital nervous system that frequently transforms because the enterprise undergoes steady transformation. The start level isn’t the know-how, it’s the working mannequin you wish to have in 5 to 10 years—then you’ll configure your tech stack to assist it.

That features treating ERP as an adaptable, versatile platform with APIs and low-code extensions; placing AI into the movement of decision-making from the primary day; and cloud and edge working in parallel for scale and velocity. Manufacturing applied sciences like IoT and digital twins ought to provide a safe connectivity layer between operations know-how (OT) and IT. A single ruled information lake ought to present the real-time insights and context mandatory for management dashboards and utilization all through the group. And since the dangers of cyber threats will solely improve with time, designing in zero-trust safety and resilience should be built-in, and from the onset.

Success is above all concerning the individuals, not the platforms. Upskilling groups concerning information and AI-informed decision-making, creating change brokers in each division, and remodeling the enterprise from an “IT undertaking” mindset of producing “new” know-how to a relentless mindset of transformation will drive sustainable adoption. Briefly, do not implement ERP first after which take into account how AI could be added later. Combine every thing collectively as a system, in a single embrace—as a result of the aggressive differentiator just isn’t the newest software program, it’s the velocity with which an organization can adapt to something that occurs subsequent.