The European Union (PPWR) entered into force in February 2025 and will generally apply from 12 August 2026, bringing new requirements around recyclability, recycled content, labelling, substances of concern, documentation, and Extended Producer Responsibility (EPR).

Many CPG companies believe they still have time to prepare for PPWR. However, operationally, they may already be too late. By the time enterprises identify non-compliant SKUs, validate supplier data, redesign packaging, and complete internal approvals, the remediation window may already be closing.

Beyond the deadline, PPWR is becoming one of the largest packaging data and operational readiness challenges many CPG companies have faced in years.

Why packaging data is now business-critical

A global CPG company may have thousands of Stock Keeping Units (SKUs) across markets, suppliers, plants, packaging formats, and material combinations.

A single beverage SKU, for example, is not just a bottle. It may include glass, an aluminum cap, a front label, a back label, a neck label, inks, adhesives, cartons, secondary packaging, and country-specific artwork. Each component has its own recyclability profile, material composition, supplier documentation, and compliance requirement.

That means a product cannot be assessed only at a broad packaging-family level. PPWR readiness needs visibility at the SKU level. This is where many enterprises discover the first challenge.

Packaging specifications may sit in Product Lifecycle Management (PLM) systems. Supplier declarations may arrive as PDF files. Procurement data may sit in Enterprise Resource Planning (ERP) systems. Sustainability reporting may run through separate tools. Certificates may be incomplete, outdated, or unaudited. Some data may still be managed through spreadsheets.

When compliance teams attempt to assess SKU-level readiness across markets, many discover that packaging information is incomplete, inconsistent, or difficult to trace across products, suppliers, and packaging components.

The cost of this fragmentation can be significant

For large CPG enterprises, fragmented packaging data can translate into millions in avoidable EPR costs, delayed product approvals, supplier non-compliance exposure, late-stage packaging redesigns, and increased audit risk.

For instance, if packaging uses virgin materials, EPR fees may be higher. If recycled content or recyclability scores are weak, redesign may be required. If supplier declarations cannot be verified, the Declaration of Conformity (DoC) becomes difficult to complete. In fact, supplier documentation is emerging as one of the biggest PPWR risk areas. Many companies still rely on incomplete declarations, outdated certificates, inconsistent material composition data, and manually validated supplier information.

The complexity also varies by country. While PPWR aims to harmonize packaging rules across the European Union (EU), companies still need to account for local EPR schemes, labelling expectations, and market-specific implementation across markets. This creates operational complexity across packaging, procurement, regulatory affairs, and supply chain teams.

What many executives underestimate is that PPWR is not just a reporting exercise. It directly impacts packaging design, supplier onboarding, product approvals, EPR cost exposure, and speed-to-market. Companies that wait too long may find themselves reacting through manual data hunts, emergency redesign programs, manual data collection and late-stage packaging redesign efforts.

So where should companies begin?

PPWR readiness begins with three practical steps:

• Assess packaging data maturity
  Organizations need to identify where packaging data resides, how complete and reliable it is, and whether material composition can be traced consistently across SKUs, suppliers, and markets. Supplier documentation quality and data availability are also critical considerations.
• Build SKU-level compliance visibility
  Teams should have centralized visibility into recyclability grades, material composition by weight, recycled content, supplier compliance status, EPR cost exposure, country-specific requirements, and supporting documentation readiness.
• Connect systems and workflows
  PPWR data cannot remain isolated within PLM systems or sustainability reports. Organizations need integrated workflows connecting PLM, ERP, procurement, supplier platforms, documentation repositories, and reporting systems so compliance can be managed continuously rather than assembled manually before audits or reporting cycles.

Where Artificial Intelligence can help

AI can significantly accelerate PPWR readiness by extracting packaging information from supplier PDFs, certificates, lab reports, and specification sheets at scale. It can also identify compliance gaps, flag high-risk materials, benchmark suppliers, and prioritize remediation actions across thousands of SKUs.

Over time, AI-enabled compliance intelligence can also help companies track regulatory changes and understand what needs to be updated across products, suppliers, and markets.

The window to act is narrowing

PPWR readiness will not come from interpreting the regulation at the last minute. It will come from building the packaging data foundation now, while there is still time to trace materials, verify supplier documentation, assess recyclability, manage country-level variation, and redesign packaging where needed.

The organizations that move early will have more time to redesign packaging, renegotiate supplier requirements, reduce EPR exposure, and improve packaging readiness and reduce compliance risk. Those that delay may face rising costs, reactive packaging changes, fragmented supplier data, and increased regulatory pressure close to enforcement timelines.

For CPG companies, the question is whether their systems, suppliers, and teams can produce the evidence needed to prove compliance, control costs, and keep products moving across European markets.

The faster companies can bring packaging data together, the more confidently they can respond to PPWR and the wider shift toward circular packaging.

To explore how CPG enterprises can prepare for PPWR with a structured, data-led approach, read our whitepaper on packaging compliance and PPWR readiness.

Author:

Paritosh Singha
Principal Consultant at 乐播传媒视频

The post PPWR Compliance Will Fail Without SKU-Level Packaging Data. Is your Company ready? appeared first on 乐播传媒视频.

What makes PPWR particularly difficult is not a single packaging assessment, but the need to continuously manage compliance across thousands of SKUs, packaging-component combinations, suppliers, markets, and evolving regulatory conditions. For many CPG enterprises, the challenge is rapidly shifting from isolated compliance activity to enterprise-wide packaging data governance.

That proof cannot be assembled at the last minute from scattered spreadsheets, supplier PDFs, PLM records, ERP extracts, sustainability tools, and email trails. This is where the real risk begins.

The biggest PPWR challenge may be system disconnect

In a large CPG enterprise, packaging data rarely lives in one place. Product and packaging specifications may sit in PLM. Procurement data may sit in ERP. Supplier declarations may come through portals, emails, or PDFs. Sustainability teams may use separate ESG or LCA tools. Regulatory teams may maintain country-level trackers. Packaging development may rely on artwork, component, and material records that are versioned differently across systems.

Individually, each system may work. Collectively, they may fail PPWR.

That is because PPWR readiness depends on the ability to connect data across the packaging lifecycle. A supplier certificate needs to link to a material record. A material record needs to link to a packaging component. A packaging component needs to link to an SKU. That SKU needs to be assessed against country-specific rules, EPR fees, recyclability thresholds, labelling requirements, and documentation obligations.

The challenge becomes even greater when packaging specifications change. A material substitution, resin update, packaging weight modification, artwork revision, or recycled content adjustment may impact compliance calculations, EPR exposure, recyclability outcomes, supplier declarations, and reporting obligations simultaneously. In disconnected environments, those changes often do not propagate consistently across systems, creating gaps between packaging reality and compliance records.

Fragmented data slows every critical decision

Disconnected packaging data creates a practical problem: teams cannot act fast enough.

A packaging team may need to know whether a new format meets recyclability expectations. Procurement may need to validate whether supplier documentation is complete. Regulatory affairs may need evidence for a Declaration of Conformity. Sustainability may need reliable portfolio-level metrics. Commercial teams may need assurance that a product can continue to move in a specific European market.

If each answer requires a manual hunt across systems, documents, suppliers, and spreadsheets, PPWR compliance becomes reactive by default. The issue is not only inefficiency, but scalability. Manual coordination across packaging, procurement, regulatory, sustainability, and supplier teams may work temporarily for isolated projects, but it becomes increasingly difficult to sustain across large packaging portfolios operating in multiple markets simultaneously.

This can delay packaging approvals, slow new product launches, trigger late-stage redesigns, and create avoidable friction between R&D, procurement, sustainability, compliance, and supply chain teams. It can also increase EPR exposure, especially where material choices, recycled content, or recyclability performance directly influence fee structures.

The hidden cost is not only regulatory penalty, it is decision latency.

Audit readiness will be a mandatory requirement

Under PPWR, companies will increasingly need to demonstrate not only that packaging complies, but also how compliance was validated, approved, and maintained over time. This creates pressure for traceable decision-making across packaging development, supplier onboarding, material changes, and market approvals.

In practice, audit readiness depends on the ability to connect packaging specifications, supplier evidence, recyclability assessments, declarations, approvals, and reporting records into a transparent compliance trail. Static spreadsheets and disconnected repositories make that process difficult to scale reliably.

Supplier evidence is becoming a control point

One of the weakest links in PPWR readiness is supplier evidence 鈥� incomplete declarations, outdated certificates, unstandardized material composition data, and important information such as proof of restricted substance compliance sitting outside formal workflows.

Under PPWR, companies will need to maintain confidence in the data behind their packaging claims. That means, supplier documentation can no longer remain a side process managed through attachments and manual follow-ups. It needs to become part of a governed workflow, connected to product records, packaging components, approval gates, and reporting requirements.

This becomes especially critical when suppliers operate across multiple geographies and packaging tiers. Many enterprises still struggle with inconsistent material declarations, varying documentation formats, outdated certificates, and limited visibility into upstream packaging composition changes. Without structured supplier traceability, compliance confidence weakens quickly.

For global CPG companies, this is especially important because compliance is not uniform in practice. PPWR may create a common regulatory direction across Europe, but country-level EPR rules, labelling expectations, artwork requirements, and implementation details still matter. The same packaging format can carry different cost, compliance, or labelling implications across markets.

What connected packaging intelligence should look like

The answer is not another standalone compliance dashboard. Most CPG enterprises already have enough systems. What they need is a packaging intelligence backbone that brings product, packaging, supplier, sustainability, compliance, and reporting data into a governed operating layer.

In practical terms, this means creating a governed digital layer where packaging specifications, supplier evidence, sustainability metrics, recyclability assessments, regulatory obligations, and market-specific compliance requirements can interact through connected workflows rather than isolated data repositories.

This does not require every enterprise to rip and replace its current systems. In most cases, the smarter move is integration. Existing systems can remain, but the data and workflows around packaging compliance need to be connected, governed, and traceable.

PLM can serve as the operational anchor for packaging specifications, BOM structures, pack hierarchies, artwork management, material substitutions, and packaging change workflows. Around that foundation, ERP, procurement platforms, supplier systems, ESG tools, LCA solutions, EPR platforms, and regulatory databases need to operate as connected ecosystems rather than disconnected repositories. The objective is not simply integration, but synchronized packaging governance across functions and markets.

To support scalable PPWR readiness, this connected operating layer should enable four core capabilities across the packaging lifecycle:

• First, it should create a single product-pack view across markets. Teams should be able to see material composition, recycled content, recyclability score, supplier evidence, labelling status, EPR exposure, and compliance gaps at SKU, packaging component, supplier, and country level. This visibility also helps enterprises assess potential EPR cost exposure, redesign priorities, and packaging portfolio risk concentrations before issues escalate operationally
• Second, it should embed compliance into workflows. Restricted substance checks, supplier declarations, documentation reviews, recyclability validation, and approval traceability need to become part of packaging development, sourcing, and change management. That is how companies reduce late-stage redesigns, delayed launches, and audit pressure.
• Third, it should make supplier evidence structured and usable, with certificates, lab reports, declarations, and material data linked directly to product and packaging records.
• Fourth, it should use AI where the work is too fragmented or high-volume for manual teams to manage efficiently. AI can help extract data from PDFs and certificates, identify missing documentation, flag high-risk materials, benchmark suppliers, surface country-level exposure, and suggest priority actions. AI can also help prioritize high-risk packaging scenarios by identifying missing evidence, inconsistent supplier data, market-specific exposure, or packaging components that may require redesign or additional validation under changing regulations.

The way forward

Building this capability requires more than regulatory interpretation. It needs packaging domain knowledge, PLM and ERP integration, supplier data management, sustainability data modelling, compliance workflow design, and AI-enabled analytics.

In practical terms, companies need to assess current gaps, define a target data model, connect PLM, ERP, supplier and sustainability systems, embed controls into workflows, and create audit-ready reporting across markets. A structured transformation approach typically begins with packaging data discovery and process assessment, followed by integration of PLM, ERP, supplier, and sustainability systems, workflow governance implementation, supplier evidence digitization, and continuous compliance monitoring across markets.

For CPG companies, the real PPWR risk may not be that they lack intent. It may be that their packaging data, systems, and workflows are too disconnected to keep pace with the regulation. The sooner they move from fragmented packaging records to connected packaging intelligence, the more control they will have over compliance, cost, supplier traceability, and market readiness.

To know how to build PPWR readiness into your enterprise download our whitepaper.

Author:

Paritosh Singha
Principal Consultant at 乐播传媒视频

The post Why Disconnected Packaging Data Could Become the Biggest PPWR Risk for CPG Companies appeared first on 乐播传媒视频.

The post Generative AI, a New Catalyst for D2C Expansion appeared first on 乐播传媒视频.

The post 10 Critical Learnings to Win in D2C in Mid to Large Sized Organizations appeared first on 乐播传媒视频.

It is a common situation that most shoppers face while buying packaged goods online. Due to high demand many daily used products go out of stock in retail sites. But it is more annoying to experience longer time in any shopping website due to lack of clarity about how to select and pay for a product. Direct-to-customer (D2C) is the new trend shaping the consumer-packaged goods (CPG) industry across the globe. Primary reason being low entry barrier, which is enabling private label brands to appear in the market with frequency higher than ever. However, not all brands could sustain the race of attracting consumers to their brands. It is more due to the marketing strategy they follow than the quality or features in the products. Drawing consumers to the products is the primary major challenge in this business model. Second major challenge is ensuring continuous availability of products, which means ensuring an uninterrupted supply chain process. If we introspect more into the primary challenge, we find three reasons underlying. First one is all about understanding the need of each & every customer and designing product as per their requirements. Second is keeping a tab of competitors鈥� offerings in the marketplace. Third is using information related to earlier two cases to develop personalised buying experience for every customer. The only solution that could help us resolve all these problems is data. Data is the ammunition in this expanding war of customer acquisition and retention. Collection of data about customers鈥� preferences and competitors鈥� new offers, storing those data and using those effectively are of primary importance in building a successful D2C business model.

If we go deeper into this, we find that next level of challenge is identification of data. It is customary for every marketer to understand and find the type of data one needs to understand customers鈥� requirements. Parallelly, one needs to find the data required on competitors鈥� offerings to strengthen the grip on the marketplace. Once understood, firms should think about the resources through which all these data can be collected and stored. And finally, how these data can be used to generate insights about customer鈥檚 behaviour.

To help firms in this journey, digital technology services are on the rise. The advent of intelligent automation has equipped the software service providers develop digital tools to understand the ongoing trend and find which areas need more focus to make the business run profitably. Robotic process automation (RPA), cloud technology, Artificial Intelligence (AI) based algorithms and machine learning (ML) programs are examples of digital tools which have paved the way for technology focused CPG firms to monitor their businesses closely and engage consumers more effectively. Every consumer has a different and unique way of shopping. Therefore, engaging with each consumer through the right channel, right promotion and right offer is undoubtedly a critical task. In top of that increasing penetration of mobile technology has brought all category of consumers at the same place and at the same time resulting in an extra level of complexity in data collection. Therefore, developing a robust data storage facility is no more a choice but a necessity for managing such increasing diversified consumer base. 乐播传媒视频 through its rich experience of working with multiple CPG consumers can provide both on-premises and cloud-based database solutions to manage terabytes of data on a continuous basis.

Once the data storage facility is set up, suitable data collection resources should be developed to ensure uninterrupted data feeding to the repository. Whenever a consumer engages in any purchasing activity through online channel, millions of data are transferred to the marketing firm. Multiplying this with number of available channels, nearly trillions of data are needed to be handled every day. Hence, the solution is to have resources having the capability to find relevant data in any format from any channel and incessant feeding of these data to the storage facility. 乐播传媒视频鈥檚 intelligent automation team can develop any customised intelligent bots using robotic process automation (RPA) for collecting data from any channel at any time with 100% efficiency. Not only from websites, but these bots can also even identify the necessary data from any document in any format. This can help the firms analyse multiple purchasing invoices to figure out average purchase value for any customer.

After collection the data, next important steps are identification of relevant KPIs and development of analytical models for the purpose of understanding the status of ongoing business and generation of insights about customer鈥檚 buying pattern. 乐播传媒视频 has a dedicated analytics team who has developed analytical models as per business need and has helped firms understand consumer journey at every touchpoint starting from exploration to procurement of any product.

After data management the next critical area where D2C firms should put highest focus is managing the supply chain of entire processes. If designing products as per consumer鈥檚 need is the primary challenge that D2C firms face now-a-days, then the next big challenge is taking these products to the consumer鈥檚 doorstep. The solution that addresses this concern is smart supply chain. Although most of the firms engage third parties for delivery of products, making the products available to delivery partner鈥檚 warehouses or distribution centres need a thorough monitoring of supply chain. 乐播传媒视频鈥檚 Industry 4.0 and Digital team together provide efficient and effective supply chain solutions with the help of Internet of Things (IoT), RPA and AIML. Not only our solutions ensure automated monitoring of entire supply chain process but also can eliminate the redundant processes, reduce the energy consumption at intermediate stages wherever possible and build models for optimising selection of packaging materials.

The problem that Sanaya faced at the beginning of this article could have easily been avoided had the brand manufacturer focussed on these issues and collected data about Sanaya鈥檚 buying pattern. Also, they should have ensured availability of the product at retailer鈥檚 site by adopting smart supply chain practices. Emerging digital technologies like robotics, artificial intelligence, cloud technology and IoT are a blessing for firms. However, leveraging these technologies to maximise the profit and capture the market share needs a blend of expertise & experience over the years. 乐播传媒视频鈥檚 rich experience of working with global CPG manufacturers in multiple channels and multiple regions for diversified products have helped develop suitable digital technology-based offers for D2C firms. In an industry like CPG where competition has been a paramount concern from new product perspective, emergence of D2C practice has made the situation more complex. To compete successfully and lead in the marketplace, firms must embrace the digital tools for navigating through the wave of unlimited new products.

Author:

Debal Chakraborty,
Principal Consultant

The post Brands that Embrace Digital will Stay Ahead in the D2C Model appeared first on 乐播传媒视频.

Imagine you are buying a few bags of potato chips to snack on. One bag has fewer chips than expected; the chips do not match the weight mentioned on the package. You will be disappointed. You will either complain to the manufacturer or simply stop trusting the brand. Worse, you could take to social media to express your anger, affecting the broader reputation of the brand. If there are a few extra chips in the bag, you will not mind it. But those extra chips can quickly add up to massive losses for the manufacturer. Either way, not controlling the grammage of products leads to unwelcome outcomes. This is not a new problem for the F&B industry. But new solutions are now available to contain and practically eliminate-the problem.

Variances in packaged food products is expected. The manufacturer of a 78 g bag of potato chips can perhaps tolerate a variance of +/- 2 grams. But by identifying the actual variance and tracking trends, upstream and downstream systems can be improved, costs can be lowered, compliance norms can be met, waste reduced and customers kept happy by offering a more consistent product. However, usually individual checkweigher or multi head weighers and baggers are used at the packaging stage to accept/reject products for the market鈥攚hen it can be too late. To overcome this, the science of Extra Grammage (EGA) Optimization needs to be mastered.

The weight of packaged food products is a tricky affair. Something as simple as extra moisture in the chips or extra oil can increase the weight. The thickness of input materials (for example, potato slices, masala or salt deposition etc. ) or even the temperature of the cooking oil or frying time can cause higher or lower weights, or the vibratory nature of the manufacturing equipment can lead to variances.听听听

Often the selling price of a product cannot be changed. In such cases the manufacturer must resort to controlling the weight.

EGA optimization is a latest Industry 4.0 solution integrates all weigher 鈥淢achine Data鈥� & 鈥淧rocess Parameters鈥� and where continuously monitors the trend of Underweight & Overweight Rejections and Extra Give Away of Materials.听 Then Auto-Insights are generated basis factual data at frequent intervals, minute level & KPIs are measured EGA%, rejections% etc. and any deviations beyond acceptable limits are alerted to respective operators to fix the production parameters causing the variance immediately, minimizing the volume of rejected products at the end of the line. The solution works for both linear and vertical manufacturing and packaging processes.听

Vertical manufacturing and packaging processes need to be dealt with a little differently from linear processes (example: potato chips versus cookies). In a vertical process, the product drop happens to multiple buckets during production. The weight may vary because of product breakage or due to residual recipe material, accumulated in the assembly line, sticking to the product.

In current practice, many CPG companies have not integrated their Machine data. Right set of Analytics not used to create meaningful alerts for operators and to improve output quality. Our implementation of this solution in a large food production plant has shown significant results, that even a 1% impact is saving thousands of dollars. But this is what production plant managers will like to hear the most: ROI in our implementation was less than six months. This is a high-impact, quick-return intervention that every manufacturer must consider.

Author:

Siddaraju G,
Senior Principal Consultant,
Business Consulting Group,
乐播传媒视频

The post A 鈥渕ust-have鈥� packing weight variation control technique appeared first on 乐播传媒视频.

Marketing and Trade Planning Needs to be Real-time and Data-Driven

By the time the organization works with distributors to collect data and plan a marketing and trade promotions campaign, markets have changed. The organization then puts its plans on hold while it comes up with better options. There is a need for systems that allow planning to be dynamic and execution to be fluid. 乐播传媒视频鈥檚 Intelligent Planning Platform for CPG organizations fills the gap. It enables high-impact near real-time data-driven planning that is focused, relevant, detailed, fluid and keeps the entire organization in synch with campaign goals.

Empower CPG Marketing Leaders with Intelligent Planning Platform听

The Intelligent Planning Platform serves as a digital nervous system to support marketing plans and execution. It tells marketing executive what to do, when to do it and why to do it. It can preempt markets by providing real-time visibility into what is happening in sales, marketing, trade promotion, schedules, volumes and the strategy of competition. Basically, it tracks and analyzes every parameter key to CPG CXOs.

It鈥檚 a Connected Platform:听

The system harmonizes processes across different parts of the organization that work together to deliver success. It keeps master data available to everyone such as distribution, marketing, communication, purchase, and finance, playing a pivotal role in converting information into plans. Its real-time dashboards assist in precise decision-making at velocity.

Enables Real-time Communication with Stakeholders

Success in fast-moving鈥攁nd fast-changing campaigns鈥攄epends on the efficiency with which communication is maintained in real time with internal and external stakeholders, distributors and customers. The platform keeps the entire marketing ecosystem in synch.

Dynamic Planning, Execution and Decision Making

It is important to have plans defined and based on data. But it is equally important to have a system that can respond to change and manage quick course corrections. Our Intelligent Planning Platform allows teams to change decisions around everything, from volumes to SKUs and pricing. The system then provides the means to re-optimize the plan and follow through on the execution.

The world of CPG has been transformed over the last few years. Today, it has multiple ways to connect directly with the customer, collect an increasing amount of data and analyze it in real time. It now needs a system that can act flawlessly on the market signals. Our Intelligent Planning Platform is precisely that system. It supports high value planning and decision-making. It prompts and manages quick adjustments in execution. And it ensures that marketing dollars deliver target ROI.

乐播传媒视频 has implemented intelligent planning platform for Leading CPG Business. We implemented an Integrated Trade Marketing & Distribution Planning to Accelerated Speed to Market. To know more about our Intelligent Planning capabilities for CPG industry read our whitepaper 鈥�Intelligent Planning 鈥� The winning tool for CPG Business in the Digital Era鈥�

Author:

Debjit Banerjee
VP, Business Consulting,
乐播传媒视频

The post Using an Intelligent Planning Platform to guarantee marketing success appeared first on 乐播传媒视频.

Vision-based computing or computer vision, aka machine vision, has grown tremendously in the last few years. The key reasons for the growth lie in the availability of affordable hardware, the growth in data sets and maturity in the science of Artificial Intelligence (AI) and Machine Learning (ML). With the COVID-19 pandemic accelerating digital adoption, vision-based analytics is bound to find wide-spread applications in several industries including manufacturing. The extraordinary drive for work place safety, the need for automation to improve productivity, and access to better quality will be the key drivers for the growth in vision-based computing. One indicator of its bullish future is reflected in a that found AI in computer vision market size would reach $144.46B by 2028 from $7.04B in 2020 (a CAGR of 45.64% from 2021 to 2028). Manufacturers who do not study use cases for vision-based computing in their organizations could lose out on the promise of generating business value and creating competitive differentiation.

An area where vision-based technology can be applied with great success is quality inspection. Take the case of manufacturing cookies in the food and beverage industry. Operators are deployed on production lines to check the quality of the output. They must examine each cookie for conformance to color, texture, shape, size, nut coverage and several other factors and benchmarks. These are important in an industry where consumers assess products visually. Human bias 鈥� even human fatigue or distraction — can affect the inspection process. Options such as interval sampling of products in a lab can improve the process but they too leave the gates open to flawed products reaching the market.

The solution is in using AI and ML-based algorithms to examine each cookie. Cameras scan the live production line before packaging, accurately picking out cookies that do not meet the pass range for quality. Even when samples are examined in an off-line mode in a lab, vision-based computing removes subjective biases.

Once a cookie on a production line is identified for non-conformance, a simple drop mechanism removes the cookie from reaching the packaging process.

Vision-based computing has several applications in factory environments. Most manufacturing plants already have several CCTV cameras used to monitor activity, human safety and business security. The number of cameras on a production floor can number anywhere between 30 and 100 鈥� a number impossible for humans to continuously scan for aberrations. This is why these cameras are usually used after the fact, to investigate incidents.

However, the camera feeds can be analyzed in real time based on EHS guidelines and even used for automated risk audits. This means the investment already made in video monitoring can go the extra mile by identifying hazards in different work areas such as slippery floors, accumulation of materials, obstacles in pathways, missing or inadvertent obstructions around firefighting equipment, violation of safety norms by employees (such as not wearing hard hats or fall arrestors), unauthorized entry of personnel in restricted areas, and the entry and exit of vehicles in plants, warehouses, collection points and so on.

Not only can vision-based computing prevent issues or generate real-time alerts, but the data can also improve processes. For example, supervisors can immediately know how many vehicles are parked in a certain area, what type of vehicles are parked and for how long, the time taken to offload material from any vehicle鈥攅ach data point allowing the supervisor to take quick and accurate decisions.

Vision-based computing is here to stay. And the race to adopt it has just begun.

Author:

Siddaraju G,
Senior Principal Consultant,
Business Consulting Group,
乐播传媒视频

The post Enhancing product quality and plant safety with vision-based computing appeared first on 乐播传媒视频.

It is never easy to stay on top of the factors that determine product development. These factors range from gathering information on what customers used in the past, their levels of satisfaction with existing products, how they can be persuaded to change their minds with a change in packaging or display, the impact of word-of-mouth on decision-making, competitive action, regulatory requirements, the intellectual property landscape, patents, available technology and ingredients, recipe suppliers鈥he list is long and daunting. This is where digital platforms come into play, supporting the effort to capture knowledge and let it flow into new product development.

There is an additional level of complexity involved. CPG organizations need to address a variety of time frames to get new products before consumers. Reactive changes to existing products may be required in the short-term. Some changes, such as shifting to sustainable ingredients, may be required in the mid-term. And launching a fundamentally new product, replacing existing products, may be required in the long-term. Also, long term sustainability and growth of the business would require the CPG organization to move quickly, focusing on product IP creation and raising barriers to entry. The question hounding every CEO pursuing new product development is, 鈥淎m I executing innovation and NPD process using the correct systems and methodologies, so that I can have the right products available just when required, to be used as the winning ammunition on the battlefield of the market?鈥澨�

To answer that question with confidence, the CEO needs to have a digital platform that takes products from concept to launch. 乐播传媒视频鈥檚 PLM based Digital Platform fills the gap. The platform is enabled with stage-gate driven accelerators and templates. It integrates business functions in the organization such as engineering, testing, packaging, graphics, commercial, marketing and legal, and enables them to collaboratively contribute to the innovation process at various stages. The platform, through its interactive dashboard, provides visibility into portfolio, programs and projects, captures who is working on what activity of which project, and the stage at which each project is. What the digital platform delivers is a system of urgency, flagging delays, identifying bottlenecks, sensing what is happening in the market and bringing it to the notice of the organization, and enforcing collaboration.

The need for such a platform has been felt for long. But the urgency has grown in recent years as end-customers are going digital. They now have the tools to look for customized, personalized and improved products. In response, CPG organizations need to work faster, conceptualize products overnight, come up with prototypes, test them and get them into the market before competition does. The only way to do this effectively is with a PLM based digital platform, such as the one provided by 乐播传媒视频, specifically designed to manage new product development and innovation.

Author:

Debjit Banerjee
VP, Business Consulting,
乐播传媒视频

The post Faster, higher, stronger: How digital platforms can win the race for new products innovation appeared first on 乐播传媒视频.