Unleashing the Power of AI: Revolutionizing KYC Compliance in the Digital Age

Organizations grapple with the challenge of efficiently verifying customer identities in a siloed and expensive risk review process in the contemporary digital landscape. The Know Your Customer (KYC) verification, critical for complying with Anti-Money Laundering (AML) laws, varies across different regions and industries, presenting hurdles for even advanced businesses. Addressing these challenges head-on, PolarisEdge, a ground-breaking platform by EdgeVerve, integrates Artificial Intelligence (AI) technologies into the core of KYC operations, offering a transformative solution.

KYC Verification Processes

KYC procedures are a legal imperative for banks and financial institutions to understand their clientele. They encompass real-time identity verification, document authentication, watchlist screening, fraud detection, and multi-factor authentication. However, the intricacies of industry and government regulations and the rise in financial crimes contribute to a rigorous KYC process.

Some of the most common KYC verification processes are:

Challenges in KYC Compliance

The challenges associated with KYC compliance are manifold. With an annual expenditure of around $150 million, labor-intensive processes face continuous inefficiencies within processing centers. Real-time access to consolidated KYC data becomes elusive, leading to operational silos and communication breakdowns across departments.

Identity fraud remains a significant challenge, requiring organizations to recognize, prevent, and mitigate its fallout to protect themselves from ever-evolving cyber criminals. Collectively, these challenges result in a cumbersome and lengthy KYC verification process, ultimately impacting the customer experience.

The Role of Technology in Scaling KYC

Operating in a global, digital marketplace demands streamlined KYC processes for scalable operations. Digital transformation introduces challenges in scaling solutions beyond initial pilot projects. The hurdle becomes more pronounced in KYC processes where legacy systems hinder seamless data integration and interoperability.

PolarisEdge: Redefining KYC with AI:

PolarisEdge emerges as a pioneering AI-driven solution for KYC. It presents a comprehensive platform that leverages cutting-edge technologies to revolutionize customer onboarding and compliance procedures. The platform’s integration of AI addresses the complexity of KYC processes, offering a unified and efficient approach to identity verification.

The AI and ML Advantage:

AI and Machine Learning (ML) are transformative in automating verification, enhancing risk assessment, and fortifying security for efficient compliance. These technologies validate identities, detect fraud, allocate risk scores, and continuously monitor customer activity for suspicious behavior. AI’s role in Re-KYC (refreshing KYC for existing customers), enhanced due diligence, and improved customer satisfaction is integral to its transformative impact.

Automated Verification

AI automates customer identity verification by:

Improved Risk Assessment

AI enhances KYC risk assessment by:

Ongoing Monitoring

AI systems continuously screen customer activity and transactions to identify abnormal behavior indicating suspicious activities. AI analyzes vast data volumes to spot complex patterns that are difficult for humans to detect.


AI automates parts of the re-KYC process, making it more effective. Only customers facing major life events require manual re-verification, minimizing the workload on compliance teams.

Enhanced Due Diligence

AI improves due diligence by collating data from various sources to develop a complete risk profile. It scans sanctions lists, social media, news reports, court records, and other sources to detect potential “red flags” requiring further investigation.

With the advent of AI, the traditional KYC landscape undergoes a revolutionary transformation. PolarisEdge harnesses AI’s power to streamline and enhance KYC processes. However, implementing AI poses challenges, such as poor data preparation, bias, staff training, ensuring customer satisfaction, and navigating varying regulations.

Challenges in Adopting KYC AI

While AI brings transformative benefits, its adoption in KYC is not without challenges. Issues such as poor data preparation, algorithmic bias, employee proficiency, customer satisfaction, and evolving regulations require careful consideration.

Poor Data Preparation

AI software feeds on vast amounts of data. Thus, model training needs accurate and complete data volumes to generate a high accuracy score. However, as organizations need help to build a single source of truth, historical data tends to get scattered across branches.


KYC processes are highly susceptible to AI bias. This phenomenon is a result of wrong assumptions in the ML algorithms. In this case, an algorithm creates systemically prejudiced results.

Training of Staff

Inadequate employee proficiency is another challenge for intelligent KYC software. This understanding is critical as organizations democratize the workplace by introducing AI in KYC.

Customer Satisfaction

People are more familiar with human interaction. Thus, the transition to automation must be made while keeping customer expectations in mind.

Varying Regulations

Based on national standards, KYC regulations and anti-money laundering rules may change occasionally. Thus, organizations must check the legislative landscape before implementing AI within KYC processes.

AI as the Future of KYC Processes

AI has evolved from a distant dream to a transformative force, even in traditionally conservative areas. Rising compliance costs and the imperative for automation have paved the way for an AI revolution in KYC processes. Integrating powerful AI processing and automated onboarding benefits customer verification minimizes fraud rates, and enables faster, more intelligent banking decisions.


PolarisEdge stands at the forefront of this transformative wave, bridging silos and amplifying the value of enterprises’ digital core investments. By seamlessly integrating AI into KYC processes, the platform ensures regulatory compliance and enhances efficiency, accuracy, and security, ultimately shaping a more intelligent, customer-centric financial sector.

The Role of Process Excellence in AI-Driven Automation

Automation may be the offspring of technology, but its triumphant success, marked by significant returns on investment, is nurtured by the principles of process excellence. In the dynamic landscape of digital transformation, organizations grapple with complexities, tackling multiple variables simultaneously to gain a sustainable competitive advantage.

The pandemic spotlighted the vulnerabilities of sub-optimal processes, prompting organizations to reevaluate and acknowledge the pivotal role of large-scale automation in fortifying against future disruptions.

Fast forward to the post-pandemic era, organizations are no longer content with mere survival; they are vigorously pursuing growth through process enhancements and harnessing the potential of AI-driven automation.

Setting the Stage for AI-driven Automation

In the realm of AI-driven automation, data reigns supreme. The ability to analyze and optimize processes hinges on the availability of robust data. Process excellence becomes the linchpin, ensuring the success of automation initiatives.

But what kind of data is indispensable? Is it sufficient to uncover the duration people spend on a process, their accuracy rates, or the time customers wait for query resolution? The challenge goes beyond technology; it entails identifying which processes to automate, prioritizing them, and ensuring the organization is primed for the necessary changes at a human-centric level.

Process Excellence: A Game-Changing Force

Traditionally, automation initiatives faced challenges due to a lack of precedents and a scientific, data-backed approach. Fortunately, this nrrative has evolved.

Advancements in process identification, capture, documentation, and analysis have empowered business processes to an unprecedented degree. Understanding processes at multiple levels has accelerated business transformations, elevating automation readiness for organizations striving to achieve impeccable efficiencies.

At the core of workflow efficiency lies the establishment of consistent and lean processes. Minimizing process variations enhances output consistency. Process excellence aims to eliminate or minimize variations, streamline processes, and solidify Standard Operating Procedures (SOPs). Comprehensive understanding of each task and the detection of bottlenecks are imperative for achieving these goals.

The New Paradigm of Process Excellence    Read Whitepaper

Process Excellence: Supported by Two Pillars

Enterprises, often comprised of numerous processes, now have solutions to address the lack of comprehensive process data—thanks to Process Discovery and Process Mining.

Process Discovery provides granular-level data by capturing user keystrokes and tracing the entire workflow, mimicking the entire process. On the other hand, Process Mining offers a broader understanding, akin to a twenty-thousand feet view, by mapping the entire workflow based on translated data.

The symbiotic relationship between Process Discovery and Process Mining unlocks unprecedented value, making them invaluable tools in the corporate arsenal.

AI-Driven Automation: A Convergence of Technologies

The distinctive role of process excellence in AI-driven automation lies in its convergence of practices, disciplines, and technologies. It delves into the study of how human teams interact with digital systems, forming the core of business management and strategies. This process extends to organization-wide transformations by upskilling teams to optimize automation, complemented by advanced applications like Machine Learning (ML), Robotic Process Automation (RPA), and AI.

Each technology plays a part, but the real power lies in the synergy. For instance, RPA-optimized organizations can achieve only 30% of their automation goals, leaving the remaining 70% to intelligent automation. Expertly adopted, configured, and managed, AI-driven automation opens the door to further automation capabilities, automating even complex processes requiring human judgment.

Leveraging Process Excellence for Success in AI-Driven Automation

Process excellence deploys a four-pronged strategy to ensure the successful implementation of AI-driven automation.

A global beverage company saved over $1 Million and 65,000 person-hours with AssistEdge Discover    Read Case Study

Implementing Process Excellence for AI-Driven Automation

While the specifics of implementing process excellence may vary for each enterprise, certain common steps guide the way.

In conclusion, the marriage of process excellence and AI-driven automation is a potent force for organizations seeking to thrive in the ever-evolving tech-driven landscape. By strategically aligning processes, leveraging data insights, and embracing advanced technologies, businesses can unlock unparalleled efficiencies and position themselves for sustained growth.

Ready to revolutionize your automation game? Dive into the future of streamlined processes with AssistEdge Discover. Contact us to know more.

Walmart Luminate and why suppliers need to act fast

From early 2024, Walmart, the world’s largest retailer, will cease support for Retail Links’ Decisions Support Systems (DSS) and switch to Walmart Luminate, an expansive new suite of data products for its U.S. suppliers. Walmart Luminate offers its suppliers access to rich, aggregated, and more granular consumer insights compared to Retail Link.

The next-generation data suite, Walmart Luminate goes beyond sales and performance data, providing insights into both store and online sales through its three modules: Shopper Behavior, Customer Perception, and Channel Performance.

For CPG and manufacturing companies selling through Walmart (acting as suppliers), this data will be crucial for making critical business decisions, owing to the substantial retail sales that Walmart generates for them. Walmart Luminate is positioned to be the single source of truth for its suppliers, bringing a host of actionable insights – provided, you are prepared to integrate and infuse that data into your systems.

To successfully switch over to Walmart Luminate, you would need a mechanism in place that can onboard and ingest the Walmart Luminate data at speed while ensuring all your existing systems, applications, or processes that might be tuned to DSS data feeds function uninterruptedly.

However, this would require your teams to put in a lot more work, rebuilding systems and data pipelines in line with Walmart Luminate data and have a new level of expertise to derive custom KPIs for your specific organizational needs. And they’d need to continually do so because the Walmart Luminate data suite will be constantly evolving.

Opportunities – and a challenge for the unprepared

Walmart Luminate comes with a Basic plan and a Charter plan. In order to democratize data and insights, the Basic plan is being offered free of cost to Walmart suppliers.

The Charter plan, a paid subscription, gives suppliers full access to the entire Walmart Luminate suite. For instance, the store and e-commerce sales data are available under both plans, but the omni-sales with channel breakout or data feeds are available only to Charter plan subscribers.

How can Infosys TradeEdge help?

Infosys TradeEdge, our intelligent supply chain platform, is unique in that it has a proven track record and over a decade of relevant expertise, assisting 35+ leading Consumer Packaged Goods (CPG) and manufacturing companies to channel data and visibility. TradeEdge has assisted prominent brands, including a Fortune 50 CPG company, swiftly onboard Walmart Luminate and deliver custom KPIs to maximize their ROI.

TradeEdge provides a pre-built, out-of-the-box adapter with pre-configured transformations, to onboard Walmart Luminate data in a matter of days instead of months, and hit the ground running. The platform’s AI-ML-powered harmonization capabilities standardize and transform the data into your organizational hierarchies, delivering consumption-ready data instantly.

Regardless of the channels, files, or formats, TradeEdge data transformation capabilities guarantee continuous data pipelines for your internal systems.

The commitment doesn’t stop there. Our team of functional experts will tackle all incremental or new data sets Walmart Luminate comes up with and ensure this data reaches organizational systems seamlessly, without hiccups.

Whether you opt for the Basic plan or the Charter plan, TradeEdge is here to assist you with Walmart Luminate and help you maximize the value of your investments.

Over to you

Like all modern businesses, yours also relies on how well you can leverage data analytics. With Walmart Luminate, you will have a substantial amount of data at your disposal. Your success will depend on how effectively you can use that data in a timely manner.

Infosys TradeEdge offers solutions to CPG and manufacturing companies, enabling them to onboard Walmart Luminate and reduce the time required, from months to days. TradeEdge gives you access to harmonized, consumption-ready data and delivers custom KPIs aligned with your business processes and goals.

Have questions? We’ll be happy to answer them.

Unlock the full potential of Walmart Luminate at speed with Infosys TradeEdge

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Disclaimer – EdgeVerve acknowledges the proprietary rights of other companies to the trademarks, product names and such other intellectual property rights mentioned in this document. EdgeVerve does not claim any right over such third party trademark and/or an association with other companies/rightholders.

How to extract insights from data – 3 industry success stories

We’ve all heard “find more data!” at some point during our week, or our day, depending on your field of work. But what is data, why do we need so much of it and what do we do with all this data we keep seeking?

There are companies like that collect 11,000 terabytes of data from one million people every day to provide them personalized experience according to the Insurance Business report. While one cannot expect the same magnitude from other companies, there is an active hunt for data to bring about data driven actions in businesses today.

Data insights come from processing your data, collecting it, analyzing it, and then acting on the data based on the requirement from your client/ that of your company. Data insights can be achieved through effective analysis strategies that help companies to draw profits, observe patterns, and streamline efforts.

Data the New Norm: Embracing a Culture of Data-Driven Innovation    Read Blog

3 core components of data insights

Data – data exists in an unstructured way which may come from a database in the form of text and numbers. It exists so someone can investigate it and draw meaning out of it. Data remains objective information that is available to the readers. Data insights are more focused on the hypothesis one’s going in with. It’s the result of looking at multiple data with a set intent and then drawing conclusions that will aid in some way or another.

Analytics – with the right strategy and tools, one can go into processing data that is laid out for them. The data gets its scope from the potential it holds for analysis. With the help of data insight tools, one can draw significantly meaningful information from dry blocks of data.

Insights – Once you have processed the data, now there is room to send targeted messages, streamline efforts and learn what the data holds. You have access to actionable insights if your approach was done right, and this is the most important objective – gain meaningful insights that give you an actionable outcome.

Some statistics around data and insights

74% of companies want to be “data-driven” but only 31% actually are according to a study by Forbes. For every 100 companies where actions are data driven, 23 are struggling to be data driven in reality. Being data driven takes skill and effort that isn’t popular. Data driven organizations can recognize relevant data, draw meaningful information and use this smartly in their area of expertise. What’s also to be noted is what kind of data to seek. This will take some time but understanding what the most relevant data sources for you are will help you. Knowing where to look, aids in finding solutions faster.

Role of AI in extracting insights from your documents

The reason AI exists to process data is that it helps people focus on the result of the process rather than the enormity of the task itself. Using machine learning helps pull in a large scale of data and process them to get results based on all documents that are relevant to the objective. Bits and pieces of information can be difficult to pick up and pull apart when there is an overwhelming amount of data for people, bringing technology into it helps minimize the room for error while giving more scope for insights and messaging.

AI also goes through data very quickly. What would take a large group of subject experts a couple of days to list out, could be done in a matter of minutes through a smart tool. It could go through large chunks of data daily to provide meaningful information with no zero time and high accuracy.

Cutting through the noise – How generative AI will change the IDP landscape    Read Blog

Why extracting insights from data is important for enterprises

Enterprises that work with a data-driven approach are often carrying multiple advantages. They’re looking at predictable outcomes and seeking patterns that will help increase the longevity of their business. There are large chunks of data that remain available. There is an overwhelming amount of it stored in the cloud and often, it gets too overwhelming to even bother with it at all. This is where AI comes in and sorts through stacks of data to provide answers that are simple and workable.

For enterprises, gaining these insights after processing relevant data increases their chance of profile while also helping them analyze their present numbers. Some businesses must process data for their bread and butter, while some others bank on data to show them what’s missing or where to look. Enterprises and data go hand in hand and the sooner there’s insights being driven from data, the quicker one can benefit from data.

3 enterprise success stories of turning data into insights

Case Study #1

Our client, one of the largest telecommunications companies in the world used XtractEdge to automate their contract review process where in we helped identify, extract, and manage data from over 650,000+ historic commercial tower lease contracts with many amendments, addendums and other relevant documents. Text Analysis and computer vision-based methods were used to extract contract clauses quicker with maximum accuracy.

With our solution, the client’s contract team was able to claim surplus expenditures and impose penalties on defaulting vendors. We made this possible by leveraging insights such as contract terms and clause deviations plus favorable clauses. This helped our client achieve $20 million in savings annually.

Read Case Study

Case Study #2

Our client is a hi-tech manufacturer. Their legal team had to go through the processing of historical customer contracts. This meant manually reading and analyzing a random sample of key contracts to generate a representative assessment of potential risks / opportunities. This is where they brought us in. XtractEdge helped process the historical load of over 30K customer contracts in nearly a week’s time. Post the set up of the product, we extracted 50 intents and 125 entities from 4 different categories of contracts with carrying complexities.

XtractEdge has successfully accelerated the contracts processing for our client, boosted 70% potential workforce improvement, reduced the report generation time from weeks to a matter of days and more.

Read Case Study

Case Study #3

A popular US based bank leveraged the benefits of XtractEdge Platform and its computer vision capability to accelerate loan processing for PPP SBA loans with high accuracy. We took up the challenge and helped them serve many impacted customers by getting them access to PPP SBA loans. We also aided with accelerating loan processing, while adhering to stringent risk and audit requirements while also helping them achieve data accuracy of around 90%.

Read Case Study

Key takeaways

Data will continue to expand every minute but the weight of it? It needn’t weigh you down. With powerful AI tools, like XtractEdge, we can process data documents and provide insights and solutions to our clients. We reduce the average time these tasks take and bring you smarter set ups that will continue to enable your enterprise as you grow.

It’s important to understand how you can benefit from AI. When it comes to managing and processing data, you can lean on AI. Let it draw you observations while you can have your human resource focus on what it means and what can be down with these observations. A careful balance of AI and teamwork can help enterprises achieve what they want quicker and more accurately. AI ensures accuracy and better time saving while human resources can bring about results based on the data. With insights from your data, you can enjoy dynamic decision making which is backed by numbers and facts. Start your data journey with XtractEdge and watch your business take the way the data points at.

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FMCG 2024: Building Growth Pipeline with Data & Insights

Over the past few decades, we are witnessing a significant shift in market trends that have reshaped the fast-moving consumer goods (FMCG) sector. Prior to digitalization, accessing consumers across the vast expanse of our country relied heavily on robust infrastructure, including roads and connectivity. Infrastructure was the bedrock upon which any industry’s growth depended. Now, as we look to the present, the proliferation of digital technologies, widespread internet access, and the rise of smartphones have revolutionized consumer behavior, and the way businesses operate. These advancements have paved the way for brands to engage with consumers on a whole new level.

So today, we delve into these transformative trends, exploring how they impact businesses and emphasizing the pivotal role of data in navigating this dynamic environment.

Major Trends in FMCG Industry

One significant transformation has been the diversification of distribution channels. The traditional or general trade, along with a thriving wholesale ecosystem, dominated the retail landscape. However, in the early 2000s, we witnessed the emergence of organized retail chains, marking the era of modern trade. Today, e-commerce platforms stormed onto the scene, offering consumers the convenience of online shopping. But the story doesn’t end there.

The COVID-19 pandemic disrupted the norm, significantly impacting out-of-home consumption. Organized efforts and a newfound focus on understanding consumers’ demands have given rise to more structured approaches in catering to this channel. Moreover, the pandemic accelerated the growth of direct-to-consumer (D2C) brands. Startups and established players alike embraced this channel, offering targeted products and personalized experiences to consumers.

Digitization has been another game-changer. Real-time data access has replaced the days of waiting for monthly reports to gauge market trends. Consumers have rapidly adopted digital formats, seeking information, discerning truth, and demanding products more quickly. Quick commerce platforms have gained prominence, promising near-instant deliveries, reshaping how consumers shop. Furthermore, the pandemic heightened health and wellness consciousness, driving consumers toward cleaner, sustainable products with fewer ingredients.

This changing landscape presents both opportunities and challenges for brands and retailers. There’s an explosion of brands vying for limited shelf space, driving a fierce competition across channels. Social commerce and live commerce are emerging trends, connecting brands directly with consumers on social media platforms. Sustainability has become a central theme, with consumers favoring eco-friendly choices.

As we journey through this blog, we’ll explore these trends in more detail, providing insights into how brands can adapt and thrive in this ever-evolving supply chain industry. But one thing is clear: data will be the guiding force, helping businesses unlock the power to propel sales and distribution growth.

How FMCG brands are achieving complete visibility?

To stay aligned with the evolving landscape of the FMCG industry in India, brands must focus on several key strategies and priorities. Let’s delve into these critical aspects:

Precision Distribution Strategies

Given the disaggregated nature of the Indian retail ecosystem, FMCG executives must craft precise distribution strategies. This entails a deep understanding of regional demand variations, supply chain efficiencies, and the dynamics of General Trade. Implementing technology-driven solutions, such as route optimization and demand forecasting, can significantly enhance distribution efficiency. Moreover, collaborating with local distributors who possess insights into specific regions can be invaluable.

SKU Rationalization

With the proliferation of Brands and SKUs, it’s crucial for executives to undertake rigorous SKU rationalization. Brands should regularly assess the performance of their product portfolio, eliminating underperforming SKUs and focusing on high-demand items. This not only streamlines production and supply chain management but also ensures that consumers have access to the most relevant products. Data analytics can aid in identifying SKU performance trends and guiding rationalization efforts.

Tailored Marketing and Product Offerings

Acknowledging income disparity and cultural diversity, FMCG brands are adopting a tailored approach to marketing and product development. Executives should invest in consumer research to understand the unique preferences and needs of different demographics and regions. Crafting localized marketing campaigns and product variants can help capture diverse market segments effectively. Building a portfolio that caters to both premium and budget-conscious consumers is a strategic move.

Technology Integration

To ensure product availability and meet consumer expectations, executives must embrace technology integration across the supply chain. Real-time data analytics, inventory management systems, and order fulfillment solutions are essential. Leveraging e-commerce platforms to complement offline distribution can bridge the gap between demand and supply. Moreover, adopting emerging technologies like blockchain for supply chain transparency can enhance consumer trust.

Generating Actionable Insights from Channel Data

In the ever-evolving landscape of FMCG brands operating in a multi-channel environment, ensuring consumers receive the right product at the right time stands as a pivotal challenge. Thus, it becomes imperative for industry leaders to harness the power of actionable insights.

Real-time Data Acquisition and Integration

FMCG brands must invest in cutting-edge technology and systems that facilitate real-time data acquisition from a spectrum of channels, encompassing General Trade, Modern Trade, and E-commerce. This data should encompass a comprehensive range, including sales figures, inventory levels, and consumer behavior. The integration of this multifaceted data holds paramount importance. The ability to have a unified, holistic view of the supply chain and sales data across all channels empowers brands to make swift, well-informed decisions.

Demand Forecasting and Inventory Management

Leveraging advanced analytics and machine learning algorithms, brands can elevate their demand forecasting capabilities to unprecedented levels of accuracy. This entails a meticulous examination of historical sales data, seasonal trends, and external influencers. For agile inventory management, systems must possess the flexibility to adapt stock levels in response to the ebb and flow of demand patterns. This dynamic approach ensures that products are consistently available in alignment with consumer preferences.

Collaboration with Channel Partners

Fostering robust relationships with distributors, retailers, and e-commerce collaborators emerges as a cornerstone of success. Brands should actively encourage their partners to partake in data sharing, encompassing sales data, inventory status, and invaluable consumer feedback. This collaborative synergy with channel partners paves the way for optimizing product availability and mitigating the risks of stockouts or overstocking.

Agile Supply Chain

The foundation of an agile supply chain lies in the brand’s ability to respond nimbly to shifts in demand. This necessitates the development of adaptable production capabilities and streamlined logistics systems. Data-driven decision-making assumes a pivotal role in ensuring that the supply chain can promptly adapt to evolving consumer preferences.

Personalization and Product Customization

Recognizing the prevailing trend toward personalization, brands should explore innovative avenues for offering tailor-made products or customized packaging. This approach caters precisely to individual consumer needs and preferences. Advanced analytics can prove instrumental in identifying distinct consumer segments with unique requirements, allowing brands to tailor their offerings accordingly.

Technology and Analytics

The adoption of technology solutions like IoT (Internet of Things) for real-time inventory tracking and the monitoring of consumer behavior in physical stores represents a strategic move. Advanced analytics, encompassing predictive and prescriptive models, offer insights into evolving consumer preferences and emerging market trends, thereby empowering brands to make data-driven decisions.

Consumer Engagement and Feedback

Active engagement with consumers across a multitude of channels, spanning social media platforms, surveys, and feedback mechanisms, constitutes a vital strategy. These direct interactions yield valuable insights into the ever-shifting landscape of consumer attitudes and preferences.

Continuous Improvement

FMCG brands should treat this entire process as an unceasing cycle of improvement. Regular review and refinement of strategies, guided by data and feedback, are essential to remaining aligned with the ever-evolving needs and expectations of consumers.

Metrics to consider while driving growth

Revenue Growth and Customer Satisfaction: At its core, the success of any business, including Consumer Packaged Goods (CPG) companies, relies on increasing revenue. This growth is closely tied to consumers purchasing and using products. To achieve this, brands must ensure their products are readily available and easily accessible to consumers, a crucial aspect of satisfying customers.

Salesforce Efficiency and Digital Tools: Enhancing Salesforce Efficiency (SFE) is crucial for revenue growth. Digital tools, such as Sales Force Automation (SFA) systems, play a pivotal role. They assist sales teams in planning efficient routes, covering outlets effectively, and promoting relevant product SKUs. Additionally, emerging tools like artificial intelligence (AI) and gamification motivate and empower salespeople.

On-Time In-Fulfill Rate (OTIF): OTIF can serve as a key performance indicator (KPI) for monitoring product availability. It measures the percentage of orders fulfilled on time and in full. A high OTIF rate indicates a high level of product availability, positively influencing sales.

Justifying Costs: To determine ROI, it’s essential to assess whether the revenue generated justifies the incurred costs. This involves analyzing whether enablement, such as deploying cloud-based systems or other digital solutions, leads to an increase in top-line sales and profitability.

Cost-Benefit Analysis: Brands should conduct a thorough cost-benefit analysis, considering various deployment aspects. The goal is to ensure that benefits, such as increased sales and cost savings, outweigh the initial investment.

TradeEdge enabling companies to navigate their next

Focusing on data, encompassing data infrastructure, harmonization, insight generation, and the transition from insights to tangible benefits. This journey into the world of data-driven decision-making aligns with our extensive experience in the CPG sector, particularly in the realm of secondary sales visibility.

TradeEdge leads to what it termed as the “Mighty Enterprise Network,” a dynamic framework that interconnects various components within the CPG value chain. In this network, brands or companies serve as the central orchestrators, bringing together retailers, distributors, financial institutions, third-party manufacturers, wholesalers, and logistics partners.

The key advocacy here revolves around establishing a fully connected ecosystem, fostering seamless data sharing among all stakeholders. This interconnectedness ultimately leads to the ability to sense demand in real time, a crucial capability in today’s rapidly evolving market.

Companies are now gaining the capacity to monitor sales almost instantaneously, using this data to forecast demand accurately and streamline replenishment and fulfillment processes, striving to achieve the goal of 24/7 product availability across multiple channels.

Forecasting has historically presented a significant challenge for CPG companies due to the vast array of SKUs and the impact of both known and unforeseen events on demand. To enhance forecast accuracy, the focus lies on implementing effective forecasting mechanisms while ensuring that high-quality, comprehensive data feeds these mechanisms.

Furthermore, addressing the demand based on forecasts necessitates automated tools like suggested ordering systems. These tools consider factors such as the customer base’s diversity and the extensive SKU portfolio, enabling efficient routing and automated replenishment, both critical elements for successful operations.

In addition, we’ve considered the vital role of empowering field sales representatives. These professionals are driven to succeed, striving to maximize sales and compete effectively in the marketplace. Today, they have access to powerful tools like Salesforce and automation solutions that provide actionable insights at the store level. This includes access to historical order data, insights into similar stores’ ordering patterns, and optimized route planning, all aimed at enhancing their effectiveness.

In conclusion, our journey through the world of data and technology underscores the importance of a connected ecosystem and data-driven decision-making in the CPG sector. Achieving real-time demand sensing, accurate forecasting, and streamlined operations is crucial for meeting consumer expectations and ensuring product availability across diverse channels. Contact us to learn more about how TradeEdge can help your enterprise.

Navigating Hurdles for Optimal Scaling and Automation ROI Maximization

The return on investment (ROI) on automation is something that all senior stakeholders keep a close eye on. Hardly surprising, given that automation holds a lot of promise.

An intelligent, AI-led automation solution can help enterprises take automation to a completely different level where speed, efficiency, and accuracy are at a never-before highs. That ushers in new capabilities and accelerates the business transformation of the organization.

However, like all major initiatives, automation brings challenges. For example, organizations relying on yesterday’s solutions battle with broken processes or sub-optimal automation. The ROI of siloed implementation will be nowhere close to what you can achieve with an optimized, connected process automation solution.

We discuss here the six principal challenges to efficient automation.

Facilitating wider automation coverage

Unlike a lot of other initiatives, ideas for automation need to come more from within your organization than outside. Being hands-on subject matter experts, your own teams are most suited to spot processes that could be great candidates for automation.

However, almost all enterprises are handicapped when it comes to tapping automation opportunity ideas from across the enterprise. Most ideas come only from a handful of people, and not all these people have full, on-ground experience with the processes they talk about.

So you want a system that can cast a wide net, include everyone, and offer everyone an equal chance to come up with automation suggestions. But the principal challenge with automation ideas is about visibility. How will you track the idea? What would be a good way of knowing if the idea has been reviewed at the right levels? When the senior stakeholders want a quick overview, where will all the information be available?

In absence of proven systems, automation opportunities will likely get a much lower priority than they deserve or – even worse – drop off the automation funnel.

What you really need: A centralized repository under a single platform is the only way to address all this, and more.

Ideally, your automation solution should have this unified, systematized repository that accepts, channels, and helps track ideas for automation from across the enterprise.

Your team members will feed their ideas for automation, including as many details as possible like addressable audience and importance of the process.

The senior team-members can watch where the idea is currently and whether it needs to be fast-tracked. Based on the reviews, optimized and important processes get a priority, with a clear tracking system. You can be sure neither ideas nor opportunities will go unrealized or even unrecorded.

Selecting the right automation approach and processes

Is your approach to automation entirely data-driven or are there gaps that are being filled with ad hoc responses? Do you have robust systems in place to accurately identify and prioritize processes for automation? Can you be always confident that you will automate only the most efficient processes?

Without automation maturity, enterprises will not make any headway in their journey to business transformation. Among other things, you always have the risk of automating an inefficient variation of the process while ignoring the most optimized version.

What you really need: Basing decisions on random observations instead of insights based on data does more harm than good. At enterprise level, you cannot afford not being data-driven.

After all, there could be literally countless variations to each process. Your automation platform, therefore, should be able to overcome the challenge by first generating data-backed insights. The solution should be able to understand which variation is the most efficient. It should be able to optimize processes before they are automated.

After all, automation delivers stronger ROI only when the processes have been optimized for efficiency and prioritized for automation.

Planning and estimating resources and activities

Ok, so now you have identified and prioritized all the processes you’d want to automate. The next logical step is planning and estimating.

The challenge here is unusual. Productivity and cost-effective efficiency are your goals in automation. If you work with a conservative estimate, there will be a shortfall leading to broken or dysfunctional processes. Planning for bots with a considerable margin would upset your budget and your ROI will start sinking.

Also, if you are not looking into scaling automation, you’re severely restricting the capabilities and reach of automation bots. When you don’t scale, your automation costs rise without associated benefits. Your per bot pricing also is higher because you haven’t fully used their capacities.

What you really need: Estimating is not just about costs. Automation planning includes estimating, procuring, setting up, and testing the bots, and triggering re-trials whenever required. You want to know which departments or business units will get a priority, because most of the planning and even the ROI will depend upon these.

You need a solution that will help you with scaling automation bots that will work in tandem with changing scenarios. In other words, upscale when there are peak loads and downscale when requirements are modest.

So basically, you need the automation partner to be able to tell you how many licenses will be required. And don’t forget that deployment method will matter too – will you deploy it on-premises or on cloud or through a combination of the two.

How this US-based healthcare insurer achieved an amazing ROI from automation is truly an illustrative study of what powerful solutions can do.

Leveraging existing documents for insights

Selecting the right processes and building a centralized pool of automation ideas form a substantial portion of all the automation challenges. But for organizations that are targeting digital transformation, the story is still incomplete.

Overlooking how your systems can leverage existing documents is a common mistake. It holds back a lot of benefits that might otherwise be possible. For instance, customer-facing teams would not be empowered unless there is full digital support from automation.

In particular, the challenge lies in extracting insights locked within processes and associated documents. How would your teams generate contextual insights in real-time when there are lots of blind spots?

What you really need: Your customer teams will agree how critical it is to have solutions that will extract the correct information even while your teams are holding a conversation with clients. It would prevent turning a customer with some questions into an exasperated customer who’d probably take a long time to cool down.

More than just saving time and energy for your teams, an intelligent automation solution fully empowers your teams. Even unstructured documents can be “understood” by such solutions. Ask for a solution that will reinforce your team’s ability to pull out the correct documents effectively, contextually, and swiftly. This will ensure your support teams serve your customers more efficiently.

Reining in timelines and costs

There are few initiatives where ‘time is money’ speaks as loudly as it does with automation. This is primarily because of your human teams’ involvement.

Deploying automation and bots doesn’t mean everything will run picture-perfect. Testing and understanding the test results is another challenge you’ll encounter.

You deploy human teams to understand what to automate, and then deploy human teams to test automation at every stage. That’s a bit of a paradox, because when not done right, it will lead to delays and low accuracy. And both will lead to a longer time to market and increased costs – both of which are the factors you wanted to eliminate with automation in the first place.

What you really need: The simple answer is: use automation to test your automation. Insist for a solution that will test and conduct retrials.

This is far more critical than it might first appear. Human-led testing can be slow and unreliable. But not so with automation technology. An expert solution will hasten testing, help automate faster, and speed up migration in a smarter way.

Managing your bot operations

End-to-end management of bots is never easy. Then there are infrastructure challenges too. Your automation solution could fall short in managing end-to-end bot operations. Add to it the challenges you’ll encounter during upgrades or migration, and things complicate further.

What’s more, you’ll need to factor in a considerable number of variables. For instance, your business scenario may have changed. How does that impact your processes? What kind of changes will that mean for your bots?

What you really need: Think of a centralized cockpit with a firm handshake with your Centre of Excellence (CoE) for automation.

This should be capable of automating every step in your automation journey. From process discovery to validation and monitoring, your solution needs to be self-reliant. The solution should know that your human teams and bots aren’t working independent of each other.

You want the solution to seamlessly integrate the workflow between your human workers and your digital workers and AI. We’d urge you to look at the success story of this global telecom company that improved its agent productivity by 20% and completely transformed customer experience.

How you can overcome these challenges

A surprising number of enterprises have unknowingly taken what has now turned out to be an ad hoc approach to automation. While such an approach is easier to take off, it produces very limited results. The adoption becomes myopic and expensive.

An intelligent automation platform will overcome challenges and produce lasting results with a strong ROI. AssistEdge 20.0 is an AI-first automation platform that has proven capabilities that are both deep and far-reaching. Our clients have benefitted from how AssistEdge 20.0 scales their automation, increases the scope of automation, and ultimately augments the productivity of your hybrid workforce.

Why not drop us a line to learn how you should approach automation to take your business transformation to the next level? We’d be delighted to speak to you!