Month: March 2022

The explosion in disposable income among the middle class has converted emerging markets into a goldmine of business opportunities for many global brands. However, more opportunity translates into more competition and other challenges at a micro-level, one of them being the lack of supply chain visibility.

What is Supply Chain Visibility, and Why is it Important?

Visibility into the existing supply chain system offers an end-to-end real-time view of the company’s logistics, inventory, warehouse, and distribution networks.

The traditional model of retail distribution in emerging markets, not initially disrupted by new-age technology, is increasingly facing competition from tech-driven direct-to-consumer models. In addition, online-only stores are fiercely competing with the traditional supply chain network to align with changing customer preferences. Hence, survival has become challenging for businesses that were too slow to predict and adapt to the change.

This is why real-time supply chain visibility is so important.

In this article, we will explore the various supply chain network complexities persisting in emerging markets regarding the beverage industry. Also, we will identify different ways supply chain visibility can help address those challenges.

How Absence of Supply Chain Visibility Adversely Affects Production Planning & Growth

The global beverage market, both alcoholic and non-alcoholic, is estimated to reach USD 1.8 trillion by 2024. Since 2017 the Asia Pacific has gradually emerged as one of the largest global markets for spirits, closely followed by Brazil, the Middle East, and North Africa. Experts believe the next leg of growth for beverage companies will come from emerging markets.

However, the changing customer preferences, idiosyncrasies of local culture and practices, disconnected logistics, and absence of supply chain visibility give rise to the new set of challenges that global beverage companies were unprepared for.

Here, we will touch on the challenges in beverage distribution:

No collaboration; poor production planning

Most business is done through personal relationships and back-of-the-envelope calculations in an emerging market. Hence, most distributors fail to provide real-time data on their sales/stocks. When many breweries/factories and multiple distributors were thrown in the mix, the existing problems for businesses compounded. And new challenges cropped up. Poor supply chain visibility makes timely and consistent viewing of inventory and secondary sales information a challenging task for the entire supply chain. Hence, making informed decisions is impossible, resulting in sub-optimal replenishments, stock-outs, and inefficient production planning.

Low tech maturity; poor sales visibility

Low tech maturity in emerging markets is a major concern for global companies. The paper-pen approach to conducting day-to-day business, emails for closures, and spreadsheets for reports create a huge technological gap between the center and its subsidiaries.

Poor supply chain visibility, absence of structured mechanisms for collecting and processing data, and manual processes present contaminated data, poor sales visibility, and incorrect future predictions.

Lack of data; no wider market reach

Developing markets mostly have distributors concentrated only in urban areas. Poor logistics and poor supply chain visibility in rural markets restrict wider market reach for beverage companies. Hence, proper planning of promotions and discounts and communicating the same to all vendors across the market remain a distant dream.

In the absence of a robust platform for small retailers to proactively place orders and distributors to communicate effectively with their customers, the overall market reach for any beverage company will automatically shrink.

Lack of consumer data; poor effective promotion

In-store purchases form nearly 70% of all buying decisions, and most are done on an impulse by the consumer. Hence, a traditional distributor-driven retail model with little or no influence on the consumers’ buying decisions rarely provides valid, actionable data.

Promotion planning and execution remain ineffective without considering stock availability, customer purchase pattern, and other related insights. Hence, possibilities of cross-sell/up-sell remain outside the planning process.

How Supply Chain Visibility is the Best Way Out?

Only technology can bring manufacturers, distributors, retailers, suppliers, and other stakeholders on the same platform. This will not only help the concerned parties gain more visibility into the supply chain network, but it will also help them make crucial data-driven decisions and forecast future sales effectively.

This vision is achievable following a collaborative and inclusive ecosystem connecting every stakeholder across the supply chain. Let’s elucidate:

Distributor collaboration using data

A collaborative data exchange platform connecting all distributors enables easy data exchange between parties. However, one should consider the following points while setting up a logistics visibility platform:

Retailer outreach via value creation

Building an all-inclusive distributor-retailer connected platform translates store sales data into insight-driven refills. This creates an ecosystem where retailers receive best-in-class distribution services.

To ensure the complete success of this platform, the following features should be considered:

The Best Way Forward

Getting your supply chain ecosystem digitized will increase the supply chain and distribution ecosystem’s visibility and help you make profitable decisions at every step. TradeEdge is user-friendly and easily matches up to varying requisites of businesses.

Benefits of Supply Chain Visibility Software:

Conclusion

Data is paramount in gaining a competitive advantage in the emerging market. However, a lack of supply chain visibility and low-tech maturity impair businesses from capturing insights and making data-driven decisions. Hence, increased visibility via AI-based supply chain management can help businesses easily optimize production, improve distribution, and increase sales.

The consequences of poor demand planning and management failures have risen with shrinking product life cycles. As a result, companies are implementing a new level of demand management technology to boost profit margins by better accounting for supply chain variability.

According to research, 50% of businesses claim it takes more than a month to detect changes in consumer demand. In today’s fast-paced business world, this is unacceptable. Improved demand sensing and shaping procedures offer considerable opportunities for organizations to increase top-line sales, profit margins, and inventory levels.

Demand Planning Vs. Forecasting

Demand planning is the technique of precisely forecasting and ordering items to have the right number of sales at any given time. In addition to preventing out-of-stock situations, accurate demand planning can help businesses develop beyond their wildest dreams.

Demand forecasting is an essential component of a trustworthy plan. The technique of demand planning, which considers previous results, considers external and internal changes, and puts out what can be anticipated based on the parameters, is the reason it can reliably predict the future.

Benefits of Demand Planning

What Hinders Demand Planning for Businesses

Demand planning relies heavily on data, the absence of which can hinder the entire planning and forecasting process. However, data is available everywhere but in an unstructured format, which, when processed properly, can help businesses with insightful decision-making and stay ahead in the competition.

Data-related challenges that hinder informed decision-making:

Data-Related Challenges Impact Businesses Significantly

Data-related challenges not only hinder proper demand planning and efficient data-driven decision-making, but also impact businesses negatively. Lack of structured data prevents stakeholders from measuring sales vs. targets needed for efficient demand planning and forecasting. From partner onboarding to higher Non-productive inventory, among data-related challenges significantly impact businesses.

Let’s elucidate with a case study on one of EdgeVerve’s clients – a multi-billion-dollar consumer goods enterprise.

The client was looking to overcome the above-mentioned challenges, strengthen the supply chain and drive sales efficiencies through a Demand Sensing solution.

The client was looking for the following features:

How TradeEdge Market Connect Helped?

TradeEdge’s cloud-based, low-cost, pay-as-you-go solution helped the client spread their risks, enabled a quicker go-to-market, and met business goals faster than earlier. TradeEdge Market Connect is based on an end-to-end partnership model that caters to delivering, consulting, product implementing, and managing various services for the client.

With TradeEdge Market Connect, the client has seen a 4-10% improvement in sales and has automated 90% of efforts spent on data acquisition and harmonization. Near real-time visibility into secondary sales and inventory data helped the client with better demand planning and forecasting.

Enterprises with a global footprint have to work closely with local distributors and suppliers. However, the complex supply chain network and technology immaturity give rise to multiple issues; hence bringing all parties on the same page became a major roadblock. Also, the tech maturity of one distributor vastly differs from the other.

The absence of supply chain visibility, poor consistency, and quality in data transfer reflect inaccurate secondary sales numbers and inventory situations for businesses.

Role of Data in Supply Chain Visibility

Any informed business decision is quite impossible in the absence of relevant data.

Hence, when we speak about increasing supply chain visibility, we imply the availability of granular data carrying information about the supply chain network. Data in the shape of numbers, graphs, emails, invoices, and others capture subtle nuances in the process, challenges, and missed opportunities. This This information is scattered across different documents, PDFs, emails, or so carry valuable insights, which, when analyzed, can help in better decision making. Furthermore, since the data reflects an accurate picture of the entire process, one can easily understand what is happening against what is perceived to be happening.

Let’s walk through the challenges enterprises face when working with a global supply chain.

Issues with Poor Supply Chain Visibility

According to market statistics, nearly 65% of procurement leaders have limited visibility beyond tier 1 suppliers. Poor or limited visibility is a significant hindrance when businesses need real-time data to strategize, forecast, and implement plans. Approximately 76% of CFOs agree that it is impossible to meet business objectives without knowing the two versions of the same truth.

Poor visibility makes data capturing a real challenge. Likewise, the supply chain network complexities remain hidden from sight in the absence of accurate data. Both are directly and indirectly connected to one another.

Below are a few challenges that arise from poor visibility of your global supply chain network.

Case Study: How TradeEdge Enabled Supply Chain Visibility for the World’s Largest Snack Company in Emerging Markets

Our client, a Fortune 500 firm and the world’s largest snack company, had to work with a complex supply chain network of distributors closely.

In the absence of a proper global supply chain management solution, the client faced several challenges, a few of which are mentioned above. Hence, they could not project future sales and forecast inventory situations without ground data. The lack of supply chain visibility and disparity in technological maturity among distributors and vendors compelled the client to seek help elsewhere.

The client needed a globally scalable data exchange platform for their fast-growing Indonesia and Malaysia markets. They were looking for an AI-based supply chain management solution to cater to the following requisites:

TradeEdge Market Connect helped increase supply chain visibility, thereby enabling the client with a complete view of the supply chain network.

How does TradeEdge Work?

TradeEdge Market Connect, a turnkey cloud-based solution backed by a robust service-level agreement (SLA), is designed to improve supply chain visibility for exchanging, cleansing, and harmonizing business data. Further, TradeEdge provides a usage-based pricing model with low capital expenditure, keeping in mind affordability in developing and emerging markets.

TradeEdge Platform features:

Conclusion

Supply chain visibility is imperative for businesses with a global footprint to forecast future sales and make data-driven decisions. However, a disjointed distributor-supplier-retailer network in emerging markets and technological immaturity can significantly hinder global brands from competing with local ones and surviving.

In a time of fierce competition from specialized companies, e-commerce acquiring a larger market share, and a general shift in customers’ purchasing behaviors, the CPG sector has proliferated in recent years. This led to a significant uproar in the supply chain network.

COVID-19 has strongly emphasized our systems’ flaws, from public health to global supply chain networks. Essential supplies had been in short supply throughout the world. Even while businesses stabilize, the dynamic nature of demand and the ongoing economic pressures leave room for improvement. The shortage is primarily due to a complete lack of visibility into the supply chain network.

The Importance of Supply Chain Resilience

Supply chains that are reliable, adaptable, and sustainable are critical to the resiliency of the construction and infrastructure industries. Organizations have already started considering alternative ways for integrating future resilience as lessons acquired from the COVID-19 pandemic are used.

Optimizing supply chain resilience necessitates a holistic approach that considers all layers. Critical programs and spend categories will require strategic supply chain maps to help identify potential areas of failure in future shocks.

Cloud-based supply chain management systems can enhance forecasting and notification of interruption repercussions. Analytics are set to determine existing resilience measures’ potential effectiveness and suggest any necessary mitigation actions before it’s too late.

What is Supply Chain Resilience

Connectedness and Cognition

The concept of supply chain resilience isn’t new; it’s been debated in academia, C-suite, and on the shop floor for years. Experts have debated risk mitigation, adaptability, and the cultural shifts required to achieve resilience since the early 2000s.

There is no foolproof way to avoid all the dangers, especially high-impact/low-probability occurrences like SARS, foot-and-mouth disease, or a sizeable terrorist strike. Furthermore, the lack of historical data precludes predictive statistical tools from aiding in risk containment.

The current pandemic has highlighted the importance of creating supply chain resilience. Now more than ever, enterprises require supply networks to recover from the current crisis and maintain stability in the aftermath.

We believe that supply chain resilience is defined by two characteristics: its ability to be “connected” and “cognitive.” All components of a connected supply chain — wholesalers, retailers, and local stores have accurate, end-to-end, near real-time visibility. A cognitive supply chain thus uses the data gathered due to its interconnectedness to learn and produce actionable insights.

Building a Solid Foundation Connectedness

A linked supply chain is one in which wholesalers, retailers, and local stores — have accurate, end-to-end, near-real-time visibility. And increased visibility of your supply chain empowers you to closely track products as they travel from supplier to manufacturer and finally to consumer.

Supply chain visibility gives you more control over your inventories, costs, various disruptions, and risks. Here, data is the connecting link fetching valuable insights from the entire supply chain network, helping companies in the following ways:

Versatile and cost-effective data collection strengthens a worldwide consumer products company’s overall demand planning. For instance, TradeEdge Market Connect also resulted in a 4-10% increase in sales, in addition to the considerable cost reductions.

The Power of Cognition

A cognitive supply chain uses the data gathered due to its interconnectedness to learn and produce actionable insights.

The supply chain generates massive amounts of data. Mostly, this data is unstructured across various documents, emails, files, invoices, and others. Analyzing them manually is no more an accepted practice given the short time companies get to make decisions.

With the help of analytics, CPG companies can get a structured summary of relevant data in the shape of graphs, charts, images, and valuable insights for making data-driven decisions. Automatic data exchange enabled by machine learning is the best bet for CPGs as the process will:

End-to-end supply chain transparency improves sales and organizational performance for a multinational beverage firm. For example, TradeEdge Market Connect contributed to a 90% reduction in manual reporting, a 20% reduction in stock-outs, and a 10% boost in case-fill rates.

Influence of Pandemic on the Supply Chain Network

The COVID-19 pandemic has put 20 years of supply chain resilience study, debate, and preparation to the test. The challenge for companies will be to strengthen their supply chains while maintaining their competitiveness.

EdgeVerve thus believes that a connected and cognitive supply chain is essential for a sustainable company. Enterprises can accomplish this objective using the TradeEdge suite of solutions.

The complexity of today’s supply chain network makes data capturing a challenging endeavor. Businesses need to classify the data broadly into three dimensions: Product, Market/Channel, and Marketing. However, there’ one thing common in each of these dimensions: a problem of plenty. The puzzle of building a model based on data captured from one location-based market and reusing it in another begs an answer: Is AI for Sales and Supply Chain?

It’s time we get an answer!

Understanding the Supply Chain Network Complexities

Artificial Intelligence and Automation have become the need of the hour. Unfortunately, unless businesses proactively adapt to the changes, they are likely to lose the game for good. And this is not just to scare you; it is just a matter of time before you find yourself left out in the mayhem.

However, jumping onto the AI bandwagon without understanding the various complexities of businesses processes is the biggest blunder to commit. One needs a ground reality-check of applying Artificial Intelligence in logistics or any value chain for that matter.

Here, we will explore how leveraging AI can help your organization overcome data challenges that you may face across the demand value chain.

AI in Supply Chain – Can this be the Future?

The Big Data Conundrum

Courtesy of Artificial Intelligence, every human action leaves behind a data footprint. More often than not, human actions or decisions start following a specific pattern, which can model those decisions on reverse-engineering.

This helps businesses, for instance, forecast sales figures for their products/services in the coming quarter. As the behavioral purchasing pattern is repetitive, future forecasts become easy, right? Maybe not!

Reasons are that the market is fragmented and highly diversified, with multiple players rolling out similar products in tune with their competitors. The problem of plenty puts tremendous pressure on businesses, as they need to evolve to stay ahead in the competition continuously.

The sooner they get a new product out, the sooner other similar products replace the former. How buyers respond to them compared to what alternatives they have at their disposal only complicates the data capturing process. Businesses’ inventories are left untouched or wasted to match the competition. Here, AI inventory management software might help, but does it answer the data capturing conundrum? Hardly!

Product Dimension

The rate at which new products are introduced in the market was hard to imagine fifteen years back. Coupled with retailers rolling out private labels and mushrooming start-ups bringing innovation on the table have compounded matters for many big brands.

Thousands of new products roll out in the market every day, making it virtually impossible to identify a new product, let alone get a perfect match for it against your product portfolio. Confusions arise when you are a global corporation competing with regional brands, a few of which are mentioned below:

Using AI inventory management might not fetch the desired outcome because AI input still needs human validation before it can be rendered useful. Moreover, this approach is not time and labor effective. Hence, the question persists – how can you make AI work for you if you fail to make AI better in the first place?

Channel Dimension

How effective will AI be, especially when more than 80% of the data needed is outside the enterprise?

Building a supply chain strategy in Vietnam and using the same in the US shouldn’t be the desired approach for multiple reasons as there’s a huge gap in size and tools used in these two markets. Besides, the rise of online shopping made measuring ‘sell-out’ versus ‘sell-in’ the new mantra for success.

Handling a complex supply chain network of local/regional suppliers and distributors became a challenge. Sales reps had the onerous task of serving the millions of new outlets through thousands of local distributors even though you had no clue what the existing distributors were doing.

This is where a strong data foundation comes into play and is undoubtedly the first step in an organization’s AI journey.

Marketing Dimension

Digital marketing spending is on the rise and is accelerating at a scale more than print or television media can match.

Hence, big brands spend nearly 20% of their revenues on promotions, wherein direct marketing or consumer promotions account for another 10%. How can one measure the efficacy of marketing spending without sufficient verifiable data?

AI in logistics, inventory, and supply chain networks using multi-variate algorithms can allow you to measure the impact of these on product-specific sales and understand the impact of one over the other. But, the absence of useful data makes it difficult to map them effectively, although most retailers acknowledge the value of collaborative planning. The latter willingly provide as much visibility of their sales to their suppliers as possible.

However, the main challenge lies in the distributor network, where such asks are generally greeted with suspicion. Then again, creating business incentives for distributors or making it a condition of their distributorship might fetch valuable data, however less granular it may be.

Role of Data and AI in Delivering Value Across the Supply Chain

Though a buzzword, Artificial Intelligence or AI is still nascent. And it survives only in the presence of data. Then again, building a high-quality data foundation takes time, and not all business functions are amenable to AI modeling. Added to that are other issues, like shorter product lifecycles, sales and marketing methods explosion, fragmented and complicated supply chain network, and rabid focus on personalization.

For AI in the supply chain and other value chains to work properly, one must constantly feed new data. Therefore, you might have to gradually start small, learn, and expand automation to other areas.

The question ‘Is AI ready for Sales and Supply Chain?’ depends wholly on how well your organization navigates the changing market dynamics.