Month: June 2022

Due to various operational distribution complexities in an extensive supply chain market, it is a huge task to monitor and manage thousands of distributors and retailers. Handling all these operational intricacies manually requires humongous efforts. Even though the distribution workflow seems to be an easy one, it needs some effective planning for a seamless flow of supply chain operations. Therefore, an all-inclusive and comprehensive distribution management system is the need of the hour for the organizations involved in the distribution supply chain.

What is a Distributor Management System (DMS)?

Distributor Management System (DMS) helps enterprises manage the supply chain and distribution network efficiently – from streamlining inventory to providing complete visibility of secondary sales data.

Here are some reasons why you need a Distributor Management System for your business:

1. Optimum utilization of resources: The most significant advantage of an efficient distributor management system is that it optimizes the use of the existing resources. In addition, DMS, a time-efficient solution, also enables a swift and seamless flow of operations. Therefore, it is fair to acknowledge that efficient order management, delivery, return process, and payment collection system assisted by powerful reporting feature plays a significant role in achieving the targets and planned growth.
2. Accurate inventory management:  With a DMS and access to real-time data, enterprises can bod goodbye to ‘out-of-stock’ scenarios and inventory challenges.
3. Effective order management: Helps streamline and simplify order management on the buy-side and the sell-side, providing real-time ordering information across the supply chain. Well-aligned
4. Promotions and pricing: With real-time information at hand, enterprises can better manage promotions and set up custom promotions and pricing. Besides this, they can set attainable targets to encourage better results from dealers and sales teams.
5. Provides real-time visibility of secondary sales data: A robust DMS helps enterprises obtain data of all distribution channels in real-time that can be converted into actionable insights to handle stock-out scenarios, better plan promotions, and drive sales growth.
6. Seamless delivery and returns management: Delivery is the most crucial stage of the supply chain process because there must be constant communication between the distributors, warehouse, retailers, and the sales team. Hence, an efficient Distribution Management System is required.
7. Common communication platform for all parties involved: For streamlined communication, all the parties involved in the sales and the supply teams can coordinate without hiccups on a common platform.
8. Well-ordered payment collection: Undeniably, a streamlined dealer Distributor Management System will certainly benefit a business that will lead to profitable revenue generation. A Distributor Management System creates due alerts, invoice generation, payment collection, and simple and coordinated reminders.
9. Effortless management of distributor claims: By implementing an all-inclusive Distribution Management System, organizations can manage claims easily and enhance the connection with distributors.
10. Improved targets & effective reporting: By executing an efficient distribution and supply chain management system, an organization can clearly understand the sales team’s performance and set realistic yet challenging targets to increase revenues.

Hence, a Distributor Management System (DMS) plays a key role in managing the supply chain, providing real-time access to data, and enabling enterprises to stay ahead of the competition.

The global supply chain network has become increasingly complex, and so also the rapidly changing consumer behavior. These factors have compounded to render traditional demand planning techniques ineffective and inadequate. Demand planners need more visibility into their demand-supply value chain and quality demand signals in order to achieve a perfect balance between surplus and adequate inventories. Moreover, keeping a close tab on external factors like global emergencies, weather trends, and economic trends is equally important to understand the change in market demand for goods/services. Hence, an intelligent demand-sensing solution has become the need of the hour for demand planners and others in the value chain to drive business growth and customer engagement.

What is demand sensing, and how does it differ from traditional techniques?

Demand sensing leverages AI/ML technologies to gather real-time data that help predict future sales in a shorter period. It helps pick short-term market trends to estimate what consumers will want, when, and where immediately.

For example, traditional demand planning techniques could have effectively planned long-term demand and sales by considering historical data. But, if companies had used demand sensing technology, they would have immediately captured the silent hints of upcoming disruptions months before the COVID virus took the shape of the global pandemic. This unpreparedness, lack of foresightedness, absence of the right tech-based tools, and obvious siloes existing in the global supply chain were responsible for companies remaining misinformed about what would happen until the worst happened. Most organizations struggled to keep the shelves of their retail and distribution centers stocked up amidst the pandemic-fueled panic-buying that went on in full blaze just before the complete lockdown norms were officially made known to the general public.

And the aftershocks of the pandemic are still being felt deep down in the supply chain networks. Demand sensing in the supply chain breaks those existing siloes and improves visibility into the network by facilitating a seamless supply of real-time insights so actionable decisions can be made effectively regarding predicting future demand and sales. There are reasons why demand sensing as a forecasting method is gathering more preferences than its predecessor. Let’s elucidate the differences between these methods in brief.

Demand sensing: Improving forecast accuracy with data

There are different ways to improve forecast accuracy with demand sensing; a few of which are elucidated below:

Use PoS data

Point of sale data at retail stores is ideal for providing real-time information like the quantity of products sold, date and time, region, and so on. PoS inputs are consolidated and compared with short-term forecasts to identify deviation and used for predicting product demand for the immediate future.

Analyze order history

While PoS inputs capture demand signals at the consumer end of the supply chain, historical data like sales history, open order history, and currently available orders are used to estimate manufacturers’ product demand. This information is valuable when planning for inventory buffers.

Track macroeconomic indicators

Macroeconomic indicators such as gross domestic product, the overall stock market, employment data, and housing sales data point to a change in consumer demand. Decisions are made based on such insights to re-adjust the short-term forecast to avoid excess inventories.

Consider competitor promotional offers

Demand sensing also tracks competitor movements to adjust short-term forecasts. Sudden last-minute promotional offers or discounts from competitors can change the game for your business, leaving no time to react or amend such situations. Marketers can predict the impact of such factors on sales and adjust forecasts accordingly. Hence, keeping a close watch over competitors is crucial for maintaining a competitive edge in the market.

Take advantage of competitor stock-outs

It is highly possible that your competitors can suddenly face stock-out situations due to the unavailability of raw materials, quality problems, or production breakdowns. Businesses can take advantage of the situation to capture the competitor’s market and re-position inventories to meet the unexpected demand by increasing production for a while. They often try to shift direction to alternative products available on the shelf.

Adjust forecasts as per weather patterns

Unlike traditional forecasting methods, demand sensing considers weather patterns, seasonal variations, and natural calamities to adjust short-term sales forecasts, raw material procurement, production plan, and distribution plans to meet end-user demand.

Conclusion

Demand sensing is currently the best bet for businesses to catch up with increasing market volatility, shorter product lifecycles, frequent changes in buying behaviors, and external factors influencing the demand for goods. With the help of AI, ML, and Automation, demand sensing solutions like

TradeEdge Demand Sensing provides actionable insights by aggregating real-time data about product sales and inventory across multiple channels. They provide granular visibility into network-wide sales and inventory, helping businesses know what is selling, where and at what speed.

The phrase building resilient supply chains has been a part of the business lexicon for decades. But the COVID pandemic brought the spotlight on the vulnerabilities of the global supply chain network and made it front-page news. Supply chains have become more complex, interconnected, and global than ever before. And traditional demand planning approaches have been proved inefficient in predicting sudden disruptions anywhere in the network. In order for businesses to build a resilient supply chain and stay future-ready always, they need to catch the demand signals as early as possible. AI-powered demand sensing is precisely what companies need today.

Importance of data in accessing real-time demand signals

AI-powered demand sensing thrives in the presence of data. Data is essential for real-time demand signals, minimizing out-of-stock situations, and preventing lost sales. However, due to persistent data challenges, businesses often struggle to meet the data needs for demand planning.

Four key challenges when it comes to demand planning data needs

There are four key challenges we see when it comes to demand planning data needs, such as: –

Demand sensing — A supply chain game-changer

According to a report by Reuters, nearly 37% of companies reported poor visibility due to internal siloes, a lack of data-driven information, and an over-reliance on their internal data. These factors impaired their ability to detect emerging threats deep down in their demand-supply network.

These numbers should not worry companies since they have all seen the worst side effect of faulty demand signal capturing measures. Hence, the question remains – how to capture the rapidly evolving demand-supply dynamics on time and how to do it right?

Intelligent demand sensing powered by AI technology is the only solution for all the problems mentioned earlier.

Hence, in order for an AI-powered demand sensing solution to work well, there should be unhindered accessibility of data. Since AI thrives in the presence of data, any silo existing can impair the actionable decision-making pertaining to demand predictions.

For instance, TradeEdge Demand Sensing aggregates real-time data about product sales and inventory across multiple channels and provides actionable insights. This provides granular visibility into network-wide sales and inventory, helping businesses understand what is selling, where and at what speed.

How is AI redefining the future of demand sensing?

Traditionally, predicting future sales was simply done by considering historical sales statistics. It is born out of the belief that history repeats itself continuously. But, the same approach was negated when the pandemic showed not everything follows the same pattern and that demand can change dramatically by unprecedented triggers.

AI demand sensing with capabilities like Deep Learning and Machine Learning helps improve forecast reliability and creates an agile and responsive supply chain network.

Benefits of demand sensing:

The bottom line is…

Demand sensing can be the best bet when markets are becoming more volatile than ever, and customer demands change at lightning speed. And, with more external factors impacting the global demand-supply value chain more frequently, creating a cascading effect downstream, it is better to catch those early signals to stay future-ready.

Supply chain management is becoming tricky due to market variabilities that change the demand-supply equation, further leading to unnecessary inventory waste and stockpiling. Understanding the needs of the customer is essential in order to make informed decisions and optimize inventory across the value chain.

How can companies manage inventory and reduce stock-outs, inventory holding cost, and revenue losses?

This is where the role of an intelligent demand sensing solution comes into play.

Demand sensing – An approach beyond traditional demand planning

Demand sensing uses AI/ML technologies to help businesses forecast the immediate future wants of the customers and curtail the unnecessary loss of goods by predicting demand accurately. It can thus curb the shortage of products besides other correlated issues.

This approach to short-term forecasting trends instantly helps companies better guess what the consumers want, when, and where. The parties involved can forecast the latest sales data and make improvements to generate more profits.

There are two aspects of demand sensing which are:

Short-term forecasting: It controls an elevated level of data granularity to examine daily demand information for the end customer and instantaneously find out the changes in demand behavior.

Increasing supply chain visibility: This is done by identifying patterns in point-of-sale (PoS), promotion, social media, NPI, weather, IoT, internet search, and economic data to make near-term developments to your forecast and inventory positioning.

Both methods cut down demand insecurity and allow crucial adjustments to the estimation without anticipating the next forecast cycle.

Hence, it is fair to conclude that demand sensing comes to the rescue of businesses to organize, standardize, and generate a more helpful supply chain and inventory management landscape.

Both methods cut down demand insecurity and allow crucial adjustments to the estimation without anticipating the next forecast cycle.

Demand Sensing in inventory management

Inventory management is harmonizing the service-level desired goals and the financial limitations for a substantial distribution of goods with the picture of demand and supply unpredictability in mind.

The inventory requires optimization that has primarily two parts:

Safety stock is the immediate function of forecast inaccuracy and service level, while cycle inventory is optimized by linear programming.

Demand sensing thus leverages real-time data to enhance forecast accuracy, thus decreasing the safety stock quantity, working capital, higher inventory movement, and lower inventory carrying cost. However, for efficient functioning, demand sensing and inventory optimization approaches should be implemented simultaneously.

How can organizations optimize inventory with demand sensing?

Lower demand latency: Demand sensing helps businesses get the appropriate information quickly by repurposing the PoS (real-time information, product sold, quantity, date and time, region) data for better sales forecasting without distributors’ insights.

Ideal operation of current inventory stocks: Demand sensing helps businesses optimize the existing stocks and balance their supply by considering the new consumer demands.

Planning inventories for new products: With new products continuing to supersede the existing product demands, it is the perfect time to implement demand sensing tools so that the businesses can meet the necessity for new products with the proper amount of the previous developments in a stockpile.

Demand sensing – A powerful solution for the future

Additionally, for businesses to gain the upper hand over their competitors, supply chain professionals should be able to identify the latest trends in the market and anticipate potential consumers’ demands along with their fluctuating preferences. However, this is not always possible with the assistance of traditional demand planning methods as it has certain limitations in predicting the future supply-demand accurate insights. Demand sensing is an invaluable resource and way of managing the inventory, primarily replenishment, the supply chains.

Therefore, organizations must leverage this intelligent solution to reduce the lead times and move other inventory optimization into the next century.

Product recalls are a costly business reality. Added to that is the limited visibility into product storage and movement, legacy technology, and existing data siloes across the supply chain. These factors hinder recall efforts and can lead to reputational, legal, and regulatory issues. Product traceability can save businesses from the problems mentioned above, but companies need access to inventory movement in real-time to reduce the burden of costly recalls, fight counterfeits, control quality, and even save lives.

Besides data unavailability, there are other challenges impairing product traceability for businesses, such as:

What is product traceability?

Product traceability can easily track inventory movements effectively, right from where they are shipped or back through their operational and production stages. Traceability helps companies identify defective or unsafe goods in their offerings, timely locate and remove them before such items impact buyers negatively, and avoid product recalls damaging to a company’s reputation.

Product traceability solutions minimize costs arising out of rejected items, recalled contaminated goods, and compensatory costs for damage control.

For example, the TradeEdge Product Traceability solution helped Mars, a global manufacturer of confectionery, pet food, and food products, meet market traceability needs for the company’s digital supply chain initiative.

How does product traceability function?

TradeEdge Product Traceability is a cloud-based and globally scalable solution designed to enable enterprises to control the inventory movement in near-real-time (Hold & Release Process).

Taking the above example of Mars here, the traceability transformation program was successfully implemented across all business segments worldwide to leverage agile ways of working in a decentralized business landscape. This enabled Mars to meet commitments regardless of Covid pandemic restrictions. TradeEdge implementation helped the global F&B company absorb and harmonize data from multiple ERP (Enterprise Resource Planning) and warehouse management systems agnostic, thus providing a unified business consumption layer to business users.

With its help, clients like Mars achieved:

The bottom line

In order for businesses to fully optimize such product traceability programs, they need to follow specific ground rules, such as:

Product traceability solutions empower businesses with real-time insights into their product supply chain and manufacturing units to address any issue arising from harmful items that need timely recall, replacing, or placing on hold. Such timely availability of crucial insights immunes businesses from damaging losses and poor reputations.