Tag: demand prediction

supply chain analytics

Weekly Round-Up: A Storyboard on The Importance of Supply Chain Analytics Solutions

LONDON: Quantzig, a leading analytics services provider, has announced the release of their latest storyboard on the importance of supply chain analytics and how it can help businesses in improving supply chain visibility and merchandising capabilities. In today’s competitive business scenario, companies find it difficult to monitor operations in real time and eliminate data silos. This is where supply chain analytics can come to the rescue.

By leveraging supply chain analytics solutions, companies can calibrate their entire supply chain network efficiently. Supply chain analytics can help companies in supply chain management and improve operational efficiency to facilitate quick time-to-market. Additionally, it can enhance the end-to-end performance of the supply chain and boost demand forecasting and logistics operations.

To stay ahead of the curve and create lean operations, supply chain leaders must leverage supply chain analytics solutions to yield the visibility they need into their entire operation.

Quantzig’s analytics solutions have helped many leading companies to make smart and data-driven decisions and boost growth. Below, we have summarized some of Quantzig’s recent success stories for this week and have also highlighted ways in which supply chain analytics can help companies to analyze market demand, the impact of indirect supply chain cost and boost ROI.

Analytics-driven control metrics enable companies to gauge critical events in the supply chain in real-time. Want to know how? Request a FREE proposal now.

#1. Supply chain analytics reduced distribution cost by about $8M: Identifying supply chain risks and opportunities by combining real-time datasets is a daunting task for businesses. But supply chain analytics solutions can make this task easier by precisely monitoring the performance data of suppliers through analytics dashboards. Also, supply chain analytics solutions can offer detailed insights into inventory and market demand. Furthermore, this can facilitate supply chain optimization and enhance supply chain flexibility.

Leading Sports Brand Leverages Supply Chain Analytics, Identifies Potential Savings Worth Around $8m

#2. What are the benefits of supply chain analytics?  Supply chain analytics can help organizations to achieve operational excellence in multiple activities ranging from procurement of raw material to order fulfilment. Also, by leveraging analytics solutions in supply chain companies can enhance their category management practices and consolidate the supplier base to minimize operational costs and improve contract compliance.

Unveiling the True Potential of Supply Chain Analytics

#3. Supply chain analytics minimized inefficiencies in supply chain management: Are obsolete inventory management systems leading to poor business outcomes? No more, as supply chain analytics is here to help you out. Supply chain analytics has the potential to help companies solve several complicated decisions by leveraging millions of decision variables, trade-offs, and restrictions. It can help in identifying the key opportunities to bring about improvements in profit margins. Furthermore, this can assist in optimizing supply chain operations by combining descriptive and prescriptive data sets.

Supply Chain Analytics Solutions for Food and Beverage Companies – A Quantzig Case Study

Customized analytics dashboards can offer a 360-degree view of the supply chain operations. Request a FREE demo below to know more.

#4. Supply chain analytics eased the interpretation of market trends and enhanced operational efficiency: Catering to the growing demands while focusing on affordability is one of the major concerns for companies across industries. One of Quantzig’s clients faced a similar issue and approached Quantzig to leverage its expertise in offering supply chain analytics to bring about significant improvements in markdown percentages. Quantzig’s supply chain analytics solutions offered unparalleled visibility into the supply chain risks and demand uncertainty by interpreting the market trends in real-time.

Supply Chain Analytics for a Power and Energy Market Client – A Quantzig Case Study

#5. What’s new in supply chain analytics in 2019? Technological progress is becoming very important for companies in every sector. Supply chain management is also witnessing new trends and technologies every day. This makes it important for companies to understand the latest and existing trends to assess the benefits of evolving technologies and prioritize organizational goals. The advent of technologies like IoT and data unification in supply chain analytics has resulted in an accurate forecast of possible complications and better supply chain visibility.

What’s New in Supply Chain Analytics This Year?

#6. Supply chain analytics transformed the existing supply chain strategies and increased savings: Developing efficient supply chain strategies can be a cause of concern for businesses but you need not fear if you have a proper supply chain analytics solutions in place. A leading skincare products manufacturer was facing the same issue but experienced a great change in operations and savings by leveraging Quantzig’s supply chain analytics solutions. These solutions helped them to anticipate customer demand and accordingly regulate their inventory levels. Additionally, it assisted them in identifying top suppliers and in fine-tuning their existing strategies that resulted in increased savings.

Supply Chain Analytics for A Leading Skin Care Products Manufacturer Helps Fine-tune Existing Supply Chain Strategies and Improve Efficiencies

Are you finding it difficult to analyze supply chain data in real-time? Get in touch with our experts.

#7. What is the importance of supply chain analytics in today’s business environment?  With the increasing pricing pressures and aggravating customer demands, companies across industries are facing predicaments in enhancing supply chain efficiency and operational speed. Companies need to evolve their supply chain execution systems and tweak their marketing techniques to accommodate the growing customer demands and dynamic market conditions. Supply chain analytics holds the solutions to all of these issues. It allows companies to analyze their supply chain data and identify the efficiency gaps. This, in turn, accelerates sales, speeds-up material movement, and improves supply chain standards.

Supply Chain Analytics: A Game-changer in Boosting Your Supply Chain Efficiency

#8. Supply chain analytics improved demand forecasting capabilities significantly: Do you really think devising an effective demand forecasting model to improve end-to-end supply chain visibility is a myth? If yes, then you must go take a look at Quantzig’s latest success story where one of its clients faced a similar predicament but realized a major improvement in their capabilities to forecast demand through the use of a suitable demand forecasting model. Furthermore, supply chain analytics solutions proved to be extremely helpful in providing end-to-end visibility on supply journey of each product.

Supply Chain Analytics: A Game-changer in Boosting Your Supply Chain Efficiency

#9. What are the key supply chain challenges? The growing complexity of business environment has forced companies to re-shape their business models. Due to such complexities, companies are facing multiple supply chain challenges increasingly complex patterns of consumer expectations and customer demand. Therefore, supply chain analytics has become the need of the hour for companies if they really want to stay ahead in the competition. It can aid companies to identify specific processes and analyze the potential areas of waste or inefficiency.

How Supply Chain Analytics Can Help Solve the Biggest Supply Chain Challenges

#10. Supply chain analytics solutions minimized inventory levels and checked vendor risks: Measuring the supply chain and vendor performance to increase profitability has become one of the major roadblocks for many companies. Are you facing the same problem? Supply chain analytics may hold the key to success. By leveraging analytics solutions in supply chain, companies can optimize their existing route and logistics operations to minimize inventory levels. Additionally, these solutions can help in measuring key vendors’ performance that can further help in mitigating future risks.

Supply Chain Analytics Helps a Leading Processed Foods Retailer Minimize Inventory Levels and Monitor Vendor Risks

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Weekly Round-Up: A Storyboard on The Benefits of Demand Forecasting Analytics

LONDON: Quantzig, a leading analytics services provider, has announced the release of their latest storyboard on the benefits of demand forecasting models and how it can help businesses identify new opportunities for revenue generation and cost reduction. With the growth of organizations globally, operations are becoming increasingly complex, leading to reduced visibility. Consequently, to remain competitive in the immensely aggressive and stressful global environment, there is a need for organizations to increase their operational efficiency across the supply chain.

Demand forecasting models can help companies in enhancing their supply chain visibility, demand forecasting methods, logistics optimization, and consequently enhance overall merchandising capabilities. Also, it can help businesses optimize their networks for improved efficiency and effective supply management.

Are you finding it difficult to have accurate inventory forecasting, achieve operational excellence in several activities, ranging from raw material procurement to order fulfillment? Get in touch with our experts now to know how our analytics solutions can help.

Quantzig’s demand forecasting models have helped more than 55 Fortune 500 companies to make data-driven decisions and tackle supply chain challenges and also offer them insights on people, processes, assets, and the entire value chain to facilitate quicker decisions for global supply chain management. Below, we have rounded up some of Quantzig’s recent success stories for this week and have also highlighted ways in which demand forecasting models have helped companies to predict needs of the customer and develop valuable and effective products and strategic plans to meet them.

#1: Demand forecasting models enabled to recapture 15% of the lost market share and increased revenue by USD 67 millionAccurate forecasting of the inventory and demand is a daunting task. Don’t you agree?  One of Quantzig’s clients faced the same problem. They approached Quantzig to leverage its expertise in offering supply chain analytics to identify different KPIs and devise robust demand forecasting models and improve inventory management efficiently. Consequently, our demand forecasting models proved very helpful for the client in gaining back 15% of lost share market in 10 months and increased revenue by USD 67 million.

Demand forecasting and inventory management delivers USD 67 million in revenues for switchgear manufacturer

#2: Insider tips to improve demand forecasting methods unveiled: Players in almost every industry are often posed with tough questions like how much of certain products or services to stock, which brand will perform the best, what is going to be the busiest time of the year. There are a few things that are easier to predict while some are very difficult. This is where demand forecasting models help. Therefore, it is advisable for businesses to use demand forecasting models to improve their business operations. You must go through some of the most useful insider tips to enhance your demand forecasting methods.

Insider Tips to Improve Your Demand Forecasting

#3: Demand forecasting models boosted service levels by 25%: This is one of the most significant success stories of Quantzig, where the client managed to determine their lead times and stock replenishment levels. This boosted their service levels by 25%. Moreover, demand forecasting models also helped the company to manage demand planning and levels and improve the overall customer service and experience.

25% improved service levels achieved by leading consumer goods manufacturer through demand forecasting and inventory management model implementation

#4: Demand forecasting models enhanced demand forecast accuracy by over 90%: Is the inability to meet the demand jeopardizing your company’s market position? If yes, then you must be going wrong somewhere in forecasting the demand of your customers which is very crucial to improve the efficiency of your operation and ROI. This is evident in Quantzig’s latest success story, where demand forecasting models helped the client to gain high accuracy in supply and demand predictions over time.

#5: Demand forecasting models optimized cash flow and minimized inventory costs: Quantzig’s demand forecasting models helped the client to align sales and marketing efforts to lower holding costs and increase turnover rates. Additionally, the unique demand planning and demand forecasting methods helped in optimizing inventory and foresee market trends effectively. Furthermore, the effective demand forecasting methods proved to be very helpful in predicting customer demands and save on warehouse and transportation costs.

Minimizing Inventory Costs and Optimizing Cash Flow for a Retail Industry Client – Quantzig’s Demand Forecasting Engagement

Are you wondering how to establish an effective demand management process, improve order fulfillment ratios, and boost operational efficiency to facilitate quick time-to-market? Request a free now!

#6: Demand forecasting models facilitated end-to-end visibility on supply chain journey: Improving end-to-end supply chain visibility and achieving high customer satisfaction during order fulfillment may sound scary. But you need not fear if you have effective demand forecasting models in place. A leading firm in the distilled spirits manufacturing sector was dealing with the same issue but experienced a great change in the demand and supply chain by leveraging Quantzig’s demand forecasting models. These models helped them to identify the areas of optimization to ensure greater product delivery and re-strategize their sourcing locations by examining the effect of supplier location and transit times on the design-to-market time of a product.

Supply Chain Analytics Helps A Distilled Spirits Manufacturing Major Improved Their Demand Forecasting Efficiency

#7: Demand forecasting models augmented conversion rates significantly: Are you wondering how to develop a hybrid supply and demand forecasting strategy to precisely predict demand? Demand forecasting models can help as it helped one of Quantzig’s clients. Demand forecasting models have the potential to enhance customer knowledge resulting in increased conversion rates. Additionally, these models are beneficial in inventory forecasting, predicting closed-loop marketing outcomes leading to better demand management.  

Quantzig’s Supply and Demand Forecasting Engagement Helped a Renowned Pharmaceutical Industry Client Precisely Predict the Demand for Pharmaceutical Products in the Australian Market

#8: Leveraging demand forecasting models to boost profit margins: Do you really think developing demand forecasting models is a mystery? If yes, then you must go through our latest success story where Quantzig’s demand forecasting models boosted the client’s profit margins significantly. With demand forecasting models, it is easy to become customer-centric through tailored services. Furthermore, proper demand planning and demand management are very helpful when it comes to critical decision making by harnessing consumer demand.

#9: What are the most important steps to successful demand forecasting? Demand forecasting methods are the keys to estimate the probable demand in the future for a product or a service accurately. These methods can be very effective and helpful for organizations in managing risk, dealing with competitors and government laws. But to get optimum results from your demand forecasting techniques, it is important that you follow a few important steps.

Four Vital Steps to Successful Demand Forecasting

#10: Demand forecasting models revamped forecast ability by 80%: Are you too facing the challenges by the regulatory laws, dynamic nature of customer expectations, market dynamics, and the ongoing technological advancements? If yes, then you are not alone as every industry player today facing the same issue. But demand forecasting models may hold the key to success. These models can evaluate the forecasting methods adopted by the peers and implement the best forecasting technique to avoid adverse impacts on their bottom line.

Demand Forecasting Helps a Healthcare Logistics Company Enhance their Demand Forecasting Ability by 80% – A Supply Chain Analytics Case Study by Quantzig

We understand the challenges companies face in demand management, network optimization, and inventory optimization. Our analytics solutions provide best-in-class frameworks to analyze spend data, improve category management practices, and consolidate the supplier base to increase contract compliance and reduce operational costs. Request a free demo to gain more insights.

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Insider Tips to Improve Your Demand Forecasting

Players in the retail industry are often posed with tough questions like how much of a certain merchandise to stock, which brand will sell the most, what is going to be the busiest time of the year. Some things might be easier to predict while others are almost impossible. However, that doesn’t stop retailers from using demand forecasting as the go-to tool for inventory planning and merchandising. Retailers have been using demand forecasting for a long time to improve their business operations. Still, only a few retailers are capable of producing a good forecast; thereby, Request Solution Demoimproving their inventory planning. Here are some insider tips to improve your forecasting:

Understand the drivers

Many companies still assume that sales is what affects forecasting and thereby base all their forecasting on sales data. This is the most blindly followed statement in the retail industry as forecasts are actually driven by demand. The difference between sales and demand is minimal and you can run into trouble when you base your forecasting on sales. For instance, if you run out of a particular SKU for few months there will be zero sales. The sales data will thus reflect that there is no demand for the item so it is worthless to buy it.

Use right inventory management system

Inventory management has a significant impact on the forecasting accuracy. It is essential to know what’s happening in the warehouse to facilitate accurate demand forecasting. Consequently, it is important to find the right software and hardware to facilitate inventory management system. Executives should ask the right questions prior to investing in an inventory management system to enable better forecasting.

Understand the drivers of uncertainty

A company’s ability to accurately forecast demand depends on numerous factors. Analyzing these factors in advance helps companies plan ahead and create an accurate demand forecasting strategy. Manufacturers should also ask questions regarding the consistency of the demand, factors influencing the variables, levels of supply chain visibility, modes of transport available, and access to multiple modes of transport. Figuring out such uncertainty refines your forecasting, which enables companies to have a backup plan in place.

Measure and report forecast accuracy

A forecast will rarely be successful in the long term if the progress is not measured and reported to all stakeholders. Standard reports often offer detailed analysis which identifies strong and weak areas. One will only get to know the forecast accuracy when the forecast is compared to the actual result. Analyzing the variance will allow companies to identify what went wrong and thereby further tweak their forecast to get more accurate results.

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Top Trends: Demand Forecasting in the Retail Industry

Predicting the future seems like an effort in vain. The predictions rarely turn out to be true due to some unforeseen circumstances or changes in the external environment. The same can be said for demand forecasting in the retail industry as well. However, retailers still carry out demand forecasting as it is essential for production planning, inventory management, and assessing future capacity requirements. Accurate demand forecasting provides businesses with valuable information about their potential in the current market to make informed decisions on pricing, market potential, and business growth strategies. The retail industry simply can’t survive without demand forecasting as they risk making poor decisions about their products and inventory, which might result in lostFree demo opportunities. So what trends are catching up in the retail industry with regards to demand forecasting?

Rising popularity of bottom-up forecasting

Today, the retail industry operates over multiple channels, which demands inventory positioning in numerous locations. As a result, retailers have to focus on bottom-up forecasting to meet the demand through various channels. Using such approach helps them fulfill orders from both e-commerce and traditional retail channels for a wide array of assortments. It enables the retailers to meet customer demand more quickly and deliver goods through the customers’ choice of channel. When the need arises, such approach can also allow retailers to balance inventory between stores and distribution centers through high-frequency inter-depot transfers.

Focus on forecast quality

Retailers usually look at demand signals when carrying out demand forecasting. However, retailers with less sophisticated planning capabilities often seek consistency in demand signals, which is often fragmented. As a result, they look for a unified model that allows all stakeholders to collaborate via “what-if” simulations. Consequently, retailers are looking to measure forecast quality by looking at external collaborations, including suppliers and end users to get better forecasts, which can then be shared with the sales team and suppliers.

Fresh view towards long-tail items

A majority of the long-tailed or slow-moving items sell because they are in inventory not because the forecast team made correct predictions. The key to master demand forecasting for slow-moving items is to ensure service levels for them. Such items cannot be planned reliably, so the retailers turn towards supply chain planning software to automatically model stock-to-service level, which accurately lists how much stock they need.

Forecasting automation

At a time when automation is gaining popularity, retailers are quick to put the burden of forecasting on automation. Since the retail industry operates on a very tight margin, they will possibly look to save on the cost of hiring planners as well. Automated demand planning applications can forecast future demand and add value to the business flawlessly. Additionally, retailers are turning towards cloud-based applications for their automation needs, which allows them to perform sophisticated forecasting without having to invest in IT infrastructure.

Managing returns

Returns are considered the dark side of e-commerce. Retailers incur significant reverse logistics cost and other additional products costs due to returns. Retailers are using sophisticated applications to help them predict returns and minimize them wherever possible. This helps them to reposition the returned goods across their inventory.

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90% accuracy in demand forecasting achieved by a consumer goods manufacturer through predictive modeling techniques

Business Challenge: Eliminating issues with inventory management process

The client wanted to optimize its inventory management through improvement in the accuracy of its demand forecasting process.

Situation: Constant issues with inventory management resulting in reduced customer satisfaction levels and profitability

The client was facing constant issues of stock outs, large inventory levels, inaccurate lead times, and inaccurate demand forecasting. These problems were affecting the customer satisfaction levels and creating a negative impact on profitability.

Solution/Approach: Regression model to predict future demand based on historic data

We deployed a regression model to conduct analysis on historic information on products, retailers and inventory levels. In addition, we also conducted analysis on customer data to predict purchase patterns, trends and buying behavior. Based on this analysis, we were we able to accurately forecast demand, uncover irregularities, and determine optimal inventory levels.

Impact: Improved accuracy of demand forecasting and improved inventory management

The client was able to achieve improved accuracy of demand forecasting up to 90%. They were also able to streamline the order management process and achieve better inventory management. This resulted in improved customer satisfaction and profitability.