Parcel Spend Management Software: Challenges and Benefits of Parcel Spend Optimization


The capacity to analyze and track parcel spend is more crucial than ever. The costs related to moving parcels from point A to point B can be quickly and effectively controlled and monitored with intelligent parcel spend management software. Shipping more packages is an excellent sign of growing sales, but without careful monitoring, shipping costs can slowly eat into your bottom line. As it turns out, eight out of ten businesses overspend on shipping by an average of 15-20%. With UPS and FedEx both announcing record-high rate increases for 2023, there has never been a necessary time to examine your company’s shipping costs. 

With costs rising due to the constantly changing business ecosystem, even the most sophisticated businesses are overpaying to get the extra edge, but they are just leaving money on the table, seriously affecting their bottom line. Carriers are raising the stakes with continuous rate hikes, policy changes, and complex billing systems. In this informative article, we will delve into the challenges businesses face related to their parcel spending and why you need to connect your business with parcel management services. 

Challenges Associated with Parcel Spend Management 

Optimizing parcel spending poses challenges for businesses, including: 

Inadequate Data 

Carriers don’t regulate pricing or maintain transparency. Instead, they independently negotiate contracts with every client, keeping you in the dark about your competitors’ spending. Relying on your own operational KPIs and conventional methods is not enough when you do not fully comprehend the complexity of your contract, how pricing is set, or whether there is room for cost savings. Negotiating lower shipping rates based on your previous contract may seem like a go-to strategy, but if your rates are too high to begin with, you are not getting best-in-the-business pricing. An optimum parcel shipping solution provider working side by side with you might be helpful in this scenario. 

Lack of Resources 

You may be charged with unwanted accessorial surcharge fees or be eligible for audit rebates you are unaware of. For instance, carriers often make sizable pricing changes before the contracts are termed out. They may also create upcoming surcharges, add fees, or adjust prices on surcharges that are not covered in your contract. When a business ships thousands of parcels daily, it is unrealistic to manually audit every parcel invoice. Most organizations lack the time and resources to monitor invoices and surcharges and observe errors or overcharges manually. 

Lack of Expertise  

Do you have relevant expertise to effectively analyze a parcel contract, or which elements are negotiable where you can save costs to support your bottom line? Anyone can negotiate savings of 3-4%, but if you are not well-versed in parcel contract negotiations  best practices, then you are most probably leaving money on the table. If you are looking for a regional carrier for your small parcel shipping, then you are selecting from thousands of options. That is why you need brilliant parcel spend management software to empower you with complete parcel spending visibility to leverage cost savings and better decision-making. 

How an Industry-Leading Parcel Shipping Solution Provider Helps  

1. Monitoring Invoices for Errors and Overcharges 

Small billing errors eventually add up to significant amounts if they are not caught on time. Outsource invoice monitoring to a solution provider that utilizes automated technology to comb your invoices for service level failures and money-back guarantee opportunities and automatically claims your savings. 

2. Negotiating Better Contracts Even Without Changing the Carriers 

Changing carriers can cause some major discrepancies among various operational levels of a business. An industry-leading parcel management solution provider can enable you to save costs without even changing your existing carriers. Look for a solution with deep industry experience to analyze carriers’ proposals, compare them to best market pricing, and empower you with the leverage you need to negotiate effectively. 

3. Diversifying Your Parcel Carriers to Maximum Agility 

In today’s world, you need a perfect blend of shipping carriers to maintain operational flexibility. For example, contracting carriers from various locations can overcome regional challenges, such as supply chain disturbances, labor shortages, and severe weather events. An expert parcel delivery management system can help you optimize spending with your current and future carriers’ service providers and help negotiate contracts and pricing. 

4. Actionable Insights to Make Data-Driven Decision 

An expert parcel spend intelligence solution that provides data and analytics tools allows you to access detailed, real-time visibility into your shipping spend. Spot trends and monitor KPIs to find areas for more savings and help analyze the bigger picture and make data-driven decisions. 

A Solution That Delivers 

Optimizing shipping costs is the key to keeping customers happy and costs down in these uncertain economic times. TransImpact’s Parcel Spend Management Software provides end-to-end visibility to maximize your parcel spending strategy and save costs. Our industry-leading experts with vast experience in parcel contract negotiations help our clients save unwanted surcharges and excessive mid-term fees. So, in simple terms, we are in the business of delivering good news to our customers. To understand more about our solutions, talk to our experts or schedule a demo. 

The Evolution of Supply Chain Management & Logistics

The Evolution of Supply Chain Management & Logistics

The advancement of supply chain management has been a constant process shaped by various factors, including changes in customers buying decisions, technological evolution, and globalization. The supply chain has developed significantly over the years as organizations have realized the use of effective and efficient logistic networks. This evolution paved the way for technology to grow exponentially and enhance customer experience.  

The early days of the supply chain were focused fundamentally on logistics and transportation. The main idea behind this was to move products and goods from point A to point B as smoothly as possible, with a crucial emphasis on the management of inventory and the coordination of manufacturers and suppliers. 

However, as businesses grew and globalized, the supply chain became more challenging to manage. This led to the innovation of new technologies and software solutions that could help manage the flow of goods and information across multiple business operations. Below are some of the key stages in the development of the supply chain. 

An Overview of Supply Chain Management’s Evolution 

The supply chain ecosystem has come a long way since its inception, with significant development in transportation and communication technologies. 

Pre-Industrial Evolution   

During this period, the supply chain was much simpler than it is today. Most products were made by hand, so there were fewer steps involved in the production process. The supply chain was comparatively shorter, with fewer intermediaries between the consumer and the producer. 

In the pre-industrial era, people mostly lived in smaller communities. This made it easier for distributors to manage the supply chain, as people could rely on personal relationships and verbal agreements rather than formal contracts. 

Industrial Revolution 

During the phase of the industrial revolution, supply chain management underwent some critical changes. The development of new technologies, such as steam engines and highly mechanized machines, led to the mass production of goods and services. 

This era revolutionized the way products were manufactured and distributed, as it became possible to manufacture goods on a large scale and at a lower cost. The supply chain became complex, with multiple sales channels involved in producing, marketing, and distributing goods. 

The industrial revolution was the steppingstone of supply chain optimization, which eventually led to the global trade of goods and the development of the international supply chain. 

20th Century  

The 20th Century witnessed significant changes and innovation in the supply chain. One of the most important developments was the invention of computers and information technology to manage and coordinate the flow of goods, location, information, and money in the supply chain.  

The innovation and introduction of enterprise resource planning (ERP) systems in the 90s was a crucial turning point for the supply chain digitalization process. This led to the rise of just-in-time and lean manufacturing practices. These systems also allowed businesses to integrate their business functions into a singular platform. This made operating inventory, tracking shipments, and coordinating with suppliers and manufacturers easier. 

21st Century 

The 21st Century has documented the continued evolution of supply chain management, with a keen focus on sustainability, improvements, and the integration of new-generation technologies. The use of advanced technologies such as SaaS, artificial intelligence (AI), blockchain, and SAP improved supply chain visibility and efficiency. These technologies helped companies to enhance their production and distribution processes, reduce excessive waste, and helped improve customer experience. 

A significant trend has been increasing focus on sustainability in supply logistic optimization. Businesses are becoming more aware of their supply chains’ environmental and social impacts. They are initiating steps to decrease their carbon footprint and improve working conditions for their employees. 

The supply chain has advanced to become a strategic organ within many organizations. Supply chain professionals are responsible for handling supplier relationships, optimizing warehouses with inventory planning software, predicting future demand with demand planning & forecasting software, and ensuring that products are delivered to customers on time and in good condition. 

Modern-Day Supply Chain Management Solutions 

For the past few years, the supply chain has continued to evolve expeditiously, offering shippers various solutions. Some of the most impacting developments have been: 

  • Concentration on real-time visibility and risk management, which improves customer satisfaction and reduces customer churn rate. 
  • Development of end-to-end supply chain, including reverse logistics. This helps businesses to maintain a perfect order rate and observe the entire life cycle of their products. 
  • Innovation of SaaS-based solutions to avoid supply chain inefficiencies.  
  • Solutions like inventory planning software enabling businesses to have optimum visibility to maintain leaner supply chains and intelligent transportation strategies. 
  • Introduction of newer technologies to access greater flexibility and better control for your inventory management to have improved logistic optimization. 

Industry Related News  

India has climbed up six places on the world banks logistic performance index of India 2023, now ranking 38th in the overall 139 countries index. This is a remarkable boost from their past ranking of 54th in 2014 and 44th in 2018. 

What is LPI? 

The LPI is an interactive benchmarking entity established by the world bank group. It helps countries identify the opportunities and challenges they face in their performance of logistics and what they can do to enhance their performance to achieve supply chain digitalization. 

LPI ranking parameters  

  • Logistic service quality 
  • Shipment tracking and tracing 
  • Ease of arranging shipments 
  • Timeliness of shipments 
  • Infrastructure quality 
  • Custom performance 

Transimpact – An Industry Leader in Supply Chain Management Solutions 

As a shipper, you have many options for your supply chain needs. But you need a brilliant, custom-made solution to your requirements, and able to work side by side with you. TransImpact offers a leading supply chain optimization system empowering you with data-driven actionable insights and an end-to-end technology solution. For a better understanding of our solution, call our experts or schedule a demo.

What do you need to know about naïve forecasting?

What Do You Need to Know About Navie Forecasting

Naïve forecasting is one of the simplest demand forecasting methods often used by sales and finance departments. It uses the actual observed sales from the last period as the forecast for the next period, without considering any predictions or factor adjustments. Though simple, it can work remarkably well for business. But it doesn’t account for the changing market conditions or seasonality, factors that can substantially affect demand. 

How is a Naïve Forecast calculated? 

Naïve forecasts can easily be calculated using spreadsheets. You can start by entering actual sales data for a certain period of time, say monthly sales numbers for the past two years. Use this data to enter forecasts for each period by choosing the actual sales data from the past period.  

Since the naïve forecasting method isn’t accurate and doesn’t account for many factors, it’s essential to calculate the error in forecasting or the deviation between the forecasted and actual sales. You can calculate the percentage variance between your actual and forecasted sales in the spreadsheets by using the formula –  

IF (Actual Sales = 0, 0, (Naive Forecast/ Actual Sales)-1) 

If the variance between actual and forecasted sales is positive (e.g., 9.05%), it means that your actual sales were greater than the forecasted numbers. This is often a preferred situation for sales professionals, allowing them to under promise and over deliver. On the other hand, if the variance is negative (e.g., -9.05%), it indicates that your forecasted sales were greater than the actual sales for a given period or that you sold less than the last period.  

 A variance of less than or equal to 10% isn’t considered problematic, but if the numbers are bigger (e.g., 41% or -41%), it can indicate bigger problems like a stockout or overstock. 

Seasonal Naïve Forecasting 

If you monitor sales data over the years, you will start noticing a pattern or trend in how your sales numbers fluctuate across seasons. A business that manufactures sweaters might experience high sales numbers between October and January and low numbers from April to July. On the contrary, a business that manufactures sundresses might see the opposite trend. 

Seasonal naïve forecasting is the process of generating better sales forecasts by accounting for seasonal change. Similar to the naïve forecasting method, this method considers the last actual sales from the same season as the forecast for the coming season – like considering the sales numbers for February last year as the forecasted sales for February in the current year.  

Though it isn’t entirely accurate, seasonal naïve forecasting can help you better prepare for your sales, especially if you experience an extreme change in demand for a particular season every year. 

The problem with Naïve Forecasting 

Though it is simple to calculate, naïve forecasts aren’t always the most accurate. As we mentioned before, the naïve method of forecasting doesn’t account for any significant factor that might affect your demand.  

Consider the percentage variance between your actual and forecasted sales that we discussed before. Suppose you get a high variance, like 41%, which would mean that you sold over 41% more products than you forecasted. Now, considering that you only held 41% more products in your inventory, there is a probability that you might have sold more had your inventory not run out. Similarly, a variance of -41% would mean that you sold less than forecasted, leading to overstocking in your inventory. You would have to pay extra to hold the excess inventory, and if you sell perishable products, it might also mean deadstock or inventory loss.  

In today’s dynamic markets, where demand fluctuates rapidly, naïve forecasting can lead to loss. A sudden bump in demand for a small period can cause you to overestimate your demand and lead to a loss in the next period. Similarly, a sudden drop can cause stockout and lead you to lose sales and often customers. Moreover, it can be hard for demand planners to determine factors affecting the sales, which might help them improve.  

Accurate Demand Planning 

When it comes to planning your demand accurately, there are many factors to consider. Though you can plan your demand manually, it can be time-consuming, inefficient, and error-prone. It is recommended  you use demand planning software to plan your demand better.  

TransImpact offers accurate demand planning software that lets you forecast and plan your demand for up to five years. It uses 250+ forecasting algorithms developed over the years to forecast your demand with up to 99% accuracy. It creates the forecast based on your past sales data, seasonality analysis, and market analysis and accounts for all the factors that affect your demand.  

You can use the forecast to better plan your inventory and ensure you have the right inventory, in the right place, at the right time. You can avoid losing sales and wastage associated with unplanned demand.  

Final words  

Though naïve forecasting is a helpful demand and sales forecasting technique, it is laced with issues that can lead to loss. These problems can be avoided by using demand planning software for your business. 

Get in touch to know how you can benefit from our demand planning software. 

Supply Chain Forecasting Methods You Should Know!


When we say forecasting, weather forecasting comes to mind for most people. We are very acquainted with the term, thanks to years of suit-clad weather forecasters gracing our breakfast time every morning. 

Just like the weather, forecasting is undeniably a significant part of the supply chain process. And just like weather forecasting, it refers to predicting upcoming business changes based on old data. 

Supply chain forecasting helps businesses estimate their sales and product performance and use that data to plan their supply chain smartly. When you can predict your supply chain, you can shape your production based on available products, manage inventory, and ensure availability.  

You can maximize your revenue while minimizing the losses in the supply chain. In the long run, it enables you to maintain a positive experience for your customers, enhance brand presence, and increase your credibility.    

What are forecasting methods? 

Forecasting methods are techniques used to estimate demand in the future based on your past sales, experts’ opinions, and more. There are multiple forecasting methods used by professionals, depending on their needs.  

They are essentially divided into two types – the quantitative and the qualitative methods. Where quantitative methods are objective and create forecasts based on data, qualitative methods are subject and rely on personal insights and observations.  

Quantitative Forecasting 

Quantitative forecasting is data-driven and based on facts. It is an unbiased process that utilizes historical data and analysis to create forecasts. They are based on mathematical models and calculations and are useful for short-term forecasts.  

Here are a few quantitative forecasting techniques given below. 

  • Naive Approach 

The naive approach relies on considering the past period’s actual sales as the forecasted sales for the coming period. It doesn’t account for any major variable that affects your demand. You can use a seasonal approach where you consider the actual sales from the same season or period from the last year as the forecast for the coming period. For example, you can use your past year’s October sales as the forecast for the October sales of the current or coming year.  

  • Moving Average 

In the moving averages method, you take the average of sales in past periods as the forecast for the coming period; say you use the sales data for the first four months to forecast demand for the fifth month, then the data from month 2 to 5 to forecast demand for the sixth month and so on. With time, as you remove old values and introduce new ones, you can move the average, hence the name. This method isn’t accurate and only useful for inventory control for low-volume since it doesn’t consider recent data’s significance in forecasting demand. 

  • Exponential Smoothing 

This method is similar to moving average, but takes a more weighted approach, adding significance to demand-altering parameters. The method focuses on recent data more while also considering old data. It is beneficial for short-term forecasting, but lags in successfully predicting future trends. Due to its reliance on historical data, it might predict demand patterns similar to the past or current ones. It also doesn’t account for seasonality during forecasting. 

  • Trend Projection 

Trend projection helps you successfully predict repetitive or seasonal trends by using your past sales data. It enables you to establish the relationship between various variables that affect demand. But it requires a large amount of long-term data to identify a pattern and properly analyze it. The method assumes that past trends will continue to be relevant and likely repeat themselves. But in reality, past data may not be apt to create a forecast for the future. 

  • Regression Analysis 

Regression analysis helps you establish a relationship between the independent and dependent variables that affect your demand. It helps you better understand your future demand based on the variables that affect them. You can add as many variables as you want to the equation. But typically, this method works best when few variables are involved, and any correlation between independent variables can affect your forecasts. 

Qualitative Forecasting 

A few significant qualitative forecasting techniques are discussed below.  

  • Executive Opinion 

The executive opinion method relies on the expertise of executive-level professionals to generate a forecast. The method is easy to perform and requires industry experts to form a collective opinion on how likely demand is to change. But it is highly subjective, relies majorly on the personal insights of the experts involved, and is found to have only poor to fair accuracy. 

  • Delphi Method 

Similar to the last method, the Delphi method also involves expert insights to generate a forecast. But, here, the forecasts are reviewed and discussed amongst the experts until they reach a common consensus. To avoid bias, personal insights are collected anonymously. It involves multiple discussions and is one of the most reliable qualitative forecasting methods available. But the process can be extremely cumbersome and time-consuming for the experts as well as the observer. 

  • Market Research 

Market research is extremely useful for businesses without historical data or during a new product launch. It uses competitor analysis, consumer surveys, polls, and questionnaires to create future forecasts. It gathers information to understand consumer expectations, bottlenecks, and potential issues to help you cater to your audience. Though useful, this method can be expensive, time-consuming, and can only target a small audience due to a lack of respondents. 

  • Historical Analysis 

This method suggests that new products would have a similar sales pattern to old ones. You can use sales data from your products or similar products from the competitors. Though it’s a good forecasting method for the long term, it won’t help you forecast trends or sales for the short term.  

  • Sales Force Estimates  

This method relies on the experience of salespeople to forecast demand based on the trends they’ve noticed in the sales over time. The process is simple and requires an estimate based on experience and expectations. The method has fair accuracy and is useful for short-term forecasting. But it requires managerial judgment to be useful, and human bias can affect the forecast accuracy.

How to find the best fit? 

Both quantitative and qualitative forecasting methods play a significant role in accurate forecasting. The ideal way is to use both moderately, but the methods differ according to your business goals. The best way to do that is to use demand planning software. It uses both qualitative and quantitative methods to give you precise demand forecasts for your business.  

TransImpact provides one of the best demand planning software in the market. It uses 250+ forecasting algorithms to give you accurate forecasts for up to five years. It uses historical data, competitor analysis, seasonality, trend analysis, market analysis, and more to ensure all demand-altering factors are considered. A thorough what-if analysis ensures that your business is prepared for any situation.  

Get in touch to learn how to optimize your supply chain with our software.