Tag: demand and capacity planning

demand forecasting

Top 3 Demand Forecasting Challenges Facing the Retail Industry in 2019

In today’s data-centric world retail environment has grown even more complex. With the influx of consumer data, businesses like retail need to have a better mechanism for demand forecasting in order to improve their customer service and stay ahead of the competitors. A good demand forecasting model enables businesses to smartly use their historical data on consumers and help them to plan strategies for future trends. Also, demand forecasting techniques help companies to anticipate when the demand will be high and establish a long-term model that can help in business growth. Retailers with the help of demand forecasting model can eliminate their dependency on instinct and intuition for decision-making. However, demand forecasting seems to be easy but in practice, retail businesses face critical challenges in building a demand forecasting model that can help them to deal with the ballooning complexities in the retail environment. In this article, our retail industry experts have listed out a few challenges that players in the retail industry are poised to witness in 2019.

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demand forecasting

Demand Forecasting Challenges

Challenge #1: Using an integrated system to track customers and business

Over a period of time, most retail companies have built out their operations and have deployed systems as they need them. This often means retailers have one system for their enterprise resource planning and another for customer resource management. Though such systems have solved the incremental needs of retail companies, the ongoing digital transformations along with the need to maintain interoperability have proved to be a barrier in two ways for retailers. First, it is resulting in duplication of information in both systems that create a siloed approach and impacts efficiency. Second, with such a system it is difficult to gain actionable insights into unstructured data sets. Lack of unintegrated system makes it difficult for retailers to improve their business operations.

Are you finding it difficult to analyze, monitor, manage, and benchmark your demand and capacity planning strategies? Our demand forecasting solutions can help. Get in touch with our experts right away.

Challenge #2: Applying the correct methodology for strategic decision-making

Retailers are making strategic decisions by setting goals for the company at large rather than for specific regions. Without a focused approach, retailers fail to gain visibility into where growth is expected. Also, such an approach does not help them to identify the regions that outperform in the competitive market and which ones underperformed against easy regional targets.  Therefore, having a proper demand management process in place is important for retail businesses to get away with instinct based decision-making.

Challenge #3: Leveraging unstructured datasets to forecast the next step

Today players in the retail industry are struggling to leverage external data or customer profiles effectively. Customer profiles offer detailed insights into what customers want enabling companies to understand demand better. Also, by using external data businesses can improve their accuracy of forecasts by accounting for external forces that were overlooked previously. Building demand forecasting models can make it possible for retail companies to distinctly segment customers and analyze the demands and preferences of target customer segments.

Our demand forecasting solutions can help you create automatic recommendations for the line-of-business to allocate, schedule, plan, and automate processes. Request a FREE proposal now to know more about our portfolio of supply chain services.

How can Quantzig help you take your demand forecasting to the next level?

Quantzig offers demand forecasting solutions that help businesses to create accurate demand capacity and plans. Our demand forecasting solutions and help companies to boost their forecast accuracy, improve service levels, manage portfolios, and maximize return on demand planning efforts. Quantzig, with its expertise in offering demand planning and forecasting solutions, empowers businesses to discover hidden performance drivers, increase profitability, improve collaboration, validate their business strategies, gain a 360-degree view of demand, and optimize ROI on operational spend.

Request a FREE demo below to find out how our customized analytics solutions can help you address the complexities of today’s consumer-driven marketplace.

Retail Inventory Management

3 Steps to Develop an Effective Capacity Planning Process

Irrespective of the size of the business, every manufacturing business benefits from the financial and logistical capabilities of capacity planning. The capacity planning process is a method of project management that takes into account the efficient use of resources through a projection of production needs. Establishing a proper capacity planning process is important for companies to maintain workforce and product manufacturing. The capacity planning process does not need to be onerous, but it should involve carefully thought-out steps to ensure businesses have the right amount and type of resources at the right time. That is why resource planning forms an integral part of the capacity planning process. In this article, our supply chain analytics experts have laid down a few important steps that are critical to developing an effective capacity planning process.

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Steps to develop an effective capacity planning process

CAPACITY PLANNING

Determining service level requirements

This is the first step in the development of a capacity planning process. In this step, a business needs to break down work into categories and quantify users’ expectations for how that work gets done.  This step involves three stages:

  • Establishing workloads
  • Determining the unit of work
  • Setting levels of service

Businesses can organize workloads by specifying either who is doing the work, the type of work performed, or the process of the work. Workloads measure the number of resources needed to accomplish the work, a unit of work helps in measuring the quantity of work completed and setting service levels helps in laying out acceptable parameters between the provider and the consumer.

Our demand and capacity planning solution help companies to ensure cost containment and improve capacity management. Request a FREE proposal now to know more about our service portfolios.

Analyze current capacity

The next step in developing the capacity planning process is to analyze the current capacity of the business operations. Businesses need to analyze their current production schedule for better capacity management. They should analyze each workload by following these four steps:

  • By comparing the measurements of any items referenced in service level agreements with their objectives
  • Strategic resource planning and checking the usage of every resource of the system
  • Analyzing the resource utilization for each workload and identifying workloads that are the major users of each resource
  • Determining points where each workload spends its time and gaining insights into which resource takes the greatest portion of response time for each workload

Quantzig’s capacity planning solutions can help you gain complete visibility into your supply chain processes and optimize your production capacity. Request a FREE demo to know more.

Plan for the future

This is the final step involved in developing an effective capacity planning process. Once the current capacity is analyzed, businesses need to know the amount of work that is expected to come over the coming quarters. Following this, they need to configure the optimal system for satisfying service levels over this period of time. The optimal configuration ensures you to meet service level requirements and offers an opportunity for companies to optimize their production process and prepare themselves for the future.

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capacity planning

Demand and Capacity Planning Helped a Machine Manufacturing Company to Reduce Demand Forecasting Errors by 10%

A leading player in the machine manufacturing industry wanted to reduce the percentage error in their demand forecasting approach, which was approximately 45%. The inconsistent nature of their current demand and capacity planning processes curtailed their ability to manage inventory stocks and ensure the ready availability of high-demand products.

The Business Challenge

Demand and capacity planning turns out to be a crucial factor when it comes to simplifying the logistics value chain. It’s growing popularity can be attributed to its ability to integrate smarter demand forecasting and predictive analytics into the capacity planning process. Unlike the obsolete demand forecasting processes where businesses had to rely solely on historic demand patterns to plan for future production needs, analytics-based capacity planning strategies empower businesses to tailor their production capacity to more accurate demand forecasts that account for numerous variables across the supply chain.

Embrace the power of analytics-based demand management solutions to gain a leading edge in the market. Request for more information now!

The client wanted to leverage demand and capacity planning to reduce their average percentage error and drive productivity. One of the core objectives was to analyze and understand the demand patterns across various regions. To do so the client chose to partner with Quantzig to leverage its demand and capacity planning solutions to coordinate their capacity planning efforts in different countries, including rationalizing SKUs and consolidating suppliers.

Solutions Offered and Value Delivered
To help the client tackle their challenges, we developed a robust demand and capacity planning framework, which included recommendations for capacity management and safety stock optimization. By leveraging demand and capacity planning solutions, we successfully reduced the total average percentage error to less than 10%, while simultaneously improving capacity management. The result was a multi-step, holistic framework developed to optimize the client’s supply chain operations. However, a significant factor of success was the comprehensive consideration of costs, real-time demand patterns, and lead times when determining the best way to maximize ROI through capacity management.

Request a FREE demo to understand how we can help you manage production capacity based on accurate, real-time demand forecasts.

Furthermore, we also improved the accuracy of demand forecasts with added business constraints, such as minimum order quantity, ordering intervals, demand patterns, and total lead times to identify and quantify risks associated with out-of-stock scenarios. The use of analytics dashboards further improved the efficiency of their demand and capacity planning process.

Quantzig’s advanced analytics solutions also enabled the client to:
• Improve demand forecasting accuracy
• Overcome out-of-stock scenarios
• Improve production capacity

From demand forecasting to capacity planning, we have the expertise and the domain knowledge to address all your supply chain challenges. Contact us to know more about the benefits of our demand and capacity planning solutions.

demand and capacity planning

Top 3 Factors Influencing Demand and Capacity Planning of Businesses

Demand and capacity planning forms an integral part of any manufacturing business irrespective of its size. Every manufacturing facility benefits from the logistical and financial potential of demand and capacity planning methods. This method includes the systematic use of resources through a proper estimate of production needs. Demand and capacity planning help manufacturing businesses to identify underutilized resources and opportunities. Also, demand and capacity planning enable businesses to manage demand based on business priorities and make smart and well-informed decisions. However, coordinating supply with current demand is a daunting task for manufacturing companies and is influenced by several factors. Here in this article, our team of experts has highlighted a few factors to help companies optimize their production schedule and supply process and excel in the competitive business sphere.

Automating demand and capacity planning can help companies share updates in real-time across the supply chain and improve demand management. Get in touch with our experts to know more.

Demand and capacity planning

Top factors influencing demand and capacity planning

#1: Identifying the bottleneck

For efficient demand and capacity planning, it is important for companies to identify bottlenecks. To do this manufacturing businesses need to estimate the overall capacity relative to overall demand along with the capacity of individual resources. Also, skilled workforce is required as it plays a pivotal role in the chain of production and supply. This can further help in improving demand and capacity planning.

Our customizable supply chain analytics solutions can help businesses to synchronize demand planning with production and boost profitability. Request a FREE proposal now to know more about our portfolio of services.

#2: The unpredictability of constraints

Demand and capacity planning can be obstructed by the constraints such as inaccurate demand forecast, limited supply of raw material, unrealistic sales goals, and the unavailability of required skills. Therefore, to yield the desired outcome, it is important that companies conduct a thorough analysis of dynamic demand patterns and have accurately predicted the constraints.

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#3: Maximize capacity to meet demands

Without proper capacity planning strategies in place, it is difficult for businesses to deal with the variability in demand. Therefore, it is important that capacity should be maximized by adopting measures such as bringing equipment online that is not normally in use, outsourcing work to other suppliers temporarily, or switching workforce from one production area to another. Also, businesses can conduct realistic data analysis utilizing advanced supply chain data analytics solutions to make smart capacity planning decisions. 

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