"Imperia creates an Analytics Demand Planning platform capable of optimizing and reducing costs associated with the supply chain"
Establishing a reliable demand forecast in a company is not an easy task. Various questions arise in different areas of the supply chain: How much and when do I need to manufacture? How many people do I need in the factory to meet the production plan? How much and when do I need to purchase raw materials? What level of inventory should I maintain?... To answer these questions, Imperia SCM was born, a young company with experience in specialized industrial sectors in Analytics Demand Planning. Three partners at the helm, Álvaro Bernabé, José Tomás Carrascoso, and Sergio Alemany, all have experience in consulting, ranging from strategic and operational to purely technological. Motivated to embark on a new project, they started from scratch with something that would motivate them every day and allow them to enjoy their work. "When you believe in something, you have to go for it. Ideas are just ideas until they are put into action, and all three agree that the time had come to take the leap, with the ups and downs. We believe in sacrifice and perseverance. We know that to make this a reality, we will have to give our all at all times." They define themselves as a company specialized in the application of analytics technology to support decision-making and process management in the supply chain. To this end, they launch the platform "Analytics Demand Planning" to the market, allowing organizations to manage their demand forecasting process and structure their information in a way that generates high added value and supports business decision-making.
"Ideas are just ideas until they are put into action." Sergio Alemany
Before we dive into the content, let's learn about the interesting story behind Imperia, which emerged during the professional careers of the three partners. During their time at Deloitte, Álvaro and José Tomás focused on projects in the operations and supply chain areas. Traditionally, the costs associated with the supply chain have always remained in the shadows and have not been an area of interest for organizations. "With the rapid pace at which we are faced with the arrival of new technologies and Industry 4.0, the need to optimize these processes and reduce costs has increased significantly in recent years," they assure. In their projects, they analyzed a large number of processes from different perspectives and a variety of companies, from fast-moving consumer goods to distribution or manufacturing. The projects they worked on shared a common similarity: How does the organization support and execute the defined and optimized process? To answer this question, existing products on the market were analyzed, and the one that best met the identified requirements was chosen. Imperia emerged when carrying out demand forecasting projects. After analyzing, optimizing, and defining the demand forecasting process that the organization would follow in the future, the tool selection phase arrived. At this point, the need for a niche tool that supports the process at a low cost, is adaptable, and scalable to the operational needs of clients became apparent. Motivated by the idea that such a tool could find its place in the market, Imperia was born with the aim of creating a high-performance technological product supported by Excel that can manage the demand forecasting process of organizations. Furthermore, Álvaro and Sergio had already worked together during their university days on some software development projects. Both had the idea of starting a venture in the future and agreed that this project could be the right one. As a result, Álvaro, Sergio, and José Tomás began working together from the very beginning to shape the business model.
Let's dive into the content. What value does Analytics Demand Planning bring to companies?
The leaders of Imperia explain that we are dealing with a critical process before making decisions, and that is where Imperia comes in by creating the "Analytics Demand Planning" platform. It takes a company's sales history and stores it in a database. Based on this history, it generates a demand forecast using various statistical models and selects the one with the lowest error by comparing it with the sales history of the most recent period.
"With accurate sales forecasting, companies can obtain high-value information for decision-making." José Tomás Carrascoso
Demand forecasting is key for a company...
When we talk about demand forecasting, we are referring to making estimates about future customer demand using sales history and other information. With accurate sales forecasting, companies can obtain high-value information for making decisions related to the business, both at a strategic level (pricing or potential markets) and a structural level (production capacities, purchasing, or inventory levels).
Traditionally, the majority of companies have used Excel spreadsheets to manage demand forecasting, applying basic corrective factors to estimate future sales forecasts based on historical sales. This can lead to numerous errors, including information loss, duplications, or forecasting mistakes.
Let's talk about a real example
Consider a company that manufactures and distributes nuts. Within their processes, they need to handle raw material procurement, manufacturing, storage, and distribution to end customers.
By managing their demand forecasting process through Analytics Demand Planning, the company can enjoy numerous benefits.
With improved sales forecasting through the calculation of statistical methods, the company will enhance its level of customer service, thereby increasing sales (delivering products that were previously unavailable due to lack of stock).
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Based on this forecast, the company can optimize production to meet the projected demand. In addition, they can plan the necessary resources to carry it out or smooth out factory capacities (avoiding overtime, which represents significant personnel cost savings).
Finally, by aligning production planning with the forecasted demand calculated in Analytics Demand Planning, the company can organize raw material purchases so that they are available in the warehouse when needed. This can reduce procurement costs by up to 50% by avoiding last-minute purchases of raw materials.
How did you pivot towards Imperia Analytics Demand Planning?
Initially, Imperia aimed to create a technological tool that supports the demand forecasting process. This management was focused on a "common" functionality found in any tool that manages the demand forecasting process: loading sales history, cleansing data, performing statistical forecasts, cleaning the forecast, and establishing the sales plan.
Although we believed that this product could find its place in the market, we wanted to do something different, something that would retain the initial essence but break away from existing solutions and provide additional value to customers, which is why we chose AnalyticsDemand Planning.
Analytics Demand Planning
Here is where the word "Analytics" comes into play. From the very beginning, we were clear that the tool would include a dashboard where users could analyze the data contained in the tool: segmented sales at any level, aggregated sales forecasts, demand behavior, and more.
So, if we already had this, which we could consider as the foundation for an analytics model, why not incorporate the essence of analytics into the tool itself? This would generate additional added value for organizations using Analytics Demand Planning.
And finally, by aligning production planning with the forecasted demand calculated in Analytics Demand Planning, the company can organize raw material purchases so that they are available in the warehouse when needed. This can reduce procurement costs by up to 50% by avoiding last-minute purchases of raw materials.
What steps did you take to validate our business idea?
You could say that the validation and development of the business model occurred simultaneously. During our time in consulting, we validated the business idea and saw how organizations increasingly demand tools that support all their production processes in the supply chain area. These range from cutting-edge market solutions (ERPs with advanced functionality) to niche tools that manage specific supply chain processes.
Therefore, once we "validated" that developing such a tool had a place in the market, we began shaping the business model, trying to incorporate the requirements and functionalities that were not covered by existing tools on the market.
How much can we trust the data?
Data is unorganized knowledge within an organization. If it is organized and analyzed properly, it can generate high added value. We believe in trusting the data, not for making the final decision, but for supporting decision-making and providing a reasoned justification.
Our platform analyzes the sales behavior of a specific product, and based on its variability (both in quantity and frequency), it suggests the appropriate treatment. For example, it may recommend that the sales manager review certain data because it carries inherent risks according to the analysis conducted by the tool.
Our solution has a strong analytical component, allowing you to measure, analyze, and visualize your information in an organized manner. It includes historical demand analysis, version comparison, ABC analysis, XYZ analysis, deviation against forecast (DFA/BIAS), and analytics in Excel, PowerBI, and QlikView.
The main barrier to entry in organizations is change management
Are organizations prepared for it?
Yes, with the rapid penetration of new technologies in the industry, organizations have adapted and prepared themselves for their incorporation into their structures. Nonetheless, to varying degrees, all organizations are working on it and would be prepared to incorporate Analytics Demand Planning into their businesses.
What are the barriers to entry in organizations today?
The main barrier to entry in organizations is change management. This means making investments in both human capital and finances to integrate and learn how to use new systems within the organization. On the other hand, there is the maturity of market players, as there are already established tools in the market with years of experience.