Key aspects of choosing a vendor. Choosing the best demand forecasting system

The demand forecast affects the entire supply chain. By planning sales and having understanding of the future demand, you can not only ensure the right amount of products on the shelves, but also understand what activities need to be carried out with specific product positions in order to generate additional profit. In addition, this allows you to maintain a high level of availability of goods with minimal inventory.

Human error factor
Read the article to find out.

Demand forecast nuances

Subjectivity and process dependence on specific specialists numerous disadvantages:

Human error factor

People are more likely to make mistakes when performing routine tasks. This often leads to extra costs or lost profits.

Subjectivity and process dependence on specific specialists

The need for manual data updating
when a new person comes, difficulties arise in understanding the processes. This leads to errors in calculations, and also entails the “dependence” of the process on individual employees.

Another familiar situation is when it is difficult for managers assigned to certain SKUs to go on vacation. When delegating tasks, the load on the remaining team increases, and when creating reserves for the period of their absence, the warehouse gets overstocked.

The need for manual data updating

The spreadsheet approach involves regular manual updating of the data by individual employees. And this increases the overall cost of labor.

In an effort to get a better forecast, business owners often turn to specialized analytical firms. However, this requires a lot of time to process a large amount of information and creates the risk of not getting very up-to-date output. The reason for this is dynamic changes in external factors.

Vendor’s experience solutions are able to take into account not only external and internal factors affecting demand, but also make the forecast as fast as possible, which is extremely important in today’s changing world.

Things to consider when choosing a demand forecasting solution

• Flexibility of forecasting terms to choose the best demand forecasting software among the many options on the market? We suggest taking into account the following points:
• Vendor’s experience

It is important that the solution vendor has a broad implementation experience, including cases from your industry. Regardless of the project complexity, the vendor must provide you with quality support at all stages of deploying and using the system.

• Available integration with related systems

In the context of the period, the forecast can be short-term, medium-term or long-term. Depending on the business need at a particular point of time, a different forecast may be required: from a week to a quarter for planned purchases, and from six months to develop a strategy. However, not all vendors can guarantee an approach with the simultaneous implementation of a forecast for different periods, so it is important to choose a system that can not only adapt to existing processes, but also quickly adapt to their change. For example, the opening of additional points of sale or the emergence of new commodity items should not create difficulties for the forecast.

Data securitytaken into account in the SMART Demand Forecast system. To learn more about the solution capabilities, fill out the form.

• Available integration with related systems
• System balanceup-to-date data for the forecast is taken from the database automatically, without requiring manual intervention.
• Data security

Since you trust the vendor with the most important information, that is, your data, the leveling of all risks in the NDA agreement is mandatory. And given that Ukraine is now actively integrating into Europe, an important criterion for choosing any modern system for business is its compliance with the GDPR (General Data Protection Regulation).

• Analytical reporting

More doesn’t always mean better. This principle also applies to the number of algorithms in a demand forecasting solution. There is a concept of ‘overtrained model’, when a solution analyzes extra data that does not affect demand. In addition, taking into account such factors, you can reduce the forecast accuracy. An experienced vendor knows which algorithms and how many factors are optimal. Such an individual approach will significantly improve the quality and accuracy of the forecast.

analysis of historical sales based on different levels of granulation & AI is an elaborate process that involves handling a significant amount of data. If you doubt the advisability of using a system based on artificial intelligence and machine learning, fill out an application for a detailed consultation from our experts.

• analysis of sales extremes and assistance in their study by various filtering of such reports
• the ability to compare the forecast quality due to historical data from the past period, thus controlling the improvement or deterioration of the forecast quality
• analysis of compensated sales. Mathematical algorithms of the system model the level of sales, taking into account out of stock
• analysis of sales extremes and assistance in their study by various filtering of such reports
• Existence of a trial (pilot) projectforecast quality due to historical data from the past period, thus controlling the improvement or deterioration of the forecast quality
• analysis of compensated sales. Mathematical algorithms of the system model the level of sales, taking into account out of stock
• Future support
• Existence of a trial (pilot) project

Having a pilot project is key when choosing an implementation partner. The opportunity to test the system will form an understanding of its capabilities, and most importantly, it will answer the question of whether you need a tool for demand forecasting at all. If the answer is no, then at least you will know what exactly you need to improve in order to build an accurate forecast. For example, if you become interested in SMART Demand Forecast, you will first receive an expert analysis of your situation from our specialists and a detailed action plan. Only after that we start the launch of the pilot project, analysis of its effectiveness and fully-fledged implementation. Thus, thanks to pilot projects, you can compare several solutions and choose the best one. The main thing is not to forget about the security of your data and insure yourself by signing an NDA.

• Future support

Before you start implementing demand forecasting tools, make sure that the partner can provide you with adequate technical support, not only during the implementation of the solution, but also in its further use.

Key points of the implementation procedure you should focus on  

At the initial stage of choosing a vendor, ask how the process of implementing the solution will be built, how the areas of responsibility will be determined, etc. This way, you can prepare your specialists and determine the expectations from the project. Using the example of the SMART Demand Forecast implementation procedure, we’ll look into the features of all stages:

1. The purpose of the first stage is the analysis and collection of the necessary data. The task of the vendor is to say exactly what data the system needs for a better forecast. Depending on the requirements, you and your contractor determine whether implementation can begin now or additional preparation in the form of historical data collection is required.
2. The second stage involves preparing data for entering into the system and launching a pilot version.
3. The next step is user testing of the system. Specialists on the vendor side conduct training for end users in accordance with the roles.
4. Subsequently, the project involves informational and technical support.

1. Analytics and data processing: the forecast should be based on data obtained as a result of integration, and the calculation should be carried out in a timely manner.
2. Automation: to ensure the transparency of the process, the human role in forecast development must be minimized.
3. Flexibility: the selected system must adapt to emerging additional requests. Whether it’s the emergence of new points of sale or the need for a longer-term forecast, you need a guarantee that you will not have to change the system due to changes or scaling of the company.
4. Analytics and data processing: the forecast should be based on data obtained as a result of integration, and the calculation should be carried out in a timely manner.
5. Automation: to ensure the transparency of the process, the human role in forecast development must be minimized.
6. Flexibility: the selected system must adapt to emerging additional requests. Whether it’s the emergence of new points of sale or the need for a longer-term forecast, you need a guarantee that you will not have to change the system due to changes or scaling of the company.

Have questions regarding SMART Demand Forecast? Contact us: sales@smart-it.com.