Supply management is crucial to the day-to-day running of a business. However, many companies still rely on unsuitable tools that quickly show their limitations. In this context, Business Intelligence is an excellent alternative to Excel for inventory management.
Stock and supply management: what is it?
Inventory management is a set of techniques for controlling the flow of goods in and out of the warehouse. For the company, the objective is to guarantee the immediate availability of any product in the event of an order, in order to meet demand. At the same time, it must limit storage costs as much as possible, while avoiding losses and waste.
Depending on the company and the sector, stored goods can take different forms. In retail, they are finished products for sale. In industry, on the other hand, it may be raw materials or intermediate products.
Supply management involves the acquisition of new goods, whether they are raw materials for the manufacture of products, products for resale to the end customer or goods for storage. It is therefore an integral part of inventory management.
The limits of stock management with Excel
Many companies use a spreadsheet program such as Excel, Numbers, or Google Sheets to manage their supply chain. This type of software has the advantage of being versatile and flexible, as it is used by all functions of the company. It is also relatively inexpensive, if not completely free: this is the case with free alternatives such as LibreOffice Calc.
With a spreadsheet, it is possible to sort and classify products according to predefined criteria, to make automatic calculations for inventory management, to generate graphical representations for analysis… All this with an unlimited volume of information and easily shareable files.
However, using Excel for stock management is not a miracle solution and the spreadsheet has its limitations:
- It lacks connectivity with business solutions and the company’s website, as it cannot interface with other software. Therefore, you have no choice but to re-enter the data in your accounting software, your CRM or any other tool.
- It requires manual data entry, which is a major source of human error and can have a significant impact on the company’s business. As a result, the reliability of the data is not guaranteed, especially as inconsistent data may not be flagged by the software.
- It is not very secure, as it is only necessary to duplicate a file in order to modify the data it contains. Although it is possible to define security macros or to lock cells, the spreadsheet’s functionality is insufficient in this respect.
- It is not updated automatically. Therefore, all data concerning supplies, use of raw materials, sales, etc. must be updated manually.
- It does not offer global visibility, at any given moment, on stock and supply management. Firstly, because the data is not updated in real time, but also because it quickly becomes obsolete after successive file exchanges.
- Finally, Excel does not allow for the automation of supply chain management tasks due to the lack of connectivity with other tools, real-time data updates or automatic generation of reports and analyses. Human intervention is required throughout the process.
Why use stock management software as an alternative to Excel?
To optimise stock management, digitalisation, and automation are now essential, not to replace human work, but to make it more efficient and reduce the risk of error.
Therefore, the interest in using a specific stock management tool, rather than a spreadsheet with limited functionality. As a result, companies are increasingly turning to ERP (Enterprise Resource Planning) systems with a dedicated module or WMS (Warehouse Management System) designed to manage supplies.
Indeed, this type of software brings many benefits:
- Employees gain productivity through a range of features that simplify their daily work.
- Low-value tasks can be automated, allowing employees to save time and focus on more important tasks.
- The risk of input or calculation errors is greatly reduced.
- Space availability is updated in real time, allowing for optimal use of storage space.
- Dashboards, reporting and predictive analysis help to synthesise information and make better decisions.
- Finally, a stock management system represents a real added value in the face of competition, particularly in areas of activity where margins are low.
Business Intelligence for Supply Management
With a Business Intelligence solution, the company can go even further in managing stocks and supplies. Far from being an equivalent of Excel, this type of tool allows a multitude of different information to be synchronised in real time: warehouse, shop, orders, purchases, stocks, raw materials, transport, etc
Gathered in a common data warehouse, this data can be processed and analysed with the help of algorithms, in order to predict stock shortages, shortages of raw materials, orders to be placed with suppliers, but also storage and warehousing costs.
However, in order to exploit the full potential of Big Data, it is necessary to distinguish between the different types of data available to the company.
Internal company data
This is data from the internal workings of the company, for example :
- Purchase history: purchase orders, invoices, delivery notes, supplier information, etc.
- The history of orders placed by the company’s customers.
- Internal company departments and projects involved in the ordering process.
- Customer data: geographical and socio-demographic information, behaviour, purchasing habits, etc.
- Information related to storage and warehousing.
Supply chain data
To optimise stock management, the data inherent in the supply chain is also used, for example :
- Data from suppliers (and their own suppliers): delivery times, quantities of products available, quality of raw materials, etc.
- Information from transporters and other actors involved in the delivery of raw materials and products.
- Data relating to other players in the supply chain: distributors, warehouse managers, etc.
Data external to the company
External data, which is not linked to the company or the supply chain, can also have an impact on supply management. For example:
- Road traffic and construction data to optimise routing and delivery routes.
- Information related to the social or political context: social movements, strikes, etc.
- Weather and climate data.
By combining these different types of data, it is possible to identify correlations between several elements:
- Customer demand.
- The company’s production.
- The ability of suppliers to deliver raw materials.
- External factors (road traffic, social movements, climatic hazards) that may affect the supply chain.
The benefits of Business Intelligence for inventory management
Ultimately, optimising stock and supply management allows the company to increase its competitiveness, while reducing its logistics costs. But with the help of Big Data and artificial intelligence, it can also perform more advanced analyses and achieve different objectives:
- Classify products with a high degree of granularity, taking into account the speed of stock turnover.
- Better understanding of market trends, for better management of stocks and customer demand.
- Highlighting product assortments: for example, groups of products purchased simultaneously.
- Improve purchasing decisions: make regular orders to avoid stock shortages, make group orders to reduce transport and delivery costs, etc.
Ultimately, the adoption of Business Intelligence for supply management allows for smoother exchanges, lower logistics costs and lost sales, and ensures customer satisfaction. Indeed, BI enables the company to deliver the right product, at the right time, at the right price and in the right quantity. And this is just a small sample of the various benefits for the supply chain.
Faced with the obvious limitations of spreadsheets, Business Intelligence is emerging as a real alternative to Excel for inventory and supply management. Flexible and customisable, with no proprietary language, a BI solution adapts to the needs of each company to help it exploit the full potential of its data. By relying on predictive analysis, it can make the best decisions and sustainably optimise its supply chain.
