How to series
How to lose your inventory management game in 7 ways. Part 1
How to series

How to lose your inventory management game in 7 ways. Part 1

10 min read
Irma Shypulia
Irma ShypuliaRetail Optimization Expert
How to lose your inventory management game in 7 ways. Part 1

Inventory is the main asset of any retail business. Efficient inventory management and continuous monitoring make it possible for the business to multiply profits and avoid excess inventory and financial losses. Read in our material in two parts what factors affect the success of the chain and what mistakes in inventory management should be avoided.

1. Not having a process to get clear, up-to-date data

Even the most efficient inventory management system fails without high-quality data. Qualitative data refers to factors such as accuracy, completeness, relevance, reliability, and consistency. Why is this so important?

In terms of inventory management, one of the most important tasks is the accuracy of orders. It is based on the analysis and simultaneous consideration of a large number of factors to determine dependencies, the elasticity of demand and building forecasts. Without correct sales and inventory data, it is difficult to build baseline forecasts using standard statistical methods. And if we are talking about using ML/AI methods, for example, to predict promotional sales, then statistics are indispensable, because huge amounts of data are used to build models (for example, LEAFIO AI Retail Platform takes into account: promotional sales with reference to discounts, types of promotions and mechanics, information on additional places, etc.), which are most often found in different sources and can be contradictory and with different formats of data or not available at all.

Except for the above, other factors also affect the accuracy of orders: the availability and correctness of the product matrix, up-to-date information on delivery schedules, suppliers’ minimum order quantity, timely closing of orders and carrying out inventory, write-off procedures, etc.

The quality of incoming data directly and very strongly influences forecast errors, which entail the negative consequences of surplus and shortages and can cost a company a lot of money. There is also a huge potential for using factors and data that are not currently involved in machine learning models.

To avoid data quality failure, you should:

  1. Establish business processes: at the system level, prohibit backdated operations and adjustments after document closure, ensure timely posting of documents, regulate inventory and write-off processes, automate the acceptance and closing of orders, etc.;
  2. Reduce the number of manual operations = the influence of the human factor: forgot, entered information incorrectly or into the wrong system;
  3. Strive for a single source for entering and updating incoming data;
  4. Appoint those responsible for each process and the relevance of the data, those who approve and who make changes;
  5. Automated error checking: for example, checking for duplicates, data formats, omissions/missing data in values, for inconsistency. With errors shifts the focus of attention only to problem areas, which increases the likelihood of working out and correcting shortcomings;

Operational dashboard for daily tasks

Operational dashboard for daily tasks in Leafio Inventory Optimization System

  1. Conduct data analytics in order to identify non-trivial errors. For example, in the LEAFIO AI Retail Solutions system, it is important to work with the following reports:
  1. The report on doubtful residual inventories shows a product with a residual, but with no sales for a certain period of time (depending on the category of demand for the product). With this report, you can identify goods with a frozen residual and work them out, which will ultimately increase turnoverю
  2. The order quantity report shows when the goods lower than the quantity was delivered. By working with it, you can find errors in the data, which helps to improve the order accuracy and avoid unreasonable surplus.

Data quality improves the accuracy of BI analytics tools and makes business users more likely to rely on them than on their own intuition or spreadsheets. This leads to more efficient business decision-making and subsequently increases sales, optimizes internal processes and gains competitive advantage.

2. Not having correct KPIs for each supply chain manager (category managers, demand planners, trade marketing team, logistics dept.)

There is a wide range of KPIs for supply chain management. But the basic metrics for inventory managers are considered to be the following:

LFL report in Leafio

LFL report in Leafio Inventory Optimization System

It is important to be aware of the KPIs of past periods, whether they got better or worse, and compare them with the target standards. This is the only way you can draw a correct conclusion about how efficiently you manage inventory.

The right combination and integration of these metrics have a much greater value for the efficiency of the entire system than using KPIs separately from each other. Bad examples of using single targets in the motivation system can be quite costly for a company.

A great example is the availability and turnover KPIs for purchasing managers that give a real indication of inventory health by balancing each other out. The category manager KPI can be focused on fulfilling the turnover plan (considering rebates), marginal profit of the category and turnover, as well as assortment optimization KPI (share of hard sell and low-turnover goods), compliance with category inventory standards (%), comparison of category development dynamics on the market and within the company. For demand planners, these are statistical indicators of forecast accuracy (for example, WMAPE) and financial indicators for lost sales, surplus and turnover. The trade marketing specialist team monitors the account growth and the increase in brand awareness, i.e., brand loyalty KPIs (these are: profits, penetration, average check, market share, profit per shelf meter, etc.).

Yes, each metric has its advantages and disadvantages, but remember that each business has its own goals: for example, rapid growth or maintaining market share. Accordingly, the “correct” supply chain KPIs will vary depending on the company.

Sometimes, finding the “right” KPIs is a matter of trial and error. To make it easier, try to avoid common mistakes in building a supply chain KPI system:

In general, KPIs provide insight into how well a company is progressing towards its goals and inform of the decisions made. In the event of inventory management, close monitoring of KPIs can help improve order accuracy, detect and respond to changes in demand, reduce surplus and lost sales, and consequently increase profits.

3. Not having top-notch tools for inventory management

The importance of having an effective inventory management tool cannot be overstated these days. These tools are designed to perform the following tasks:

The system objectives are to achieve high order accuracy, prevent stock-outs, speed up turnover and reduce write-offs, all of which increase sales and profits. This gives managers more time to analyze and eliminate problematic issues due to current assignments.

You should urgently reconsider using your inventory management tool if you notice the following triggers:

Proper inventory management will improve customer satisfaction and the efficiency of the entire supply chain.

We share the results of our clients: reduction of surplus by 30-60%, sales growth by 20%, turnover acceleration by 20-30%, and release of money out of inventory.

Continue reading in Part 2.

Irma Shypulia
Irma ShypuliaRetail Optimization Expert



Don't miss our weekly news letter