INVENTORY KPI

The first thing to do is to understand in which processes of the company to invest time and money.

It is necessary to select the most important processes, those that create value, to break them down into phases and activities so as to identify the performance associated with all the phases and activities identified.

For each performance considered useful to be monitored, it is necessary to define the actual KPI, i.e. to establish the metrics, the method of calculation, to establish the frequency of determination, and then every time to reprocess the data to determine the result and to verify the deviation from the previous measurement.

One would set targets, ranges of values for each KPI, and also set thresholds of values that would trigger an alert if reached or exceeded.

Establish the level of aggregation because there is a hierarchical level that links activities, phases and processes and there will also be a hierarchical level in the KPIs linked to them, and finally we need to establish the source of the data, i.e. the data used to calculate these indicators come from which systems.

The next step is to formalize a documentation, describe the processes, list the KPIs, describe the properties, requirements, etc. This step is important because it allows everyone to know how to carry out that particular activity and to have a basis for thinking about an improvement process.

Finally, it is necessary to verify that what has been constructed makes sense, to verify for example by means of known data whether the results obtained are equally known, to verify whether when faced with extreme situations the result is equally extreme,

otherwise it means that there is an error in the metrics, then test and finalize what has been done.

SPECIFIC STOCK

A productivity-related performance indicator that the planner must monitor is the specific stock.

In order to understand what type of solution to adopt, whether to use the same storage solution for all products handled by the company for example, the planner performs an analysis of the stock profile, an example of which can be found in figure 31.

Figure 31: ABC Analysis for the choice of storage solution

In the first table, the quantity of pallets in stock compared to the number of articles handled in the warehouse, so this gives us an idea of how many pallets per article there may be.

Reasoning in overall terms, it can be seen that there is an average of around 7.5 pallets per article and this is neither high nor low, so when faced with situations of this kind, one has to think about whether multi-depth solutions can be efficient or not.

When there comes a point where the choice on which solution to adopt is not

immediately apparent, one can use an ABC analysis, which is a statistical analysis used to categorise a company's inventory by assigning a class to each item (or SKU, stock keeping unit). Typically, class A is the class associated with the most sold or consumed items and class C with the least sold or consumed items.

In this case, we see that 19% of the items use 74% of the pallets in stock. So if the total average was 7.5 pallets per article, in reality for these first 800 articles, the average stock pallet is almost 30 pallets per article.

Even at this point, one might think of moving towards solutions that increase stock density for these class A articles and use more conventional solutions for the remainder

of the articles (class B and C) which are a majority in terms of articles but represent a minority in terms of stock.

In order to have an even higher level of detail, one could redo the analysis by focusing on the products that represent a majority in terms of stock, i.e. in this case category A products.

In the third table, the same ABC analysis is made, but only the category A products. It can be seen that of those 800 articles, 200 are responsible for almost half of the total pallets in stock, with a number of pallets per SKU of almost 75. Faced with these numbers, different pictures begin to emerge, on the one hand, with the first ABC analysis we see that there are articles that are worth densifying and others that are not, with the second analysis we see that, even among those that are worth densifying, further differentiations can be made and say that there are articles for which it is possible to go deeper and articles with which it is easier to go shallower.

A key parameter in the analysis of multi-deepness is filling, i.e. the factor that

determines how depth is used. In the example above, since you have more pallets/SKUs for class AAA articles, it is easier to fill the channel, so channels with a greater depth could be implemented.

For class AA and A articles, one must stop at a shallower depth in order to be able to fill the channel with the pallets one has available and thus try to reach the theoretical

capacity as far as possible.

7.2.2 MULTI-DEPTH ANALYSIS FOR SHIPPING CHANNELS NUMBER OF PALLETS

If multi-deepness is designed for shipping channels, one way to choose the optimal depth is to study every single shipment in a year.

It is analysed how the pallets of each shipment fill the channels according to the channel itself, which varies. In this case, it is important to know the number of channels required by all shipments throughout the year and their area in square metres.

In this way, it is studied, for all the shipments handled, what filling is to be achieved.

Figure 32: Example of an analysis by number of pallets

In the example in figure 32, it can be seen that by increasing the depth of the channel, at the beginning, the net capacity in terms of pallets per net square meter improves

because it is possible to have such a high profile of pallets per shipment that even by increasing the depth, the number of pallets saturates the channels well.

Above a threshold value, however, this net capacity decreases. This is because, at this point, the profile is such that the channels cannot be filled well and this leads to choosing a certain depth.

In the example, 6 is the depth that minimises the required surface area because it takes an optimal target fill that allows for potentially the best net capacity.

7.2.3 INVENTORY TURNOVER

Number of times, within a considered period, during which the stock is completely renewed.

This index is crucial because it gives an idea of the way in which the financial resources committed to inventories are recovered. This is because with stock the company

anticipates the purchase of products and these costs will only be covered after the consumption and sale of these products.

The longer goods are in stock, the more capital is tied up, so a measurement of this type is important.

The inverse of the turnover ratio expresses the average stay of goods in stock, the coverage, which can be defined in days, weeks or months depending on the results.

7.2.4 ITEM FILL RATE & ORDER FILL RATE

This is an indicator that measures the fraction of demand that can be met immediately from the available stock of a specific article.

The higher this indicator is, the more it means that the company is able to satisfy its demand immediately. On the other hand, the higher it is, the higher the stock will be and therefore the cost of inventory is high.

The Order fill rate is the fraction of orders that can be filled with stock. It depends on the item fill rate.

7.2.5 WAREHOUSE OCCUPATION INDEX

This index indicates the saturation of the warehouse, i.e. the occupation of space.

This indicator can be calculated as the number of occupied rooms/total rooms or occupied surface area/total surface area or occupied volume/total volume.

Depending on how I decide to measure it, this will give me different indications, for example it may be that with the pallets available I occupy all the available surface area, but these pallets are half the height of the available space, so I have not optimized the space in terms of volume. In this case, the solution will not be to look for a larger warehouse due to lack of space, but the company will have to make a different

intervention by modifying the structures and recovering spaces by modifying the height of the compartments.

Looking only at the formula with the occupied area compared to the total area would not lead to this type of solution, the information would be incomplete and the solutions suboptimal.

7.2.6 INVENTORY ACCURACY INDEX

Indicator that can be calculated as number of articles with errors/total number of articles; or as misaligned stock quantity/average stock; or as misaligned stock value/average stock value.

7.2.7 HANDLING INDEX

It relates to flows in the warehouse, it is a measure of incoming rows and outgoing rows, a trend over time to identify upward or downward trends.

Indicator that can be calculated as daily incoming (outgoing) rows/total daily rows.

7.2.8 PRODUCTIVITY INDEX

It indicates efficiency in the sense of resource utilization capacity.

This indicator can be calculated as rows of unloading or loading vehicles per day (or hour), rows of planting per day (or hour), rows of picking per day (or hour).