Inventory management technics for product management
by Nikolay Donets
– April 16, 2022 · 5 min read
Analysis of texts (app reviews, emails, chats, phone transcripts) is essential for proper product development planning. Clusterization of texts and extraction of keywords can help organise a backlog of projects, identify those with the biggest impact. How to make it less manual and optimised?
The first step is to extract keywords. This problem is out of the article scope. Let's assume that the problem of keyword extraction is solved using one of the Keyword and Keyphrase Retrieval techniques like KeyBERT. One of the approaches to make the analysis less manual is to use inventory management technics. Let's focus on how to get analysis of texts for product development using two methods: ABC and XYZ analyses.
The ABC method is based on the Pareto principle – 80-20 rule. ABC analysis is a technique used to categorize inventory items based on their importance. The ABC classification goes like this:
– A items are important and need close attention
– B items are semi-important and require some attention
– C items are of low importance and can be given less attention
Importance is often assigned based on factors such as cost, turnover, and impact on quality. In our case, it can be, as it was already mentioned, a time that support agents spend solving a customer issue. Once keywords have been divided into categories, it is easier to plan and prioritise feature requests. For example, if A keywords represent cases that are critical to the success of a customer or a business, then these should be given the highest priority. Similarly, if C keywords represent issues that are not essential, then they can be given a lower priority.
Another method is known as XYZ analysis. The XYZ analysis is a method of inventory management that seeks to identify the items in a company's inventory that have stable sales, high turnover, or are slowly moving. The analysis is named for the three categories that items are placed into:
– X items are those with the highest turnover
– Y items are those with moderate turnover
– Z items are those with the lowest turnover
For support cases and, in the bottom, for keywords, it means that we want to understand how frequent we see them during some period of time. In the majority of cases, it is a week or month interval, but it can be a day for some businesses
with a high number of support requests.
However, a separate usage of ABC or XYZ analysis usually is not enough for proper planning, especially when the number of extracted keyword combinations is huge. For such cases, consider a combination of ABC and XYZ analysis and nine groups ordered by importance-frequency combination: AX, AY, AZ, BX, BY, BZ, CX, CY, and CZ. The most crucial one is AX that contains important and frequent items. This must be planned first. The remaining groups can be planned in any order.
Now, when we are familiar with ABC and XYZ, let's talk about the proportions. For ABC the typical proportion is A=70%, B=10%, C=10% and for XYZ the typical proportion is X=70%, Y=15%, Z=15%. However, these proportions are not universal and must be applied on the basis of knowledge about your customers and your business.
||Important and frequent
||Important but rare
||Not important but frequent
Putting together all steps gives the next pipeline:
1. Keyword extraction
2. Definition of importance and association of it with keywords
3. ABC analysis for keywords
4. XYZ analysis for keywords
5. Extraction of cases from AX and the rest of groups
6. Backlog review using cases from step 5
Periodic review of the backlog is crucial to ensure that it still contains the items that are the most important for your customer. And inventory management technics can help to ensure that it is filled with the most impactful candidate items for development. It helps to reduce manual work significantly. When it comes to more precise prioritisation of candidate items, it is down to you what to use next: Kano analysis, MoSCoW, KJ method, or something else. But that's another story.