Case Studies

Case Study: Rivals Analysis

We completed our first ever, annual analysis of twelve Human Resource Management rivals and our client, by comparing their results in September 2023 with those of the same month in 2024. The repeated running of the system and subsequent analysis took just two elapsed days, and four human hours to complete. We were quickly able to compare relative changes of each company vs each other, and to compare their performance between these time periods.

The high-level results showed adventuring companies focusing on innovation, Artificial Intelligence, Blockchain, inclusivity and diversity, and improving sustainability. Significant progress was being made by several organizations, while others languished.

The results also showed the previous leader struggling with the pain of being merged into an unrelated tech company, and falling back into the pack. At the same time, Alexis pointed out the weaker players and the possibility of their being swallowed or disappearing from the market. She was able to show that the market was responding positively to the intensifying competition overall.

Due to the nature of this case study, we are unable to provide the AIs analyses here, but they followed the same format as all of our other recent analyses.

Result

A one-off complete exercise of this nature would take many months for a team of analysts to partially complete and cost at least a quarter of a million dollars to do, making it prohibitively expensive. We completed this exercise in two days for just $5,000, making it affordable for most organisations seeking a self-audit and fast, competitive intelligence.

Learning

Planned connection to the Internet, by the end of 2024 will make Rivals analysis a real-time capability. We will work to have auto-alerting of significant changes to rivals positioning available shortly after the Internet connection is firmly established.

We also found that we can now queue up analyses at the outset, removing the need to feed and mind the AI and speeding up her outputs. In this way, we can now run seven analyses a day from a single computer. More available machines can increase this number ad infinitum.

The arrival of quantum computing will reduce the AIs compute time to mere minutes, and remove the current production capacity constraint. We are also working to have the AI effect the current manual output analysis automatically so that we, and our clients, can achieve the overall result in less than one hour in the near future.

September 2024.