The buzz word 'Machine Learning' (ML) is so overused these days, that I sometimes wonder if it puts people off. It’s certainly fair to say that most CEOs don’t take full advantage of the possibilities ML offers and that is particularly true when it comes to procurement – which can be hugely costly for businesses and take employees hours of research.

For big businesses procurement can be such a huge area they will often bring in business intelligence engineers, data scientists and IT professionals to create complex analysis models from data to help them make better informed decisions. What is great about machine learning and products like Amazon Business is that you don’t need to be an expert to make sense of procurement data and build narratives… anyone can do it.

Example: Let’s say you wanted to evaluate the order history data of thousands of employees to make purchasing decisions. Using some online purchasing solutions, you can create a simple narrative to give top management a senior level overview - without first having to analyse complex graphics or decipher data tables line by line. You can also drill down to get much more detailed information at a granular level.

There are two other ways Amazon Business allows you to break down this data:

  • Aggregated visualisations offer the possibility to gain deeper insights, as the data can be filtered by unique patterns or specific details.
  • Raw tabular data allow a very detailed analysis of the granular information on which the more general narratives and visualisations are based.

I’ve outlined these options in more detail below:

1) Aggregated visualisations

The reason aggregated visualisations are important is that the majority of purchasing managers need more than simple narratives to be able to understand the purchasing behaviour of their employees. For this group, a more detailed dashboard with extensive KPIs, diagrams, drilldowns and filter functions is suitable.

For example, if a manager has a Guided Buying policy in place for their company, the dashboard can be used to check how these policies are affecting the purchasing behaviour of employees. Expenditures can be broken down by category, preferred and restricted items, users and groups, and viewed at a glance in a bar chart. A purchasing manager can even trace non-compliant purchases back to the responsible employee and thus further optimize his procurement management.

2) Tabular raw data

While simple narratives and visualisations are usually sufficient, there may be situations where financial or procurement experts need to analyse the data very deeply and in detail in order to get to the bottom of a particular issue.

For a full investigation, users can get deep into the analysis by first setting relevant filters and then accessing the data in more. If you don't want to take the detour via the filter system but want to analyse a specific graphic in more detail, you can export the raw data directly from it as a CSV file.

These are just some of the ways Amazon Business can make your life easier – for more detailed information visit Amazon Business.