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BAM Tender matching
with SAM

An app that optimize the matching proces

BAM called on the help of the #RunLiveTruck. Together with a group of young professionals from the youth organization within BAM – Young BAM – they worked on the case: “How can we ensure that we get our tender projects better under control with the help of existing data? The answer: through Machine Learning!

Tender matching with SAM

BAM works a lot with tender projects. This involves pitching for a project alongside many other building companies. The client then chooses who carries out the project. BAM wants to optimize this process, so it can make more conscious choices around which projects to pitch for. This tender matching process takes quite some time, and costs a lot of money, because lots of small bits of data are spread and saved all over of the different sub-organizations within BAM. It makes things tricky for a tender matcher to filter the right data and maintain an overview.

That’s why, with a group of Young BAM in the #RunLiveTruck, we worked on an application called ‘SAM’. SAM stands for Search, Analyze, Match. Machine Learning is at the heart of this application. What SAM does is ensure that a new tender is automatically matched with previous tenders. Based on diverse KPIs - chances to win the project, customer satisfaction, risk profile, and financial details, for example - the tender matcher gets insight into whether the project is worth acquiring or not. The top 5 past tenders appear on a dashboard, based on matches that best align with the current tender. It is so much easier for the tender matcher to make more conscious choices. The chances of winning a tender is also increased, because the reasoning as to why an earlier tender was successful can be reviewed, or explanations as to what resulted in losing the tender.



Watch how the tender process within BAM is optimized with Machine Learning from SAP Leonardo.

Machine Learning: don’t be afraid about replacing people, but reinforce your gut feeling instead.

By: Twan van den Broek

The ‘Internet of Things’ hype is slowly starting to make way for a new one: Machine Learning. Computers can take on more complex tasks and answer more difficult questions. This is how the suggestion – and the fear – has come about that machines will take over our jobs; that eventually they will replace people. 


A more efficient tender process with Machine Learning

How can we optimize BAM’s tender process so that new project applications can be compared with historical ones? The answer is Machine Learning application SAM: Search. Analyze. Match.


Noteworthy previous cases

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