Tender Management

Tender Management 

For many companies the flood of daily available tenders poses a great challenge to the focus on relevant topics. Our solution for the automated processing of tenders supports you in increasing your conversion rate and it provides transparency.


Both the number and complexity of awards and tenders on the German market are high. A detailed and manual pre-check for relevance to the company is very time-consuming. There is usually no central department within the company for this purpose and accordingly tenders are mostly only requested on an individual basis.

As a result, tenders are often submitted too late or not in full, which means that a contract is not awarded. More seriously still, the prioritization of the offers to be prepared is set wrongly and too little time is spent on the more important tenders for the company. As a result, companies lose valuable contracts.

The Challenge

The main challenge in the process of preparing an offer is the initial screening of the tenders to assess whether an offer should be prepared. As the tender progresses, the offer is prepared drawing on the support of several departments, which have to be coordinated. This process can lead to long processing times and insufficient or incorrect prioritization.
In the entire process from the tendering process to the submission of bids, IT support in many companies is limited to Excel and partial use of databases. As a rule, these applications prove better for data collection with their manual input functionality.

Keeping track of which documents need to be submitted and in which time period is an immense effort for the responsible departments.

Automated data acquisition and the use of machine learning components, such as an automated classification of the relevance of a tender for the bidding company, would be particularly useful for supporting the tender/award process.

Our Solution

KPMG has developed a solution for the automated processing of tenders. KPMG Ignite is an AI platform with a modular component architecture that can be integrated into existing processes. It uses advanced analysis algorithms to process data and knowledge from tenders to improve, accelerate and automate decisions. Our solution extracts all relevant attributes of a contract and makes them available in the form of a result, thus optimizing the further business process.

The first step is to convert the image files or PDF files into a machine-readable format. The tenders are divided into different categories (tender types) such as 'public' or 'commercial'. Depending on the type of tender, each tender is searched for specific attributes and paragraphs in the second step. The information extracted from this, such as tender contents, conditions, deadlines, required references, etc., creates transparency at a central point in the company and allows optimized process design. In this context, the following aspects can be improved:

  • Data transfer from public procurement offices
  • Data readout from tenders
  • Prioritization of awards
  • Routing to the appropriate contact person
  • Relevant deadlines and dates at a glance
  • Data consolidation of different departments for the creation of offers
  • Checklist for the data/forms to be submitted

Your added value

The automated processing of tenders opens up many advantages:

  • KPMG offers you an efficient and cost-effective extraction of your tenders. You receive quality-assured and structured tender data that you can process directly.
  • Tenders can be classified and prioritized without additional effort in terms of time and content.
  • All tender attributes of all tenders are centrally available and linked to the original tenders.
  • The system is managed by KPMG tendering experts.
  • Additional support services from our specialists can be provided if required.

Start now!

Here you can request your demo access.
You already have your login data for the demo? Then you can start directly with the demo.


Order Demo

Start Demo

Find more information on KPMG Source.


Go to KPMG Source