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Tender management
The customer frequently pursues medium to large tender bids. Each tender bid requires the customer to base their proposal on a significant number of documents. These documents are relevant to a varying number of disciplines, including legal teams, project managers and various technical experts. The winning proposal will be selected based mostly on completeness and the lowest price tag. The challenge in this scenario is:
1
Supporting multidisciplinary data extraction and search ranking. Each involved discipline has their own definition of what data is relevant, how documents are internally related and what the order of document importance is.
2
A tender collection contains a large variety of documents and information. The search solution will need the capability to process and extract information with many types of data structures. These could be traditional text documents, tabular information, technical drawings, contracts, scanned (handwritten) documents, calculations etc. Not all information initially suitable for searching, so meaningful features will need to be generated for each type of document.
3
Note of change and document dependencies. Documents refer to each other in several ways. Documents can either be related through topic, act as a supporting document for a main document that only contains a brief description or a combination of these. Additionally, Notes of Change are regularly published that announce content changes or clarifications for some documents. Sometimes new versions of the affected documents are generated, but not always. In the that case it becomes increasingly difficult over time for users to track which documents are affected in what way.
4
Compare proposal details to previous Tender bids and their results. Due to the often massive amount of information present in each Tender, it is difficult for users to compare their approach to earlier bids; this is both because of time pressure in the current bid and the difficulty of finding the right historic information. Comparing approaches and results of those bids would be valuable for future bids.
To solve this use-case, a search solution is needed with the following components.
If the use-case is solved correctly the customer will: reduce the time it takes to (re-)read available Tender information, paving the way for increased focus on polishing the proposal to the highest quality instead of making sure their information is correct. But the customer will also reduce mistakes in the proposal. Due to lack of time information can always be misinterpreted or missed entirely when (re-)reading documents. The search solution will make it much easier to find the right details in the information and how it’s connected.
The customer will help users to track and visualize changes in documents over time, without the need to re-read the entire documents to make sure no newly details are missed. Information from previous Tender bids can be used to improve the quality of future bids. Which will help the customer eventually.
SERVICE OPTIMIZATION
Providing swift support, sometimes in challenging environments, is the customers responsibility. The service engineers need remote access to detailed technical documentation from an array of sources. But searching through documents in order to find what they need is slow and frustating. This proces often requiers hours of cross-validation and the manual exploration of documents. Many documents are isolated in data silos acrozz the organization. This process is timeconsuming. When time costs this much money, every second counts. Find out how digitalNXT Search can help in service optimization!
PROBLEMS, CAUSUS, SOLUTIONS
Installing and troubleshooting equipment is the customers responsibility. The posibility that some equipment breaks, does not respond or perform up to standards is inevitable. The customer needs to fix the issues within the shortest time possible, whatever the issue is. Because downtime is usually very costly.
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