As-built Documentation

Digitize as-built documentation workflows to reduce manual data management and take cost out of the as-built documentation process.

prescience quality as-built documentation ring binders

Too Much Paperwork

Meeting as-built documentation requirements with pen and paper is both painful and expensive.

  • Recording data on paper is extremely error prone.
  • Collecting data from operators is complex to manage.
  • Typing up handwritten as-built data generate errors and double work.
  • Validating data integrety and accuracy is extremely tedious.
  • Sending as-built documentation to customers via email wastes resources filing and archiving and increases the risks of data loss.
  • Manual as-built documentation reviews are painful because all errors, missing data and out-of-spec values must be detected manually.
  • Finally, the data is “dead” data because it cannot easily be analyzed at scale, this poses an opportunity loss.

What if there was a better way?

Automate As-built Documentation

Prescience improves data management to make the as-built documentation process lean and efficient.

  • All suppliers use the latest template revision.
  • Data can be collected with a smartphone on the production floor.
  • Operators work collaboratively to provide as-built documentation.
  • Data is touched once, no one has to type up handwritten notes.
  • Data is automatically consolidated and shared with customers.
  • Customers can improve the as-built review process.
  • Customers can pre-review parts of the as-built documentation.
prescience quality documentation reduce remove paperwork

What Are Your As-built Documentation Use Cases?

Here are a few examples where Prescience can streamline as-built documentation:

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Get a free 1:1 demo by a product expert to learn how Prescience can help you.

prescience web app quality assurance track data form completion

Track As-built Completion

Prescience measures as-built documentation progress to highlight where data is missing.

Prescience measures documentation completion to make it easy for users to plan and prioritize their work. This means users are in control and avoid the pain of managing documentation manually.

Validate Data Input

Prescience validates input to reduce documentation errors and improve overall data quality.

This is almost impossible when relying on pen and paper. Even with Word or Excel it can be difficult as users often corrupt data unintendedly.

Prescience prevents users from saving invalid data and provides feedback letting users know why their input is invalid. Similarly, dropdrown input controls ensures that users select their input from a valid list of answers instead of letting them provide free text answers.

As a result users provide correct data the first time. Ultimately, this reduces errors, ease data cleansing and improve overall data quality.

prescience quality assurance data format validation
prescience quality assurance data form evaluation

Evaluate Responses Immediately

Prescience evaluates input instantly based on pass/fail criteria to detect non-conformities ealier.

This provides immediate evaluation and allow users to spot obvious typos and, more importantly, help users identify defective components.

This is key to enable swift rework, easier root cause analysis and reduces indirect costs incurred by passing defective parts down the value stream.

Customized to Your As-built Requirements

You have the as-built use case, we have the toolbox and infrastructure to make it happen.

As-built documenation requirements are customer specific. This is why Prescience is designed to be customizable, flexible and fast to implement. As a result, new as-built forms can be designed and published in minutes.

Each as-built form is structured into groups of data points. Likewise, each data point can be configured to specify input control type, help text, input options, input validation and pass/fail criteria.

prescience quality documentation data form group data point
prescience quality extract data analyze at scale

Analyze As-built Data at Scale

Prescience allows you to analyze as-built data at scale, using your preferred data analysis tool.

Normally, as-built documentation serves to certify individual components. However, we understand the value of “big” data and we believe your as-built data can serve multiple purposes, for example:

  • Analyze data values accross a product category or supplier portfolio.
  • Track evolution over time to drive continuous improvement.
  • Benchmark suppliers to measure best-in-class performance.
  • Identify historical components that share origin, traits or subparts.
With an API Key you can access the as-built data with your existing business intelligence solution. This means that you can merge data with other data sources and build your own custom reports.

More Business Cases

See more use cases to learn how Prescience can support your supply chain execution.

Plan and Track Production

Push production plans to suppliers and track their production execution.

Capacity Planning

Capture supplier capacities and analyse overall capacity availability.

Quality Assurance

Digital quality checklists that provide accountability and audit trail.

Inbound Delivery

Plan and manage inbound raw material deliveries.

Inventory Management

Manage finished goods inventories and measure inventory levels.

Outbound Shipment

Plan and manage outbound shipments of finished goods.

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