Align Your Technical DataCase Study
One Source of Truth for Technical Data
How a design consultancy brought scattered project data into one structure
- Client
- Example Design Consultants Ltd (fictional multi-discipline design consultancy)
- Prepared by
- Pro Solutors
- Reference
- PS-SAMPLE-003
- Edition
- Sample, October 2026
This is an illustrative sample. The company, project and all figures are fictional and are not real client data or real client results. It shows the structure and standard of our reports.
01
The result at a glance
- -72%
- time searching and reconciling data (6.5 to 1.8 hours a week)
- 22% to 5%
- drawing and calculation mismatches at checking
- 14 to 2
- places where project data was kept
- About 4.5 months
- payback on the one-off investment
| Item | Detail |
|---|---|
| Client | Example Design Consultants Ltd (fictional multi-discipline design consultancy) |
| Our solution | Align Your Technical Data |
| Duration | 3 weeks of audit and design, then 6 months of piloting and roll-out with the client team |
| Outcome | Search and reconciliation time cut by 72%, data mismatches cut by three quarters, one structure for every project. |
All results are fictional and illustrative.
02
The challenge
Example Design Consultants (45 engineers, 3 offices) had grown quickly. Each team kept its drawings, calculations, equipment schedules, models and test results in its own way. Engineers knew the data existed somewhere but could not be sure which version was right, and errors were being found late, at the checking stage or on site.
Scattered data
Project data lived in 14 places: shared drives, email, personal folders, spreadsheets and cloud links.
Many versions
Equipment schedules existed in three versions per project on average, with no clear master.
Mismatches
In a sample of 6 projects, 22% of drawing and calculation pairs disagreed.
Lost time
Engineers spent about 6.5 hours a week searching for data and reconciling versions.
Slow onboarding
New engineers took about 3 weeks to find their way around a live project.
03
Our approach
Audit
Took an inventory of drawings, calculations, schedules, models and test results across 6 sample projects.
Map
Found duplicates, conflicts and gaps, and traced how data moved between disciplines and offices.
Design
Designed one structure: naming, metadata, ownership and change control, held in one database.
Align
Piloted on two live projects, fixed what did not work, then rolled out to every team with training.
04
The roadmap
- Step 1 · Weeks 1 to 3
1. Audit and map
Inventory and conflicts
Goal: Know what exists and where it disagrees
- Step 2 · Weeks 4 to 6
2. Design
Naming, register, ownership
Goal: One agreed structure
- Step 3 · Months 2 to 3
3. Pilot
Two live projects
Goal: Prove it works under real deadlines
- Step 4 · Months 4 to 6
4. Roll out
All teams; training; review
Goal: Adopt it company-wide and lock in gains
05
The evidence and results
| Measure | Before | After | Change |
|---|---|---|---|
| Hours per engineer per week searching and reconciling | 6.5 | 1.8 | -72% |
| Places where project data is kept | 14 | 2 | -12 |
| Drawing and calculation mismatches at checking | 22% | 5% | -17 points |
| Late design changes caused by data errors (per project) | 9 | 3 | -67% |
| Time for a new engineer to become productive on a project | 3 weeks | 1 week | -67% |
The time saving grew as each office joined. The biggest drop came when the pilot projects proved the structure and the roll-out began (months 3 and 4).
| Period | Value |
|---|---|
| Start | 6.5 |
| Month 1 | 6.4 |
| Month 2 | 5.6 |
| Month 3 | 4.2 |
| Month 4 | 3 |
| Month 5 | 2.2 |
| Month 6 | 1.8 |
06
Value delivered (illustrative)
| Annual benefit | USD thousands |
|---|---|
| Reclaimed engineering time (about 5,800 hours put to billable work) | 162 |
| Fewer errors and less rework at issue stage | 48 |
| Faster onboarding of new engineers | 15 |
| Total annual benefit | 225 |
| One-off investment | 85 |
Payback
07
What made it work
Audit before designing.
Seeing the real conflicts convinced the leadership team more than any presentation.
One structure, not one tool.
The standard came first. The database simply holds it.
Pilot under real deadlines.
Two live projects exposed problems that a test never would.
Named owners.
Every data set had a person responsible, so the structure stayed clean after we left.
08
What comes next
- Connect the register to the company project management and invoicing records.
- Add automatic checks for new disciplines as they join the system.
- Review the data health score every quarter and set new targets.
- Consider the Solve and Prove solution for any recurring technical problem the clean data now makes visible.
Assumptions and limits
- Example Design Consultants Ltd is fictional. All data, results and costs are illustrative.
- A real case study would use the client data and be published only with their written permission.
- Results depend on the client starting point, team and discipline, and are never guaranteed.
This is an illustrative sample. The company, project and all figures are fictional and are not real client data or real client results. It shows the structure and standard of our reports.
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Technical Data Health Check
We audit what you have, show you where it disagrees, and give you a roadmap.
What happens after you submit
Problem received
You describe it through the form.
Read by an engineer
Every submission is read by an engineer.
A clear yes or no, and a next step
You hear back within 2 working days.