Why pre-construction can’t afford siloed data

Pre-construction is where scope, cost and risk are frozen (or should be). When information is scattered:

• Bids stall while estimators hunt for the latest quantities or historic unit-rates.
  
  

• Errors multiply as scope gaps or duplicate allowances slip through.
  
  

• Strategic decisions blur because no-one trusts “the number” long enough to act on it.
  
  

HS2 is a megaproject-scale example, but the pattern is universal. A global Autodesk + FMI study found that bad or incomplete construction data wiped out $1.8 trillion in productivity in 2020 alone and drove 14 % of all avoidable rework.

Conversely, firms that get data right in the front-end reap outsized returns. FMI’s State of Global Preconstruction report shows organisations with mature, connected pre-con workflows are 52 % more likely to be profitable and report 40 % higher client satisfaction — yet fewer than one-in-five contractors operate at that level.

Inside the HS2 failure: a cautionary timeline

(Sources: UK PAC report, Hansard statement, Guardian coverage) 

What integrated data looks like in pre-construction

Imagine the opposite of the HS2 story:

• One cloud database for quantities, rates, and mark-ups — every change time-stamped and permission-controlled.
  
  

• Live links between the estimate and the CPM schedule, so shifting a work package automatically updates prelims and cash-flow.
  
  

• Scope libraries (spec sections, boiler-plate, alternates) served via search — not someone’s inbox.
  
  

• Historical cost & performance tagged to CSI/UniFormat codes and surfaced by AI so the next bid starts at 80 % complete, not zero.
  
  

• Structured stakeholder input captured through form-based RFIs and design decision logs, eliminating “lost” emails.

DPR Construction’s recent roll-out of an AI platform that merges estimating spreadsheets, ERP data, Primavera schedules and Procore files into a single dashboard is a live, positive example of what this looks like in practice.

A playbook for breaking silos before day 1

1. Map the data flow — list every dataset touched between pursuit and GMP sign-off; flag duplicate entry points.
   
   

2. Choose a primary system of record (your “common data environment”) and integrate, don’t clone, feeder systems.
   
   

3. Standardise coding (cost codes, WBS, location breakdown) so disparate apps speak the same language.
   
   

4. Automate validation — run nightly checks for missing cost codes, orphaned quantities, version mismatches.
   
   

5. Surface insights early — push dashboards on contingency burn, design maturity and cost per key measure to execs weekly.
   
   
   

Why does it matter?

HS2 shows, in billion-dollar neon, what happens when a project is “too big to fail” yet runs on disconnected spreadsheets: delays, distrust, and eventually a public-sector apology in the House of Commons.

For contractors and owners alike, integrated pre-construction data isn’t a tech upgrade — it’s risk insurance. The earlier you unify scope, cost and schedule into a single, trusted dataset, the faster you bid, the fewer surprises you inherit, and the stronger your margin protection when the shovels hit the ground.