2
the client in the case where ground conditions were signifi-
cantly different from those described in the project tender.
However, the clause also stated that in order to be eli-
gible for this claim, the contractor must notify the client
within 7 days and must not materially disturb the ground
until the client could inspect it.
After two months of losses, a review by the commercial
team in head office revealed that if the poor ground condi-
tions had been flagged earlier, they would have qualified
for latent condition treatment, allowing the contractor to
recover costs.
Upon this realization, the contractor immediately noti-
fied the client, and compensation was secured for future
work. However, the client rejected the claims for the previ-
ous two months as the 7 day notification time bar had not
been met. This equated to a ~$400k in unrealised profit for
the contractor.
In general, the contractor did not like to use contrac-
tual mechanisms such as this to claim money from their cli-
ents, however in this case they would have made this claim
as the project was losing significant amounts of money.
GAP AND ROOT CAUSE ANALYSES
An investigation was subsequently held to identify the pro-
cess gaps and root causes of the incident. The process was
facilitated by the central commercial team and involved a
series of interviews with key stakeholders as well as a review
of the site reports and communications.
The gap analysis found issues in each of the three stages
of the claim process:
1. Identifying the claim: The site team did not ini-
tially identify the deteriorating conditions as a
latent condition as they did not understand this
clause in the contract.
2. Processing the claim: Once the site team did
identify the potential claim, they did not follow
the contractual process for notifying the client
within the 7 day time bar. They were distracted
with the operational issues at hand and therefore
failed to flag this to the client or to the central
commercial team.
3. Defending the claim: Once the commercial team
was aware of the issue and the claim had been pro-
cessed, it was rejected by the client due to failure
to meet the notification time bar. The contractor
team searched through emails for evidence of any
such notification, however some people had left
the business by this stage and they didn’t have an
easy way to search through past correspondence.
The root cause analysis found the following factors to be
the key drivers of the loss:
Organizational Factors
• Procedures: The contractor did not have a proce-
dure in place to ensure commercial or contractual
implications were considered in the case of major
operational changes.
• Training: The contractor did not have a formal train-
ing framework in place to ensure Project Managers
were competent in contract administration.
• Systems: The contractor did not have a system in
place to facilitate contract management or collabora-
tion with commercial teams beyond standard email.
• Culture: The contractor had an organizational cul-
ture of “leaving the contract in the drawer”.
• Organizational Structure: Commercial team mem-
bers were based in head office and so relied purely on
site teams to proactively alert them to potential issues
Task/Environmental Factors
• Focus: The project team were all extra busy due to
the operational issues leading to lack of focus on the
commercial issues.
• Geology: The conditions deteriorated slowly over
an extended period of time so the site team did not
initially consider it significant enough to warrant a
claim.
Team Factors
• Leadership: The Project Manager on this project
was relatively inexperienced in this style of con-
tract, they were accustomed to contracts where the
extra time and cost would have been compensated
automatically.
POTENTIAL ARTIFICIAL INTELLIGENCE
SOLUTIONS
Recent advancements in Artificial Intelligence have enabled
a range of software tools that can help prevent these types
of contractual issues.
Specifically, Large Language Models now allow soft-
ware applications to:
• Read and understand documents such as contracts
• Interpret natural language queries from users
• Respond to queries in natural language
the client in the case where ground conditions were signifi-
cantly different from those described in the project tender.
However, the clause also stated that in order to be eli-
gible for this claim, the contractor must notify the client
within 7 days and must not materially disturb the ground
until the client could inspect it.
After two months of losses, a review by the commercial
team in head office revealed that if the poor ground condi-
tions had been flagged earlier, they would have qualified
for latent condition treatment, allowing the contractor to
recover costs.
Upon this realization, the contractor immediately noti-
fied the client, and compensation was secured for future
work. However, the client rejected the claims for the previ-
ous two months as the 7 day notification time bar had not
been met. This equated to a ~$400k in unrealised profit for
the contractor.
In general, the contractor did not like to use contrac-
tual mechanisms such as this to claim money from their cli-
ents, however in this case they would have made this claim
as the project was losing significant amounts of money.
GAP AND ROOT CAUSE ANALYSES
An investigation was subsequently held to identify the pro-
cess gaps and root causes of the incident. The process was
facilitated by the central commercial team and involved a
series of interviews with key stakeholders as well as a review
of the site reports and communications.
The gap analysis found issues in each of the three stages
of the claim process:
1. Identifying the claim: The site team did not ini-
tially identify the deteriorating conditions as a
latent condition as they did not understand this
clause in the contract.
2. Processing the claim: Once the site team did
identify the potential claim, they did not follow
the contractual process for notifying the client
within the 7 day time bar. They were distracted
with the operational issues at hand and therefore
failed to flag this to the client or to the central
commercial team.
3. Defending the claim: Once the commercial team
was aware of the issue and the claim had been pro-
cessed, it was rejected by the client due to failure
to meet the notification time bar. The contractor
team searched through emails for evidence of any
such notification, however some people had left
the business by this stage and they didn’t have an
easy way to search through past correspondence.
The root cause analysis found the following factors to be
the key drivers of the loss:
Organizational Factors
• Procedures: The contractor did not have a proce-
dure in place to ensure commercial or contractual
implications were considered in the case of major
operational changes.
• Training: The contractor did not have a formal train-
ing framework in place to ensure Project Managers
were competent in contract administration.
• Systems: The contractor did not have a system in
place to facilitate contract management or collabora-
tion with commercial teams beyond standard email.
• Culture: The contractor had an organizational cul-
ture of “leaving the contract in the drawer”.
• Organizational Structure: Commercial team mem-
bers were based in head office and so relied purely on
site teams to proactively alert them to potential issues
Task/Environmental Factors
• Focus: The project team were all extra busy due to
the operational issues leading to lack of focus on the
commercial issues.
• Geology: The conditions deteriorated slowly over
an extended period of time so the site team did not
initially consider it significant enough to warrant a
claim.
Team Factors
• Leadership: The Project Manager on this project
was relatively inexperienced in this style of con-
tract, they were accustomed to contracts where the
extra time and cost would have been compensated
automatically.
POTENTIAL ARTIFICIAL INTELLIGENCE
SOLUTIONS
Recent advancements in Artificial Intelligence have enabled
a range of software tools that can help prevent these types
of contractual issues.
Specifically, Large Language Models now allow soft-
ware applications to:
• Read and understand documents such as contracts
• Interpret natural language queries from users
• Respond to queries in natural language