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Common mistakes when building project profiles in ERP.

Why do many "digital transformation" systems still function like an upgraded Excel
December 17, 2025 by
Common mistakes when building project profiles in ERP.
Nguyễn Văn Minh

​Although modern ERP systems are fully equipped with project management modules, many businesses still fail to generate reliable data and reports with practical value. This study analyzes the root cause, which lies not in technological limitations, but in the way project documentation is designed and used from the initial stages. Through an analysis of organizational behavior, data structures, and ERP implementation practices, the study identifies systemic errors that lead to the degradation of project data value, thereby undermining the ERP's decision-making functionality.

​The reality of ERP implementation in many businesses reveals a paradox:
​"The system is becoming more complete – the amount of data is increasing – but trust in the data is decreasing"
  • Common manifestations include:
+ Project data exists but is not used for decision-making.
+ Reports exist but do not reflect actual progress.
+ Personnel still rely on verbal inquiries, Zalo messages, and phone calls.
  • The research question is:

Why is the project file – the "backbone" of the Project module – failing to fulfill its role?

Mistake 1: Turning Project Documents into a Formal Administrative Tool

​The first and most common mistake is that businesses treat project documents as a mere administrative form to be completed as part of a formality. These documents are created once at project inception and are then rarely updated or used as a real-world operational tool. This approach quickly leads to outdated information, creating a situation where the system looks good on screen but looks bad in real life. Essentially, when project documents only serve as static storage, the ERP system is downgraded to a digital document repository, losing its core function of supporting real-time operations and control.

Mistake 2: Increasing the number of data fields without a unified usage convention

​Many ERP systems allow the configuration of numerous information fields related to time, status, roles, departments, or job tags. However, expanding data without a unified usage convention leads to semantic chaos. Each user interprets and updates data in their own way, without knowing which fields are required, when to update them, and what purpose they serve. As a result, the data becomes inconsistent, rendering aggregated reports meaningless. Instead of increasing system power, "cramming" data fields only exposes a lack of operational discipline and data management within the organization.

Mistake 3: Misusing the Essence of Core Management Concepts

​A more dangerous mistake lies in using the right techniques but the wrong management mindset. Concepts like milestones, states, or task cards are misused: milestones are used to divide internal tasks without being linked to commitments or delivery deadlines; states are used to indicate priority levels instead of control states; and task cards are used instead of processes. The ERP system still runs smoothly technically, but the management logic is fundamentally flawed. ERP cannot judge right from wrong; it only honestly records what users input. When the management mindset is wrong, the system will consistently store and amplify that error.

Mistake 4: Failure to clearly separate plan and reality

​Some project records only record the start and end dates without distinguishing between the plan and the reality. This failure to separate these two layers of data prevents businesses from measuring deviations, identifying the causes of delays, and evaluating the team's performance. From a management perspective, without actual data, any plan becomes merely a beautiful assumption. Without a plan-reality comparison, ERP cannot support process improvements or enhance the efficiency of subsequent projects.

Mistake 5: Ignoring Dependencies Between Tasks

​Many projects are divided into dozens of tasks, but these tasks are set up as independent entities, without showing any before-and-after relationships or blocked states. The failure to declare dependencies prevents the system from analyzing the causes of delays or identifying the domino effect when a key task is delayed. In this case, the ERP's analytical role is replaced by human memory, forcing managers to question each individual. A project lacking a clear dependency structure is essentially not managed by the system, but by personal intuition and experience.

Mistake 6: Viewing Project Records as the Project Manager's Sole Responsibility

​When updating project records is solely the responsibility of the project manager, while other team members don't feel accountable for the data, information will always be updated late or superficially. The data is then seen as "extra work," not directly related to the interests of the person performing the task. As a result, management decisions are always based on outdated information, significantly reducing the value of the ERP system. Essentially, ERP is not a personal tool of the Project Manager, but a shared work platform where data is co-created by the entire team.

Mistake 7: Closing the project without leveraging accumulated knowledge

​One of the biggest wastes in digital transformation is closing project files as soon as the project is completed without summarizing, comparing the plan and reality, or drawing lessons learned. When data is not used for learning and improvement, ERP only serves as a record of the past. Meanwhile, the core value of project data lies in its ability to generate knowledge for the future, helping businesses perform better, faster, and more accurately.

  • Practical Implications for Businesses Implementing ERP
​From the mistakes analyzed, several management implications can be drawn for businesses that are currently implementing or will implement ERP.
​First, ERP implementation must begin with redesigning project management, not with software configuration. If the project management process is unclear, lacks defined responsibilities, and has no standards for planning, execution, and control, then ERP can only reflect that ambiguity in the form of digital data.
​Second, project documentation needs to be considered a living entity, existing alongside and evolving with the project. This requires businesses to clearly define: when data needs to be updated, who is responsible for each type of data, and what decisions that data serves. When data is not linked to decisions, updates will always be overlooked.
​Third, the role of the project manager needs to be redefined. Instead of being data collectors and report makers, they must become information structure designers, data quality monitors, and data users to coordinate resources. Responsibility for data updates needs to be allocated to the specific areas where the work originates.
​Fourth, businesses need to invest seriously in data discipline, including naming conventions, state definitions, timeline usage, and reporting standards. This isn't a technical issue, but a matter of governance and organizational culture.
  • Strategic Implication: ERP is a mirror of management thinking.
​At the strategic level, this research shows that ERP doesn't automatically make an organization better or worse. ERP only amplifies what already exists. An organization that manages projects intuitively will have an ERP system full of data but lacking knowledge. Conversely, an organization with clear management thinking will turn ERP into a competitive advantage.
​Therefore, the most important question is not "Can ERP do it?" but rather:

"Does our organization have sufficient clarity and discipline for ERP to accurately reflect reality and support decision-making?"

  • Conclusion

​The analysis shows that failures in ERP implementation do not stem from a lack of features, but from a misunderstanding and misuse of project documentation. ERP truly becomes a strategic management tool when project documentation is viewed as an operational dashboard rather than administrative paperwork, when data is standardized, regularly updated, and used for learning. Conversely, if businesses continue to maintain old thinking in a new system, they are only digitizing their own complexities.

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