Implementing an Enterprise Resource Planning (ERP) system is a complex and transformative undertaking for any organization. However, amidst the excitement of adopting new technologies and streamlining business processes, the importance of data governance often tends to be overlooked. Yet, the success of an ERP implementation is intrinsically tied to the quality, accuracy and accessibility of its data.
Effective data governance ensures that the right data is available to the right people at the right time, enabling informed decision-making and maximizing the benefits of an ERP adoption. Data governance plays a critical role in achieving a successful ERP implementation and the following key considerations should be noted to ensure a solid foundation for data management throughout the implementation journey.
A large majority of the issues that lead to the need for a new ERP implementation or upgrade are a result of continued mismanagement of data across an organization. There are three common data management challenges most organizations face inside their legacy ERP system: the overgrowth of data, lack of data cleanliness and the lack of understanding around data flow. When properly mitigated through the use of effective data governance, organizations can significantly improve the success of their ERP implementation.
Overgrowth of data
Many organizations embarking on an ERP upgrade have been using their existing system for a decade or more, resulting in a complex data landscape. With numerous users, varying standards, outdated or abandoned areas and a variety of human errors, the legacy data environment becomes a messy and inefficient space. This overgrowth of data is often due to an increased number of individual user workarounds within the system and arises when users find alternative ways to access or input data, leading to the creation of countless one-off records that clutter the database. When multiplied across numerous employees and ERP sections, these discrepancies overload the system with redundant and irrelevant data.
When implementing a new ERP system, the data migration process must assume a significant role, taking careful consideration of the amount of legacy data to be brought over. Data migration requires the establishment of policies and conventions to ensure data quality. This includes decisions regarding data naming conventions, storage formats and overall data integrity. As part of data governance practices, a thorough cleansing process is often undertaken to align relevant data with the desired format, ensuring consistency and adherence to established standards. Consequently, data governance becomes intricately intertwined with the data migration process, enabling organizations to set a solid foundation for data quality within the new ERP system going forward.
Lack of data cleanliness
When users overlook the importance of data cleanliness, they often negatively impact the reliability of certain datasets and reports within their organization. When datasets are cluttered with redundant or irrelevant information, it becomes challenging to identify the most relevant data points. This not only hampers the efficiency of reporting but also undermines the credibility of the information presented, creating untrustworthy data.
When implementing an ERP system within a data governance framework, the first step is to identify data owners who are departmental leads or subject matter experts with a deep understanding of the business processes and the context of the data. These data owners play a crucial role in setting the standards for good data quality by determining what data is deemed valuable and necessary. A higher body, typically the data governance committee, holds the data owners accountable for maintaining these standards and collaborates in building the necessary infrastructure to effectively communicate and enforce these standards across all system users. This ensures that a consistent and high level of data quality is maintained throughout the organization's ERP system, promoting accurate decision-making and overall operational efficiency.
Lack of understanding of data flow
When users possess little understanding of where the data they utilize is sourced from and where it will flow to, there is often a disregard for the negative consequences of poor data management. An ERP system serves as the central application for an organization, with other systems either pulling data from or feeding data into the ERP. While users often possess deep knowledge within their specific areas, they may lack a comprehensive understanding of how various pieces of data interact, where the data originates or where it ultimately ends up. Such gaps in knowledge can have a significant impact on maintaining an accurate and reliable ERP system.
For example, if an individual responsible for data entry in the ERP arbitrarily assigns item codes without understanding their purpose, downstream users may struggle to interpret the data and make accurate decisions. ERP training is essential to familiarize users with the flow of the system, from one screen and field to another. Such training helps users recognize the importance of maintaining clean data as they understand how their actions impact downstream processes. Data governance plays a crucial role in defining these interdependencies and ensuring that downstream users can set standards for data input upstream, thus maintaining consistency and integrity throughout the system.
As a result of these common data issues, some organizations opt to start fresh with a new ERP system, considering the existing data as unsalvageable or too costly to clean up. But organizations seeking to resolve these challenges through a new or upgraded ERP must recognize that without proper data governance in place, they risk recreating similar issues in the future. No tool or software exists on the market today that can overcome data governance issues by itself. Despite the advancements in technology, human behavior and routine practices can still lead to data quality issues and inconsistencies, and implementing a data governance framework becomes imperative to address this.
When implementing or upgrading an ERP system within a data governance framework, organizations have a robust collection of data governance initiatives and tools available to support a smoother transition into the new system.
Organizational data governance framework
The ERP project team will naturally be prioritizing all of these data challenges, but they will also be held to tight implementation timelines which may pose an incentive to lower governance standards. For this reason, it is critical that these data governance efforts be held in check by a strong governance framework which can define standards and hold the ERP project team accountable.
An organizational data governance framework establishes roles and responsibilities within the framework and defines a hierarchy of governance authority. This process begins with the formation of a data governance committee, tasked with defining high-level standards and policies. Subsequently, data owners and stewards, who are subject matter experts in their respective areas, play a vital role in implementing these standards and policies within their specific domains.
During an ERP implementation, they provide valuable insights and guidance, particularly regarding its impact on configuration, setup and user roles. By involving these individuals, the organization ensures that data governance practices align with the needs and requirements of each area, contributing to the overall success of the implementation process.
Business glossaries and data catalogs
The use of business glossaries and data catalogs provides a comprehensive and standardized resource that helps users define, understand and maintain consistency in terms of terminology, mappings and security measures associated with the new data elements. These resources provide on-hand references for end users.
For example, a glossary may clarify that the term "customer" in the new ERP system is equivalent to "client" in the old one, specify the definition of terms and direct specific questions to relevant personnel. These resources facilitate the review and consistency of data during the ERP implementation, ensuring a crosswalk between the old and new systems. Providing resources for users to discover and learn about the ERP system and the data contained within, promotes organizational consistency and establishes a single source of truth for data definitions and standards.
Data governance policies
Establishing data governance policies with varying degrees of depth and reach is crucial during an ERP implementation to ensure consistency, data accuracy and compliance across different data domains. Effective policies promote efficient data management practices and help organizations leverage the full potential of their ERP system. Master data management policies define guidelines and procedures for identifying, capturing, organizing and maintaining critical data elements within an ERP system, establishing them as the authoritative source of truth. This enables effective decision-making across the organization as it works to prevent conflicting data from scattered spreadsheets or other external applications.
Information security policies encompass access controls, risk management, data retention, disaster recovery and cybersecurity measures. By having well-defined information security policies, organizations can safeguard sensitive data, mitigate risks and ensure compliance with relevant regulations. Implementing these policies allows organizations to establish standards, promote data integrity, enhance security measures and facilitate ongoing monitoring and improvement of data-related processes.
Data governance is a critical pillar in ensuring the long-term success of system implementation, with several key factors contributing to its significance. Firstly, maintaining quality data is essential for unlocking the full functionality of an ERP system as it relies on accurate and reliable data to perform its functions effectively. Without high-quality data, the ERP system will underperform, and organizations may experience disruptions in decision-making and encounter difficulties in both future-state planning and meeting customer demands. Investing in data quality initiatives ensures that the ERP system operates optimally, enabling organizations to leverage its full potential and derive valuable insights for strategic decision-making.
Additionally, effective data governance policies play a crucial role in informing the best configuration of the system, particularly within permissions and process. Security policies and access and decision rights are essential components that data governance can stand up as a major resource in an ERP. By understanding the specific access requirements for individuals in different departments, organizations can ensure that the ERP system is configured to meet specific user needs and align with established governance frameworks.
These policies have a direct impact on the workflows within the ERP as they often involve a sequence of activities that pass through different teams or departments, such as product development, sales to market, or customer service processes. By incorporating these policies into the governance framework, organizations can streamline and optimize their processes, ensuring smoother operations within the ERP system.
A data-illiterate organization is doomed to recreate the issues of the previous ERP. By providing end users with helpful resources like business glossaries, process flows and policies to serve as guardrails, the learning curve to adopting the new system is significantly reduced. Implementing a new ERP system can be a substantial change for many employees, as they may have been accustomed to the old system for years and now find themselves unsure of the meaning of certain fields or the revised approval processes. By providing readily accessible resources, organizations can support effective change management as users can quickly find answers to their questions and empower themselves to utilize these resources, preventing them from making assumptions and potentially poor decisions based on an inadequate understanding.
Most importantly, successful adoption of the new system and its long-term sustainability rely on organizational buy-in and change management support. By ensuring that everyone understands the benefits of the new system and has access to the necessary resources, organizations can foster a positive mindset and expedite the adoption process. Data governance becomes more than just an IT initiative but a comprehensive effort involving all stakeholders, emphasizing the importance of aligning people, processes and technology across the organization.
Data governance is vital in sustaining the success of system implementation by maintaining data quality, informing system configuration, providing user resources and facilitating change management efforts. By leveraging these aspects, organizations can optimize the performance of their ERP systems and drive positive outcomes for the entire organization.
Baker Tilly Digital supports organizations to use their data to gain insights that will accelerate accurate decision-making and advance strategic and operational objectives. We work collaboratively across our Data solutions and Enterprise solutions service offerings to provide organizations with the necessary data governance and management support needed to establish the right policies at each level of an organization throughout an ERP implementation. To learn more about establishing effective data governance during your ERP implementation, contact one of our professionals today.