Master Data: The Key to Successful Change Implementation

There are a number of risks associated to managing your data poorly, such as;

• Reduced efficiency and productivity: Poor data quality can lead to inaccurate or incomplete information, which can cause delays, errors, rework and waste within your supply chain processes. For example, if your product information for weights and dimensions are incorrect, that could impact picking, packing, loading and shipping of goods, resulting in higher costs and lower efficiency.
• Impaired decision making: Poor data quality can undermine the reliability and validity of data analysis and reporting, affecting strategic and operational decisions and plans. For example, if demand or inventory data is inaccurate, this can result in overstocking or understocking impacting service levels, cash flow and profitability.
• Increased compliance and reputational risks: Poor data quality can expose your business to legal or contractual penalties as well as damaging reputation and brand image. For example, incorrect product or supplier data can result in non-compliance on quality, safety, environmental or ethical standards.

These risks will negatively impact your ability to implement change throughout your organisation. Inaccurate data makes achieving your supply chain goals and objectives much more difficult.

Your ability to implement change is being hijacked by poor data

When implementing change, every organisation encounters resistance. Employees are often reluctant to change what they are comfortable with, and at board level, there must be a justification and return on investment for the change. Inaccurate data will significantly impact your ability to manage this resistance due to several key factors.

• Lack of trust: Stakeholder confidence in a change initiative diminishes the moment they see inaccurate data impact the outputs of said change. You could have presented the return on investment for a new automated solution based on volumes that turn out to be far from reality or have implemented a new planning system that is producing unexpected results due to inaccurate inputs. These challenges will make this resistance to change stronger.
• Communication breakdown: Effective communication relies on clear and accurate information. Poor data can lead to mixed messages, confusion, and misinformation. If different departments have conflicting data, it becomes challenging to present a unified vision and strategy, further fuelling resistance.
• Fear of the unknown: When data quality is compromised, it’s harder to predict outcomes accurately. Employees may fear the potential negative impacts of change, such as job losses or increased workloads, leading to resistance. Transparent and accurate data can help mitigate these fears by providing a clear picture of what to expect.

Why is accurate data so important?

Accurate data is crucial for smooth change management as it enables informed decision-making, fosters trust, facilitates clear communication, and supports a transparent, well-coordinated approach aligned with strategic goals and operational needs.

Now you know the issues related to poor data, how can you manage your data to ensure accuracy?

• Establish data governance; Set policies and procedures for data management to ensure consistency, quality, and security. This includes defining roles and responsibilities, as well as dedicating resources to the maintenance of data. Most organisations ignore this because they see the time spent as a waste of profit-generating time. However, all of this helps reduce errors and enhance the reliability of data.
• Implement data quality management within the responsibilities you set up include regular data cleansing to remove duplicates and correct errors. Periodic audits of your data can also help identify errors that might otherwise be missed.
• Centralised data storage, whether in a data warehouse or a cloud-based solution, helps ensure the accessibility, consistency, and security of your data. This data store should have restricted access so that only those responsible for the data can make changes, preventing accidental mistakes. Centralisation also reduces the issue of data silos within your organisation.
• Promote a data driven culture, the value of data in decision making cannot be overlooked, once employees understand that they will begin to prioritise data accuracy. Establishing data champions within your teams can help drive this culture.

Conclusion

In conclusion, master data is crucial to organisational efficiency and successful change implementation. It encompasses core information vital to business operations, such as product, customer, supplier and location data. Despite its importance, many businesses overlook data maintenance due to perceived low immediate value and resource constraints. However, you should care about data, as poor data quality can lead to reduced efficiency, impaired decision-making, and increased compliance risks, ultimately hindering change initiatives.

Avoid these common pitfalls by establishing robust data governance, ensuring data quality management, centralising data storage, and fostering a data-driven culture. These initiatives will facilitate smoother, more effective operations and change management.