Master data management (MDM) is essential for organizing and managing the information of an enterprise so that a single trustworthy source is established. In order to keep the initiative optimized and productive, a data governance arrangement is required. More often than not both the programs do not produce the desired results because of poor implementation or lack of interest. A successful MDM program requires the integration of technical solutions into business processes. The entire project needs a supervisory mechanism to spot errors and inconsistencies quickly. This monitoring framework is provided by governance. In fact, it can be said that data management and supervisory programs are dependent on each other for achieving success. In this article, we are discussing some MDM best practices which ease the work of data governance services.
1. Link Business Goals To The MDM Program
In many organizations, the scheme fails because MDM is treated as a purely technical initiative. It is necessary to link the program to clear business goals so that the project’s value is understood by the enterprise. Identify the problem areas in the business and see how access to consistent information can help resolve the issues. Once a clear business objective is associated with the program, the importance of all the technical processes becomes clear. The entire organization will start connecting the plan with the goal and make sure that it is executed smoothly. This will reduce errors in handling the information assets which is one of the primary goals of the monitoring system.
2. Involve The Executive Leadership
The program needs the support of the top decision-makers of the corporation to succeed. The executive leadership needs to be educated about the benefits of managing information efficiently. Explain the strategic impact and the possible outcome of the venture to them. Once they understand the value of accurate and consistent data, they will help in the smooth execution of the plan. They will see to it that the project gets adequate funding and receives support at all levels in the enterprise. Their involvement will automatically remove the roadblocks, eliminate possibilities of conflicts and pave the way for the implementation of an effective monitoring scheme.
3. Encourage Active Participation Of Business Sections
MDM helps in controlling information spread across different departments so that the entire organization accesses only consistent data sets. The main objective of this approach is to improve the company’s performance and facilitate better decision-making. This will convince the top executives but most problems occur because the low and mid-level employees feel that the program does not have any visible benefits for them. Help them get rid of this misconception by explaining how adherence to stated policies improves the efficiency of their regular tasks. Make them understand that the business sections and the IT department are equal stakeholders in the project. This will be helpful in creating a favorable atmosphere for an effective data governance approach.
4. Prepare An Elaborate Plan For The Initiative
A major reason the supervisory groups spots a large number of anomalies in the management processes and procedures is that there are inherent flaws in the entire project structure. This situation can be avoided if enough time and thought are invested during the planning stages. Consult the possible stakeholders and prospective owners to know their pain points and expectations. This will provide an idea about the kind of processes and solutions needed to resolve the issues and fulfill the objectives. All the technological tools must also be evaluated on different vital parameters like usability, cost, and scalability. This will help in the creation of optimized procedures and selection of effective tools.
5. Create An Adequate Infrastructure
Another MDM aspect that impacts its monitoring framework is the project infrastructure. Most organizations make the mistake of choosing only suitable processes and technological solutions while creating their management structure. Once they identify these requirements, they must, at this stage only finalize the governance practices. This will help in laying down guidelines for controlling the integration of data from different sources. Most of the consolidation takes place in real time making it necessary to oversee the processes as and when they happen. Choose flexible data sets and intuitive processes which can be scaled up or down according to changes in the future.
6. Identify The Most Appropriate Personnel
Handling of information assets seems to be a largely technical task but an organization’s human resources are vital for its success. Selection of the personnel who will execute the plan and run operations becomes critical. It is essential to pick the most suitable candidates for different roles. An appropriate appointment makes all the difference between success and failure. Make sure that the chosen team is provided high-quality training and knows how to handle the different technical solutions.
7. Implement The Program In Phases
Rolling out the program across the entire organization in a single phase causes numerous problems. Shifting to another approach cannot be done without some teething problems. The workforce will need some time in adapting to new procedures and tools. The plan must be implemented in stages across the different sections of an enterprise. This will help the supervisory team to oversee the execution in an efficient manner. It can spot problems and report them to the relevant stakeholders. On the other hand, not using the iterative implementation approach will lead to chaos and impact the productivity of the business.
The Master Data Management project cannot be successful without an adequate framework for monitoring its operations. Companies must engage data governance consulting firms to define an efficient supervisory plan.