Use the best MDM Solutions to Improve Data at an Early Stage

High quality data is an essential component of effective decision making. When the volume of data is significant errors are bound to creep in. These errors could be simple yet difficult to remove. Often it might even cost the organization several million dollars before the reliable. Since organizations cannot do without data, it is essential to install data quality governance when the data collection is small and manageable.

Here are some common ways to maintain data quality in an organization.

1. Data profiling:

Data profiling is the process by which the data availability is checked for in an existing source to pull out detailed statistics and further information about such data. Data needs to be profiled for completeness and accuracy with regular upkeep. The quality needs to be measured and adhered to, to ensure that the data remains usable and reliable at all points of time.

2. Standardization:

Data standardization is the process of ensuring that a common data format is used in every process to ensure uniformity. It ensures that the data is constant in all aspects and improves decision making as less time is taken for corrections or alterations. Proper data standards will improve performance and reduce time taken for decision making.

3. Linking:

Data linking is to connect data with other data sources with relative characteristics. With a proper data quality governance process it becomes easier to merge databases and to use them as a single source of information in the future.

4. Data monitoring:

with the help of professional supervision helps maintain the quality of data at a high level.

ERP implementation best practices always rely on using a single set of data that is uniform and complete in all aspects. Such data is created by constant practices of entering key fields. Maintaining the high quality of this database reduces the possibility of data redundancy, duplication, erroneous entries, etc. Moreover, this will also facilitate the use of database by a multitude of departments for proper planning and organization.

The following departments can streamline their operations by establishing MDM solutions in the early days:

Engineering:

The engineering department will require a steady supply of materials of all forms. MDM solutions help maintain a good database of materials that are complete in all aspects. It will reduce wrong stock reports thus eliminating the possibility of unnecessary purchases.

Accounting:

The accounting department will be able to pull out accurate material consumption reports thus creating accurate accounting records. Organizational profitability and future material demands can be drawn with better accuracy with high quality data.

Warehousing:

Supply chain organizations spend millions on warehousing and storing their goods until they are ready for delivery. With accurate material masters, it is possible to derive correct data about how long the material has been lying in the warehouse, its shelf life, expiry date, consignment details and much more without any complications.

Forecasting:

Budgeting and forecasting become easier and more reliable with MDM solutions. Accurate forecasts without serious fluctuations can be made and depend on creating financial budgets and records.

Purchasing:

The biggest benefactor of MDM solutions is perhaps the purchasing department. The department is able to prepare purchase indents to suppliers on a timely basis and for the right quantity without any errors. They can take the material master to be correct by all means.

Material master data management has come out of its nascent stages. It has reached a level of maturity where every organization is gearing up to set up sound MDM practices. Selecting a vendor with high proficiency and experience is of utmost importance to manage all functions in an efficient manner. MDM solutions should preferably be established in the early stages of the business so that data quality can be maintained and sustained in the long-term. It will definitely go a long way in eliminating data quality issues that can reduce profitability.

The author is an expert in the field of master data management. The writer has flair for writing and he keeps on writing various articles and blogs related to the industry.