Big Data is a very popular buzzword. All companies seem to try to find out how Big Data can help them create a competitive advantage for their business. In practice I see many companies forget “getting the basics right”, which impacts both daily business and Big Data related initiatives.
The biggest challenges
- How can we implement Master Data Management (MDM) effectively with our ERP system?
- I use master data throughout multiple systems, how can I ensure its consistency?
- How can proper MDM mitigate risks within our organisation?
MDM is back on the agenda, due to a focus on creating a competitive advantage through data, cost savings, investigating centralization options, and minimizing process inefficiencies. Also market and compliancy regulations such as SOX, BASEL II, Solvency2 which all in some way address the topic of having control on data integrity and reliable reporting can be triggers for MDM initiatives.
MDM refers to the processes, governance structures, systems and content in place to ensure consistent and accurate source data for the transaction processes. Examples are management of customer master data, vendor master data, materials, products, etc.
How bad master data management impacts good business
Because master data is often used by multiple applications and processes, an error in master data can have a huge effect on the business processes. Every time wrong data is detected in the system, a root-cause analysis and corrective actions must be performed in order to correct and remediate issues. This together with the process rework takes considerable time of resources.
Decision making in the context of bad data
Companies have invested in Business Intelligence solutions to reach better insight in: process performance, customer and product profitability, etc. Reporting insights are often the basis for key decision making. Bad data quality leads to misinformed or under-informed decisions.
Operational impact of bad master data
In case master data is missing, out of date, or incorrect, the business may suffer delays or money losses. For example, stops in the production process due to incorrect material or vendor information. Some examples have been known where incorrect product master data was recorded on product labels for consumer products which resulted in the rejection of a whole shipment resulting in considerable financial and reputational losses.
To comply with legislations, companies must meet criteria which are impacted by the quality of data in the system. As an example healthcare, pharmaceutical or food & beverage companies which are regulated by health and safety standards may have significant legal implications and can even lose their licenses in case of incorrect master records on expiration dates, product composition, storage locations, recording of ingredients, etc.
What to do next?
MDM consists out of four pillars:
- Content & Quality
- Systems & Tooling
All pillars should receive joint attention in order to realize effective MDM. “Numbers tell the tale”. An objective insight into the quality of master data and ist management is of crucial importance to be able to manage, improve and determine whether or not the business requirements are being met. “Get it right” and you will be able to utilize your data to create a competitive advantage!