Data Catalogs – Governing & Provisioning Data in a Data Driven Enterprise (7 June 2024, Live Streaming Training)
Building a Competitive Data Strategy for a Data Driven Enterprise (17 May 2024, Live Streaming Training)
Smart Infrastructure & Smart Applications for the Smart Business – Infrastructure & Application Performance Monitoring
Data Warehouse Automation & Real-time Data – Reducing Time to Value in a Distributed Analytical Environment
Below are answers to 4 key questions that often get asked when starting MDM projects. Hope you find them useful.
1. What are the factors that trigger a company’s Master data management initiative?
- The need to improve processes
- The need to shift focus from product to customer orientation
- The need to get control of expenditure with suppliers in procurement (Supplier and Materials master data is particularly important)
- The need to improve accuracy of reporting for financial position when they have multiple ERP instances and multiple charts of accounts
2. What kinds of industries are quick to recognise the value of data governance & information related initiatives?
- Process oriented businesses like manufacturing and pharmaceuticals will see its value quickly.
- Financial services moving from product oriented to customer oriented risk management will also be receptive.
- Insurance is having it forced upon them with Solvency II EU legislation.
- Investment banks need customer master data to reduce risk and both customer and securities master data to improve process execution from Trade to Settlement to Custody
3. Why are companies so slow to start Information management, data governance and MDM initiatives?
Lack of basic understanding of core master and transaction data and where it is used in their business. This plus insufficient understanding of how core business processes work and how these processes cut across multiple departments and applications mean that people don’t understand the impact of bad or inconsistent data. IT in particular often have very limited understanding of business processes and therefore cannot see how lack of information management impacts business performance. Therefore they find it difficult to create a business case. For these reasons they do not see how data problems can impact:
- Operational costs – data defects increase cost of operating
- Speed of process execution
- Data defects slow down process execution
- This can impact on customers if customers are waiting on a product
- Can also make it difficult to scale the business without imposing high operational costs
- Decision making
- Data defects impact on timeliness of decisions or the ability to make a decision at all
- Data defects impact on accuracy of decisions
- Data defects may mean event patterns that require action are not seen
- Data defects cause reconciliation problems
- Inability to see across the value chain
- Inability to report on financial performance
- Risk management
- Data defects can increase risk if risk cannot be identified due to lack of availability of information or lack of accuracy
- Data security breaches cause brand damage and can lose customers,
- Regulatory reporting errors that result in penalties
- Damage to share price that impacts executive pay
For example, Customer master data is needed in Sales, marketing, service, finance, and distribution. It is not just a CRM problem. In addition, IT need to learn more about business to help to understand how to build a business case. I say ‘Follow your processes from end to end and see how they currently work”. This teaches you where data governance and MDM can make a difference and the business impact it can have.
4. What are the factors that cause failure or delays in a MDM initiative?
- Lack of basic understanding of:
- How core business processes work
- Core master data entities used in their business
- Where the master data is located (i.e. what operational and BI systems)
- Who currently maintains it
- How it flows across applications
- How it is synchronised
- Impact on business performance from poor master data
- Inability to recognize that master data is not owned by an application and should not be associated with just one application
- No business ownership of master data to govern it
- No data governance control board and no Chief Data Officer/Architect