Amir Zaki recently attended the MDM and Data Governance Summit in Sydney and he shares some of the key takeaways.
The MDM and Data Governance Summit this year covered a wide range of topics; from the Keynote by Aaron Zornes (Chief Research Officer of The MDM Institute) discussing the emerging trends to the pros and cons of existing Master Data, Data Governance and Reference Data product vendors. In addition, a number of case studies explored implementations across various levels of maturity within organisations.
The two key takeaways from the summit are summarised below;
1. Vendors are Embracing Cloud
What was not possible for smaller organisations in the past, has now more than ever become possible with the use of Cloud. Smaller organisations can now implement tier 1 technologies without the infrastructure outlay historically associated with an MDM solution. The MDM vendors are now focussing on ensuring the stability and extensibility of their platforms in the cloud, which naturally will drive more and more implementations.
However, the focus on Cloud implementation growth has led many vendors to focus less on investment in their MDM products. Hence, when performing a toolset selection, an important factor to consider is both ongoing investment by the vendor into their toolset, in addition to cloud investment.
2. One product and implementation does not fit all
Some MDM Vendors offer specialised products, for example, Product Information Management (PIM) or Customer Data Integration (CDI) while other vendors offer generic multi-domain products. In addition, a number of vendors offer multiple products with very different implementations that they tailor based on an organisation’s needs.
One product or one implementation may not meet all the needs of your organisation, and a combination of tools may be required to provide the necessary capabilities.
As most of the Tier 1 products require a large capital outlay, choosing the right toolset becomes a fundamental decision that can take an organisation on an implementation journey that is difficult to unwind. The key to making this decision a success is to define use cases that are tested thoroughly in the proof of concept phase. A number of example considerations are listed below;
- Specificity on what capabilities are being introduced now and in the future within the organisation. E.g. Customer Mastering, Reference Data Management.
- Alignment with your organisations architectural roadmap with regards to the role the product will play overtime. E.g. Batch integration vs. Real-time integration.
- The maturity of data governance and workflow the product can provide to augment the people and process aspects of Data Governance
- The volume of data the product can process which may differ per domain for your organisation e.g. Customers vs. Products.
- The software’s complexity and footprint, and does the organisation have the required capabilities to manage it ongoing
- The products roadmap and further investment by the vendor
Altis offers a range of services to support you in designing and implementing MDM and Data Governance best practice solutions. By taking a holistic view of Strategy, Structure, Policies, People, Processes and Systems, we work with you to define pragmatic and right-sized recommendations. Read more about how we can help on our Strategy and Advisory page.
