Master Data Management
Five critical factors in implementing effective master data management
If you search on the internet why business intelligence projects fail, data issues would be one of the core reasons on every list.
Organisations often face challenges with sourcing data from different verticals in a compatible format. This causes information gaps, data silos, and prolonged communication problems between departments.
As a result, organisations constantly streamline their data and business processes for operational growth, efficiency, and regulatory compliances. Master data management (MDM) helps organisations streamline business processes and improve data quality across different verticals.
What is a master data management strategy?
Organisations want to create the best version of data spread across their verticals, such as sales, product development, marketing, finance, and suppliers. An efficient MDM strategy assists all these verticals by retaining distinct data and enriching, matching, merging, and governing that data from a central system. This helps the verticals receive and access clean and consistent data, in line with the larger business objectives like cost-effectiveness, improved data quality, faster product launches, and efficient regulatory compliance. However, MDM’s success requires a highly structured approach.*
Key success factors for master data management implementation
The sheer volume of enterprise-wide data is expanding at an unprecedented rate. Therefore, one of the major challenges organisations face is to manage this data. However, implementing master data management (MDM) has little to do with technology and more to do with planning the implementation properly. Let’s take a look at a few factors that will help organisations in implementing effective MDM:
- Set clear objectives: Spend sufficient time identifying and setting the right objectives with measurable outcomes. The best way is to define these outcomes in non-technical terms. This will allow stakeholders to ascertain the level of understanding regarding the outcomes. True digital transformation is possible where an organisation not only makes money but also implements net-new processes. The next course of action is to define the sequence of activities and a roadmap based on priorities. It is also important to get the consent of the senior management to safeguard against any mergers or acquisitions in the future.
- Remember that MDM is not just another database:
- Partner with the key stakeholders:
- Measure and communicate the business value:
- Keep the information backfill for the next stage:
The goal of an MDM system is to break down the barriers across high-value data assets and create a model where data is readily available to the right stakeholders in a proper format. Many organisations make the mistake of considering it as just another database, which it isn’t. MDM has its own set of rules, and the master data management best practices help achieve a simple and clean model that is easy to manage and provides great value to the organisation.
Once the MDM system is in place, the organisation needs to take ownership of data as an asset. This implies shared ownership among the key stakeholders, with each managing their share. This could also often lead to difference in opinion wherein the consultation of an experienced master data management implementation team will be helpful.
The organisation must have a communication plan in place to address the progress, changes, and success of the initiative to the employees. This should include quantifiable results along with any unexpected benefits that the organisation can present to its team. For a successful master data management implementation, it is essential to inform the employees and ensure seamless adoption at every step.
Information backfill refers to sending high-quality data back to its source systems resulting in data clean-up. For example, the master data management could send data back to its source ERP system via a data bus architecture. This type of architecture needs to be set up alongside the initial master data management implementation from the start of the project at an additional cost.
There is a lot of value generated by having only one authoritative source of high-quality data, that is, the MDM system. By doing so, an organisation can achieve the results and start seeing ROI quickly. One can keep the information backfill for a later stage once the initial goal of having a high-quality data source is met.
Read how Infosys BPM helped a global consumer product company save $15.5 million, reduce time-to-market by 6x, and achieve 90% automation with MDM services.
How Infosys BPM can help ?
We deliver end-to-end solutions around MDM, master data management solutions and services covering advisory services, data quality management, and operational support. We customise services to fit our clients’ business needs, delivering clean and unified data for enterprises, as well as helping them achieve effective data governance with continuous data quality improvements.
With a dedicated MDM practice, Infosys BPM has significant experience in managing enterprise data across key domains such as products, materials, customers, vendors, pricing, and employees, to name a few.
*For organisations on the digital transformation journey, agility is key in responding to a rapidly changing technology and business landscape. Now more than ever, it is crucial to deliver and exceed on organisational expectations with a robust digital mindset backed by innovation. Enabling businesses to sense, learn, respond, and evolve like a living organism, will be imperative for business excellence going forward. A comprehensive, yet modular suite of services is doing exactly that. Equipping organisations with intuitive decision-making automatically at scale, actionable insights based on real-time solutions, anytime/anywhere experience, and in-depth data visibility across functions leading to hyper-productivity, Live Enterprise is building connected organisations that are innovating collaboratively for the future.