How does my organization become more data-driven? This question is common to many retailers. The customer journey is increasingly starting digitally. The customer only sees the physical product at the very end of the purchase process, when visiting the store or even after the online order for home delivery. The retailer must therefore present the right data to the right customer at the right time. He must be able to get into the digital skin of the customer. Companies that are successful in this area lay the foundation with good master data.

What do we mean by master data? Master data is all data that is recorded once and used in multiple places.

This distinguishes master data from transactional data, which are dynamic, such as current inventories. Master data is not limited to the product domain, such as item descriptions, product features. You can also think of assets, such as images and videos, and domains such as customers, suppliers and locations.

In three blogs we will discuss three aspects for a successful data-driven organization. This blog discusses setting up a master data strategy. The next blog is about data governance, controlling and managing high quality master data. Finally, master data is a moving target because customers are constantly raising the bar and market parties such as GS1 and Amazon are continuously developing. The third blog therefore focuses on lean master data management (lean MDM).

The MDM strategy

When can a Master Data Management (MDM) strategy be successful? This will only work if the MDM strategy fits seamlessly with the business strategy. The MDM strategy then answers the question: how does data contribute to the realization of the company’s strategic goals?

To answer this question, we can look at six business drivers, which are decisive in most organizations:

Business enabler
Master data is required to meet essential internal or external requirements. Think, for example, of supplying product data via a GDSN or ETIM data pool.

Precondition for e-commerce
Master data is required for a consistent product experience across all digital touchpoints. In a retail environment this leads to a higher conversion.

Business accelerator
Master data shortens time-to-market for product introductions and campaigns.

Operational excellence
Master data leads to consistent data with fewer errors, less rework, higher efficiency and lower costs. In a retail environment, good master data can lead to a decrease in the number of returns.

Higher data quality
Master data is merged from different sources into one single point of truth of high quality and without duplicates.

Compliance
Master data management guarantees that all laws and regulations can be met. In a retail environment, customers must receive correct and complete product information, for example about allergenic ingredients in foods or cosmetics. In addition, there are more and more conscious consumers who are specifically looking for products with a sustainability or fair trade label.

Is this information need only available to customers? The business drivers already show that this is not the case. For example, compliance data can be of great importance for the entire chain from raw material supplier to consumer. And recording correct master data directly at the source contributes to operational excellence. This applies not only to product data, but also to other domains such as supplier and customer data.

Vision and strategy
It explains how a data-driven organization’s MDM strategy contributes to the company’s strategic objectives.

data architecture
The data architecture makes clear to the entire organization what the scope and meaning of the master data is. Which data objects are needed, how are they defined, what are mutual relationships, which conditions apply? What are the golden-record attributes that each item must contain? This also requires a good understanding of which data is needed where and when.

Organization and governance
An MDM strategy can only be successful if it aligns with the business strategy and is supported throughout the organization. If the MDM strategy spans many domains, it can affect virtually every department. Additional budget is often required and it must be clear to management how this will contribute to the objectives.

Processes
The design of an operational MDM process often leads to new ways of working. It is often wise to implement the changes step by step, so that employees are constantly asked for changes. Time and attention will be needed for this change management process.

data quality
For a successful MDM program it is essential that the data is complete and accurate. This can partly be overcome by (automatic) data validations before data is released for publication to users. In addition, dashboards and reports can be built to continuously monitor and improve data quality. This not only provides insight, but can also be very motivating for users to get and keep the data quality high.

ICT support
Technical tools such as MDM, PIM and CRM systems are indispensable to guarantee a high quality of master data. Choices in this respect depend on the maturity of the organization in the field of data management. ICT support is crucial, not only for setting up the infrastructure and the first implementation, but also for interfacing between systems, maintenance and upgrades and solving malfunctions.

Best practices for a successful MDM strategy

Based on customer experiences, we can share some best practices for building a successful MDM strategy.

There are different stages of MDM maturity in companies. In fast-paced markets with a large online sales share, awareness is often high, for all data domains (product, customer, supplier, assets, etc.). Other companies in more traditional markets, often in the B2B segment, may still struggle with a legacy of flawed structure and low data quality. Sometimes management is not yet aware of this.

It is therefore crucial to create urgency in the organization. A clear business case can quantify the need. This can indicate how MDM can contribute to the business drivers and solve bottlenecks in the organization. This creates support for the necessary changes and associated budgets.

It is important to build a strong data governance team, in which all disciplines are represented, such as data management, process management, organizational and change management, ICT and, last but not least, the users from the business such as marketing, sales, e-commerce, purchase and logistics. Knowledge from outside can help if it is not (yet) available internally. Start small with a strong management sponsor and a few early adopters, then expand step by step.

Implementing an MDM software solution can be realized quite quickly in itself and is often not the bottleneck. The business processes are often set up and linked to each other over a period of many years. Especially in large, complex organizations it can be much more complicated to adapt the data management processes to the desired new MDM strategy. All disciplines involved must be able to think and discuss at an early stage, so that there is support and the benefits of MDM can be optimally utilized.

Developments in the market, technology and organizations are moving very quickly. In the retail environment, for example, consider the rapid rise of flash delivery services. It is therefore important that the MDM strategy also has a certain flexibility. The MDM software solutions and business processes must therefore also be able to be adapted to an adjusted strategy. For large complex organizations, it is also important that the solutions are scalable to multiple countries, business units or domains.

It is essential that the MDM vision and strategy are broadly supported by all stakeholders in the organization. Only then start with an MDM project and make sure that it does not run parallel with all kinds of other projects. Don’t compromise on the desired process flow, data model and business logic that are defined in the design. There is sometimes a temptation to do so if it simplifies integration with existing systems. But then the situation does not really get better and a lot of repair work is needed later on to achieve the desired result.

After delivery of the MDM project, the work is not done. The software and the business processes must be maintained and adapted to changing requirements of users, technology and the market. It is important to maintain good contact with stakeholders and to continue communicating about the contribution of MDM to the success of the company.

Conclusions

If growth or efficiency is important, as a company you cannot do without an MDM strategy. MDM is not a must, it can ensure that the company can maintain speed and remain flexible. A good MDM strategy requires vision and the willingness to invest in tools and organization. Everyone must be included, because everyone in the company is a link in managing data.