We spend the majority of our time comparing and contrasting new shiny tools without focusing on the right type of talent needed to achieve clean governed data. But, here’s the thing…
Platforms and processes are nothing without people.
This is the exact topic we covered in a recent panel discussion about effective master data management at ThinkLinker’s MDM’s Data Management Marathon 5.0 event. Four data management experts joined me on the panel:
- Moli S. Thomas of NWEA
- Rute Felix Vendeirinho of European Investment Bank
- Ari Cohen of Investec
- Kuldeep Sharma of The Hershey Company
In this panel discussion, we explored the makeup of different team approaches to
accomplishing effective master data management (MDM) and turning data into business insights.
To inspire your data improvement initiatives, here are some of the most valuable insights from the panel.
1. What are the roles of a modern data team?
One of the themes present in the panel is the importance of creating a cohesive approach to data across the organization. Modern data teams need to engage users from all stripes of the organization to demystify data governance and promote data literacy.
One way to do this is by building up team members who are familiar with both business and technical concepts and can speak confidently about both. These people can serve as data stewards for their respective functional areas and work as liaisons across multiple departments.
If organizations aren’t focused on developing such individuals that may seem like “unicorns” they will never be successful.
It’s also important to provide data literacy education at an organizational level. Data plays an important role across your entire organization, so establishing baseline data knowledge (and continually improving on that) makes your data management strategy more efficient.
2. Why are these team models shifting?
Several forces are driving this change with data teams.
One of the main reasons data teams are changing is simply because data capabilities have also changed. Thanks to rapid digital transformation, people can do more with data than ever before. However, there’s a tradeoff to having that superpower—more pressure to perform and more challenges to navigate.
Modern data teams have to evolve to keep up with the speed of transformation, especially as more tooling is thrown into the mix. This means a continued focus on maturing processes and data literacy.
Another big reason for this transition is meeting consumer demands in a highly regulated environment—given the rise of legislation like GDPR and CCPA. It’s a really interesting time, where “the customer is always right” has taken on a whole new dimension. Consumers are becoming more data literate and this grassroots type of movement is really pushing where organizations are going.
Succeeding in this consumer-driven, data-driven world relies on the strength of your master data management and the strength of your teams.
Data privacy is no longer just the privacy team’s area of responsibility. Everyone needs to take responsibility for how data gets managed. You must have cross-functional collaboration to achieve compliance and also leverage data to successfully compete and be a profitable business.
3. Why is effective master data management so important for organizations?
Consumers have adopted digital technologies en masse in recent years, both in the workplace and in their personal lives. This has dramatically changed customer expectations when it comes to data management. Because of this, effective master data management improves client acquisition, customer experience, and retention rates.
Additionally, data management strategies have become more expensive in recent years. Having a master data plan in place across the organization makes things more efficient, allowing organizations to keep costs reasonable if they take an iterative, step-wise approach.
“Rules before tools” was a resounding theme of the panel. Think twice before spending a big budget on master data management tools until you get the “process and people” foundation in place.
4. How do you set up a successful master data management program?
Panelists noted that it can be difficult to find employees who know how to approach data holistically at an enterprise level. This leads to data silos across the organization and gaps in responsibility, which makes it very difficult to set up a master data management strategy.
To avoid this problem, it’s important to clearly define your data quality rules, business processes, and key principles before starting an enterprise-wide implementation. This results in less confusion and makes it easier to create a single source of truth for your organization.
However, it’s also important to make sure you don’t get completely bogged down in your processes. So, you’ll need to be able to adapt to real-life scenarios.
5. What architectural challenges make MDM more difficult?
Technological innovation in recent years has been very beneficial for data management teams as MDM tools and platforms have become more robust. But some of these innovations also present unique challenges.
It seems like there are new data architectures, terms, and patterns that are coined every day. Some stand the test of time while others are forgotten as fads.
One trend that took IT by storm in recent years was the push to microservices. Many organizations have implemented microservices architecture to their business application development practices for the better, but some have taken it too far. While this is often helpful for application integrity, it causes data silos if there is no data governing body included in the process.
Moral of the Story: Rules Before Tools
Tools do not define the strategy…people and processes define it.
Tools are a means to an end, so you can’t hide behind them. What’s more important? Guidelines! You must have an open architecture for tools to play their part.
Looking for a partner to help define your data strategy and data governance framework? Get in touch with Skypoint’s Cloud Solutions Group to get a free 30-min workshop for analyzing your current state recommendations.
