21st Edition
Data Management Leaders Conference
Driving data as an asset concept within the business
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What are the key considerations when it comes to developing a robust data governance framework?
The fundamental consideration for a robust data governance framework is to secure business sponsorship and engagement at top levels of the company. Business stakeholders tend to perceive data governance as a function of IT which is fundamentally wrong. Recognizing and addressing this early on in the program is key to success. Another key consideration is to choose a high impact area with sufficient business support to test & learn, then be methodical about scaling what works. Data Governance is a field of many possibilities. There are hundreds of frameworks and consultants out there eager to help but it needs to fit into the culture of an enterprise. Finally, it is imperative to be clear on expected outcomes and how success of data governance will be measured. It is not about implementing tools such as Data Catalog, Data Lineage or Data Quality for the sake of it.
What could be some of the future challenges as well as the trends within the governance process?
We expect continued evolution in making data governance simpler for Business to understand and implement. The fundamentals of data governance will only slightly evolve but we expect to see a massive simplification in tools and practical implementation guides. Already today we see major technology providers offering more complete and consolidated software packages to connect elements of data governance in one place, but they are still clunky for an average business user. In addition, we expect a breakthrough in how meta data is created to enable faster activation of governance. With existing boom in data creation (e.g. with IoT devices) we will need automated ways of populating data glossaries, lineage, etc.
How has data governance process changed in the recent climate and what are the major challenges today?
In recent years data governance has become a priority for many companies. Business leaders today fully understand the power data to support business objectives, such as understanding consumers or designing better products. More and more they realize that business goals will only be achieved if foundational data governance is in place. Nowadays, data quality and data ownership topics occur in every conversation about new IT capabilities. With this, expectations for data governance to ensure data can be trusted have accelerated big time. Key challenges which we observe are: (1) expectations far exceed speed with which data governance is established – we need to remain focused and methodical not to boil the ocean, (2) finding simple language to educate business partners on their role in data governance, and helping them find practical ways to go about it.
How or to what extend does poor data quality threaten the business?
Poor data quality creates obvious business risks ranging from bad decision making to legal exposure. Not to mention hours spent on fixing bad and chasing missing data. Risks are easier to address when both ownership for data creation and its usage are within the same organization. In this case middle and upper management recognize the need to improve and set clear priorities. When poor quality concerns data crossing the enterprise, originating in one division and consumed in another, challenges grow exponentially. Often data quality requirements of the consuming division are unknown or different to what the originating function considers to be good enough. Solving such challenges requires crossing silos and creating multi-functional teams, as well as significant education.
Ahead of the 21st Edition Data Management Leaders conference we spoke with Mikolaj Maciejewski, Senior Director, Data Management Transformation Leader at Mondelēz International, Switzerland. Mikolaj (Miko) is a global Senior Director of Data Management Transformation at Mondelēz. He engages leaders across business functions to increase business value through digitized, orchestrated and governed data processes. Prior to Mondelēz Miko worked at Procter & Gamble as IT leader driving global transformations and running solutions across Marketing, Supply Chain and Data Management. He has combined 18 years of IT and shared services experience in FMCG industry.
25-27 January, 2023
DoubleTree by Hilton Amsterdam Centraal Station | Amsterdam, Netherlands
Mikolaj will be presenting a case study during day two (27/1/2023) of the 21st Edition Data Management Leaders conference!
For registration pricing and multiple attendee discounts, please contact:
Ria Kiayia
All Rights Reserved. marcus evans ® 2022
Interested? Do you feel you will benefit?
An interview with Mikolaj Maciejewski, Senior Director, Data Management Transformation Leader at Mondelēz International, Switzerland
What do you hope to gain by attending this Data Management Leaders conference and what can attendees to learn from your presentation?
Attendees will learn about Mondelēz’s approach to offering trusted data in our data hub. It is an approach and certainly not the only one which can work. Therefore I expect to learn from others how they are solving for the problem of data governance and trusted data.
Case Study: An Approach to Trusted Master Data in the Data Hub
As enterprises invest in digital transformation and accelerate data & analytics objectives, the need to access trusted master data has grown exponentially. However, often master data is spread across multiple systems, data governance is not yet in place, and projects underestimate importance of data quality. How can this be solved?
