Why Do You Need a Data Democratization Strategy in Master Data Management
So, you’ve got a newly implemented master data management (MDM) system, an MDM strategy is in the works, you have your eyes on the goals, and you have aligned people and processes in the business and IT departments. It’s time to make better sense of your data, base your judgments on cold hard facts, achieve your goals targeted at business improvements, gain competitive advantage, improve operational efficiency, begin digitalization, find new avenues for growth, and plan business makeovers.
And the one strategy embedded within your MDM strategy, which plays a silent but vital role, is your data democratization strategy. It’s what makes sure that the right kind of data remains accessible to the right individuals at the right time to make optimal decisions for organization’s best interest. Therefore, most importantly, there is a need to see data democratization not as an isolated concept but through the context of MDM because any hindrance to democratization can derail the best of MDM goals. Here’s taking a closer look at it.
Data Democracy: Essential to Analytics and Insight
One of the critical purposes of MDM is to perform accurate data analysis to obtain high-quality data insights and integrate them into decision-making, which concludes in taking appropriate action. In the entire process, what matters most is the value as well as the speed of attaining insights. And that’s where data democracy matters.
Since every insight is tied to a decision which is further tied to a business opportunity, it becomes imperative for high-quality data to reach the right people, so they can generate the right response, develop and deploy the right solutions needed to create the right capabilities. Therefore, democratized data ensures that the process remains flawless, lean, and efficient.
Data Democracy: The Route to Data Governance
Data governance is at the heart of MDM. Governance involves individuals right from the executive level, strategic level, tactical level, right down to the operational level. It is about creating policies, and rules, allocating roles and responsibilities for data ownership and secure access, compliance, transparency, maintenance, and accountability. Well-governed data further assists in data classification, modeling, quality control, data link and merge, and data usage.
Democratized data thus becomes a significant requirement to ensure that the correct data is discovered by data stewards, analysts, and data scientists. Hence, they develop structured, meaningful, and speedy data solutions to present unified, 360-degree customer views. In other words, data democratization is the first step to disentangle the complexity that data governance simplifies.
Data Democracy Is About People, Processes, and Business (Just Like MDM!)
The idea of data democracy is rooted in a data-driven culture. A culture that thrives on empowering people, enabling processes, and helping business objectives. For example, organizations heavily dependent on a culture of ‘IT ownership’ will find it hard to implement MDM as IT solely manages the data. Therefore, all the data requests will need to go through queries sent to the IT department. To truly make MDM work, interdepartmental teams, including non-technical users, must be formed. It requires a concerted effort from people within the organization to make sure data is seen from a democratic lens and is detached from traditional practices and legacy management structures. Changing mindsets is the first step to MDM.
Train People (in Data Democracy) to Succeed in MDM
Even with the right intentions, an untrained staff may not be the right fit for undertaking data democratization initiatives. When organizations have the tools or have implemented the platform, but employees lack the training, it can only lead to wasted efforts, inconsistencies, and inaccuracies in activities such as writing queries and interpretation of data. Creating a ‘manual’ is an excellent way to train the staff to understand data definitions and enter, access, and interpret data—but it is not enough. However, more than making the staff understand the tools, it’s imperative to make them comprehend the actual scope, significance, and business relevance of data democratization for the entire organization.
Leadership Buy-in and Belief in Data Democracy (Leads to Successful MDM!)
Data democracy starts at the top. It begins with a belief (in data) that trickles down from the upper to the middle management and finally to the bottom echelons of the organization. The cultural shift brought in by the leadership’s belief in data democracy challenges, legacy mindsets and provides the needed underpinning to meet organizational objectives and alignment with evolving strategies, visions, and priorities. Therefore, if the leadership displays a firm belief in data empowerment and actively works towards removing any impediments to democratize data, it will pave the path towards an excellent understanding of data within the organization and lead to extracting the right value from data initiatives.
Wrapping Up: MDM Needs Data Democracy and Vice-Versa
For master data management to focus on ensuring the accuracy, consistency, and integrity of critical data elements across organizations, a solid foundation supported by democratized data is crucial. Data democracy provides widespread data access and usability for a broad range of users across different teams and departments to carry out MDM processes and initiatives. More importantly, the essential elements of data democracy, such as data literacy, meaning and relevance of data types, and emphasizing the understanding of data in front of a larger group of stakeholders, lays the right foundation for MDM. A democratized data environment leads to ‘data enlightenment,’ empowering and enabling organizations to uncover the value of data, enhancing the organization’s overall data maturity.
To summarize, it can’t be stressed enough that a thriving data-democratic environment can be tremendously valuable for MDM to flourish.
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