Tag: Data Quality

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Trends in customer master data management and how Pretectum CMDM supports adapting to these changes

Master Data Management (MDM) serves as a foundational pillar in navigating the complexities of the contemporary business environment.

As organizations grapple with the challenges of managing vast datasets, customer MDM in particular, emerges as a critical solution to ensure the accuracy, consistency, and reliability of customer master data records.

Pretectum CMDM‘s adaptive response to the changing customer MDM landscape comes with some key features and benefits that you should consider when you are looking holistically at CMDM.

MDM refers to the structured processes and technologies employed by organizations to manage their critical business data systematically. MDM encompasses data entities such as customer information, product details, and other core elements that are integral to the organization’s operations but the customer master and customer master data management (CMDM) represents a significant data element that has market and outreach campaigns as a starting point and goods and services delivery accompanied by payments and collections as an endpoint.

The significance of CMDM therefore, cannot be overstated. The efficient management of customer master data ensures that organizations have a unified and accurate view of the customer, fostering informed decision-making and contributing to overall operational excellence.

It is important to therefore define the importance, and current state of CMDM across the enterprise, recognise the challenges faced by businesses in managing customer master data, and the role of technology in CMDM. We can anticipate some of the future trends that will shape the CMDM landscape but ultimately it is about how adaptive measures can and should be taken to align CMDM with emerging environmental trends.

The current state of CMDM is characterized by both opportunities and challenges. Organizations are grappling with the increasing volume and complexity of customer data, facing obstacles in maintaining data accuracy and consistency and remaining compliant. Technology often plays a pivotal role in addressing these challenges and optimizing CMDM processes.

The state of CMDM today is marked by a growing recognition of its necessity, not only operationally, but strategically. Organizations that are actively implementing CMDM solutions can streamline their customer data management, yet they face the ubiquitous challenge of data quality, systems and data integration, and appropriateness of levels of data governance.

Despite the benefits of CMDM, businesses still encounter challenges such as business-unit-based data silos, inconsistencies in data formats, and difficulties in ensuring customer data quality and accuracy. Such challenges hinder the seamless flow of information across the organization.

If an organization takes on technology acts as an enabler for more effective CMDM, then you take advantage of the advancements in technology that can contribute to improved data processing, integration, and analytics. Organizations that leverage technological solutions such as the Pretectum CMDM, to overcome the hurdles posed by the complex nature of master data are immediately at an advantage in sharp contrast to their competitors..

Pretectum Data Governance Wheel
Pretectum Data Governance Wheel

The Future Trends of CMDM must be shaped somewhat by emerging technologies that promise to revolutionize data management. Cloud-based CMDM solutions have already gained prominence, they emphasize the importance of real-time data, data governance, and the integration of AI and machine learning in CMDM processes.

Emerging technologies, including AI and machine learning, are transforming the CMDM landscape. Such technologies enhance data quality, automate governance processes, and provide valuable insights, paving the way for more efficient and intelligent data management.

Cloud-based CMDM solutions like Pretectum CMDM, are pretty prevalent, they seamlessly offer scalability, flexibility, and accessibility without the overhead of on-premise or captive legacy IT . Those organizations that gravitate towards such solutions for centralized and efficient management of customer master data recognise that this aligns with a general industry trend, and position roganizations to more effectively meet their compliance obligations.

Organizations that dismiss customer data governance and stewardship, do so at their own peril. Such topics are gaining prominence as organizations recognize their pivotal role in ensuring data quality, compliance, and security. Future CMDM trends emphasize the need for robust data governance frameworks of customer mater data management, aligning with Pretectum CMDM‘s focus on comprehensive tools for data stewardship, audit trails, and policy enforcement.

These days, AI and machine learning suggest a transformative role in CMDM, offering advanced capabilities in data matching, deduplication, and enrichment. Pretectum CMDM integrates these technologies to empower organizations with enhanced analytics and data-driven decision-making.

We believe that Pretectum CMDM stands as a noteworthy player in the CMDM landscape, offering a centralized solution that adapts to the evolving needs of organizations around customer master data management.

Pretectum CMDM is a robust CMDM solution designed to centralize and manage customer master data efficiently. Its architecture is optimized for real-time and batched data processing, providing organizations with optins for a seamless and responsive platform for customer data management.

Pretectum CMDM demonstrates agility in adapting to the changing CMDM landscape. Embracing the cloud and integrating AI and machine learning algorithms as required, Pretectum CMDM incorporates data quality for data integrity, and focuses on providing an intuitive user experience. Adaptive measures position Pretectum CMDM as a forward-looking solution aligned with future CMDM trends.

Organizations stand to benefit from Pretectum CMDM‘s adaptive features, including enhanced data quality, real-time data processing, and comprehensive data governance. The platform’s user-friendly interface and accessibility across devices contribute to an improved overall CMDM experience.

Consider these key aspects of your CMDM strategy and determine their importance for your organization

Pretectum Schema Management Screenshot
Pretectum Schema Management Screenshot with a Country data domain picklist

Data Minimalism: Your organization should only be collecting the information you need to do business. Are you giving your customers the ability to decide exactly what they want to share with you? According to Forrester, 60-73% of the data that is collected is unused anyway. By focusing on essential data, you can streamline processes and reduce the risk of data breaches. Pretectum support multiple data configurations and allows your customers to tell you what they are happy for you to store.

Transparency and Trust: Per Mckinsey, consumers are becoming increasingly intentional about what types of data they share and with whom and companies that are transaparent about data collection and privacy policies are more trusted. Pretectum CMDM supports self service consent.

Data Security: So much customer data is being transmitted online, that it’s crucial that businesses guard customer data from unauthorized parties. Any security breaches severely impact customer confidence and can affect business revenue despite the perspective that first party data is expensive to own, there are a good many reasons why zero and first party data is superior to second and third-party data.

Consumer Data Protection and Privacy: We already mentioned the growing minefield of privacy and data security regulations that are popping up globally, consumers continue to adopt digital technologies unrelentingly, the data they generate creates both an opportunity for enterprises to improve their consumer engagement and a responsibility to keep consumer data safe. Pretectum CMDM helps ensure that the customer data remains secure by encrypting any data that you capture and holding it safe and secure with appropriate RBAC to ensure no unauthorised access is prossible.

Rethink your approach to customer data management, focus on building trust with customers, ensuring data security, and adhering to regulations. Visit Pretectum to learn more.

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Federated Customer Master Data Management

a street with a line of street names on the side of it

Federated customer data governance is an approach to customer data management that allows organizations to implement data governance policies and controls in a decentralized manner across multiple domains or business units. This is an intrinsic characteristic of the Pretectum CMDM approach to Customer Master Data Management (CMDM)

Key aspects of federated data governance are the establishment of governance authorities within each data domain or business unit to define the rules, policies, and standards specific to that business or data domain. These domain-specific governance authorities work collaboratively to ensure alignment with overall organizational goals and data governance requirements. Where appropriate, enterprise or federated business data rules and structures are established and leveraged to influence and control the data creation and management processes.

Federated customer data governance supports the balance between decentralized data ownership/management and centralized data governance, allowing the business domains to work autonomously within their own defined interoperability standards, connecting to their business unit-specific data sources and sharing data internally.

This approach is essential for implementing a successful data mesh architecture, where data is treated as a product and managed in a decentralized manner. The key benefit of federated data governance for customer master data management is that it allows organizations to scale data governance practices across a complex, distributed data landscape while maintaining agility and business and data domain-specific requirements.

Customer MDM Maturity Model

Federated data governance facilitates the centralization of data governance, data quality, and data lifecycle management across an organization.

There are several key steps for implementing a successful customer master data management program that need to be considered:

An organization should begin with an ‘as-is’ state analysis and stakeholder engagement. Understand the vision and key drivers, assess the current state, and document all the “pain points” and goals of the different data stakeholders.

Selecting tools that are contextually appropriate for the organization is an important decision point. Any tooling that is considered should offer a ready-to-run platform for business leaders to easily carry out their customer master data governance, allowing easy access and updating of master data, and the support of seamless integration with any, and all, third-party and internal systems as required.

Approaches to Customer MDM
Approaches to Customer MDM

The adoption of new or different tooling has to be with one goal in mind, namely the establishment of better data governance by integrating business operations, data collection, and data optimization requirements. This goes a long way toward ensuring the business runs smoothly and effectively, all the while, complying with privacy, data handling, and regulatory policies; in accordance with local, regional, and international law.

It should also be recognized and acknowledged, that maintaining a customer-centric approach is a concept that, just like customer data itself, is constantly evolving. Any customer master data management solution should be composable, adaptable, and evolve with the compliance, integration, and business needs of the organization, seamlessly. Only through the best possible customer data can an organization hope to ultimately build and maintain strong customer relationships.

The user experiences within the tools and applications should also be supportive of employees and employee tasking while also helping in the handling and safe access and sharing of specific customer data to accelerate digital transformation, meet business needs, and ultimately support the organization’s pursuit of exceeding customer expectations.

Role-based-Access-Controls (RBAC) are an important control element in ensuring that only the right people have access to the right data and platform functionality. Extensive auditing and logging is an important aspect that needs to be in place here also.

Any platform under consideration should also continuously maintain the customer master data to ensure accurate and up-to-date information, avoid discrepancies in the customer master, and maintain the highest possible data quality.

By considering all of these aspects, organizations can better implement an effective customer master data management program that delivers trusted, high-quality data to drive operational efficiency, improve customer experience, and enable better business decisions.

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Best Practice: Cleansed Customer Master Data

broom sweeping up

Poorly managed and unclean customer master data can give rise to numerous issues and hurdles for businesses. At its core, these challenges often manifest as inaccuracies in data, encompassing incorrect contact details, addresses, and other vital information. Such inaccuracies can lead to misunderstandings, miscommunications, and failed business transactions, alongside the accumulation of duplicate records in the system. The presence of duplicate customer entries can sow confusion, waste resources, and introduce errors in analysis and reporting processes.

Additionally, the absence of crucial details may impede effective customer communication, hinder marketing efforts, and adversely affect overall customer relationship management. This, in turn, can impact decision-making processes, resulting in faulty strategic decisions, ineffective targeted marketing campaigns, and misallocation of resources. The repercussions extend to reduced productivity, with employees expending more effort and time in managing data.

Furthermore, the ramifications of poorly maintained customer data extend to a subpar customer experience marked by irrelevant communications or difficulties in accessing services. This dissatisfaction can potentially lead to the loss of business. Finally, inaccurate or outdated customer data poses the risk of non-compliance with data protection regulations, legal issues, fines, and damage to the organization’s reputation.

Outdated and irrelevant customer data creates a messy and purposeless digital landscape. This demands immediate attention. Far from being acceptable, this situation necessitates a decisive move toward comprehensive bulk data cleaning; because nearly all aspects of an organization’s information are intricately linked through the customer master and this may reside in CRM, a CDP, or some other customer data management platform but likely is not in a CMDM (Customer Master Data Management) system.

The imperative here is clear then – preserve this invaluable data asset not by choice, but by necessity. Unkempt customer data not only raises questions about your organization’s credibility but also poses a tangible risk to operational efficiency and compliance.

The rate at which customer data becomes obsolete can vary greatly depending on the industry, the type of data, and how often it’s updated. However, it’s important to note that data can become outdated quite quickly. The Data Genomics Index found that over 40% of stored data has not been touched in over three years, and is considered ‘stale’.

A significant portion of stored data is considered redundant, obsolete, or trivial (ROT). A 2016 Veritas Global Databerg Report found that 33% of data is considered ROT and provides little or no business value at all.

All this serves to underscore the importance of regular data cleansing and updating to maintain the accuracy and relevance of customer data. It’s also crucial to have a robust data governance framework in place to manage the lifecycle of data and ensure its quality and compliance.

Establishing a Single Source of Truth (SSoT) is considered the “brass ring” of data capability in that it refers to a definitive and centralized repository for customer information that acts as the authoritative source for all customer-related data across the organization.

Having regularized standard Data Governance Processes provides some assurances around data accuracy and completeness, and integrating Customer Data with Other Systems and Data Sources allows for a more comprehensive view of the customer. The presence of Data Lineage and Auditing in all your data management activities helps you to track the origin of data and changes made to it over time.

Providing Self-Service Capabilities for customers to manage their data empowers the customer. It can lead to more accurate zero and first-party data which is preferred over second and third-party data.

Regularly Evaluating and Improving Processes for Customer Data Management is part of continuous improvement and is key to maintaining high-quality data. Taking Security seriously and ensuring data privacy should be integral to all your organization does with customer data to build and maintain customer trust.

Customer data master Data Cleansing isn’t just a clean-up; it’s a strategic process meticulously executed to purge irrelevant and corrupted records, creating a pristine canvas for accurate data entries. The significance of doing this extends beyond driving operational efficiency – it is a cornerstone for optimizing data management operations, with the further promise of access to invaluable customer insights.

The clutter within customer data masters, if left unchecked, becomes a bottleneck in customer data management. The domino effect is felt most acutely through the inefficiency of incomplete and duplicated records that may be present in the data landscape.

A daily ritual of data cleansing should be not just a routine; but a habit that holds all data-using teams together. Any deviation, be it due to data inaccuracies or outdated information, sends compounding waves of chaos through normally streamlined processes, derailing promises to upsell, marketing, service, and support.

Data Cleansing Action

Data cleansing shouldn’t be viewed as a pointless chore; it’s a catalyst for unlocking the new, freeing teams from broken, outdated, and duplicated data. Success in outreach and communications campaigns hinges on a hygienic robust database of customer data. Cleaning the customer data master allows teams to channel focus toward accurate accounts, bypassing the wasteful exercise of re-verifying incorrect information through emails or calls.

Cleaning the customer data master is not to be trivialized, at scale, in particular, it can be a challenge. Fortunately, systematic automated data cleansing is possible, liberating companies from a historically time-consuming activity.

Understanding the nuances of data cleaning is paramount, irrespective of the chosen method.

Clear out Duplicates: Duplicates are stealthy infiltrators, entering customer data masters through various channels. Identifying and eliminating them is not just a best practice; it’s a necessity to prevent potential customer loss. Automation takes centre stage to proactively block duplicates and fortify data integrity.

Archive the Old Data: Archiving old data in the customer data master recognizes its latent value. Though seemingly dormant, certain data holds perpetual importance, adapting to the context of the moment.

Data Cleansing Tools: Choosing the right data cleansing tools is a strategic decision. Opt for tools equipped with smart duplicate data detectors, data formatting capabilities, and automation functionalities. The aim is not just to prevent bad data but to fortify customer data masters against inaccuracies.

Customer data master data cleansing transcends the realm of a mere cleanup tool; it emerges as the catalyst propelling your company toward sustained growth. The strategic elimination of obstacles – duplication, data overload, or inaccuracies – accelerates overall growth and amplifies your company’s performance. The focus should not merely be on eliminating unwanted data; it should encompass the optimization of data quality, ensuring the CMDM system operates as a beacon of efficiency within your organizational framework.

The key lies in eliminating the unwanted and embracing the ethos of better quality and efficient data management – the essence of customer master data cleansing.