Search for:
Customer MDM and the SMB

Small and Medium Businesses (SMBs) face several core challenges when adopting enterprise Master Data Management (MDM) solutions, whether this be a Reltio, Stibo, Profisee or one of the even bigger multidomain solutions. These challenges are often due to a misalignment between the complex nature of these tools and the more limited resources and simpler needs of SMBs.

The main challenges are these:

  • Cost and Complexity: Historically, MDM was seen as prohibitively expensive with lengthy deployments. While modern cloud native SaaS models reduce upfront hardware costs, the total cost of ownership (TCO) and consulting fees can remain high for many SMBs with limited budgets and IT expertise. SMBs often find the full scope of features and complexity of enterprise MDM to be overkill for their simpler needs, such as basic deduplication or customer 360, leading to them paying for advanced features they don’t use.
  • Time to Value: Implementations of enterprise MDM solutions can stretch for months or even years, which strains SMB patience and expectations for return on investment (ROI). New features and customizations may also have to wait for product-wide releases, delaying time-to-value for SMBs.
  • Resource Burden and Skills Gaps: Enterprise MDM typically requires deep organization-wide data governance, custom data stewardship, and significant post-launch maintenance, which can be overwhelming for lean SMB teams. Effective use of these tools demands specialized training for administrators, developers, and data stewards, a stretch for smaller teams not solely dedicated to data management. SMBs particularly feel the pain of vendor-dependent workflow changes, as they often lack in-house MDM experts.
  • Support Responsiveness and Vendor Dependency: SMBs often experience support delays, sometimes waiting days or longer for vendors to deploy or fix critical system components. Even basic customizations, like workflow updates or expanding data domains, frequently require vendor action, slowing SMB agility and innovation.
  • Usability and Integration Issues: Complex features such as survivorship configuration, match rules, and large data exports can be cumbersome for smaller IT teams, especially when technical resources are limited and the user interface or documentation falls short. Slow large data downloads and JSON formats as default outputs place extra strain on SMBs who lack robust Business Intelligence (BI) or integration resources. SMBs need simple, pre-built connectors and quick integrations, and solutions requiring heavy customization can leave them behind.
  • Unpredictable Operating Expenses: Many SaaS MDM offerings including Pretectum CMDM, impose quotas or API call limits, which may force SMBs to incur extra costs as their own data volumes and integrations expand, creating unplanned operational expenses.

Despite technical advancements in SaaS solutions, SMB customers commonly complain about excessive complexity, a high reliance on the vendor, support delays, and a fundamental mismatch between what enterprise MDM offers and what SMBs truly value. The “DNA” of enterprise MDM, with its inherent complexity and resource demands, persists even in “SMB-friendly” SaaS wrappers.

This is why we think Pretectum may present as a generally better fit for the SMB market with its equally complex needs for Customer Master Data Management (MDM), but less resources.

The Hidden Infrastructure Crisis: Why CIOs Face a Perfect Storm in IT Talent Management


As organizations navigate the complex landscape of digital transformation, CIOs are confronting an unprecedented crisis that extends far beyond the typical challenges of recruitment and retention. At its core, this crisis represents a fundamental misalignment between traditional IT infrastructure management and modern development practices – a gap that threatens to widen as experienced IT professionals retire […]

The post The Hidden Infrastructure Crisis: Why CIOs Face a Perfect Storm in IT Talent Management appeared first on DATAVERSITY.


Read More
Author: Daniel Clydesdale-Cotter

MDM vs. CDP: Which Does Your Organization Need?


Most, if not all, organizations need help utilizing the data collected from various sources efficiently, thanks to the ever-evolving enterprise data management landscape. Often, the reasons include:   1. Data is collected and stored in siloed systems 2. Different verticals or departments own different types of data 3. Inconsistent data quality across the organization Implementing a central […]

The post MDM vs. CDP: Which Does Your Organization Need? appeared first on DATAVERSITY.


Read More
Author: Mahtab Masood and Arjun Vishwanath

How to Become a Data Science Freelancer


Entering the world of freelance as a data professional offers freedom, diversity in projects, and the thrill of entrepreneurship. But how does one transition from a traditional job to a successful freelance career in the data field? Insights from an experienced freelance data consultant shed light on this journey. Table Of Contents 1Key Skills and […]

The post How to Become a Data Science Freelancer appeared first on LightsOnData.


Read More
Author: George Firican

woman and man discussing work matters together
When none is better than bad

Selecting a data management consultant is a critical decision for any organization that aims to effectively manage and leverage its data assets. The value of choosing one you have worked with before cannot be overstated. In this fast-paced digital era, where data is considered the new oil, organizations need an expert who can navigate the complex world of data management and help them extract meaningful insights. Consider some key reasons why selecting a familiar data management consultant is advantageous.

Working with a consultant you have previously collaborated with provides a level of familiarity and trust. Building a strong working relationship takes time, and having prior experience with a consultant ensures a smoother and more efficient process. The consultant already understands your organization’s specific needs, challenges, and goals. They are familiar with your data infrastructure, systems, and processes. This familiarity minimizes the learning curve and enables the consultant to hit the ground running, saving valuable time and resources.

A known data management consultant brings a wealth of contextual knowledge about your organization. They possess insights into your data management history, past projects, and the overall data landscape. This knowledge is invaluable when it comes to identifying potential pitfalls, leveraging existing data assets, and aligning data management strategies with your business objectives. The consultant can provide tailored recommendations and solutions that are aligned with your organization’s unique requirements, resulting in more effective outcomes.

An advantage of working with a consultant you have previously engaged with is their understanding of your organizational culture. Every organization has its own set of values, practices, and communication styles. By selecting a consultant who has worked with your organization before, you ensure a cultural fit. The consultant is aware of your organizational dynamics, decision-making processes, and stakeholder expectations. This familiarity enables them to integrate seamlessly into your team, collaborate effectively, and communicate in a manner that resonates with your organization’s culture, ultimately leading to better outcomes and higher adoption rates of data management initiatives.

A known consultant can leverage their previous experience and successes to drive continuous improvement. They can build upon previous projects, lessons learned, and best practices to optimize your data management processes. By understanding what has worked well in the past, the consultant can identify areas for enhancement and implement strategies to overcome challenges more effectively. This iterative approach ensures that your organization’s data management practices evolve and stay up to date with the latest industry trends, ultimately maximizing the value derived from your data.

Selecting a data management consultant you have worked with before can result in cost savings. Engaging a new consultant often requires investing time and resources in onboarding, training, and knowledge transfer. By choosing a familiar consultant, these expenses can be minimized or even eliminated. The consultant is already familiar with your systems, data models, and workflows, reducing the need for extensive orientation. This efficiency allows you to allocate your budget and resources more effectively, focusing on the actual implementation and execution of data management strategies.

The importance of selecting a data management consultant you have worked with before cannot be overstated. The advantages of familiarity, contextual knowledge, cultural fit, continuous improvement, and cost savings make this decision crucial for successful data management initiatives.

By leveraging the existing relationship and expertise, organizations can enhance their data management capabilities, derive valuable insights, and stay ahead in the data-driven landscape of the modern business world.

What you should know about data democratization and what it can do for your business data operations


In this digital age, the growth and success of businesses depend on the utilization of data. According to a 2020 report by Experian, 98% of organizations say that having high quality data is extremely important in achieving their company objectives. While data is a valuable asset, historically it has been controlled by in-house IT teams. Data […]

The post What you should know about data democratization and what it can do for your business data operations appeared first on LightsOnData.


Read More
Author: Ben Herzberg