Tag: Implementation

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The Importance of Customer Master Data Management in Evolving Customer Relationship Management

photo of crowd of people in the market

The evolution of commerce and trade, particularly to consumers, has undergone a major shift in recent decades with the emergence of formalized retail beyond community markets.

In the early days, customer relationship management (CRM) was simply about knowing a customer’s name and having a basic understanding of their needs. However, with the rise of technology and the availability of data, customer management has transformed into a sophisticated system that relies heavily on customer data, personalized service, and intimate knowledge of the customer and their circumstances, demographic, preferences, socio-economic status, past purchase history, and customer knowledge.

Management of customer relationships has become an essential tool for businesses to maintain brand allegiance and loyalty. Companies now recognize the value of customer data and its potential to increase revenue, improve customer satisfaction, and reduce costs. The ability to gather, analyze and leverage customer data is what sets successful companies apart from the rest.

A customer master data management system (CMDM) is a crucial component of managing customer relations. CMDM refers to the process of creating and maintaining accurate, consistent, and complete customer data across multiple systems and applications. This ensures that a company has a complete understanding of the customer, with all the necessary data points in one place. A CMDM system allows companies to access customer data in real time, making it easier to provide personalized service and make informed decisions.

The benefits of a CMDM system also go beyond just improving CRM. It also helps with compliance and regulatory requirements, reduces errors and duplicates, and increases operational efficiency. Companies with a CMDM system in place can make better decisions and deliver better service, ultimately leading to increased customer loyalty.

Companies should think more intentionally about customer master data management to maintain brand allegiance and loyalty too! This means creating a strategy for collecting, managing, and leveraging customer data. The first step is to establish clear objectives and goals for the CMDM system. This includes defining what data to collect, how it will be used, and who will have access to it. Companies should also develop policies and procedures for data collection, storage, and use.

Next, companies need to invest in the right technology to support the CMDM process. This includes selecting a system that can integrate with existing applications and provide real-time access to customer data. The system should also be scalable, secure, and customizable to meet the specific needs of the business.

Training and education are also essential for successful and effective CMDM. Employees need to understand the importance of customer data and how to use it effectively. Companies should also provide ongoing training to ensure that employees are up-to-date on the latest technology and best practices.

Finally, companies need to measure the effectiveness of their CMDM initiatives and any system adoption. This means tracking key metrics such as customer satisfaction, retention, and revenue. Companies can use this data to make adjustments to their CMDM strategy and improve their more general CRM efforts.

The progression of customer relationship management since the emergence of formalized retail beyond community markets has been significant; customer data, personalized service, and intimate knowledge of the customer and their circumstances, demographic, preferences, socioeconomic status, past purchase history, and customer knowledge are now critical components of successful CRM.

A CMDM system like the Pretectum CMDM is essential to managing customer data effectively and maintaining brand allegiance and loyalty. Companies that invest in the Pretectum CMDM will be better positioned to provide personalized service, make informed decisions, and ultimately increase revenue and customer satisfaction.

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Your customer data in the cloud

The security of customer data in the cloud depends on several factors, including the security measures implemented by the cloud service provider, the security controls in place for the specific data and the configurations set by the customer.

When customer data is stored in the cloud, it is typically protected by a number of security measures, including: network, physical, encryption, access control, monitoring and auditing. When considering how you manage your customer master data, consider how all these aspects are being handled.

Cloud solutions like the Pretectum CMDM applications are housed in data centers that are secured with access controls, surveillance, and other physical security measures; we make use of the some of the best in class implement network security measures, such as firewalls and data encryption to protect your customer data as it is transmitted over the internet. This data is encrypted both at rest and in transit, to protect it from unauthorized access.

Access to your tenancy and actual data is strictly controlled through role based access controls (RBAC) to ensure that only authorized users can access customer data. In addition, we monitor and audit our systems for security incidents and the potential of attemp[ts to gain unauthorized access to customer data.

Pretectum believe that customer data stored in the cloud is often more secure than data you house in your own systems due to the investment that we make in security infrastructure and personnel, and the implementation of security controls and processes that are designed to protect customer data.

It’s nonetheless important for you to carefully evaluate the security measures we use, and implement additional security controls as needed according to your specific requirements.

Adoption of SaaS based CMDM like the Pretectum CMDM has a number of advantages over on-premise or even private-cloud MDM.

SaaS MDM is typically more affordable as it operates on a subscription-based model and eliminates the need for expensive or dedicated hardware and IT infrastructure The intent with SaaS MDM is to also easily scale up or down to meet changing business needs, making it an ideal solution for organizations that are growing or experiencing changes in the volume of their data.

This approach is also easier to implement and typically require minimal setup and configuration, allowing your organization to quickly realize the benefits of a centralized data management solution. We also continuously update and improve the solution, meaning that our customers always have access to the latest features and security enhancements.

The Pretectum CMDM is also accessible from anywhere with an internet connection, making it easy for employees to access and manage data from different locations and reference the centralized repository for customer master data, improving the quality and accuracy of data across the organization.

To learn more about how you can take advantage of the Pretectum CMDM, contact us to take advantage of a free trial evaluation.

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Data Governance: Master Data is but one facet

Here is an outline of some facets of a robust data governance program that you might want to consider as part of your overarching approach to customer master data management.

Start with goals and strategy

Put aside the data for now and think more holistically about your business objectives. A good business strategy that understands its dependence and relationship with data helps your business to understand what data you need to have and for what purposes. This in turn will inform your data strategy.

Answer these fundamental questions to guide your strategy:

  • What is the problem you are trying to solve with data?
  • What kind of data do you need, where and when?
  • What is the data literacy of your organization and do you need to improve it?
  • What is your data worth? Justify this proposition with CLV or other measures.
  • How do you exchange, collate, disseminate and control the data you have?

A considered and well-formulated data strategy has a strong vision, clear goals, well-defined success metrics and compelling business rationale.

Roles and responsibilities

All successful data governance and data management programs including those that only consider Master Data Management as a first step, have to be implemented by people. These could be stakeholders from the business, members of IT, a specialized group of people that form a data management organization (DMO) or they could be external consultants or service providers.

Answer these fundamental questions to guide your organizational definition:

  • Will you have dedicated people for data management or will this be an integral part of the role of existing peoples’ day jobs?
  • Have you committed to your initiative being a business-led initiative as opposed to technology and It led one?
  • Do all the participants in the process understand their roles and responsibilities with respect to proper and appropriate activities and decisions around the data?
  • Do you have assigned data owners?
  • Do you have a decided escalation or triage process for contentious issues?
  • Do you subscribe to the concept of “Data Stewardship”?

Recognising that part of the responsibilities of people undertaking data stewardship is the creation and handling of the Data Management Body of Knowledge (DMBoK); defining, evaluating and resolving data quality assessment; documenting policies and procedures ultimately help with transitioning to a more evolved state of organizational data governance.

Defining and measuring success

There is an old adage, often attributed to W Edwards Deming, statistician and QC expert, that “you can’t manage what you can’t measure”. The same is true of your data management program. If you have not defined measures and are not evaluating those measures, are you in fact managing your data?

Very little data enjoy a static existence, more often than not, data evolves and changes according to the needs and usage of the business. Setting up monitoring of data is therefore one of the key tasks for the teams responsible for data management.

These are the common measures you might expect to see

  • Assessment of Accuracy
  • Evaluation of Relevance
  • Completeness checks
  • Consistency checks
  • Rights and permissions

What you use to perform these assessments and checks is less important than ensuring that they are undertaken regularly and consistently and reported on.

Remediation plans can only be put in place and be executed if you are performing these checks.

Data quality measures can include different things such as information like the number of completeness checks, root cause analysis, and recurrence relative significance of certain types of issues encountered. Your metrics may vary when compared with other organizations but in some instances, there are standard measures for industry sectors and your peers. What’s crucial is to establish key metrics for assessing data quality and follow through on leveraging them.

Communication and education

A well-implemented data governance program avoids being labelled as bureaucratic and instead demonstrates effective management and use of data through a comprehensive and elaborate communication programme.

This means that those people with the assigned responsibilities of data governance need to bring strong communication skills to the table when dealing with people and process issues. Since data governance is often accompanied by business process change or digital transformation, many of the communication approaches will be common.

If this is a new initiative for the business there are a couple of critical communication touchpoints that might be beneficial.

  • Develop a timeline and a schedule for your communication activities and channels.
  • Introduce others to the initiative by way of an executive sponsor in the town hall, internal newsletters or communique.
  • Make use of social media and print media on noticeboards, corporate screensavers and email banners.
  • Clearly articulate business expectations in terms of outcomes – why are we doing this and what expected benefits will we or our customers all enjoy
  • We talked about roles and responsibilities already but reiterate these so everyone understands especially those not a part of the team.
  • Avoid buzzword bingo and jargon in conveying the message and building organizational understanding.
  • Communicate on a regular basis.

The more others understand what you are doing and why you are doing it, the greater the likelihood of success.

Fitting MDM into the big picture

Master data management encompasses the processes, standards and tools that are used to support the creation and management of master data.

MDM is a cornerstone of data management and data governance. At its core, MDM is the maintenance of the relationships between the master file and all other masters and transactions with the Masterfile for the customer in particular being a key point of reference.

A well-implemented and maintained MDM practice avoids duplicates, redundancy and inconsistencies.

The long game

Things that are worth doing, often take time, and the same is perfectly true about data governance and the implementation of master data management as part of a more broadly focused data management program. It isn’t something you do once, and then you’re done.

Over time your organization will determine that the true value of data is often hidden in how it is used in ways that were perhaps less obvious at the outset.

Fast-evolving data and data needs mean that the job of data governance never really ends and so your business will need to keep pace with these changes both in terms of how the data itself is managed and also in how teams think about the data.

We view Pretectum C-MDM as a flexible and adaptable complementary technology to any data governance program with our special focus on customer master data management, contact us today to find out how we can be of benefit to you in your data governance initiative.