Tag: Gartner

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Successful low-risk Customer Master Data implementation

STrategy and Tactics jigsaw pieces

Setting precise objectives is an indispensable factor in the successful implementation of Customer Master Data Management (CMDM).

The fundamental threat to a burgeoning CMDM program lies in its initiation with unclear or ambiguous business objectives. Although overarching goals such as enhancing data quality, supporting informed decision-making, achieving a unified truth, or obtaining a 360-degree customer view might seem logically sound, they often lack the specificity required for the effective execution of a CMDM program.

Gartner, a leading research and advisory company, highlights four key reasons for Master Data Management (MDM) program failures, among them insufficient executive sponsorship, inadequate adjustment of business processes, a lack of validation, and the potential pitfalls of an “all at once” or “big-bang” implementation strategy. These pitfalls underscore the critical importance of a carefully structured and well-defined approach in implementing CMDM initiatives.

One notable aspect contributing to failure might be the absence of a structured framework to measure the value of data management for an organization, particularly within the domain of customer data. Without well-defined objectives, CMDM initiatives often struggle to progress beyond their initial stages or may fail outright during implementation.

To mitigate the risk of CMDM failure and ensure the success of the program, it is imperative to follow a systematic approach. The first step involves defining measurable business outcomes related specifically to customer data. The litmus test for these objectives lies in the ability to articulate CMDM outcomes in non-technical terms that resonate with both business and IT stakeholders. If an organization cannot express its objectives without relying on technical jargon, it raises a red flag, indicating the need for re-evaluation.

A helpful technique in this regard is to encourage organizations to state their objectives without using the word “data” Instead, the focus should be on articulating business objectives related to customer data that CMDM aims to address.

  • Increasing customer retention rates: Achieved by reducing customer service response times to a specific duration, for example.
  • Augmenting cross-sell opportunities: Achieved through a more personalized enhancement of the customer experience. This might be another.
  • Improving CSAT scores: As a lagging indicator through more accurate and timely responses to customer interactions.

By steering away from technical language and concentrating on specific business outcomes linked to customer data, organizations can ensure that CMDM objectives are clear, understandable, and relevant to all stakeholders.

Understanding the core motivations behind CMDM initiatives is paramount. Whether the objective is to increase customer loyalty, optimize marketing strategies, or personalize customer interactions, there must be a compelling business reason underpinning CMDM efforts. Organizations need to document these customer-centric business challenges and connect them to the “what” and “how” of the CMDM project.

Failure to establish this connection can lead to confusion and a loss of focus. To prevent this, organizations must emphasize the value of CMDM by demonstrating its ability to drive customer-centric outcomes, such as personalized marketing campaigns, improved customer service, or enhanced customer loyalty programs. Identifying specific quick wins related to customer data is crucial to showcasing the tangible value of the CMDM program.

Beyond traditional Return on Investment (ROI) studies, CMDM initiatives focused on customer data require a roadmap that outlines the core business problem and provides a detailed plan to address it. This roadmap should encompass stakeholder engagement and commitment strategies, ensuring that the CMDM program progresses smoothly from conception to implementation, specifically in the domain of customer master data.

An effective “Strategic Outcomes Blueprint” (SOB) is instrumental in identifying quick wins related to customer data that prioritize business outcomes, thereby highlighting the value of the CMDM program.

A “Strategic Outcomes Blueprint” should include:

  • A clear description of the customer-centric business opportunity, such as increasing customer lifetime value or improving customer retention rates.
  • Prioritized initiatives and resource allocation focusing on customer data management.
  • Key performance indicators specific to customer data quality, customer satisfaction, or customer engagement.
  • Quantification of projected ROI related to customer-centric outcomes.

By creating a compelling business case through the SOB, organizations can think big while starting small, focusing on targeted problem-solving related to customer data and demonstrating the immediate value of the CMDM program.

It’s crucial to recognize that CMDM in the context of customer master data is not a one-time project but a continuous journey. By tying CMDM implementations to real-world business challenges specific to customer data and showcasing their value through quick wins, organizations can establish CMDM as an ongoing initiative. Celebrating achievements and sharing insights derived from clean, trusted customer data helps maintain momentum and enthusiasm among stakeholders.

Furthermore, CMDM programs related to customer data often involve multi-domain challenges, such as customer relationships, product preferences, and service histories. By mastering one customer data domain at a time and celebrating successes, organizations can expand their CMDM efforts gradually, addressing various aspects of customer interactions. This incremental approach enables businesses to build expertise, tackle specific challenges related to customer data, and continuously demonstrate value to stakeholders.

Any successful CMDM program focused on customer master data necessitates clear and customer-centric objectives, active collaboration between business and IT teams, a deep understanding of underlying customer-centric business challenges, and a well-defined roadmap specific to customer data management.

By following these steps, organizations can steer clear of potential pitfalls, reduce risks, and ensure that CMDM initiatives focused on customer data deliver meaningful and measurable results. Implementation of CMDM in the context of customer master data is not merely a project; it’s a continuous journey toward customer data excellence, personalized customer experiences, and sustainable growth in today’s customer-centric business landscape.

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Data Privacy : Stats and Trends 2024

two gray bullet security cameras

Omnibus Privacy Law are comprehensive national privacy law that defines and recognizes parties as Data Controllers and Data Processors. 

The US currently does not have a federal omnibus privacy law, but the States are beginning to pass privacy laws to address the processing of personal data.  The Federal Trade Commission (FTC) has taken a more aggressive approach toward protecting consumer data, with a focus on health, biometrics, and children’s information.

Various other US regulators, such as the Consumer Financial Protection Bureau (CFPB) and Securities and Exchange Commission (SEC), have modified and strengthened privacy and security compliance obligations for entities under their jurisdictions.

There have been comprehensive privacy laws at the individual state level, such as the EU-US Data Privacy Shield, which is important for United States-based companies. The pace of change in the regulation of data privacy continues to increase, with 2023 being a year of substantial change in virtually every area of privacy regulation and now into 2024, pushing organizations to increasingly focus efforts around respecting privacy.

In the EU and many other countries, an omnibus approach to privacy regulation has been in place for a while with one overarching law that regulates privacy consistently across all industries. 

Such Omnibus laws cover a broad spectrum of organizations or natural persons, rather than simply a certain market sector or population. The adoption of omnibus privacy laws across now more than 160 countries underscores the growing importance of privacy compliance for businesses in general.

It’s widely acknowledged among business leaders that privacy isn’t merely a regulatory box to check but a fundamental aspect of maintaining customer trust.

According to the latest Cisco 2024 Data Privacy Benchmark Study, which surveyed over 2,600 security and privacy professionals across 12 geographies, 94% of organizations recognize that customers won’t engage with them if their data isn’t adequately safeguarded.

Customers are also actively seeking tangible proof of data protection measures, some 98% consider external privacy certifications. Though consumers may not be explicitly familiar with privacy certifications, companies that present things like ISO 27701 and APEC Cross-Border Privacy Rule adherences are essentially influencing purchasing decisions indirectly by presenting their credentials around respecting data privacy.

Pretectum CMDM aligns with these concerns by offering robust self-service consent and data verification services, coupled with state-of-the-art encryption, sophisticated Role-Based Access Control (RBAC), and a resilient cloud architecture.

Pretectum CMDM addresses many of the privacy compliance challenges head-on by facilitating transparent applications, ensuring a combination of explainable deterministic and human oversight in processes.

These features empower organizations to not only comply with privacy laws but also gain a competitive edge by fostering trust and confidence among their customer base.

Despite the additional costs and operational requirements imposed by privacy laws, organizations overwhelmingly perceive them as beneficial. 80% of respondents in the study reported a positive impact from privacy laws, highlighting the alignment between regulatory compliance and business interests.

With Pretectum CMDM’s streamlined processes and automated controls, organizations can effectively manage the complexities of data cataloging, classifying, and managing customer data thereby minimizing the operational burden associated with meeting compliance obligations.

From an economic standpoint, privacy investments yield attractive returns for organizations worldwide. 95% of respondents believe the benefits of privacy outweigh the costs.

The study also highlights persistent challenges in leveraging emerging technologies like artificial intelligence (AI) while maintaining transparency and customer trust. Despite growing concerns among consumers about AI’s impact on data privacy, organizations have made limited progress in addressing these apprehensions. By integrating AI ethics management programs into their operations, organizations can work towards building trust and reassuring customers about the ethical use of their data. The Cisco study underscores the transformative potential of generative AI applications, alongside the associated risks of data exposure and confidentiality breaches.

Pretectum CMDM ‘s robust security measures for data assurance include granular access controls and data encryption, these mitigate some risks, safeguarding sensitive information from unauthorized access or disclosure. By implementing stringent controls and educating employees on the risks associated with breaches, organizations can harness its benefits while upholding privacy standards.

What’s changed since last year?

The key differences between the 2023 results outlined in a previous article and the new 2024 data privacy benchmark studies suggest some changes in sentiments. More regulations, privacy by design, more enforcement and fines, and answering customers’ concerns.

In 2022, there was an emphasis on increased regulatory scrutiny and the introduction of stricter data protection regulations globally. The trend of more countries implementing new privacy laws was anticipated to continue. In 2024, the privacy landscape is expected to see significant developments characterized by heightened regulatory activity and even more countries enacting data privacy laws.

Industry analyst, Gartner, predicts that by the end of 2024, 75% of the world’s population will have their personal data covered under modern privacy regulations.

In 2022, there was an anticipation of more emphasis on data ethics, with consumers becoming more aware of the importance of ethical data use. Organizations were expected to focus on implementing ethical data practices to gain the trust of their customers. In 2024, the growing importance of Privacy by Design is likely to be highlighted, advocating for the integration of privacy into system design and development. This signifies a shift in how organizations approach privacy.

In 2022, the focus was on GDPR fines, with Meta receiving the biggest GDPR fine ever imposed, surpassing €1.2 billion. This reflected increased scrutiny of tech giants and emphasized the need for robust data protection measures. In 2023, the emphasis was on increased regulatory activity and enforcement, with GDPR fines collectively reaching over €4.4 billion. Data Protection Authorities (DPAs) were hiring more staff and allocating additional resources to handle the growing number of data protection cases.

In the 2023 survey, consumers were increasingly aware of their data privacy rights and the risks of sharing their data online. They expected companies to take responsibility for protecting their data and were willing to share their data if they trusted the company and understood how their data would be used. In the 2024 survey, the Study revealed that 94% of organizations believed that their customers wouldn’t buy from them if their data was not properly protected, highlighting the critical role of privacy in enabling customer trust.

By leveraging Pretectum CMDM ‘s advanced capabilities in self-service consent, data verification, and secure encryption of data at rest and across the wire, together with comprehensive RBAC, and cloud architecture, organizations can not only achieve regulatory compliance but also differentiate themselves in the market as trustworthy stewards of customer data.

Through continued investment in privacy initiatives supported by Pretectum CMDM , organizations can realize substantial economic and operational benefits while navigating the evolving landscape of data privacy and security in their management of customer master data

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Customer Master Data Quality is relative

skyscrapers with reflecting walls in modern megapolis

Data are not fuel, not energy, not a life force. In itself, customer data, in particular, holds no innate value to your business beyond the purpose for which your business acquired it and uses it.

However, all that said, the decisions that an enterprise takes based on insights from customer data can lead to different outcomes some of which can be very detrimental to the health of the business. For this reason, the quality of the customer master data may be the one thing that you really want to focus on, in relation to customer master data overall.

In the absence of good data quality, data-driven initiatives are sub-optimal and may even be rendered useless. This is why, ensuring that you have quality customer master data is pretty foundational to avoiding missteps, reducing risk and harvesting meaningful benefits from your customer master data.

Absolute data quality is probably an unattainable goal and quite honestly, the value of absolute data quality is relative to the nature of the data itself. Data that is sourced as zero-party and first-party data should typically be of better quality but the effectiveness of capturing good quality 0PD and 1PD is dependent on the data capture and collection methods and the control mechanisms put in place to provide data quality assurance.

One of the ways that the Pretectum Customer Master Data Management (CMDM) platform helps, is with the ability to capture and edit new and existing records through interactive screens with built-in data validations. Another way is to leverage the Pretectum CMDM APIs and integrate these with your business applications to provide added data quality assurance at the time of customer master data capture and edit. Rules and data quality measures are all driven by the schema definitions that overarch a given dataset.

The $1-$10-$100 Rule

Capturing the best possible data at the time of origination is the first prize in approaches to customer master data collection. According to Gartner and D&B, the costs associated with the collection of a single record can be as much as US$1, this cost not including other acquisition costs. But, if there are any fatally bad data elements, the resolution costs, which are basically investigations and workarounds, could be as much as US$10 per record. Correcting those records at the sources reaches a whopping US$100 per record.

This is commonly known as the 1-10-100 rule. It is a rule-of-thumb model illustrating the hard costs to an organization of chasing mistakes and reinforces the argument that failure to take notice and correct mistakes early on, escalates costs the later they are realized.

The counter-position is that a shared source prevents the time and costs of rekeying and verifying information entered into separate disconnected systems.

A single source for customer master data also eliminates the costly and embarrassing mistakes that are created with disconnected systems and the absence of real-time or near real-time synchronization and integration.

All this comes down to the simple calculation that if your company holds 1M consumer records, it would have cost you potentially US$1M to acquire them over their lifetime. If there is 10% inaccuracy in any customer master data dataset, you’ll be spending just as much on data issue triage during the lifetime of those records and millions more on correcting those same records to avoid the triage costs.

A couple of studies cited in the MITSloan Management Review based on research by Experian plc, as well as consultants James Price of Experience Matters and Martin Spratt of Clear Strategic IT Partners Pty. Ltd. estimated the cost of bad data to be 15% to 25% of revenue for most companies. That’s astonishingly high but seems to align with the high cost to triage and remediate just customer data alone.

Multifaceted data quality

What becomes pretty clear the moment you start reviewing data quality across your systems estate, is that data quality is multifaceted. Consistency, accuracy, recency, completeness, and de-duplication are obvious aspects, but when you consider the typically siloed nature of systems you quickly come to the realization that consistency, for example, doesn’t carry quite the same weight for all business use cases.

Many organizations field ten or more systems of record. These range from ERP, CRM, CDP, POS, Service, Support, and warranties through to the many spreadsheets and Access databases as well as other specialist systems of record that a given organization might have.

The data quality problem is further compounded when you examine data ownership and who is designated as the most responsible person for customer data and which systems are considered the true authority in relation to the customer master.

A customer master data management platform like the Pretectum CMDM provides an organization with the ability to define what good customer master data should look like and then, is able to assess data added or loaded into the system in relation to its conformity with the customer master data quality definitions.

The adoption of the CMDM platform affords the average organization not just a centralized customer master collation and insights point, it can also serve as the hub to a multispoked approach to servicing customer master data to different systems with different needs and usage.

Through the combination of manual data stewardship and automation, a CMDM like a Pretectum Customer MasterData Management platform can also reduce the cost of triage and remediation, depending on the implementation approach.

The relative quality of customer master data records can be assessed holistically and compared and contrasted with data sourced from other upstream data collection systems and repositories.

Most importantly, the records, even with variations in their content, can be consolidated and converge on a single source of truth. To learn more about how Pretectum can help with your Customer Master Data Management challenges, contact us today.